ESA CCI Surface Soil Moisture COMBINED active+passive Product
Load in Python
from intake import open_catalog
cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/2012_ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED.yaml")
ds=cat.netcdf.read()Metadata
| title | ESA CCI Surface Soil Moisture COMBINED active+passive Product |
| location | /shared/land/CCI/daily_files/COMBINED/2012 |
| tags | global,satellite,daily |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/2012_ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED.yaml |
| last updated | 2021-09-02 |
Dataset Contents
<xarray.Dataset>
Dimensions: (lat: 720, lon: 1440, time: 366)
Coordinates:
* lat (lat) float64 89.88 89.62 89.38 ... -89.38 -89.62 -89.88
* time (time) int64 15340 15341 15342 15343 ... 15703 15704 15705
* lon (lon) float64 -179.9 -179.6 -179.4 ... 179.4 179.6 179.9
Data variables:
sm (time, lat, lon) float32 dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
sm_uncertainty (time, lat, lon) float32 dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
flag (time, lat, lon) float32 dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
freqbandID (time, lat, lon) float32 dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
dnflag (time, lat, lon) float32 dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
mode (time, lat, lon) float32 dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
sensor (time, lat, lon) float32 dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
t0 (time, lat, lon) float64 dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
Attributes:
title: ESA CCI Surface Soil Moisture COMBINED acti...
institution: Technical University of Vienna (AUT); Vande...
contact: cci_sm_contact@eodc.eu
source: WARP 5.5R1.1/AMI-WS/ERS12 Level 2 Soil Mois...
platform: Nimbus 7, DMSP, TRMM, AQUA, Coriolis, GCOM-...
sensor: SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, S...
references: http://www.esa-soilmoisture-cci.org; Dorigo...
product_version: v06.1
id: ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED-20120...
tracking_id: f721cb4e-b5b4-469f-ac28-a9de2e22622d
Conventions: CF-1.7
standard_name_vocabulary: NetCDF Climate and Forecast (CF) Metadata C...
summary: This dataset was produced with funding of t...
keywords: Soil Moisture/Water Content
naming_authority: TU Wien
keywords_vocabulary: NASA Global Change Master Directory (GCMD) ...
cdm_data_type: Grid
comment: This dataset was produced with funding of t...
history: 2021-02-16 04:59:06 - product produced
date_created: 20210216T045906Z
creator_name: Department of Geodesy and Geoinformation, T...
creator_url: https://climers.geo.tuwien.ac.at/
creator_email: cci_sm_contact@eodc.eu
project: Climate Change Initiative - European Space ...
license: Data use is free and open for all registere...
time_coverage_start: 20120101T000000Z
time_coverage_end: 20120101T235959Z
time_coverage_duration: P42Y
time_coverage_resolution: P1D
geospatial_lat_min: -90.0
geospatial_lat_max: 90.0
geospatial_lon_min: -180.0
geospatial_lon_max: 180.0
geospatial_vertical_min: 0.0
geospatial_vertical_max: 0.0
geospatial_lat_units: degrees_north
geospatial_lon_units: degrees_east
geospatial_lat_resolution: 0.25 degree
geospatial_lon_resolution: 0.25 degree
spatial_resolution: 25km
time_coverage_start_product: 19781101T000000Z
time_coverage_end_product: 20201231T235959Zxarray.Dataset
- lat: 720
- lon: 1440
- time: 366
- lat(lat)float6489.88 89.62 89.38 ... -89.62 -89.88
- standard_name :
- latitude
- units :
- degrees_north
- valid_range :
- [-90. 90.]
- _CoordinateAxisType :
- Lat
array([ 89.875, 89.625, 89.375, ..., -89.375, -89.625, -89.875])
- time(time)int6415340 15341 15342 ... 15704 15705
- standard_name :
- time
- units :
- days since 1970-01-01T00:00:00+00:00
- calendar :
- standard
array([15340, 15341, 15342, ..., 15703, 15704, 15705])
- lon(lon)float64-179.9 -179.6 ... 179.6 179.9
- standard_name :
- longitude
- units :
- degrees_east
- valid_range :
- [-180. 180.]
- _CoordinateAxisType :
- Lon
array([-179.875, -179.625, -179.375, ..., 179.375, 179.625, 179.875])
- sm(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- dtype :
- float32
- units :
- m3 m-3
- valid_range :
- [0. 1.]
- long_name :
- Volumetric Soil Moisture
- _CoordinateAxes :
- time lat lon
Array Chunk Bytes 1.52 GB 4.15 MB Shape (366, 720, 1440) (1, 720, 1440) Count 1098 Tasks 366 Chunks Type float32 numpy.ndarray - sm_uncertainty(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- dtype :
- float32
- units :
- m3 m-3
- valid_range :
- [0. 1.]
- long_name :
- Volumetric Soil Moisture Uncertainty
- _CoordinateAxes :
- time lat lon
Array Chunk Bytes 1.52 GB 4.15 MB Shape (366, 720, 1440) (1, 720, 1440) Count 1098 Tasks 366 Chunks Type float32 numpy.ndarray - flag(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- dtype :
- int8
- long_name :
- Flag
- _CoordinateAxes :
- time lat lon
- flag_values :
- [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 127]
- flag_meanings :
- ['no_data_inconsistency_detected', 'snow_coverage_or_temperature_below_zero', 'dense_vegetation', 'combination_of_flag_values_1_and_2', 'others_no_convergence_in_the_model_thus_no_valid_sm_estimates', 'combination_of_flag_values_1_and_4', 'combination_of_flag_values_2_and_4', 'combination_of_flag_values_1_and_2_and_4', 'soil_moisture_value_exceeds_physical_boundary', 'combination_of_flag_values_1_and_8', 'combination_of_flag_values_2_and_8', 'combination_of_flag_values_1_and_2_and_8', 'combination_of_flag_values_4_and_8', 'combination_of_flag_values_1_and_4_and_8', 'combination_of_flag_values_2_and_4_and_8', 'combination_of_flag_values_1_and_2_and_4_and_8', 'weight_of_measurement_below_threshold', 'combination_of_flag_values_1_and_16', 'combination_of_flag_values_2_and_16', 'combination_of_flag_values_1_and_2_and_16', 'combination_of_flag_values_4_and_16', 'combination_of_flag_values_1_and_4_and_16', 'combination_of_flag_values_2_and_4_and_16', 'combination_of_flag_values_1_and_2_and_4_and_16', 'combination_of_flag_values_8_and_16', 'combination_of_flag_values_1_and_8_and_16', 'combination_of_flag_values_2_and_8_and_16', 'combination_of_flag_values_1_and_2_and_8_and_16', 'combination_of_flag_values_4_and_8_and_16', 'combination_of_flag_values_1_and_4_and_8_and_16', 'combination_of_flag_values_2_and_4_and_8_and_16', 'combination_of_flag_values_1_and_2_and_4_and_8_and_16', 'combination_of_flag_values_1_and_2_and_4_and_8_and_16_and_32_and_64']
- bits :
- [0 1 2 3 4 5 6 7]
- 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', 'NaN']
- valid_range :
- [ 0 127]
Array Chunk Bytes 1.52 GB 4.15 MB Shape (366, 720, 1440) (1, 720, 1440) Count 1098 Tasks 366 Chunks Type float32 numpy.ndarray - freqbandID(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- dtype :
- int16
- long_name :
- Frequency Band Identification
- _CoordinateAxes :
- time lat lon
- flag_values :
- [ 0 1 2 3 8 9 10 11 64 65 66 67 72 73 74 75]
- flag_meanings :
- ['NaN', 'L14', 'C53', 'L14+C53', 'C68', 'L14+C68', 'C53+C68', 'L14+C53+C68', 'X107', 'L14+X107', 'C53+X107', 'L14+C53+X107', 'C68+X107', 'L14+C68+X107', 'C53+C68+X107', 'L14+C53+C68+X107']
- valid_range :
- [ 0 511]
- bits :
- [0 1 2 3 4 5 6 7 8 9]
- bit_meanings :
- ['NaN', 'L14', 'C53', 'C66', 'C68', 'C69', 'C73', 'X107', 'K194', 'MODEL']
Array Chunk Bytes 1.52 GB 4.15 MB Shape (366, 720, 1440) (1, 720, 1440) Count 1098 Tasks 366 Chunks Type float32 numpy.ndarray - dnflag(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- dtype :
- int8
- long_name :
- Day / Night Flag
- _CoordinateAxes :
- time lat lon
- flag_values :
- [0 1 2 3]
- flag_meanings :
- ['NaN', 'day', 'night', 'day_night_combination']
- bits :
- [0 1 2]
- bit_meanings :
- ['NaN', 'day', 'night']
- valid_range :
- [0 3]
Array Chunk Bytes 1.52 GB 4.15 MB Shape (366, 720, 1440) (1, 720, 1440) Count 1098 Tasks 366 Chunks Type float32 numpy.ndarray - mode(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- dtype :
- int8
- long_name :
- Satellite Mode
- _CoordinateAxes :
- time lat lon
- flag_values :
- [0 1 2 3]
- flag_meanings :
- ['NaN', 'ascending', 'descending', 'ascending_descending_combination']
- bits :
- [0 1 2]
- bit_meanings :
- ['NaN', 'ascending', 'descending']
- valid_range :
- [0 3]
Array Chunk Bytes 1.52 GB 4.15 MB Shape (366, 720, 1440) (1, 720, 1440) Count 1098 Tasks 366 Chunks Type float32 numpy.ndarray - sensor(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- dtype :
- int16
- long_name :
- Sensor
- _CoordinateAxes :
- time lat lon
- flag_values :
- [ 0 4 16 20 64 68 80 84 256 260 272 276 320 324 336 340 768 772 784 788 832 836 848 8192 8196 8208 8212 8256 8260 8272 8276 8448 8452 8464 8468 8512 8516 8528 8532 8960 8964 8976 8980 9024 9028 9040 9044]
- flag_meanings :
- ['NaN', 'TMI', 'WindSat', 'TMI+WindSat', 'SMOS', 'TMI+SMOS', 'WindSat+SMOS', 'TMI+WindSat+SMOS', 'ASCATA', 'TMI+ASCATA', 'WindSat+ASCATA', 'TMI+WindSat+ASCATA', 'SMOS+ASCATA', 'TMI+SMOS+ASCATA', 'WindSat+SMOS+ASCATA', 'TMI+WindSat+SMOS+ASCATA', 'ASCATA+ASCATB', 'TMI+ASCATA+ASCATB', 'WindSat+ASCATA+ASCATB', 'TMI+WindSat+ASCATA+ASCATB', 'SMOS+ASCATA+ASCATB', 'TMI+SMOS+ASCATA+ASCATB', 'WindSat+SMOS+ASCATA+ASCATB', 'FY3B', 'TMI+FY3B', 'WindSat+FY3B', 'TMI+WindSat+FY3B', 'SMOS+FY3B', 'TMI+SMOS+FY3B', 'WindSat+SMOS+FY3B', 'TMI+WindSat+SMOS+FY3B', 'ASCATA+FY3B', 'TMI+ASCATA+FY3B', 'WindSat+ASCATA+FY3B', 'TMI+WindSat+ASCATA+FY3B', 'SMOS+ASCATA+FY3B', 'TMI+SMOS+ASCATA+FY3B', 'WindSat+SMOS+ASCATA+FY3B', 'TMI+WindSat+SMOS+ASCATA+FY3B', 'ASCATA+ASCATB+FY3B', 'TMI+ASCATA+ASCATB+FY3B', 'WindSat+ASCATA+ASCATB+FY3B', 'TMI+WindSat+ASCATA+ASCATB+FY3B', 'SMOS+ASCATA+ASCATB+FY3B', 'TMI+SMOS+ASCATA+ASCATB+FY3B', 'WindSat+SMOS+ASCATA+ASCATB+FY3B', 'TMI+WindSat+SMOS+ASCATA+ASCATB+FY3B']
- valid_range :
- [ 0 16383]
- bits :
- [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14]
- bit_meanings :
- ['NaN', 'SMMR', 'SSMI', 'TMI', 'AMSRE', 'WindSat', 'AMSR2', 'SMOS', 'AMIWS', 'ASCATA', 'ASCATB', 'SMAP', 'MODEL', 'GPM', 'FY3B']
Array Chunk Bytes 1.52 GB 4.15 MB Shape (366, 720, 1440) (1, 720, 1440) Count 1098 Tasks 366 Chunks Type float32 numpy.ndarray - t0(time, lat, lon)float64dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- dtype :
- float64
- long_name :
- Observation Timestamp
- _CoordinateAxes :
- time lat lon
- valid_range :
- [15339. 15341.]
- units :
- days since 1970-01-01T00:00:00+00:00
- calendar :
- proleptic_gregorian
Array Chunk Bytes 3.04 GB 8.29 MB Shape (366, 720, 1440) (1, 720, 1440) Count 1098 Tasks 366 Chunks Type float64 numpy.ndarray
- title :
- ESA CCI Surface Soil Moisture COMBINED active+passive Product
- institution :
- Technical University of Vienna (AUT); VanderSat B.V. Noordwijk (NL)
- contact :
- cci_sm_contact@eodc.eu
- source :
- WARP 5.5R1.1/AMI-WS/ERS12 Level 2 Soil Moisture; WARP 5.4R1.0/AMI-WS/ERS2 Level 2 Soil Moisture; H119: Metop ASCAT Surface Soil Moisture Climate Data Record 12.5 km sampling; H119: Metop ASCAT Surface Soil Moisture Climate Data Record 12.5 km sampling;; LPRMv061/SMMR/Nimbus 7 L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv061/SSMI/F08, F11, F13 DMSP L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv061/TMI/TRMM L2 Surface Soil Moisture, Ancillary Params, and QC; LPRMv061/AMSR-E/Aqua L2B Surface Soil Moisture, Ancillary Params, and QC; LPRMv061/WINDSAT/CORIOLIS L2 Surface Soil Moisture, Ancillary Params, and QC; LPRMv061/AMSR2/GCOM-W1 L3 Surface Soil Moisture, Ancillary Params; LPRMv061/SMOS/MIRAS L3 Surface Soil Moisture, CATDS Level 3 Brightness Temperatures (L3TB) version 300 RE03 & RE04; LPRMv061/SMAP_radiometer/SMAP L2 Surface Soil Moisture, Ancillary Params, and QC; LPRMv061/GMI/GPM L3 Surface Soil Moisture, Ancillary Params, and quality flags; LPRMv061/VIRR/FengYun-3B L3 Surface Soil Moisture, Ancillary Params, and quality flags;;
- platform :
- Nimbus 7, DMSP, TRMM, AQUA, Coriolis, GCOM-W1, MIRAS, SMAP, GPM, FengYun-3B; ERS-1, ERS-2, METOP-A, METOP-B
- sensor :
- SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS, SMAP_radiometer, GMI, VIRR; AMI-WS, ASCAT-A, ASCAT-B
- 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
- product_version :
- v06.1
- id :
- ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED-20120215000000-fv06.1.nc
- tracking_id :
- f721cb4e-b5b4-469f-ac28-a9de2e22622d
- Conventions :
- CF-1.7
- standard_name_vocabulary :
- NetCDF Climate and Forecast (CF) Metadata Convention
- summary :
- This dataset was produced with funding of the ESA CCI+ Soil Moisture project; ESRIN Contract No: 4000126684/19/I-NB
- keywords :
- Soil Moisture/Water Content
- naming_authority :
- TU Wien
- keywords_vocabulary :
- NASA Global Change Master Directory (GCMD) Science Keywords
- 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
- history :
- 2021-02-16 04:59:06 - product produced
- date_created :
- 20210216T045906Z
- creator_name :
- Department of Geodesy and Geoinformation, Technical University of Vienna
- creator_url :
- https://climers.geo.tuwien.ac.at/
- creator_email :
- cci_sm_contact@eodc.eu
- project :
- Climate Change Initiative - European Space Agency
- license :
- Data use is free and open for all registered users.
- time_coverage_start :
- 20120101T000000Z
- time_coverage_end :
- 20120101T235959Z
- time_coverage_duration :
- P42Y
- time_coverage_resolution :
- P1D
- geospatial_lat_min :
- -90.0
- geospatial_lat_max :
- 90.0
- geospatial_lon_min :
- -180.0
- geospatial_lon_max :
- 180.0
- geospatial_vertical_min :
- 0.0
- geospatial_vertical_max :
- 0.0
- geospatial_lat_units :
- degrees_north
- geospatial_lon_units :
- degrees_east
- geospatial_lat_resolution :
- 0.25 degree
- geospatial_lon_resolution :
- 0.25 degree
- spatial_resolution :
- 25km
- time_coverage_start_product :
- 19781101T000000Z
- time_coverage_end_product :
- 20201231T235959Z