ESA CCI SM MODELFREE Long-term Climate Data Record of Surface Soil Moisture from merged multi-satellite observations

This dataset was produced with funding from the European Space Agency (ESA) Climate Change Initiative (CCI) Plus Soil Moisture Project (CCN 3 to ESRIN Contract No: 4000126684/19/I-NB "ESA CCI+ Phase 1 New R&D on CCI ECVS Soil Moisture").  Project website: https://climate.esa.int/en/projects/soil-moisture/

This dataset contains information on the Surface Soil Moisture (SM) content derived from satellite observations in the microwave domain.

Abstract

The MODELFREE product of the ESA CCI SM v9.1 science data suite provides - similar to the COMBINED product - global, harmonized daily satellite soil moisture measurements from both radar and radiometer observations. This product contains soil moisture estimates at 0.25-degree spatial resolution, and covers the period from 2002-2023. Soil moisture is derived from observations of 13 different active and passive satellites operating across various frequency bands (K, C, X, and L-band). Unlike the COMBINED product, for which soil moisture fields from the GLDAS Noah model dataset are used to harmonize individual satellite sensor measurements, the MODELFREE product utilizes a satellite-only scaling reference dataset. This reference incorporates gap-filled soil moisture derived from AMSR-E (2002-2010) and from intercalibrated SMAP/SMOS brightness temperature data (2010-2023). The merging algorithm employed is consistent with that of the v9.1 COMBINED product. The new scaling reference leads to significantly different absolute soil moisture values, especially in latitudes above 60 °N. Data from the SMMR, SSMI and ERS missions are not included in this product.

This product is in its early development stage and should be used with caution, as it may contain incomplete or unvalidated data.

Summary

• First version of a model-independent version of the ESA CCI SM COMBINED product

• 2002-2023, global, 0.25 deg. resolution

• GLDAS Noah (model) is replaced with a purely satellite-based scaling reference

• Different absolute value range compared to the COMBINED product is expected due to the different scaling reference used

Known issues

• A temporal inconsistency is observed between the AMSR-E and SMOS period (at 01-2010). This can affect long-term trends in the data

• In the period from 01-2002 to 06-2002 no data are available above 37 °N and below 37 °S respectively (all measurements in this period are from the TRMM Microwave Imager)

Technical Details

The dataset provides global daily estimates for the 2002-2023 period at 0.25° (~25 km) horizontal grid resolution. Daily images are grouped by year (YYYY), each subdirectory containing one netCDF image file for a specific day (DD), month (MM) in a 2-dimensional (longitude, latitude) grid system (CRS: WGS84). The file name has the following convention:

ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED_MODELFREE-YYYYMMDD000000-fv09.1.nc

Each netCDF file contains 3 coordinate variables (WGS84 longitude, latitude and time stamp), as well as the following data variables:

• sm: (float) The Soil Moisture variable reflects estimates of daily average volumetric soil moisture content (m3/m3) in the soil surface layer (~0-5 cm) over a whole grid cell (0.25 degree).
• sm_uncertainty: (float) The Soil Moisture Uncertainty variable reflects the uncertainty (random error) of satellite observations. Derived using triple collocation analysis.
• dn_flag: (int) Indicator for satellite orbit(s) used in the retrieval (day/nighttime). 1=day, 2=night, 3=both
• flag: (int) Indicator for data quality / missing data indicator. For more details, see netcdf attributes.
• freqbandID: (int) Indicator for frequency band(s) used in the retrieval. For more details, see netcdf attributes.
• mode: (int) Indicator for satellite orbit(s) used in the retrieval (ascending, descending)
• sensor: (int) Indicator for satellite sensor(s) used in the retrieval. For more details, see netcdf attributes.
• t0: (float) Representative time stamp, based on overpass times of all merged satellites.

Additional information for each variable is given in the netCDF attributes.

Software to open netCDF files

These data can be read by any software that supports Climate and Forecast (CF) conform metadata standards for netCDF files, such as:

• Xarray (python)
• netCDF4 (python)
• esa_cci_sm (python)
• Similar tools exists for other programming languages (Matlab, R, etc.)
• Software packages and GIS tools can open netCDF files, e.g. CDO, NCO, QGIS, ArCGIS
• You can also use the GUI software Panoply to view the contents of each file

References

R. Madelon et al., “Toward the Removal of Model Dependency in Soil Moisture Climate Data Records by Using an L-Band Scaling Reference," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 831-848, 2022, doi: 10.1109/JSTARS.2021.3137008.

Related Records

The following records are all part of the Soil Moisture Climate Data Records from satellites community