{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Access to Data in NetCDF format viewed as Zarr\n",
    "\n",
    "Some datasets offered by the Open Data Portal are provided via \n",
    "[references format](https://fsspec.github.io/kerchunk/spec.html) \n",
    "as specified by the [kerchunk](https://fsspec.github.io/kerchunk/) \n",
    "package. This allows accessing to the original NetCDF data files with \n",
    "an I/O performance comparable to [Zarr](https://zarr.readthedocs.io/). \n",
    "\n",
    "The data is available via store identifier 'cci-kerchunk-store'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from xcube.core.store import new_data_store"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "kerchunk_store = new_data_store('esa-cci-kc')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again, let's see what data sets are available. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ESACCI-BIOMASS-L4-AGB-CHANGE-100m-2018-2017-fv4.0-kr1.1',\n",
       " 'ESACCI-BIOMASS-L4-AGB-CHANGE-100m-2019-2018-fv4.0-kr1.1',\n",
       " 'ESACCI-BIOMASS-L4-AGB-CHANGE-100m-2020-2010-fv4.0-kr1.1',\n",
       " 'ESACCI-BIOMASS-L4-AGB-CHANGE-100m-2020-2019-fv4.0-kr1.1',\n",
       " 'ESACCI-BIOMASS-L4-AGB-MERGED-100m-2010-2020-fv4.0-kr1.1',\n",
       " 'ESACCI-L3C_CLOUD-CLD_PRODUCTS-ATSR2_AATSR-199506-201204-fv3.0-kr1.1',\n",
       " 'ESACCI-L3C_CLOUD-CLD_PRODUCTS-AVHRR_AM-199109-201612-fv3.0-kr1.1',\n",
       " 'ESACCI-L3C_CLOUD-CLD_PRODUCTS-AVHRR_PM-198201-201612-fv3.0-kr1.1',\n",
       " 'ESACCI-L3C_SNOW-SWE-MERGED-19790102-20200524-fv2.0-kr1.1',\n",
       " 'ESACCI-L4_FIRE-BA-MODIS-20010101-20200120-fv5.1-kr1.2',\n",
       " 'ESACCI-LC-L4-LCCS-Map-300m-P1Y-1992-2015-v2.0.7b-kr1.1',\n",
       " 'ESACCI-LC-L4-PFT-Map-300m-P1Y-1992-2020-v2.0.8-kr1.1',\n",
       " 'ESACCI-LST-L3C-LST-MODISA-0.01deg_1MONTHLY_DAY-200207-201812-fv3.00-kr1.1',\n",
       " 'ESACCI-LST-L3C-LST-MODISA-0.01deg_1MONTHLY_NIGHT-200207-201812-fv3.00-kr1.1',\n",
       " 'ESACCI-LST-L3C-LST-MODIST-0.01deg_1MONTHLY_DAY-200003-201812-fv3.00-kr1.1',\n",
       " 'ESACCI-LST-L3C-LST-MODIST-0.01deg_1MONTHLY_NIGHT-200003-201812-fv3.00-kr1.1',\n",
       " 'ESACCI-LST-L3S-LST-IRCDR_-0.01deg_1MONTHLY_DAY-199508-202012-fv2.00-kr1.1',\n",
       " 'ESACCI-LST-L3S-LST-IRCDR_-0.01deg_1MONTHLY_NIGHT-199508-202012-fv2.00-kr1.1',\n",
       " 'ESACCI-PERMAFROST-L4-ALT-ERA5_MODISLST_BIASCORRECTED-AREA4_PP-1997-2002-fv03.0-kr1.1',\n",
       " 'ESACCI-PERMAFROST-L4-ALT-MODISLST_CRYOGRID-AREA4_PP-2003-2019-fv03.0-kr1.1',\n",
       " 'ESACCI-SOILMOISTURE-L3S-SSMS-ACTIVE-19910805-20211231-fv07.1-kr1.1',\n",
       " 'ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED-19781101-20211231-fv07.1-kr1.1',\n",
       " 'ESACCI-SOILMOISTURE-L3S-SSMV-PASSIVE-19781101-20211231-fv07.1-kr1.1',\n",
       " 'ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED_ADJUSTED-19781101-20211231-fv07.1-kr1.1']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datasets = kerchunk_store.list_data_ids()\n",
    "datasets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The names are similar but different to the ones from the Climate Toolbox store.\n",
    "We can have a look at a dataset's metadata to find out more about it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/json": {
       "attrs": {
        "Conventions": "CF-1.9",
        "cdm_data_type": "Grid",
        "comment": "This dataset was produced with funding of the ESA CCI+ Soil Moisture project; ESRIN Contract No: 4000126684/19/I-NB",
        "contact": "cci_sm_contact@eodc.eu",
        "creator_email": "cci_sm_developer@eodc.eu",
        "creator_name": "Department of Geodesy and Geoinformation, Vienna University of Technology",
        "creator_url": "https://climers.geo.tuwien.ac.at/",
        "date_created": "File created: 2022-04-06 09:13:45.810237",
        "geospatial_lat_max": "90.0",
        "geospatial_lat_min": "-90.0",
        "geospatial_lat_resolution": "0.25 degree",
        "geospatial_lat_units": "degrees_north",
        "geospatial_lon_max": "180.0",
        "geospatial_lon_min": "-180.0",
        "geospatial_lon_resolution": "0.25 degree",
        "geospatial_lon_units": "degrees_east",
        "geospatial_vertical_max": "0.0",
        "geospatial_vertical_min": "0.0",
        "history": "2022-04-06 09:12:42 - product produced\nKerchunk file created on 26/09/23\nKerchunk file last updated by CEDA on 03/10/23 in the context of the CCI Knowledge Exchange Project",
        "id": "ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED-19781101-20211231-fv07.1",
        "institution": "TU Wien (AUT); VanderSat B.V. (NL)",
        "kerchunk_creation_date": "031023T093359",
        "kerchunk_revision": "kr1.1",
        "key_variables": "sm",
        "keywords": "soil moisture, soil water content, microwave remote sensing, active, passive, combined, climate data record",
        "keywords_vocabulary": "NASA Global Change Master Directory (GCMD) Science Keywords",
        "license": "Data use is free and open for all registered users.",
        "naming_authority": "TU Wien",
        "platform": "Nimbus 7, DMSP, TRMM, AQUA, Coriolis, GCOM-W1, MIRAS, SMAP, GPM, FengYun-3B, FengYun-3C, FengYun-3D; ERS-1, ERS-2, METOP-A, METOP-B",
        "processing_level": "Quality-controlled, super-collocated (L3S) Satellite Soil Moisture (SM) data from multiple sensors",
        "product_version": "v07.1",
        "project": "Climate Change Initiative - European Space Agency",
        "references": "http://www.esa-soilmoisture-cci.org; Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F.,  Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017) ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001; Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., Dorigo, W. (2019) Evolution of the ESA CCI Soil Moisture Climate Data Records and their underlying merging methodology. Earth System Science Data 11, 717-739, https://doi.org/10.5194/essd-11-717-2019; Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. https://doi.org/10.1109/TGRS.2017.2734070",
        "sensor": "SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS, SMAP_radiometer, GMI, VIRR-3B, VIRR-3C, VIRR-3D; AMI-WS, ASCAT-A, ASCAT-B, ASCAT-C",
        "source": "WARP 5.5R1.1/AMI-WS/ERS12 Level 2 Soil Moisture; WARP 5.4R1.0/AMI-WS/ERS2 Level 2 Soil Moisture; H115: Metop ASCAT Surface Soil Moisture Climate Data Record v5 12.5 km sampling, DOI: 10.15770/EUM_SAF_H_0006; H116: Metop ASCAT Surface Soil Moisture Climate Data Record v5 Extension 12.5 km sampling; H115: Metop ASCAT Surface Soil Moisture Climate Data Record v5 12.5 km sampling, DOI: 10.15770/EUM_SAF_H_0006; H116: Metop ASCAT Surface Soil Moisture Climate Data Record v5 Extension 12.5 km sampling; H115: Metop ASCAT Surface Soil Moisture Climate Data Record v5 12.5 km sampling, DOI: 10.15770/EUM_SAF_H_0006; H116: Metop ASCAT Surface Soil Moisture Climate Data Record v5 Extension 12.5 km sampling;; LPRMv7/SMMR/Nimbus 7 L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv7/SSMI/F08, F11, F13 DMSP L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv7/TMI/TRMM L2 Surface Soil Moisture, Ancillary Params, and QC; LPRMv7/AMSR-E/Aqua L2B Surface Soil Moisture, Ancillary Params, and QC; LPRMv7/WINDSAT/CORIOLIS L2 Surface Soil Moisture, Ancillary Params, and QC; LPRMv7/AMSR2/GCOM-W1 L3 Surface Soil Moisture, Ancillary Params; LPRMv7/SMOS/MIRAS L3 Surface Soil Moisture, CATDS Level 3 Brightness Temperatures (L3TB) version 300 RE03 & RE04; LPRMv7/SMAP_radiometer/SMAP L2 Surface Soil Moisture, Ancillary Params, and QC; LPRMv7/GMI/GPM L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv7/VIRR/FengYun-3B L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv7/VIRR/FengYun-3C L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv7/VIRR/FengYun-3D L3 Surface Soil Moisture, Ancillary Params, and quality flags;;",
        "spatial_resolution": "25km",
        "standard_name_vocabulary": "CF Standard Name Table v77",
        "summary": "This dataset was produced with funding of the ESA CCI+ Soil Moisture project; ESRIN Contract No: 4000126684/19/I-NB",
        "time_coverage_duration": "P43Y",
        "time_coverage_end": "20211231T235959Z",
        "time_coverage_end_product": "20211231T235959Z",
        "time_coverage_resolution": "P1D",
        "time_coverage_start": "19781101T000000Z",
        "time_coverage_start_product": "19781101T000000Z",
        "title": "ESA CCI Surface Soil Moisture COMBINED active+passive Product",
        "tracking_id": "dc6ade2c-e51b-4a94-81fa-751df95a85a6"
       },
       "bbox": [
        -180,
        -90,
        180,
        90
       ],
       "coords": {
        "lat": {
         "attrs": {
          "_CoordinateAxisType": "Lat",
          "standard_name": "latitude",
          "units": "degrees_north",
          "valid_range": [
           -90,
           90
          ]
         },
         "dims": [
          "lat"
         ],
         "dtype": "float64",
         "name": "lat"
        },
        "lon": {
         "attrs": {
          "_CoordinateAxisType": "Lon",
          "standard_name": "longitude",
          "units": "degrees_east",
          "valid_range": [
           -180,
           180
          ]
         },
         "dims": [
          "lon"
         ],
         "dtype": "float64",
         "name": "lon"
        },
        "time": {
         "dims": [
          "time"
         ],
         "dtype": "datetime64[ns]",
         "name": "time"
        }
       },
       "data_id": "ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED-19781101-20211231-fv07.1-kr1.1",
       "data_type": "dataset",
       "data_vars": {
        "dnflag": {
         "attrs": {
          "_CoordinateAxes": "time lat lon",
          "bit_meanings": [
           "NaN",
           "day",
           "night"
          ],
          "bits": [
           "0b0",
           "0b1",
           "0b10"
          ],
          "dtype": "int8",
          "flag_meanings": [
           "NaN",
           "day",
           "night",
           "day_night_combination"
          ],
          "flag_values": [
           0,
           1,
           2,
           3
          ],
          "long_name": "Day / Night Flag",
          "valid_range": [
           0,
           3
          ]
         },
         "chunks": [
          1,
          720,
          1440
         ],
         "dims": [
          "time",
          "lat",
          "lon"
         ],
         "dtype": "float32",
         "name": "dnflag"
        },
        "flag": {
         "attrs": {
          "_CoordinateAxes": "time lat lon",
          "bit_meanings": [
           "no_data_inconsistency_detected",
           "snow_coverage_or_temperature_below_zero",
           "dense_vegetation",
           "others_no_convergence_in_the_model_thus_no_valid_sm_estimates",
           "soil_moisture_value_exceeds_physical_boundary",
           "weight_of_measurement_below_threshold",
           "all_datasets_deemed_unreliable",
           "barren_ground_advisory_flag",
           "NaN"
          ],
          "bits": [
           "0b0",
           "0b1",
           "0b10",
           "0b100",
           "0b1000",
           "0b10000",
           "0b100000",
           "0b1000000",
           "0b10000000"
          ],
          "dtype": "int16",
          "flag_meanings": [
           "no_data_inconsistency_detected",
           "snow_coverage_or_temperature_below_zero",
           "dense_vegetation",
           "combination_of_flag_values_1_and_2",
           "soil_moisture_value_exceeds_physical_boundary",
           "combination_of_flag_values_1_and_8",
           "combination_of_flag_values_2_and_8",
           "barren_ground_advisory_flag",
           "combination_of_flag_values_1_and_64",
           "combination_of_flag_values_2_and_64",
           "combination_of_flag_values_1_and_2_and_64",
           "combination_of_flag_values_8_and_64",
           "combination_of_flag_values_1_and_8_and_64",
           "combination_of_flag_values_2_and_8_and_64",
           "combination_of_flag_values_1_and_2_and_4_and_8_and_16_and_32_and_64"
          ],
          "flag_values": [
           0,
           1,
           2,
           3,
           8,
           9,
           10,
           64,
           65,
           66,
           67,
           72,
           73,
           74,
           127
          ],
          "long_name": "Flag",
          "standard_name": "soil_moisture_content status_flag",
          "valid_range": [
           0,
           255
          ]
         },
         "chunks": [
          1,
          720,
          1440
         ],
         "dims": [
          "time",
          "lat",
          "lon"
         ],
         "dtype": "float32",
         "name": "flag"
        },
        "freqbandID": {
         "attrs": {
          "_CoordinateAxes": "time lat lon",
          "bit_meanings": [
           "NaN",
           "L14",
           "C53",
           "C66",
           "C68",
           "C69",
           "C73",
           "X107",
           "K194",
           "MODEL"
          ],
          "bits": [
           "0b0",
           "0b1",
           "0b10",
           "0b100",
           "0b1000",
           "0b10000",
           "0b100000",
           "0b1000000",
           "0b10000000",
           "0b100000000"
          ],
          "dtype": "int16",
          "flag_meanings": [
           "NaN",
           "C66",
           "X107",
           "C66+X107"
          ],
          "flag_values": [
           0,
           4,
           64,
           68
          ],
          "long_name": "Frequency Band Identification",
          "valid_range": [
           0,
           511
          ]
         },
         "chunks": [
          1,
          720,
          1440
         ],
         "dims": [
          "time",
          "lat",
          "lon"
         ],
         "dtype": "float32",
         "name": "freqbandID"
        },
        "mode": {
         "attrs": {
          "_CoordinateAxes": "time lat lon",
          "bit_meanings": [
           "NaN",
           "ascending",
           "descending"
          ],
          "bits": [
           "0b0",
           "0b1",
           "0b10"
          ],
          "dtype": "int8",
          "flag_meanings": [
           "NaN",
           "ascending",
           "descending",
           "ascending_descending_combination"
          ],
          "flag_values": [
           0,
           1,
           2,
           3
          ],
          "long_name": "Satellite Mode",
          "valid_range": [
           0,
           3
          ]
         },
         "chunks": [
          1,
          720,
          1440
         ],
         "dims": [
          "time",
          "lat",
          "lon"
         ],
         "dtype": "float32",
         "name": "mode"
        },
        "sensor": {
         "attrs": {
          "_CoordinateAxes": "time lat lon",
          "bit_meanings": [
           "NaN",
           "SMMR",
           "SSMI",
           "TMI",
           "AMSRE",
           "WindSat",
           "AMSR2",
           "SMOS",
           "AMIWS",
           "ASCATA",
           "ASCATB",
           "SMAP",
           "MODEL",
           "GPM",
           "FY3B",
           "FY3D",
           "ASCATC",
           "FY3C"
          ],
          "bits": [
           "0b0",
           "0b1",
           "0b10",
           "0b100",
           "0b1000",
           "0b10000",
           "0b100000",
           "0b1000000",
           "0b10000000",
           "0b100000000",
           "0b1000000000",
           "0b10000000000",
           "0b100000000000",
           "0b1000000000000",
           "0b10000000000000",
           "0b100000000000000",
           "0b1000000000000000",
           "0b10000000000000000"
          ],
          "dtype": "int32",
          "flag_meanings": [
           "NaN",
           "SMMR"
          ],
          "flag_values": [
           0,
           1
          ],
          "long_name": "Sensor",
          "valid_range": [
           0,
           131071
          ]
         },
         "chunks": [
          1,
          720,
          1440
         ],
         "dims": [
          "time",
          "lat",
          "lon"
         ],
         "dtype": "float64",
         "name": "sensor"
        },
        "sm": {
         "attrs": {
          "_CoordinateAxes": "time lat lon",
          "ancillary_variables": "sm_uncertainty flag t0",
          "dtype": "float32",
          "long_name": "Volumetric Soil Moisture",
          "standard_name": "soil_moisture_content",
          "units": "m3 m-3",
          "valid_range": [
           0,
           1
          ]
         },
         "chunks": [
          1,
          720,
          1440
         ],
         "dims": [
          "time",
          "lat",
          "lon"
         ],
         "dtype": "float32",
         "name": "sm"
        },
        "sm_uncertainty": {
         "attrs": {
          "_CoordinateAxes": "time lat lon",
          "dtype": "float32",
          "long_name": "Volumetric Soil Moisture Uncertainty",
          "standard_name": "soil_moisture_content standard_error",
          "units": "m3 m-3",
          "valid_range": [
           0,
           1
          ]
         },
         "chunks": [
          1,
          720,
          1440
         ],
         "dims": [
          "time",
          "lat",
          "lon"
         ],
         "dtype": "float32",
         "name": "sm_uncertainty"
        },
        "t0": {
         "attrs": {
          "_CoordinateAxes": "time lat lon",
          "dtype": "float64",
          "long_name": "Observation Timestamp",
          "valid_range": [
           3225,
           3227
          ]
         },
         "chunks": [
          1,
          720,
          1440
         ],
         "dims": [
          "time",
          "lat",
          "lon"
         ],
         "dtype": "datetime64[ns]",
         "name": "t0"
        }
       },
       "dims": {
        "lat": 720,
        "lon": 1440,
        "time": 15767
       },
       "spatial_res": 0.25,
       "time_period": "1D",
       "time_range": [
        "1978-10-31",
        "2021-12-31"
       ]
      },
      "text/plain": [
       "<xcube.core.store.descriptor.DatasetDescriptor at 0x7f84834486e0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kerchunk_store.describe_data('ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED-19781101-20211231-fv07.1-kr1.1')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cubes can easily be opened from the store like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "html[data-theme=dark],\n",
       "body[data-theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 654GB\n",
       "Dimensions:         (time: 15767, lat: 720, lon: 1440)\n",
       "Coordinates:\n",
       "  * lat             (lat) float64 6kB 89.88 89.62 89.38 ... -89.38 -89.62 -89.88\n",
       "  * lon             (lon) float64 12kB -179.9 -179.6 -179.4 ... 179.6 179.9\n",
       "  * time            (time) datetime64[ns] 126kB 1978-11-01 ... 2021-12-31\n",
       "Data variables:\n",
       "    dnflag          (time, lat, lon) float32 65GB dask.array&lt;chunksize=(1, 720, 1440), meta=np.ndarray&gt;\n",
       "    flag            (time, lat, lon) float32 65GB dask.array&lt;chunksize=(1, 720, 1440), meta=np.ndarray&gt;\n",
       "    freqbandID      (time, lat, lon) float32 65GB dask.array&lt;chunksize=(1, 720, 1440), meta=np.ndarray&gt;\n",
       "    mode            (time, lat, lon) float32 65GB dask.array&lt;chunksize=(1, 720, 1440), meta=np.ndarray&gt;\n",
       "    sensor          (time, lat, lon) float64 131GB dask.array&lt;chunksize=(1, 720, 1440), meta=np.ndarray&gt;\n",
       "    sm              (time, lat, lon) float32 65GB dask.array&lt;chunksize=(1, 720, 1440), meta=np.ndarray&gt;\n",
       "    sm_uncertainty  (time, lat, lon) float32 65GB dask.array&lt;chunksize=(1, 720, 1440), meta=np.ndarray&gt;\n",
       "    t0              (time, lat, lon) datetime64[ns] 131GB dask.array&lt;chunksize=(1, 720, 1440), meta=np.ndarray&gt;\n",
       "Attributes: (12/46)\n",
       "    Conventions:                  CF-1.9\n",
       "    cdm_data_type:                Grid\n",
       "    comment:                      This dataset was produced with funding of t...\n",
       "    contact:                      cci_sm_contact@eodc.eu\n",
       "    creator_email:                cci_sm_developer@eodc.eu\n",
       "    creator_name:                 Department of Geodesy and Geoinformation, V...\n",
       "    ...                           ...\n",
       "    time_coverage_start:          19781101T000000Z\n",
       "    time_coverage_start_product:  19781101T000000Z\n",
       "    title:                        ESA CCI Surface Soil Moisture COMBINED acti...\n",
       "    tracking_id:                  dc6ade2c-e51b-4a94-81fa-751df95a85a6\n",
       "    kerchunk_revision:            kr1.1\n",
       "    kerchunk_creation_date:       031023T093359</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7915ad4c-27f3-4113-ad6b-39356456ffe7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7915ad4c-27f3-4113-ad6b-39356456ffe7' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 15767</li><li><span class='xr-has-index'>lat</span>: 720</li><li><span class='xr-has-index'>lon</span>: 1440</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-5cadc28b-ff17-47f2-a5ab-5583a6d6c330' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5cadc28b-ff17-47f2-a5ab-5583a6d6c330' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>89.88 89.62 89.38 ... -89.62 -89.88</div><input id='attrs-8d403145-b8ef-4858-9106-1bf58ca07183' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d403145-b8ef-4858-9106-1bf58ca07183' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-843a300d-fdc0-4ff0-b96d-e5f223f25dd0' class='xr-var-data-in' type='checkbox'><label for='data-843a300d-fdc0-4ff0-b96d-e5f223f25dd0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_range :</span></dt><dd>[-90.0, 90.0]</dd></dl></div><div class='xr-var-data'><pre>array([ 89.875,  89.625,  89.375, ..., -89.375, -89.625, -89.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-179.9 -179.6 ... 179.6 179.9</div><input id='attrs-c41eaaa4-74e3-4f09-9690-8372e925bcb3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c41eaaa4-74e3-4f09-9690-8372e925bcb3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-316518fe-275e-4b6a-94a8-c06f15a92d9c' class='xr-var-data-in' type='checkbox'><label for='data-316518fe-275e-4b6a-94a8-c06f15a92d9c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_range :</span></dt><dd>[-180.0, 180.0]</dd></dl></div><div class='xr-var-data'><pre>array([-179.875, -179.625, -179.375, ...,  179.375,  179.625,  179.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1978-11-01 ... 2021-12-31</div><input id='attrs-d0e3bf34-beb4-4e9d-8ebf-650d6b0da9c3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d0e3bf34-beb4-4e9d-8ebf-650d6b0da9c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d819ee3-0e49-4ccd-b918-b919b1adebe7' class='xr-var-data-in' type='checkbox'><label for='data-1d819ee3-0e49-4ccd-b918-b919b1adebe7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1978-11-01T00:00:00.000000000&#x27;, &#x27;1978-11-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1978-11-03T00:00:00.000000000&#x27;, ..., &#x27;2021-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-12-30T00:00:00.000000000&#x27;, &#x27;2021-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e4c6662f-df3e-4f93-ac3c-98297060bef1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e4c6662f-df3e-4f93-ac3c-98297060bef1' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>dnflag</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 720, 1440), meta=np.ndarray&gt;</div><input id='attrs-62c1585e-9cdb-4c67-bc01-6264f5f75dcc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62c1585e-9cdb-4c67-bc01-6264f5f75dcc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a058f252-da9e-407a-aa95-91aa37324013' class='xr-var-data-in' type='checkbox'><label for='data-a058f252-da9e-407a-aa95-91aa37324013' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxes :</span></dt><dd>time lat lon</dd><dt><span>bit_meanings :</span></dt><dd>[&#x27;NaN&#x27;, &#x27;day&#x27;, &#x27;night&#x27;]</dd><dt><span>bits :</span></dt><dd>[&#x27;0b0&#x27;, &#x27;0b1&#x27;, &#x27;0b10&#x27;]</dd><dt><span>dtype :</span></dt><dd>int8</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;NaN&#x27;, &#x27;day&#x27;, &#x27;night&#x27;, &#x27;day_night_combination&#x27;]</dd><dt><span>flag_values :</span></dt><dd>[0, 1, 2, 3]</dd><dt><span>long_name :</span></dt><dd>Day / Night Flag</dd><dt><span>valid_range :</span></dt><dd>[0, 3]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 60.90 GiB </td>\n",
       "                        <td> 3.96 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (15767, 720, 1440) </td>\n",
       "                        <td> (1, 720, 1440) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 15767 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"168\" height=\"154\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"33\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"33\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"37\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"41\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"45\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"48\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"52\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"56\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"36\" y2=\"59\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"63\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"67\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"71\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"74\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"78\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"82\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"62\" y2=\"85\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"89\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"93\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"97\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"100\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,104.53348012265594 10.0,33.94524482853829\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"48\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"51\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"55\" y2=\"7\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"59\" y2=\"11\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"62\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"66\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"70\" y2=\"22\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"74\" y2=\"26\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"77\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"81\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"85\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"88\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"92\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"96\" y2=\"48\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"100\" y2=\"52\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"103\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"107\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"111\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"114\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"48\" y1=\"0\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 48.08837924859138,0.0 118.67661454270903,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"104\" x2=\"118\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"118\" y1=\"70\" x2=\"118\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 118.67661454270903,70.58823529411765 118.67661454270903,104.53348012265594 80.58823529411765,104.53348012265594\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"99.632425\" y=\"124.533480\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1440</text>\n",
       "  <text x=\"138.676615\" y=\"87.560858\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,138.676615,87.560858)\">720</text>\n",
       "  <text x=\"35.294118\" y=\"89.239362\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,89.239362)\">15767</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 720, 1440), meta=np.ndarray&gt;</div><input id='attrs-a8922409-c0af-4826-b2d4-16af1b1c4065' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a8922409-c0af-4826-b2d4-16af1b1c4065' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0e8abab-1cac-4944-9256-81f26c8815a7' class='xr-var-data-in' type='checkbox'><label for='data-f0e8abab-1cac-4944-9256-81f26c8815a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxes :</span></dt><dd>time lat lon</dd><dt><span>bit_meanings :</span></dt><dd>[&#x27;no_data_inconsistency_detected&#x27;, &#x27;snow_coverage_or_temperature_below_zero&#x27;, &#x27;dense_vegetation&#x27;, &#x27;others_no_convergence_in_the_model_thus_no_valid_sm_estimates&#x27;, &#x27;soil_moisture_value_exceeds_physical_boundary&#x27;, &#x27;weight_of_measurement_below_threshold&#x27;, &#x27;all_datasets_deemed_unreliable&#x27;, &#x27;barren_ground_advisory_flag&#x27;, &#x27;NaN&#x27;]</dd><dt><span>bits :</span></dt><dd>[&#x27;0b0&#x27;, &#x27;0b1&#x27;, &#x27;0b10&#x27;, &#x27;0b100&#x27;, &#x27;0b1000&#x27;, &#x27;0b10000&#x27;, &#x27;0b100000&#x27;, &#x27;0b1000000&#x27;, &#x27;0b10000000&#x27;]</dd><dt><span>dtype :</span></dt><dd>int16</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;no_data_inconsistency_detected&#x27;, &#x27;snow_coverage_or_temperature_below_zero&#x27;, &#x27;dense_vegetation&#x27;, &#x27;combination_of_flag_values_1_and_2&#x27;, &#x27;soil_moisture_value_exceeds_physical_boundary&#x27;, &#x27;combination_of_flag_values_1_and_8&#x27;, &#x27;combination_of_flag_values_2_and_8&#x27;, &#x27;barren_ground_advisory_flag&#x27;, &#x27;combination_of_flag_values_1_and_64&#x27;, &#x27;combination_of_flag_values_2_and_64&#x27;, &#x27;combination_of_flag_values_1_and_2_and_64&#x27;, &#x27;combination_of_flag_values_8_and_64&#x27;, &#x27;combination_of_flag_values_1_and_8_and_64&#x27;, &#x27;combination_of_flag_values_2_and_8_and_64&#x27;, &#x27;combination_of_flag_values_1_and_2_and_4_and_8_and_16_and_32_and_64&#x27;]</dd><dt><span>flag_values :</span></dt><dd>[0, 1, 2, 3, 8, 9, 10, 64, 65, 66, 67, 72, 73, 74, 127]</dd><dt><span>long_name :</span></dt><dd>Flag</dd><dt><span>standard_name :</span></dt><dd>soil_moisture_content status_flag</dd><dt><span>valid_range :</span></dt><dd>[0, 255]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 60.90 GiB </td>\n",
       "                        <td> 3.96 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (15767, 720, 1440) </td>\n",
       "                        <td> (1, 720, 1440) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 15767 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"168\" height=\"154\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"33\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"33\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"37\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"41\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"45\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"48\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"52\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"56\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"36\" y2=\"59\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"63\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"67\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"71\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"74\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"78\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"82\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"62\" y2=\"85\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"89\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"93\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"97\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"100\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,104.53348012265594 10.0,33.94524482853829\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"48\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"51\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"55\" y2=\"7\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"59\" y2=\"11\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"62\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"66\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"70\" y2=\"22\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"74\" y2=\"26\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"77\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"81\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"85\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"88\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"92\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"96\" y2=\"48\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"100\" y2=\"52\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"103\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"107\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"111\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"114\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"48\" y1=\"0\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 48.08837924859138,0.0 118.67661454270903,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"104\" x2=\"118\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"118\" y1=\"70\" x2=\"118\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 118.67661454270903,70.58823529411765 118.67661454270903,104.53348012265594 80.58823529411765,104.53348012265594\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"99.632425\" y=\"124.533480\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1440</text>\n",
       "  <text x=\"138.676615\" y=\"87.560858\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,138.676615,87.560858)\">720</text>\n",
       "  <text x=\"35.294118\" y=\"89.239362\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,89.239362)\">15767</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>freqbandID</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 720, 1440), meta=np.ndarray&gt;</div><input id='attrs-533ea259-efe8-46ed-9b13-7d7415730565' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-533ea259-efe8-46ed-9b13-7d7415730565' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c92339e4-a478-47d3-aa71-7b98b42b400a' class='xr-var-data-in' type='checkbox'><label for='data-c92339e4-a478-47d3-aa71-7b98b42b400a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxes :</span></dt><dd>time lat lon</dd><dt><span>bit_meanings :</span></dt><dd>[&#x27;NaN&#x27;, &#x27;L14&#x27;, &#x27;C53&#x27;, &#x27;C66&#x27;, &#x27;C68&#x27;, &#x27;C69&#x27;, &#x27;C73&#x27;, &#x27;X107&#x27;, &#x27;K194&#x27;, &#x27;MODEL&#x27;]</dd><dt><span>bits :</span></dt><dd>[&#x27;0b0&#x27;, &#x27;0b1&#x27;, &#x27;0b10&#x27;, &#x27;0b100&#x27;, &#x27;0b1000&#x27;, &#x27;0b10000&#x27;, &#x27;0b100000&#x27;, &#x27;0b1000000&#x27;, &#x27;0b10000000&#x27;, &#x27;0b100000000&#x27;]</dd><dt><span>dtype :</span></dt><dd>int16</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;NaN&#x27;, &#x27;C66&#x27;, &#x27;X107&#x27;, &#x27;C66+X107&#x27;]</dd><dt><span>flag_values :</span></dt><dd>[0, 4, 64, 68]</dd><dt><span>long_name :</span></dt><dd>Frequency Band Identification</dd><dt><span>valid_range :</span></dt><dd>[0, 511]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 60.90 GiB </td>\n",
       "                        <td> 3.96 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (15767, 720, 1440) </td>\n",
       "                        <td> (1, 720, 1440) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 15767 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"168\" height=\"154\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"33\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"33\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"37\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"41\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"45\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"48\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"52\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"56\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"36\" y2=\"59\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"63\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"67\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"71\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"74\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"78\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"82\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"62\" y2=\"85\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"89\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"93\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"97\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"100\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,104.53348012265594 10.0,33.94524482853829\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"48\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"51\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"55\" y2=\"7\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"59\" y2=\"11\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"62\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"66\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"70\" y2=\"22\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"74\" y2=\"26\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"77\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"81\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"85\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"88\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"92\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"96\" y2=\"48\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"100\" y2=\"52\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"103\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"107\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"111\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"114\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"48\" y1=\"0\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 48.08837924859138,0.0 118.67661454270903,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"104\" x2=\"118\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"118\" y1=\"70\" x2=\"118\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 118.67661454270903,70.58823529411765 118.67661454270903,104.53348012265594 80.58823529411765,104.53348012265594\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"99.632425\" y=\"124.533480\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1440</text>\n",
       "  <text x=\"138.676615\" y=\"87.560858\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,138.676615,87.560858)\">720</text>\n",
       "  <text x=\"35.294118\" y=\"89.239362\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,89.239362)\">15767</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mode</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 720, 1440), meta=np.ndarray&gt;</div><input id='attrs-b9ad4199-40c5-485f-a61a-432efec57166' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b9ad4199-40c5-485f-a61a-432efec57166' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ee81f10-4c00-48e9-bf44-2ab40f25a461' class='xr-var-data-in' type='checkbox'><label for='data-4ee81f10-4c00-48e9-bf44-2ab40f25a461' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxes :</span></dt><dd>time lat lon</dd><dt><span>bit_meanings :</span></dt><dd>[&#x27;NaN&#x27;, &#x27;ascending&#x27;, &#x27;descending&#x27;]</dd><dt><span>bits :</span></dt><dd>[&#x27;0b0&#x27;, &#x27;0b1&#x27;, &#x27;0b10&#x27;]</dd><dt><span>dtype :</span></dt><dd>int8</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;NaN&#x27;, &#x27;ascending&#x27;, &#x27;descending&#x27;, &#x27;ascending_descending_combination&#x27;]</dd><dt><span>flag_values :</span></dt><dd>[0, 1, 2, 3]</dd><dt><span>long_name :</span></dt><dd>Satellite Mode</dd><dt><span>valid_range :</span></dt><dd>[0, 3]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 60.90 GiB </td>\n",
       "                        <td> 3.96 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (15767, 720, 1440) </td>\n",
       "                        <td> (1, 720, 1440) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 15767 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"168\" height=\"154\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"33\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"33\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"37\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"41\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"45\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"48\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"52\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"56\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"36\" y2=\"59\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"63\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"67\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"71\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"74\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"78\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"82\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"62\" y2=\"85\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"89\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"93\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"97\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"100\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,104.53348012265594 10.0,33.94524482853829\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"48\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"51\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"55\" y2=\"7\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"59\" y2=\"11\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"62\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"66\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"70\" y2=\"22\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"74\" y2=\"26\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"77\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"81\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"85\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"88\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"92\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"96\" y2=\"48\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"100\" y2=\"52\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"103\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"107\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"111\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"114\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"48\" y1=\"0\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 48.08837924859138,0.0 118.67661454270903,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"104\" x2=\"118\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"118\" y1=\"70\" x2=\"118\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 118.67661454270903,70.58823529411765 118.67661454270903,104.53348012265594 80.58823529411765,104.53348012265594\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"99.632425\" y=\"124.533480\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1440</text>\n",
       "  <text x=\"138.676615\" y=\"87.560858\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,138.676615,87.560858)\">720</text>\n",
       "  <text x=\"35.294118\" y=\"89.239362\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,89.239362)\">15767</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sensor</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 720, 1440), meta=np.ndarray&gt;</div><input id='attrs-d71a2649-343f-4750-9780-164a7d7487f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d71a2649-343f-4750-9780-164a7d7487f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b93ee088-c750-42bb-b65e-faa909d66222' class='xr-var-data-in' type='checkbox'><label for='data-b93ee088-c750-42bb-b65e-faa909d66222' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxes :</span></dt><dd>time lat lon</dd><dt><span>bit_meanings :</span></dt><dd>[&#x27;NaN&#x27;, &#x27;SMMR&#x27;, &#x27;SSMI&#x27;, &#x27;TMI&#x27;, &#x27;AMSRE&#x27;, &#x27;WindSat&#x27;, &#x27;AMSR2&#x27;, &#x27;SMOS&#x27;, &#x27;AMIWS&#x27;, &#x27;ASCATA&#x27;, &#x27;ASCATB&#x27;, &#x27;SMAP&#x27;, &#x27;MODEL&#x27;, &#x27;GPM&#x27;, &#x27;FY3B&#x27;, &#x27;FY3D&#x27;, &#x27;ASCATC&#x27;, &#x27;FY3C&#x27;]</dd><dt><span>bits :</span></dt><dd>[&#x27;0b0&#x27;, &#x27;0b1&#x27;, &#x27;0b10&#x27;, &#x27;0b100&#x27;, &#x27;0b1000&#x27;, &#x27;0b10000&#x27;, &#x27;0b100000&#x27;, &#x27;0b1000000&#x27;, &#x27;0b10000000&#x27;, &#x27;0b100000000&#x27;, &#x27;0b1000000000&#x27;, &#x27;0b10000000000&#x27;, &#x27;0b100000000000&#x27;, &#x27;0b1000000000000&#x27;, &#x27;0b10000000000000&#x27;, &#x27;0b100000000000000&#x27;, &#x27;0b1000000000000000&#x27;, &#x27;0b10000000000000000&#x27;]</dd><dt><span>dtype :</span></dt><dd>int32</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;NaN&#x27;, &#x27;SMMR&#x27;]</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>long_name :</span></dt><dd>Sensor</dd><dt><span>valid_range :</span></dt><dd>[0, 131071]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 121.80 GiB </td>\n",
       "                        <td> 7.91 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (15767, 720, 1440) </td>\n",
       "                        <td> (1, 720, 1440) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 15767 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"168\" height=\"154\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"33\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"33\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"37\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"41\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"45\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"48\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"52\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"56\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"36\" y2=\"59\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"63\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"67\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"71\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"74\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"78\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"82\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"62\" y2=\"85\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"89\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"93\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"97\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"100\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,104.53348012265594 10.0,33.94524482853829\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"48\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"51\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"55\" y2=\"7\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"59\" y2=\"11\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"62\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"66\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"70\" y2=\"22\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"74\" y2=\"26\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"77\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"81\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"85\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"88\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"92\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"96\" y2=\"48\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"100\" y2=\"52\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"103\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"107\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"111\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"114\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"48\" y1=\"0\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 48.08837924859138,0.0 118.67661454270903,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"104\" x2=\"118\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"118\" y1=\"70\" x2=\"118\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 118.67661454270903,70.58823529411765 118.67661454270903,104.53348012265594 80.58823529411765,104.53348012265594\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"99.632425\" y=\"124.533480\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1440</text>\n",
       "  <text x=\"138.676615\" y=\"87.560858\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,138.676615,87.560858)\">720</text>\n",
       "  <text x=\"35.294118\" y=\"89.239362\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,89.239362)\">15767</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sm</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 720, 1440), meta=np.ndarray&gt;</div><input id='attrs-71a0a4cb-6b80-4fe1-877a-e481446d4351' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-71a0a4cb-6b80-4fe1-877a-e481446d4351' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f134857d-efdf-4195-a2a6-08c01d1dc632' class='xr-var-data-in' type='checkbox'><label for='data-f134857d-efdf-4195-a2a6-08c01d1dc632' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxes :</span></dt><dd>time lat lon</dd><dt><span>ancillary_variables :</span></dt><dd>sm_uncertainty flag t0</dd><dt><span>dtype :</span></dt><dd>float32</dd><dt><span>long_name :</span></dt><dd>Volumetric Soil Moisture</dd><dt><span>standard_name :</span></dt><dd>soil_moisture_content</dd><dt><span>units :</span></dt><dd>m3 m-3</dd><dt><span>valid_range :</span></dt><dd>[0.0, 1.0]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 60.90 GiB </td>\n",
       "                        <td> 3.96 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (15767, 720, 1440) </td>\n",
       "                        <td> (1, 720, 1440) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 15767 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"168\" height=\"154\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"33\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"33\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"37\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"41\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"45\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"48\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"52\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"56\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"36\" y2=\"59\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"63\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"67\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"71\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"74\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"78\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"82\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"62\" y2=\"85\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"89\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"93\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"97\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"100\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,104.53348012265594 10.0,33.94524482853829\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"48\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"51\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"55\" y2=\"7\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"59\" y2=\"11\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"62\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"66\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"70\" y2=\"22\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"74\" y2=\"26\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"77\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"81\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"85\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"88\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"92\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"96\" y2=\"48\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"100\" y2=\"52\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"103\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"107\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"111\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"114\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"48\" y1=\"0\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 48.08837924859138,0.0 118.67661454270903,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"104\" x2=\"118\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"118\" y1=\"70\" x2=\"118\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 118.67661454270903,70.58823529411765 118.67661454270903,104.53348012265594 80.58823529411765,104.53348012265594\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"99.632425\" y=\"124.533480\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1440</text>\n",
       "  <text x=\"138.676615\" y=\"87.560858\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,138.676615,87.560858)\">720</text>\n",
       "  <text x=\"35.294118\" y=\"89.239362\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,89.239362)\">15767</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sm_uncertainty</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 720, 1440), meta=np.ndarray&gt;</div><input id='attrs-fb08caf7-2b1a-42e6-a517-de8cb5d85fa9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb08caf7-2b1a-42e6-a517-de8cb5d85fa9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3dd4e9ca-32d0-4cc8-b885-3dadf88774a4' class='xr-var-data-in' type='checkbox'><label for='data-3dd4e9ca-32d0-4cc8-b885-3dadf88774a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxes :</span></dt><dd>time lat lon</dd><dt><span>dtype :</span></dt><dd>float32</dd><dt><span>long_name :</span></dt><dd>Volumetric Soil Moisture Uncertainty</dd><dt><span>standard_name :</span></dt><dd>soil_moisture_content standard_error</dd><dt><span>units :</span></dt><dd>m3 m-3</dd><dt><span>valid_range :</span></dt><dd>[0.0, 1.0]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 60.90 GiB </td>\n",
       "                        <td> 3.96 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (15767, 720, 1440) </td>\n",
       "                        <td> (1, 720, 1440) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 15767 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"168\" height=\"154\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"33\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"33\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"37\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"41\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"45\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"48\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"52\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"56\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"36\" y2=\"59\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"63\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"67\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"71\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"74\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"78\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"82\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"62\" y2=\"85\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"89\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"93\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"97\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"100\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,104.53348012265594 10.0,33.94524482853829\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"48\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"51\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"55\" y2=\"7\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"59\" y2=\"11\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"62\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"66\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"70\" y2=\"22\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"74\" y2=\"26\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"77\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"81\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"85\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"88\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"92\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"96\" y2=\"48\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"100\" y2=\"52\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"103\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"107\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"111\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"114\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"48\" y1=\"0\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 48.08837924859138,0.0 118.67661454270903,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"104\" x2=\"118\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"118\" y1=\"70\" x2=\"118\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 118.67661454270903,70.58823529411765 118.67661454270903,104.53348012265594 80.58823529411765,104.53348012265594\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"99.632425\" y=\"124.533480\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1440</text>\n",
       "  <text x=\"138.676615\" y=\"87.560858\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,138.676615,87.560858)\">720</text>\n",
       "  <text x=\"35.294118\" y=\"89.239362\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,89.239362)\">15767</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t0</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 720, 1440), meta=np.ndarray&gt;</div><input id='attrs-7c34a059-f0a0-4534-aa62-f707077916c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c34a059-f0a0-4534-aa62-f707077916c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56465fd7-8ddb-4947-b82b-240482ea6211' class='xr-var-data-in' type='checkbox'><label for='data-56465fd7-8ddb-4947-b82b-240482ea6211' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxes :</span></dt><dd>time lat lon</dd><dt><span>dtype :</span></dt><dd>float64</dd><dt><span>long_name :</span></dt><dd>Observation Timestamp</dd><dt><span>valid_range :</span></dt><dd>[3225.0, 3227.0]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 121.80 GiB </td>\n",
       "                        <td> 7.91 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (15767, 720, 1440) </td>\n",
       "                        <td> (1, 720, 1440) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 15767 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> datetime64[ns] numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"168\" height=\"154\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"33\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"33\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"37\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"41\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"45\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"48\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"52\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"56\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"36\" y2=\"59\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"63\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"67\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"71\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"74\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"78\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"82\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"62\" y2=\"85\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"89\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"93\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"97\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"100\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,104.53348012265594 10.0,33.94524482853829\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"48\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"51\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"55\" y2=\"7\" />\n",
       "  <line x1=\"21\" y1=\"11\" x2=\"59\" y2=\"11\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"62\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"66\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"70\" y2=\"22\" />\n",
       "  <line x1=\"36\" y1=\"26\" x2=\"74\" y2=\"26\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"77\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"81\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"85\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"88\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"92\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"96\" y2=\"48\" />\n",
       "  <line x1=\"62\" y1=\"52\" x2=\"100\" y2=\"52\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"103\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"107\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"111\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"114\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"48\" y1=\"0\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 48.08837924859138,0.0 118.67661454270903,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"118\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"104\" x2=\"118\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"118\" y1=\"70\" x2=\"118\" y2=\"104\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 118.67661454270903,70.58823529411765 118.67661454270903,104.53348012265594 80.58823529411765,104.53348012265594\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"99.632425\" y=\"124.533480\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1440</text>\n",
       "  <text x=\"138.676615\" y=\"87.560858\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,138.676615,87.560858)\">720</text>\n",
       "  <text x=\"35.294118\" y=\"89.239362\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,89.239362)\">15767</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-acefb9f6-ceb5-4348-9b73-0d9d966f31ab' class='xr-section-summary-in' type='checkbox'  ><label for='section-acefb9f6-ceb5-4348-9b73-0d9d966f31ab' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-46a65726-bc43-418a-a9d2-b5fc3f68960b' class='xr-index-data-in' type='checkbox'/><label for='index-46a65726-bc43-418a-a9d2-b5fc3f68960b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 89.875,  89.625,  89.375,  89.125,  88.875,  88.625,  88.375,  88.125,\n",
       "        87.875,  87.625,\n",
       "       ...\n",
       "       -87.625, -87.875, -88.125, -88.375, -88.625, -88.875, -89.125, -89.375,\n",
       "       -89.625, -89.875],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=720))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-80156547-2894-4f41-b037-9bcca8ade164' class='xr-index-data-in' type='checkbox'/><label for='index-80156547-2894-4f41-b037-9bcca8ade164' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-179.875, -179.625, -179.375, -179.125, -178.875, -178.625, -178.375,\n",
       "       -178.125, -177.875, -177.625,\n",
       "       ...\n",
       "        177.625,  177.875,  178.125,  178.375,  178.625,  178.875,  179.125,\n",
       "        179.375,  179.625,  179.875],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=1440))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7f534df3-6188-4e1b-8bb4-ff96c60d7402' class='xr-index-data-in' type='checkbox'/><label for='index-7f534df3-6188-4e1b-8bb4-ff96c60d7402' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1978-11-01&#x27;, &#x27;1978-11-02&#x27;, &#x27;1978-11-03&#x27;, &#x27;1978-11-04&#x27;,\n",
       "               &#x27;1978-11-05&#x27;, &#x27;1978-11-06&#x27;, &#x27;1978-11-07&#x27;, &#x27;1978-11-08&#x27;,\n",
       "               &#x27;1978-11-09&#x27;, &#x27;1978-11-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2021-12-22&#x27;, &#x27;2021-12-23&#x27;, &#x27;2021-12-24&#x27;, &#x27;2021-12-25&#x27;,\n",
       "               &#x27;2021-12-26&#x27;, &#x27;2021-12-27&#x27;, &#x27;2021-12-28&#x27;, &#x27;2021-12-29&#x27;,\n",
       "               &#x27;2021-12-30&#x27;, &#x27;2021-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=15767, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-063a46f5-1d30-44f5-a2e6-f71694d8bf8a' class='xr-section-summary-in' type='checkbox'  ><label for='section-063a46f5-1d30-44f5-a2e6-f71694d8bf8a' class='xr-section-summary' >Attributes: <span>(46)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.9</dd><dt><span>cdm_data_type :</span></dt><dd>Grid</dd><dt><span>comment :</span></dt><dd>This dataset was produced with funding of the ESA CCI+ Soil Moisture project; ESRIN Contract No: 4000126684/19/I-NB</dd><dt><span>contact :</span></dt><dd>cci_sm_contact@eodc.eu</dd><dt><span>creator_email :</span></dt><dd>cci_sm_developer@eodc.eu</dd><dt><span>creator_name :</span></dt><dd>Department of Geodesy and Geoinformation, Vienna University of Technology</dd><dt><span>creator_url :</span></dt><dd>https://climers.geo.tuwien.ac.at/</dd><dt><span>date_created :</span></dt><dd>File created: 2022-04-06 09:13:45.810237</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>geospatial_lat_min :</span></dt><dd>-90.0</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.25 degree</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_max :</span></dt><dd>180.0</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.25 degree</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_vertical_max :</span></dt><dd>0.0</dd><dt><span>geospatial_vertical_min :</span></dt><dd>0.0</dd><dt><span>history :</span></dt><dd>2022-04-06 09:12:42 - product produced\n",
       "Kerchunk file created on 26/09/23\n",
       "Kerchunk file last updated by CEDA on 03/10/23 in the context of the CCI Knowledge Exchange Project</dd><dt><span>id :</span></dt><dd>ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED-19781101-20211231-fv07.1</dd><dt><span>institution :</span></dt><dd>TU Wien (AUT); VanderSat B.V. (NL)</dd><dt><span>key_variables :</span></dt><dd>sm</dd><dt><span>keywords :</span></dt><dd>soil moisture, soil water content, microwave remote sensing, active, passive, combined, climate data record</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>license :</span></dt><dd>Data use is free and open for all registered users.</dd><dt><span>naming_authority :</span></dt><dd>TU Wien</dd><dt><span>platform :</span></dt><dd>Nimbus 7, DMSP, TRMM, AQUA, Coriolis, GCOM-W1, MIRAS, SMAP, GPM, FengYun-3B, FengYun-3C, FengYun-3D; ERS-1, ERS-2, METOP-A, METOP-B</dd><dt><span>processing_level :</span></dt><dd>Quality-controlled, super-collocated (L3S) Satellite Soil Moisture (SM) data from multiple sensors</dd><dt><span>product_version :</span></dt><dd>v07.1</dd><dt><span>project :</span></dt><dd>Climate Change Initiative - European Space Agency</dd><dt><span>references :</span></dt><dd>http://www.esa-soilmoisture-cci.org; Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F.,  Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017) ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001; Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., Dorigo, W. (2019) Evolution of the ESA CCI Soil Moisture Climate Data Records and their underlying merging methodology. Earth System Science Data 11, 717-739, https://doi.org/10.5194/essd-11-717-2019; Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. https://doi.org/10.1109/TGRS.2017.2734070</dd><dt><span>sensor :</span></dt><dd>SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS, SMAP_radiometer, GMI, VIRR-3B, VIRR-3C, VIRR-3D; AMI-WS, ASCAT-A, ASCAT-B, ASCAT-C</dd><dt><span>source :</span></dt><dd>WARP 5.5R1.1/AMI-WS/ERS12 Level 2 Soil Moisture; WARP 5.4R1.0/AMI-WS/ERS2 Level 2 Soil Moisture; H115: Metop ASCAT Surface Soil Moisture Climate Data Record v5 12.5 km sampling, DOI: 10.15770/EUM_SAF_H_0006; H116: Metop ASCAT Surface Soil Moisture Climate Data Record v5 Extension 12.5 km sampling; H115: Metop ASCAT Surface Soil Moisture Climate Data Record v5 12.5 km sampling, DOI: 10.15770/EUM_SAF_H_0006; H116: Metop ASCAT Surface Soil Moisture Climate Data Record v5 Extension 12.5 km sampling; H115: Metop ASCAT Surface Soil Moisture Climate Data Record v5 12.5 km sampling, DOI: 10.15770/EUM_SAF_H_0006; H116: Metop ASCAT Surface Soil Moisture Climate Data Record v5 Extension 12.5 km sampling;; LPRMv7/SMMR/Nimbus 7 L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv7/SSMI/F08, F11, F13 DMSP L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv7/TMI/TRMM L2 Surface Soil Moisture, Ancillary Params, and QC; LPRMv7/AMSR-E/Aqua L2B Surface Soil Moisture, Ancillary Params, and QC; LPRMv7/WINDSAT/CORIOLIS L2 Surface Soil Moisture, Ancillary Params, and QC; LPRMv7/AMSR2/GCOM-W1 L3 Surface Soil Moisture, Ancillary Params; LPRMv7/SMOS/MIRAS L3 Surface Soil Moisture, CATDS Level 3 Brightness Temperatures (L3TB) version 300 RE03 &amp; RE04; LPRMv7/SMAP_radiometer/SMAP L2 Surface Soil Moisture, Ancillary Params, and QC; LPRMv7/GMI/GPM L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv7/VIRR/FengYun-3B L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv7/VIRR/FengYun-3C L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv7/VIRR/FengYun-3D L3 Surface Soil Moisture, Ancillary Params, and quality flags;;</dd><dt><span>spatial_resolution :</span></dt><dd>25km</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF Standard Name Table v77</dd><dt><span>summary :</span></dt><dd>This dataset was produced with funding of the ESA CCI+ Soil Moisture project; ESRIN Contract No: 4000126684/19/I-NB</dd><dt><span>time_coverage_duration :</span></dt><dd>P43Y</dd><dt><span>time_coverage_end :</span></dt><dd>20211231T235959Z</dd><dt><span>time_coverage_end_product :</span></dt><dd>20211231T235959Z</dd><dt><span>time_coverage_resolution :</span></dt><dd>P1D</dd><dt><span>time_coverage_start :</span></dt><dd>19781101T000000Z</dd><dt><span>time_coverage_start_product :</span></dt><dd>19781101T000000Z</dd><dt><span>title :</span></dt><dd>ESA CCI Surface Soil Moisture COMBINED active+passive Product</dd><dt><span>tracking_id :</span></dt><dd>dc6ade2c-e51b-4a94-81fa-751df95a85a6</dd><dt><span>kerchunk_revision :</span></dt><dd>kr1.1</dd><dt><span>kerchunk_creation_date :</span></dt><dd>031023T093359</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 654GB\n",
       "Dimensions:         (time: 15767, lat: 720, lon: 1440)\n",
       "Coordinates:\n",
       "  * lat             (lat) float64 6kB 89.88 89.62 89.38 ... -89.38 -89.62 -89.88\n",
       "  * lon             (lon) float64 12kB -179.9 -179.6 -179.4 ... 179.6 179.9\n",
       "  * time            (time) datetime64[ns] 126kB 1978-11-01 ... 2021-12-31\n",
       "Data variables:\n",
       "    dnflag          (time, lat, lon) float32 65GB dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>\n",
       "    flag            (time, lat, lon) float32 65GB dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>\n",
       "    freqbandID      (time, lat, lon) float32 65GB dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>\n",
       "    mode            (time, lat, lon) float32 65GB dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>\n",
       "    sensor          (time, lat, lon) float64 131GB dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>\n",
       "    sm              (time, lat, lon) float32 65GB dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>\n",
       "    sm_uncertainty  (time, lat, lon) float32 65GB dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>\n",
       "    t0              (time, lat, lon) datetime64[ns] 131GB dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>\n",
       "Attributes: (12/46)\n",
       "    Conventions:                  CF-1.9\n",
       "    cdm_data_type:                Grid\n",
       "    comment:                      This dataset was produced with funding of t...\n",
       "    contact:                      cci_sm_contact@eodc.eu\n",
       "    creator_email:                cci_sm_developer@eodc.eu\n",
       "    creator_name:                 Department of Geodesy and Geoinformation, V...\n",
       "    ...                           ...\n",
       "    time_coverage_start:          19781101T000000Z\n",
       "    time_coverage_start_product:  19781101T000000Z\n",
       "    title:                        ESA CCI Surface Soil Moisture COMBINED acti...\n",
       "    tracking_id:                  dc6ade2c-e51b-4a94-81fa-751df95a85a6\n",
       "    kerchunk_revision:            kr1.1\n",
       "    kerchunk_creation_date:       031023T093359"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cube = kerchunk_store.open_data('ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED-19781101-20211231-fv07.1-kr1.1')\n",
    "cube"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Subsets of the data may easily be created like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "html[data-theme=dark],\n",
       "body[data-theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2GB\n",
       "Dimensions:         (time: 366, lat: 324, lon: 324)\n",
       "Coordinates:\n",
       "  * lat             (lat) float64 3kB 40.38 40.12 39.88 ... -39.88 -40.12 -40.38\n",
       "  * lon             (lon) float64 3kB -23.38 -23.12 -22.88 ... 56.88 57.12 57.38\n",
       "  * time            (time) datetime64[ns] 3kB 2000-01-01 ... 2000-12-31\n",
       "Data variables:\n",
       "    dnflag          (time, lat, lon) float32 154MB dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;\n",
       "    flag            (time, lat, lon) float32 154MB dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;\n",
       "    freqbandID      (time, lat, lon) float32 154MB dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;\n",
       "    mode            (time, lat, lon) float32 154MB dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;\n",
       "    sensor          (time, lat, lon) float64 307MB dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;\n",
       "    sm              (time, lat, lon) float32 154MB dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;\n",
       "    sm_uncertainty  (time, lat, lon) float32 154MB dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;\n",
       "    t0              (time, lat, lon) datetime64[ns] 307MB dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;\n",
       "Attributes: (12/46)\n",
       "    Conventions:                  CF-1.9\n",
       "    cdm_data_type:                Grid\n",
       "    comment:                      This dataset was produced with funding of t...\n",
       "    contact:                      cci_sm_contact@eodc.eu\n",
       "    creator_email:                cci_sm_developer@eodc.eu\n",
       "    creator_name:                 Department of Geodesy and Geoinformation, V...\n",
       "    ...                           ...\n",
       "    time_coverage_start:          19781101T000000Z\n",
       "    time_coverage_start_product:  19781101T000000Z\n",
       "    title:                        ESA CCI Surface Soil Moisture COMBINED acti...\n",
       "    tracking_id:                  dc6ade2c-e51b-4a94-81fa-751df95a85a6\n",
       "    kerchunk_revision:            kr1.1\n",
       "    kerchunk_creation_date:       031023T093359</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a49a6ebb-598f-41dc-aebd-1e18b1e5d359' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a49a6ebb-598f-41dc-aebd-1e18b1e5d359' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 366</li><li><span class='xr-has-index'>lat</span>: 324</li><li><span class='xr-has-index'>lon</span>: 324</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9c2e052b-9595-453d-a1cc-3651e9a980b1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9c2e052b-9595-453d-a1cc-3651e9a980b1' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>40.38 40.12 39.88 ... -40.12 -40.38</div><input id='attrs-a7dd8888-049a-4a0b-86f2-349fc5f34609' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a7dd8888-049a-4a0b-86f2-349fc5f34609' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2b5e764-fed9-4924-bd51-03707e54b90d' class='xr-var-data-in' type='checkbox'><label for='data-a2b5e764-fed9-4924-bd51-03707e54b90d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_range :</span></dt><dd>[-90.0, 90.0]</dd></dl></div><div class='xr-var-data'><pre>array([ 40.375,  40.125,  39.875, ..., -39.875, -40.125, -40.375])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-23.38 -23.12 ... 57.12 57.38</div><input id='attrs-3d559f9f-5e29-463e-81bc-50cfe1e5abc8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d559f9f-5e29-463e-81bc-50cfe1e5abc8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd6962f3-fd27-435f-b6f7-416041043c0f' class='xr-var-data-in' type='checkbox'><label for='data-fd6962f3-fd27-435f-b6f7-416041043c0f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_range :</span></dt><dd>[-180.0, 180.0]</dd></dl></div><div class='xr-var-data'><pre>array([-23.375, -23.125, -22.875, ...,  56.875,  57.125,  57.375])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-01-01 ... 2000-12-31</div><input id='attrs-f346b284-7080-4a49-b068-adf906218437' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f346b284-7080-4a49-b068-adf906218437' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64cd947e-1383-41d6-95c6-dcf7244d168d' class='xr-var-data-in' type='checkbox'><label for='data-64cd947e-1383-41d6-95c6-dcf7244d168d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2000-01-01T00:00:00.000000000&#x27;, &#x27;2000-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-01-03T00:00:00.000000000&#x27;, ..., &#x27;2000-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-12-30T00:00:00.000000000&#x27;, &#x27;2000-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-67ecbaf9-00ac-4d60-95eb-302ba1d3e7dd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-67ecbaf9-00ac-4d60-95eb-302ba1d3e7dd' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>dnflag</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;</div><input id='attrs-8227a4ed-539d-422c-ab29-c868510339af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8227a4ed-539d-422c-ab29-c868510339af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4af196b-18ad-40aa-aeb3-99425bb67583' class='xr-var-data-in' type='checkbox'><label for='data-a4af196b-18ad-40aa-aeb3-99425bb67583' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxes :</span></dt><dd>time lat lon</dd><dt><span>bit_meanings :</span></dt><dd>[&#x27;NaN&#x27;, &#x27;day&#x27;, &#x27;night&#x27;]</dd><dt><span>bits :</span></dt><dd>[&#x27;0b0&#x27;, &#x27;0b1&#x27;, &#x27;0b10&#x27;]</dd><dt><span>dtype :</span></dt><dd>int8</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;NaN&#x27;, &#x27;day&#x27;, &#x27;night&#x27;, &#x27;day_night_combination&#x27;]</dd><dt><span>flag_values :</span></dt><dd>[0, 1, 2, 3]</dd><dt><span>long_name :</span></dt><dd>Day / Night Flag</dd><dt><span>valid_range :</span></dt><dd>[0, 3]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 146.57 MiB </td>\n",
       "                        <td> 410.06 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (366, 324, 324) </td>\n",
       "                        <td> (1, 324, 324) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 366 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"236\" height=\"226\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"106\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"106\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"109\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"113\" />\n",
       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"117\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"121\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"124\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"128\" />\n",
       "  <line x1=\"35\" y1=\"25\" x2=\"35\" y2=\"132\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"135\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"139\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"143\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"146\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"150\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"154\" />\n",
       "  <line x1=\"61\" y1=\"51\" x2=\"61\" y2=\"158\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"161\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"165\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"169\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"172\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,176.81774349083895 10.0,106.22950819672131\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"116\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"119\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"123\" y2=\"7\" />\n",
       "  <line x1=\"20\" y1=\"10\" x2=\"127\" y2=\"10\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"131\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"134\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"138\" y2=\"22\" />\n",
       "  <line x1=\"35\" y1=\"25\" x2=\"142\" y2=\"25\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"145\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"149\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"153\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"156\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"160\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"164\" y2=\"48\" />\n",
       "  <line x1=\"61\" y1=\"51\" x2=\"168\" y2=\"51\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"171\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"175\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"179\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"182\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"116\" y1=\"0\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 116.22950819672131,0.0 186.81774349083895,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"176\" x2=\"186\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"186\" y1=\"70\" x2=\"186\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 186.81774349083895,70.58823529411765 186.81774349083895,176.81774349083895 80.58823529411765,176.81774349083895\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"133.702989\" y=\"196.817743\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >324</text>\n",
       "  <text x=\"206.817743\" y=\"123.702989\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,206.817743,123.702989)\">324</text>\n",
       "  <text x=\"35.294118\" y=\"161.523626\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,161.523626)\">366</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;</div><input id='attrs-fd71b21f-3da0-4507-921f-8e5edea9693f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd71b21f-3da0-4507-921f-8e5edea9693f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-950f250d-d4ea-497b-986b-57f962ae0ace' class='xr-var-data-in' type='checkbox'><label for='data-950f250d-d4ea-497b-986b-57f962ae0ace' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxes :</span></dt><dd>time lat lon</dd><dt><span>bit_meanings :</span></dt><dd>[&#x27;no_data_inconsistency_detected&#x27;, &#x27;snow_coverage_or_temperature_below_zero&#x27;, &#x27;dense_vegetation&#x27;, &#x27;others_no_convergence_in_the_model_thus_no_valid_sm_estimates&#x27;, &#x27;soil_moisture_value_exceeds_physical_boundary&#x27;, &#x27;weight_of_measurement_below_threshold&#x27;, &#x27;all_datasets_deemed_unreliable&#x27;, &#x27;barren_ground_advisory_flag&#x27;, &#x27;NaN&#x27;]</dd><dt><span>bits :</span></dt><dd>[&#x27;0b0&#x27;, &#x27;0b1&#x27;, &#x27;0b10&#x27;, &#x27;0b100&#x27;, &#x27;0b1000&#x27;, &#x27;0b10000&#x27;, &#x27;0b100000&#x27;, &#x27;0b1000000&#x27;, &#x27;0b10000000&#x27;]</dd><dt><span>dtype :</span></dt><dd>int16</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;no_data_inconsistency_detected&#x27;, &#x27;snow_coverage_or_temperature_below_zero&#x27;, &#x27;dense_vegetation&#x27;, &#x27;combination_of_flag_values_1_and_2&#x27;, &#x27;soil_moisture_value_exceeds_physical_boundary&#x27;, &#x27;combination_of_flag_values_1_and_8&#x27;, &#x27;combination_of_flag_values_2_and_8&#x27;, &#x27;barren_ground_advisory_flag&#x27;, &#x27;combination_of_flag_values_1_and_64&#x27;, &#x27;combination_of_flag_values_2_and_64&#x27;, &#x27;combination_of_flag_values_1_and_2_and_64&#x27;, &#x27;combination_of_flag_values_8_and_64&#x27;, &#x27;combination_of_flag_values_1_and_8_and_64&#x27;, &#x27;combination_of_flag_values_2_and_8_and_64&#x27;, &#x27;combination_of_flag_values_1_and_2_and_4_and_8_and_16_and_32_and_64&#x27;]</dd><dt><span>flag_values :</span></dt><dd>[0, 1, 2, 3, 8, 9, 10, 64, 65, 66, 67, 72, 73, 74, 127]</dd><dt><span>long_name :</span></dt><dd>Flag</dd><dt><span>standard_name :</span></dt><dd>soil_moisture_content status_flag</dd><dt><span>valid_range :</span></dt><dd>[0, 255]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 146.57 MiB </td>\n",
       "                        <td> 410.06 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (366, 324, 324) </td>\n",
       "                        <td> (1, 324, 324) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 366 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"236\" height=\"226\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"106\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"106\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"109\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"113\" />\n",
       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"117\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"121\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"124\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"128\" />\n",
       "  <line x1=\"35\" y1=\"25\" x2=\"35\" y2=\"132\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"135\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"139\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"143\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"146\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"150\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"154\" />\n",
       "  <line x1=\"61\" y1=\"51\" x2=\"61\" y2=\"158\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"161\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"165\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"169\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"172\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,176.81774349083895 10.0,106.22950819672131\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"116\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"119\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"123\" y2=\"7\" />\n",
       "  <line x1=\"20\" y1=\"10\" x2=\"127\" y2=\"10\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"131\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"134\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"138\" y2=\"22\" />\n",
       "  <line x1=\"35\" y1=\"25\" x2=\"142\" y2=\"25\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"145\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"149\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"153\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"156\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"160\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"164\" y2=\"48\" />\n",
       "  <line x1=\"61\" y1=\"51\" x2=\"168\" y2=\"51\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"171\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"175\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"179\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"182\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"116\" y1=\"0\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 116.22950819672131,0.0 186.81774349083895,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"176\" x2=\"186\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"186\" y1=\"70\" x2=\"186\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 186.81774349083895,70.58823529411765 186.81774349083895,176.81774349083895 80.58823529411765,176.81774349083895\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"133.702989\" y=\"196.817743\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >324</text>\n",
       "  <text x=\"206.817743\" y=\"123.702989\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,206.817743,123.702989)\">324</text>\n",
       "  <text x=\"35.294118\" y=\"161.523626\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,161.523626)\">366</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>freqbandID</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;</div><input id='attrs-e10a5077-3520-44da-bffd-8769d087c834' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e10a5077-3520-44da-bffd-8769d087c834' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-416e9105-a4fa-4a71-a61f-4ac30b008c8d' class='xr-var-data-in' type='checkbox'><label for='data-416e9105-a4fa-4a71-a61f-4ac30b008c8d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxes :</span></dt><dd>time lat lon</dd><dt><span>bit_meanings :</span></dt><dd>[&#x27;NaN&#x27;, &#x27;L14&#x27;, &#x27;C53&#x27;, &#x27;C66&#x27;, &#x27;C68&#x27;, &#x27;C69&#x27;, &#x27;C73&#x27;, &#x27;X107&#x27;, &#x27;K194&#x27;, &#x27;MODEL&#x27;]</dd><dt><span>bits :</span></dt><dd>[&#x27;0b0&#x27;, &#x27;0b1&#x27;, &#x27;0b10&#x27;, &#x27;0b100&#x27;, &#x27;0b1000&#x27;, &#x27;0b10000&#x27;, &#x27;0b100000&#x27;, &#x27;0b1000000&#x27;, &#x27;0b10000000&#x27;, &#x27;0b100000000&#x27;]</dd><dt><span>dtype :</span></dt><dd>int16</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;NaN&#x27;, &#x27;C66&#x27;, &#x27;X107&#x27;, &#x27;C66+X107&#x27;]</dd><dt><span>flag_values :</span></dt><dd>[0, 4, 64, 68]</dd><dt><span>long_name :</span></dt><dd>Frequency Band Identification</dd><dt><span>valid_range :</span></dt><dd>[0, 511]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 146.57 MiB </td>\n",
       "                        <td> 410.06 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (366, 324, 324) </td>\n",
       "                        <td> (1, 324, 324) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 366 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"236\" height=\"226\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"106\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"106\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"109\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"113\" />\n",
       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"117\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"121\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"124\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"128\" />\n",
       "  <line x1=\"35\" y1=\"25\" x2=\"35\" y2=\"132\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"135\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"139\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"143\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"146\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"150\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"154\" />\n",
       "  <line x1=\"61\" y1=\"51\" x2=\"61\" y2=\"158\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"161\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"165\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"169\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"172\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,176.81774349083895 10.0,106.22950819672131\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"116\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"119\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"123\" y2=\"7\" />\n",
       "  <line x1=\"20\" y1=\"10\" x2=\"127\" y2=\"10\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"131\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"134\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"138\" y2=\"22\" />\n",
       "  <line x1=\"35\" y1=\"25\" x2=\"142\" y2=\"25\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"145\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"149\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"153\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"156\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"160\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"164\" y2=\"48\" />\n",
       "  <line x1=\"61\" y1=\"51\" x2=\"168\" y2=\"51\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"171\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"175\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"179\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"182\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"116\" y1=\"0\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 116.22950819672131,0.0 186.81774349083895,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"176\" x2=\"186\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"186\" y1=\"70\" x2=\"186\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 186.81774349083895,70.58823529411765 186.81774349083895,176.81774349083895 80.58823529411765,176.81774349083895\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"133.702989\" y=\"196.817743\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >324</text>\n",
       "  <text x=\"206.817743\" y=\"123.702989\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,206.817743,123.702989)\">324</text>\n",
       "  <text x=\"35.294118\" y=\"161.523626\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,161.523626)\">366</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mode</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;</div><input id='attrs-619150bf-d7c9-4759-94cb-b5b56de25c6c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-619150bf-d7c9-4759-94cb-b5b56de25c6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5793626-c917-43cb-8045-49faf97eac61' class='xr-var-data-in' type='checkbox'><label for='data-f5793626-c917-43cb-8045-49faf97eac61' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxes :</span></dt><dd>time lat lon</dd><dt><span>bit_meanings :</span></dt><dd>[&#x27;NaN&#x27;, &#x27;ascending&#x27;, &#x27;descending&#x27;]</dd><dt><span>bits :</span></dt><dd>[&#x27;0b0&#x27;, &#x27;0b1&#x27;, &#x27;0b10&#x27;]</dd><dt><span>dtype :</span></dt><dd>int8</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;NaN&#x27;, &#x27;ascending&#x27;, &#x27;descending&#x27;, &#x27;ascending_descending_combination&#x27;]</dd><dt><span>flag_values :</span></dt><dd>[0, 1, 2, 3]</dd><dt><span>long_name :</span></dt><dd>Satellite Mode</dd><dt><span>valid_range :</span></dt><dd>[0, 3]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 146.57 MiB </td>\n",
       "                        <td> 410.06 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (366, 324, 324) </td>\n",
       "                        <td> (1, 324, 324) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 366 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"236\" height=\"226\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"106\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"106\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"109\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"113\" />\n",
       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"117\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"121\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"124\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"128\" />\n",
       "  <line x1=\"35\" y1=\"25\" x2=\"35\" y2=\"132\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"135\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"139\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"143\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"146\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"150\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"154\" />\n",
       "  <line x1=\"61\" y1=\"51\" x2=\"61\" y2=\"158\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"161\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"165\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"169\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"172\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,176.81774349083895 10.0,106.22950819672131\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"116\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"119\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"123\" y2=\"7\" />\n",
       "  <line x1=\"20\" y1=\"10\" x2=\"127\" y2=\"10\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"131\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"134\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"138\" y2=\"22\" />\n",
       "  <line x1=\"35\" y1=\"25\" x2=\"142\" y2=\"25\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"145\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"149\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"153\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"156\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"160\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"164\" y2=\"48\" />\n",
       "  <line x1=\"61\" y1=\"51\" x2=\"168\" y2=\"51\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"171\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"175\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"179\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"182\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"116\" y1=\"0\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 116.22950819672131,0.0 186.81774349083895,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"176\" x2=\"186\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"186\" y1=\"70\" x2=\"186\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 186.81774349083895,70.58823529411765 186.81774349083895,176.81774349083895 80.58823529411765,176.81774349083895\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"133.702989\" y=\"196.817743\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >324</text>\n",
       "  <text x=\"206.817743\" y=\"123.702989\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,206.817743,123.702989)\">324</text>\n",
       "  <text x=\"35.294118\" y=\"161.523626\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,161.523626)\">366</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sensor</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;</div><input id='attrs-4e88d36d-c29b-43a8-8f06-80e3d424e073' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e88d36d-c29b-43a8-8f06-80e3d424e073' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-174d37e5-9919-4deb-97b0-e95a5f8b3d8f' class='xr-var-data-in' type='checkbox'><label for='data-174d37e5-9919-4deb-97b0-e95a5f8b3d8f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxes :</span></dt><dd>time lat lon</dd><dt><span>bit_meanings :</span></dt><dd>[&#x27;NaN&#x27;, &#x27;SMMR&#x27;, &#x27;SSMI&#x27;, &#x27;TMI&#x27;, &#x27;AMSRE&#x27;, &#x27;WindSat&#x27;, &#x27;AMSR2&#x27;, &#x27;SMOS&#x27;, &#x27;AMIWS&#x27;, &#x27;ASCATA&#x27;, &#x27;ASCATB&#x27;, &#x27;SMAP&#x27;, &#x27;MODEL&#x27;, &#x27;GPM&#x27;, &#x27;FY3B&#x27;, &#x27;FY3D&#x27;, &#x27;ASCATC&#x27;, &#x27;FY3C&#x27;]</dd><dt><span>bits :</span></dt><dd>[&#x27;0b0&#x27;, &#x27;0b1&#x27;, &#x27;0b10&#x27;, &#x27;0b100&#x27;, &#x27;0b1000&#x27;, &#x27;0b10000&#x27;, &#x27;0b100000&#x27;, &#x27;0b1000000&#x27;, &#x27;0b10000000&#x27;, &#x27;0b100000000&#x27;, &#x27;0b1000000000&#x27;, &#x27;0b10000000000&#x27;, &#x27;0b100000000000&#x27;, &#x27;0b1000000000000&#x27;, &#x27;0b10000000000000&#x27;, &#x27;0b100000000000000&#x27;, &#x27;0b1000000000000000&#x27;, &#x27;0b10000000000000000&#x27;]</dd><dt><span>dtype :</span></dt><dd>int32</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;NaN&#x27;, &#x27;SMMR&#x27;]</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>long_name :</span></dt><dd>Sensor</dd><dt><span>valid_range :</span></dt><dd>[0, 131071]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 293.13 MiB </td>\n",
       "                        <td> 820.12 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (366, 324, 324) </td>\n",
       "                        <td> (1, 324, 324) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 366 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"236\" height=\"226\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"106\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"106\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"109\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"113\" />\n",
       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"117\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"121\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"124\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"128\" />\n",
       "  <line x1=\"35\" y1=\"25\" x2=\"35\" y2=\"132\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"135\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"139\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"143\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"146\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"150\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"154\" />\n",
       "  <line x1=\"61\" y1=\"51\" x2=\"61\" y2=\"158\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"161\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"165\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"169\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"172\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,176.81774349083895 10.0,106.22950819672131\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"116\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"119\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"123\" y2=\"7\" />\n",
       "  <line x1=\"20\" y1=\"10\" x2=\"127\" y2=\"10\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"131\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"134\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"138\" y2=\"22\" />\n",
       "  <line x1=\"35\" y1=\"25\" x2=\"142\" y2=\"25\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"145\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"149\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"153\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"156\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"160\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"164\" y2=\"48\" />\n",
       "  <line x1=\"61\" y1=\"51\" x2=\"168\" y2=\"51\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"171\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"175\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"179\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"182\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"116\" y1=\"0\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 116.22950819672131,0.0 186.81774349083895,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"176\" x2=\"186\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"186\" y1=\"70\" x2=\"186\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 186.81774349083895,70.58823529411765 186.81774349083895,176.81774349083895 80.58823529411765,176.81774349083895\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"133.702989\" y=\"196.817743\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >324</text>\n",
       "  <text x=\"206.817743\" y=\"123.702989\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,206.817743,123.702989)\">324</text>\n",
       "  <text x=\"35.294118\" y=\"161.523626\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,161.523626)\">366</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sm</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;</div><input id='attrs-a51303e6-e248-4d3f-8a7e-bce98a31b2b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a51303e6-e248-4d3f-8a7e-bce98a31b2b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d60c8e1-7028-453f-a896-464274de56ca' class='xr-var-data-in' type='checkbox'><label for='data-6d60c8e1-7028-453f-a896-464274de56ca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxes :</span></dt><dd>time lat lon</dd><dt><span>ancillary_variables :</span></dt><dd>sm_uncertainty flag t0</dd><dt><span>dtype :</span></dt><dd>float32</dd><dt><span>long_name :</span></dt><dd>Volumetric Soil Moisture</dd><dt><span>standard_name :</span></dt><dd>soil_moisture_content</dd><dt><span>units :</span></dt><dd>m3 m-3</dd><dt><span>valid_range :</span></dt><dd>[0.0, 1.0]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 146.57 MiB </td>\n",
       "                        <td> 410.06 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (366, 324, 324) </td>\n",
       "                        <td> (1, 324, 324) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 366 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"236\" height=\"226\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"106\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"106\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"109\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"113\" />\n",
       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"117\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"121\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"124\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"128\" />\n",
       "  <line x1=\"35\" y1=\"25\" x2=\"35\" y2=\"132\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"135\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"139\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"143\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"146\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"150\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"154\" />\n",
       "  <line x1=\"61\" y1=\"51\" x2=\"61\" y2=\"158\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"161\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"165\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"169\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"172\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,176.81774349083895 10.0,106.22950819672131\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"116\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"119\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"123\" y2=\"7\" />\n",
       "  <line x1=\"20\" y1=\"10\" x2=\"127\" y2=\"10\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"131\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"134\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"138\" y2=\"22\" />\n",
       "  <line x1=\"35\" y1=\"25\" x2=\"142\" y2=\"25\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"145\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"149\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"153\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"156\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"160\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"164\" y2=\"48\" />\n",
       "  <line x1=\"61\" y1=\"51\" x2=\"168\" y2=\"51\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"171\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"175\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"179\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"182\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"116\" y1=\"0\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 116.22950819672131,0.0 186.81774349083895,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"176\" x2=\"186\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"186\" y1=\"70\" x2=\"186\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 186.81774349083895,70.58823529411765 186.81774349083895,176.81774349083895 80.58823529411765,176.81774349083895\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"133.702989\" y=\"196.817743\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >324</text>\n",
       "  <text x=\"206.817743\" y=\"123.702989\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,206.817743,123.702989)\">324</text>\n",
       "  <text x=\"35.294118\" y=\"161.523626\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,161.523626)\">366</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sm_uncertainty</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;</div><input id='attrs-9a57a247-1b7d-4d22-b27e-1f88da0a2dbe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a57a247-1b7d-4d22-b27e-1f88da0a2dbe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e79e45a-5b48-4619-ba90-37c2802498c4' class='xr-var-data-in' type='checkbox'><label for='data-7e79e45a-5b48-4619-ba90-37c2802498c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxes :</span></dt><dd>time lat lon</dd><dt><span>dtype :</span></dt><dd>float32</dd><dt><span>long_name :</span></dt><dd>Volumetric Soil Moisture Uncertainty</dd><dt><span>standard_name :</span></dt><dd>soil_moisture_content standard_error</dd><dt><span>units :</span></dt><dd>m3 m-3</dd><dt><span>valid_range :</span></dt><dd>[0.0, 1.0]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 146.57 MiB </td>\n",
       "                        <td> 410.06 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (366, 324, 324) </td>\n",
       "                        <td> (1, 324, 324) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 366 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"236\" height=\"226\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"106\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"106\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"109\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"113\" />\n",
       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"117\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"121\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"124\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"128\" />\n",
       "  <line x1=\"35\" y1=\"25\" x2=\"35\" y2=\"132\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"135\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"139\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"143\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"146\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"150\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"154\" />\n",
       "  <line x1=\"61\" y1=\"51\" x2=\"61\" y2=\"158\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"161\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"165\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"169\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"172\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,176.81774349083895 10.0,106.22950819672131\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"116\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"119\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"123\" y2=\"7\" />\n",
       "  <line x1=\"20\" y1=\"10\" x2=\"127\" y2=\"10\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"131\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"134\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"138\" y2=\"22\" />\n",
       "  <line x1=\"35\" y1=\"25\" x2=\"142\" y2=\"25\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"145\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"149\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"153\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"156\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"160\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"164\" y2=\"48\" />\n",
       "  <line x1=\"61\" y1=\"51\" x2=\"168\" y2=\"51\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"171\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"175\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"179\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"182\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"116\" y1=\"0\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 116.22950819672131,0.0 186.81774349083895,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"176\" x2=\"186\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"186\" y1=\"70\" x2=\"186\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 186.81774349083895,70.58823529411765 186.81774349083895,176.81774349083895 80.58823529411765,176.81774349083895\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"133.702989\" y=\"196.817743\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >324</text>\n",
       "  <text x=\"206.817743\" y=\"123.702989\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,206.817743,123.702989)\">324</text>\n",
       "  <text x=\"35.294118\" y=\"161.523626\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,161.523626)\">366</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t0</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;</div><input id='attrs-e5447852-5183-4140-b6a2-9130273ccce5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5447852-5183-4140-b6a2-9130273ccce5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93bd399f-9e1e-4324-be5e-01be31f72469' class='xr-var-data-in' type='checkbox'><label for='data-93bd399f-9e1e-4324-be5e-01be31f72469' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxes :</span></dt><dd>time lat lon</dd><dt><span>dtype :</span></dt><dd>float64</dd><dt><span>long_name :</span></dt><dd>Observation Timestamp</dd><dt><span>valid_range :</span></dt><dd>[3225.0, 3227.0]</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 293.13 MiB </td>\n",
       "                        <td> 820.12 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (366, 324, 324) </td>\n",
       "                        <td> (1, 324, 324) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 366 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> datetime64[ns] numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"236\" height=\"226\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"106\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"106\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"13\" y2=\"109\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"17\" y2=\"113\" />\n",
       "  <line x1=\"20\" y1=\"10\" x2=\"20\" y2=\"117\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"24\" y2=\"121\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"28\" y2=\"124\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"128\" />\n",
       "  <line x1=\"35\" y1=\"25\" x2=\"35\" y2=\"132\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"135\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"43\" y2=\"139\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"143\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"146\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"150\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"154\" />\n",
       "  <line x1=\"61\" y1=\"51\" x2=\"61\" y2=\"158\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"65\" y2=\"161\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"69\" y2=\"165\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"73\" y2=\"169\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"172\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,176.81774349083895 10.0,106.22950819672131\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"116\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"13\" y1=\"3\" x2=\"119\" y2=\"3\" />\n",
       "  <line x1=\"17\" y1=\"7\" x2=\"123\" y2=\"7\" />\n",
       "  <line x1=\"20\" y1=\"10\" x2=\"127\" y2=\"10\" />\n",
       "  <line x1=\"24\" y1=\"14\" x2=\"131\" y2=\"14\" />\n",
       "  <line x1=\"28\" y1=\"18\" x2=\"134\" y2=\"18\" />\n",
       "  <line x1=\"32\" y1=\"22\" x2=\"138\" y2=\"22\" />\n",
       "  <line x1=\"35\" y1=\"25\" x2=\"142\" y2=\"25\" />\n",
       "  <line x1=\"39\" y1=\"29\" x2=\"145\" y2=\"29\" />\n",
       "  <line x1=\"43\" y1=\"33\" x2=\"149\" y2=\"33\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"153\" y2=\"37\" />\n",
       "  <line x1=\"50\" y1=\"40\" x2=\"156\" y2=\"40\" />\n",
       "  <line x1=\"54\" y1=\"44\" x2=\"160\" y2=\"44\" />\n",
       "  <line x1=\"58\" y1=\"48\" x2=\"164\" y2=\"48\" />\n",
       "  <line x1=\"61\" y1=\"51\" x2=\"168\" y2=\"51\" />\n",
       "  <line x1=\"65\" y1=\"55\" x2=\"171\" y2=\"55\" />\n",
       "  <line x1=\"69\" y1=\"59\" x2=\"175\" y2=\"59\" />\n",
       "  <line x1=\"73\" y1=\"63\" x2=\"179\" y2=\"63\" />\n",
       "  <line x1=\"76\" y1=\"66\" x2=\"182\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"116\" y1=\"0\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 116.22950819672131,0.0 186.81774349083895,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"186\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"176\" x2=\"186\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"186\" y1=\"70\" x2=\"186\" y2=\"176\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 186.81774349083895,70.58823529411765 186.81774349083895,176.81774349083895 80.58823529411765,176.81774349083895\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"133.702989\" y=\"196.817743\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >324</text>\n",
       "  <text x=\"206.817743\" y=\"123.702989\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,206.817743,123.702989)\">324</text>\n",
       "  <text x=\"35.294118\" y=\"161.523626\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,161.523626)\">366</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-7c3213eb-0403-411c-83bf-c2b16d7a07ba' class='xr-section-summary-in' type='checkbox'  ><label for='section-7c3213eb-0403-411c-83bf-c2b16d7a07ba' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-58debda3-3ef4-4125-b16e-0ff9d1440a85' class='xr-index-data-in' type='checkbox'/><label for='index-58debda3-3ef4-4125-b16e-0ff9d1440a85' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 40.375,  40.125,  39.875,  39.625,  39.375,  39.125,  38.875,  38.625,\n",
       "        38.375,  38.125,\n",
       "       ...\n",
       "       -38.125, -38.375, -38.625, -38.875, -39.125, -39.375, -39.625, -39.875,\n",
       "       -40.125, -40.375],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=324))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ef1e1cfa-7174-43c6-aaf3-253c8b35a551' class='xr-index-data-in' type='checkbox'/><label for='index-ef1e1cfa-7174-43c6-aaf3-253c8b35a551' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-23.375, -23.125, -22.875, -22.625, -22.375, -22.125, -21.875, -21.625,\n",
       "       -21.375, -21.125,\n",
       "       ...\n",
       "        55.125,  55.375,  55.625,  55.875,  56.125,  56.375,  56.625,  56.875,\n",
       "        57.125,  57.375],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=324))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4d74d0bc-b402-49b6-949d-efa61967324d' class='xr-index-data-in' type='checkbox'/><label for='index-4d74d0bc-b402-49b6-949d-efa61967324d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2000-01-01&#x27;, &#x27;2000-01-02&#x27;, &#x27;2000-01-03&#x27;, &#x27;2000-01-04&#x27;,\n",
       "               &#x27;2000-01-05&#x27;, &#x27;2000-01-06&#x27;, &#x27;2000-01-07&#x27;, &#x27;2000-01-08&#x27;,\n",
       "               &#x27;2000-01-09&#x27;, &#x27;2000-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2000-12-22&#x27;, &#x27;2000-12-23&#x27;, &#x27;2000-12-24&#x27;, &#x27;2000-12-25&#x27;,\n",
       "               &#x27;2000-12-26&#x27;, &#x27;2000-12-27&#x27;, &#x27;2000-12-28&#x27;, &#x27;2000-12-29&#x27;,\n",
       "               &#x27;2000-12-30&#x27;, &#x27;2000-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=366, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0ed67f8f-d1af-4e9b-a69d-f2ec6abf1151' class='xr-section-summary-in' type='checkbox'  ><label for='section-0ed67f8f-d1af-4e9b-a69d-f2ec6abf1151' class='xr-section-summary' >Attributes: <span>(46)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.9</dd><dt><span>cdm_data_type :</span></dt><dd>Grid</dd><dt><span>comment :</span></dt><dd>This dataset was produced with funding of the ESA CCI+ Soil Moisture project; ESRIN Contract No: 4000126684/19/I-NB</dd><dt><span>contact :</span></dt><dd>cci_sm_contact@eodc.eu</dd><dt><span>creator_email :</span></dt><dd>cci_sm_developer@eodc.eu</dd><dt><span>creator_name :</span></dt><dd>Department of Geodesy and Geoinformation, Vienna University of Technology</dd><dt><span>creator_url :</span></dt><dd>https://climers.geo.tuwien.ac.at/</dd><dt><span>date_created :</span></dt><dd>File created: 2022-04-06 09:13:45.810237</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>geospatial_lat_min :</span></dt><dd>-90.0</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.25 degree</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_max :</span></dt><dd>180.0</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.25 degree</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_vertical_max :</span></dt><dd>0.0</dd><dt><span>geospatial_vertical_min :</span></dt><dd>0.0</dd><dt><span>history :</span></dt><dd>2022-04-06 09:12:42 - product produced\n",
       "Kerchunk file created on 26/09/23\n",
       "Kerchunk file last updated by CEDA on 03/10/23 in the context of the CCI Knowledge Exchange Project</dd><dt><span>id :</span></dt><dd>ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED-19781101-20211231-fv07.1</dd><dt><span>institution :</span></dt><dd>TU Wien (AUT); VanderSat B.V. (NL)</dd><dt><span>key_variables :</span></dt><dd>sm</dd><dt><span>keywords :</span></dt><dd>soil moisture, soil water content, microwave remote sensing, active, passive, combined, climate data record</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>license :</span></dt><dd>Data use is free and open for all registered users.</dd><dt><span>naming_authority :</span></dt><dd>TU Wien</dd><dt><span>platform :</span></dt><dd>Nimbus 7, DMSP, TRMM, AQUA, Coriolis, GCOM-W1, MIRAS, SMAP, GPM, FengYun-3B, FengYun-3C, FengYun-3D; ERS-1, ERS-2, METOP-A, METOP-B</dd><dt><span>processing_level :</span></dt><dd>Quality-controlled, super-collocated (L3S) Satellite Soil Moisture (SM) data from multiple sensors</dd><dt><span>product_version :</span></dt><dd>v07.1</dd><dt><span>project :</span></dt><dd>Climate Change Initiative - European Space Agency</dd><dt><span>references :</span></dt><dd>http://www.esa-soilmoisture-cci.org; Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F.,  Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017) ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001; Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., Dorigo, W. (2019) Evolution of the ESA CCI Soil Moisture Climate Data Records and their underlying merging methodology. Earth System Science Data 11, 717-739, https://doi.org/10.5194/essd-11-717-2019; Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. https://doi.org/10.1109/TGRS.2017.2734070</dd><dt><span>sensor :</span></dt><dd>SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS, SMAP_radiometer, GMI, VIRR-3B, VIRR-3C, VIRR-3D; AMI-WS, ASCAT-A, ASCAT-B, ASCAT-C</dd><dt><span>source :</span></dt><dd>WARP 5.5R1.1/AMI-WS/ERS12 Level 2 Soil Moisture; WARP 5.4R1.0/AMI-WS/ERS2 Level 2 Soil Moisture; H115: Metop ASCAT Surface Soil Moisture Climate Data Record v5 12.5 km sampling, DOI: 10.15770/EUM_SAF_H_0006; H116: Metop ASCAT Surface Soil Moisture Climate Data Record v5 Extension 12.5 km sampling; H115: Metop ASCAT Surface Soil Moisture Climate Data Record v5 12.5 km sampling, DOI: 10.15770/EUM_SAF_H_0006; H116: Metop ASCAT Surface Soil Moisture Climate Data Record v5 Extension 12.5 km sampling; H115: Metop ASCAT Surface Soil Moisture Climate Data Record v5 12.5 km sampling, DOI: 10.15770/EUM_SAF_H_0006; H116: Metop ASCAT Surface Soil Moisture Climate Data Record v5 Extension 12.5 km sampling;; LPRMv7/SMMR/Nimbus 7 L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv7/SSMI/F08, F11, F13 DMSP L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv7/TMI/TRMM L2 Surface Soil Moisture, Ancillary Params, and QC; LPRMv7/AMSR-E/Aqua L2B Surface Soil Moisture, Ancillary Params, and QC; LPRMv7/WINDSAT/CORIOLIS L2 Surface Soil Moisture, Ancillary Params, and QC; LPRMv7/AMSR2/GCOM-W1 L3 Surface Soil Moisture, Ancillary Params; LPRMv7/SMOS/MIRAS L3 Surface Soil Moisture, CATDS Level 3 Brightness Temperatures (L3TB) version 300 RE03 &amp; RE04; LPRMv7/SMAP_radiometer/SMAP L2 Surface Soil Moisture, Ancillary Params, and QC; LPRMv7/GMI/GPM L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv7/VIRR/FengYun-3B L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv7/VIRR/FengYun-3C L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv7/VIRR/FengYun-3D L3 Surface Soil Moisture, Ancillary Params, and quality flags;;</dd><dt><span>spatial_resolution :</span></dt><dd>25km</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF Standard Name Table v77</dd><dt><span>summary :</span></dt><dd>This dataset was produced with funding of the ESA CCI+ Soil Moisture project; ESRIN Contract No: 4000126684/19/I-NB</dd><dt><span>time_coverage_duration :</span></dt><dd>P43Y</dd><dt><span>time_coverage_end :</span></dt><dd>20211231T235959Z</dd><dt><span>time_coverage_end_product :</span></dt><dd>20211231T235959Z</dd><dt><span>time_coverage_resolution :</span></dt><dd>P1D</dd><dt><span>time_coverage_start :</span></dt><dd>19781101T000000Z</dd><dt><span>time_coverage_start_product :</span></dt><dd>19781101T000000Z</dd><dt><span>title :</span></dt><dd>ESA CCI Surface Soil Moisture COMBINED active+passive Product</dd><dt><span>tracking_id :</span></dt><dd>dc6ade2c-e51b-4a94-81fa-751df95a85a6</dd><dt><span>kerchunk_revision :</span></dt><dd>kr1.1</dd><dt><span>kerchunk_creation_date :</span></dt><dd>031023T093359</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 2GB\n",
       "Dimensions:         (time: 366, lat: 324, lon: 324)\n",
       "Coordinates:\n",
       "  * lat             (lat) float64 3kB 40.38 40.12 39.88 ... -39.88 -40.12 -40.38\n",
       "  * lon             (lon) float64 3kB -23.38 -23.12 -22.88 ... 56.88 57.12 57.38\n",
       "  * time            (time) datetime64[ns] 3kB 2000-01-01 ... 2000-12-31\n",
       "Data variables:\n",
       "    dnflag          (time, lat, lon) float32 154MB dask.array<chunksize=(1, 324, 324), meta=np.ndarray>\n",
       "    flag            (time, lat, lon) float32 154MB dask.array<chunksize=(1, 324, 324), meta=np.ndarray>\n",
       "    freqbandID      (time, lat, lon) float32 154MB dask.array<chunksize=(1, 324, 324), meta=np.ndarray>\n",
       "    mode            (time, lat, lon) float32 154MB dask.array<chunksize=(1, 324, 324), meta=np.ndarray>\n",
       "    sensor          (time, lat, lon) float64 307MB dask.array<chunksize=(1, 324, 324), meta=np.ndarray>\n",
       "    sm              (time, lat, lon) float32 154MB dask.array<chunksize=(1, 324, 324), meta=np.ndarray>\n",
       "    sm_uncertainty  (time, lat, lon) float32 154MB dask.array<chunksize=(1, 324, 324), meta=np.ndarray>\n",
       "    t0              (time, lat, lon) datetime64[ns] 307MB dask.array<chunksize=(1, 324, 324), meta=np.ndarray>\n",
       "Attributes: (12/46)\n",
       "    Conventions:                  CF-1.9\n",
       "    cdm_data_type:                Grid\n",
       "    comment:                      This dataset was produced with funding of t...\n",
       "    contact:                      cci_sm_contact@eodc.eu\n",
       "    creator_email:                cci_sm_developer@eodc.eu\n",
       "    creator_name:                 Department of Geodesy and Geoinformation, V...\n",
       "    ...                           ...\n",
       "    time_coverage_start:          19781101T000000Z\n",
       "    time_coverage_start_product:  19781101T000000Z\n",
       "    title:                        ESA CCI Surface Soil Moisture COMBINED acti...\n",
       "    tracking_id:                  dc6ade2c-e51b-4a94-81fa-751df95a85a6\n",
       "    kerchunk_revision:            kr1.1\n",
       "    kerchunk_creation_date:       031023T093359"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub_cube = cube.sel({\n",
    "    'lat': slice(40.40, -40.40),\n",
    "    'lon': slice(-23.40, 57.40),\n",
    "    'time': slice('2000-01-01', '2000-12-31')\n",
    "    }\n",
    ")\n",
    "sub_cube"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "... and we can plot the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f8472243080>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sub_cube.sm.sel(time='2000-07-01 12:00:00', method='nearest').plot.imshow(cmap='Greys_r', figsize=(8, 8))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}