ESA CCI Surface Soil Moisture merged ACTIVE Product
Load in Python
from intake import open_catalog
cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/1991_ESACCI-SOILMOISTURE-L3S-SSMS-ACTIVE.yaml")
ds=cat.netcdf.read()Metadata
| title | ESA CCI Surface Soil Moisture merged ACTIVE Product |
| location | /shared/land/CCI/daily_files/ACTIVE/1991 |
| tags | global,satellite,daily |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/1991_ESACCI-SOILMOISTURE-L3S-SSMS-ACTIVE.yaml |
| last updated | 2021-09-01 |
Dataset Contents
<xarray.Dataset>
Dimensions: (lat: 720, lon: 1440, time: 149)
Coordinates:
* lat (lat) float64 89.88 89.62 89.38 ... -89.38 -89.62 -89.88
* time (time) int64 7886 7887 7888 7889 ... 8031 8032 8033 8034
* 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 merged ACTIVE...
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: ERS-1, ERS-2, METOP-A, METOP-B
sensor: AMI-WS, ASCAT-A, ASCAT-B
references: http://www.esa-soilmoisture-cci.org; Dorigo...
product_version: v06.1
id: ESACCI-SOILMOISTURE-L3S-SSMS-ACTIVE-1991100...
tracking_id: 87b0d142-aaaf-4c60-9af5-63a01177f083
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: 2021-02-15 23:12:54 - product produced
date_created: 20210215T231254Z
creator_name: Department of Geodesy and Geoinformation, T...
creator_url: https://climers.geo.tuwien.ac.at/
creator_email: cci_sm_developer@eodc.eu
project: Climate Change Initiative - European Space ...
license: Data use is free and open for all registere...
time_coverage_start: 19910805T000000Z
time_coverage_end: 19910805T235959Z
time_coverage_duration: P29Y
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: 19910805T000000Z
time_coverage_end_product: 20201231T235959Zxarray.Dataset
- lat: 720
- lon: 1440
- time: 149
- 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)int647886 7887 7888 ... 8032 8033 8034
- standard_name :
- time
- units :
- days since 1970-01-01T00:00:00+00:00
- calendar :
- standard
array([7886, 7887, 7888, 7889, 7890, 7891, 7892, 7893, 7894, 7895, 7896, 7897, 7898, 7899, 7900, 7901, 7902, 7903, 7904, 7905, 7906, 7907, 7908, 7909, 7910, 7911, 7912, 7913, 7914, 7915, 7916, 7917, 7918, 7919, 7920, 7921, 7922, 7923, 7924, 7925, 7926, 7927, 7928, 7929, 7930, 7931, 7932, 7933, 7934, 7935, 7936, 7937, 7938, 7939, 7940, 7941, 7942, 7943, 7944, 7945, 7946, 7947, 7948, 7949, 7950, 7951, 7952, 7953, 7954, 7955, 7956, 7957, 7958, 7959, 7960, 7961, 7962, 7963, 7964, 7965, 7966, 7967, 7968, 7969, 7970, 7971, 7972, 7973, 7974, 7975, 7976, 7977, 7978, 7979, 7980, 7981, 7982, 7983, 7984, 7985, 7986, 7987, 7988, 7989, 7990, 7991, 7992, 7993, 7994, 7995, 7996, 7997, 7998, 7999, 8000, 8001, 8002, 8003, 8004, 8005, 8006, 8007, 8008, 8009, 8010, 8011, 8012, 8013, 8014, 8015, 8016, 8017, 8018, 8019, 8020, 8021, 8022, 8023, 8024, 8025, 8026, 8027, 8028, 8029, 8030, 8031, 8032, 8033, 8034]) - 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 :
- percent
- valid_range :
- [ 0. 100.]
- long_name :
- Percent of Saturation Soil Moisture
- _CoordinateAxes :
- time lat lon
Array Chunk Bytes 617.93 MB 4.15 MB Shape (149, 720, 1440) (1, 720, 1440) Count 447 Tasks 149 Chunks Type float32 numpy.ndarray - sm_uncertainty(time, lat, lon)float32dask.array<chunksize=(1, 720, 1440), meta=np.ndarray>
- dtype :
- float32
- units :
- percent
- valid_range :
- [ 0. 100.]
- long_name :
- Percent of Saturation Soil Moisture Uncertainty
- _CoordinateAxes :
- time lat lon
Array Chunk Bytes 617.93 MB 4.15 MB Shape (149, 720, 1440) (1, 720, 1440) Count 447 Tasks 149 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 4 5 127]
- flag_meanings :
- ['no_data_inconsistency_detected', 'snow_coverage_or_temperature_below_zero', 'others_no_convergence_in_the_model_thus_no_valid_sm_estimates', 'combination_of_flag_values_1_and_4', '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 617.93 MB 4.15 MB Shape (149, 720, 1440) (1, 720, 1440) Count 447 Tasks 149 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 2]
- flag_meanings :
- ['NaN', 'C53']
- 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 617.93 MB 4.15 MB Shape (149, 720, 1440) (1, 720, 1440) Count 447 Tasks 149 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 617.93 MB 4.15 MB Shape (149, 720, 1440) (1, 720, 1440) Count 447 Tasks 149 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 617.93 MB 4.15 MB Shape (149, 720, 1440) (1, 720, 1440) Count 447 Tasks 149 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 :
- [ 0 128]
- flag_meanings :
- ['NaN', 'AMIWS']
- 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 617.93 MB 4.15 MB Shape (149, 720, 1440) (1, 720, 1440) Count 447 Tasks 149 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 :
- [7885. 7887.]
- units :
- days since 1970-01-01T00:00:00+00:00
- calendar :
- proleptic_gregorian
Array Chunk Bytes 1.24 GB 8.29 MB Shape (149, 720, 1440) (1, 720, 1440) Count 447 Tasks 149 Chunks Type float64 numpy.ndarray
- title :
- ESA CCI Surface Soil Moisture merged ACTIVE 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; EXPERIMENTAL: Metop ASCAT Surface Soil Moisture Climate Data Record 12.5 km sampling; EXPERIMENTAL: Metop ASCAT Surface Soil Moisture Climate Data Record 12.5 km sampling;
- platform :
- ERS-1, ERS-2, METOP-A, METOP-B
- sensor :
- 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-SSMS-ACTIVE-19911007000000-fv06.1.nc
- tracking_id :
- 87b0d142-aaaf-4c60-9af5-63a01177f083
- 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 :
- 2021-02-15 23:12:54 - product produced
- date_created :
- 20210215T231254Z
- creator_name :
- Department of Geodesy and Geoinformation, Technical University of Vienna
- creator_url :
- https://climers.geo.tuwien.ac.at/
- creator_email :
- cci_sm_developer@eodc.eu
- project :
- Climate Change Initiative - European Space Agency
- license :
- Data use is free and open for all registered users.
- time_coverage_start :
- 19910805T000000Z
- time_coverage_end :
- 19910805T235959Z
- time_coverage_duration :
- P29Y
- 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 :
- 19910805T000000Z
- time_coverage_end_product :
- 20201231T235959Z