2026-05-10T10:50:28Z https://researchdata.tuwien.ac.at/oai2d

oai:researchdata.tuwien.ac.at:tqrwj-t7r58 2026-04-29T16:57:22Z community-soilmoisture-climaterecords openaire_data

4.3 TUW.TUDATA 10.48436/tqrwj-t7r58 oai:researchdata.tuwien.ac.at:tqrwj-t7r58 Lems, Johanna Johanna Lems TU Wien Preimesberger, Wolfgang Wolfgang Preimesberger 0000-0002-6655-0588 TU Wien Dorigo, Wouter Arnoud Wouter Arnoud Dorigo 0000-0001-8054-7572 TU Wien TU Wien 2025 Soil moisture root zone ESA CCI CLIMERS satellite microwave remote sensing climate climate change 2025-10-28 2026-04-29 10.5194/gmd-16-4957-2023 10.48436/rvjsz-e8y12 10.48436/v8cwj-jk556 https://researchdata.tuwien.ac.at/communities/soilmoisture-climaterecords/ 9.2 Creative Commons Attribution 4.0 International 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 Root Zone Soil Moisture (RZSM) content derived from satellite observations in the microwave domain. The operational (ACTIVE, PASSIVE, COMBINED) ESA CCI SM products are available at https://catalogue.ceda.ac.uk/uuid/c256fcfeef24460ca6eb14bf0fe09572/ (Dorigo et al., 2017; Gruber et al., 2019; Preimesberger et al., 2021). Abstract Soil moisture is a key variable in monitoring climate and an important component of the hydrological, carbon, and energy cycles. Satellite products ameliorate the sparsity of field measurements but are inherently limited to observing the near-surface layer, while water available in the unobserved root-zone controls critical processes like plant water uptake and evapotranspiration. A variety of approaches exist for modelling root-zone soil moisture (RZSM), including approximating it from surface layer observations through an infiltration model (Pasik et al., 2023; Wagner et al., 1999, Albergel et al., 2008). Here, we apply the method described by Pasik et al. (2023) to the COMBINED product of ESA CCI SM v9.2 to derive RZSM and uncertainty estimates in four depth layers of the soil (0-10, 10-40, 40-100, and 0-100 cm) over the period from January 1980 to December 2024 at ~25 km spatial sampling. In situ soil moisture measurements from the International Soil Moisture Network (Dorigo et al., 2021) were used for (global) T-parameter calibration and to quantify the (structural) model error component required to propagate surface measurement uncertainties to the root-zone layers. The 0-1 m layer is a (weighted) average of the other three layers. The dataset has been validated against ERA5 reanalysis RZSM fields, with global median correlations of ~0.6 [-] and ubRMSD <0.04 m³/m³. Summary Global estimates of root-zone soil moisture from 01-1980 to 12-2024 at ~25 km spatial sampling based on the COMBINED product of ESA CCI SM v9.2. Method: Exponential filter model, calibrated with in situ measurements for 3 depth layers: 0-10, 10-40, 40-100 cm with uncertainty estimates. Additionally, one layer representing the average condition from 0-1 m depth is provided. See Pasik et al. (2023) for more details. Good agreement with independent reanalysis data (R ~0.6 [-] and ubRMSD <0.04 m³/m³), decreasing performance for deeper layers due to weaker coupling with surface SM. Programmatic (bulk) download You can use command-line tools such as wget or curl to download (and extract) data for multiple years. The following command will download and extract the complete data set to the local directory ~/Download on Linux or macOS systems. #!/bin/bash# Set download directoryDOWNLOAD_DIR=~/Downloadsbase_url="https://researchdata.tuwien.at/records/tqrwj-t7r58/files"# Loop through years 1980 to 2024 and download & extract datafor year in {1980..2024}; do echo "Downloading $year.zip..." wget -q -P "$DOWNLOAD_DIR" "$base_url/$year.zip" unzip -o "$DOWNLOAD_DIR/$year.zip" -d $DOWNLOAD_DIR rm "$DOWNLOAD_DIR/$year.zip"done Data details Filename template The dataset provides global daily estimates for the 1980-2024 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) and month (MM) of that year in a 2-dimensional (longitude, latitude) grid system (CRS: WGS84). The file name follows the convention: ESACCI-SOILMOISTURE-L3S-RZSMV-COMBINED-YYYYMMDD000000-fv09.2.nc Data Variables Each netCDF file contains 3 coordinate variables lon: longitude (WGS84), [-180,180] degree W/E lat: latitude (WGS84), [-90,90] degree N/S time: float, datetime encoded as "number of days since 1970-01-01 00:00:00 UTC"  and the following data variables rzsm_1: (float) Volumetric Root Zone Soil Moisture at 0-10 cm depth rzsm_2: (float) Volumetric Root Zone Soil Moisture at 10-40 cm depth rzsm_3: (float) Volumetric Root Zone Soil Moisture at 40-100 cm depth rzsm_1m: (float) Root Zone Soil Moisture at 0-1 m uncertainty_1: (float) Volumetric Root Zone Soil Moisture uncertainty at 0-10 cm depth uncertainty_2: (float) Volumetric Root Zone Soil Moisture uncertainty at 0-10 cm depth uncertainty_3: (float) Volumetric Root Zone Soil Moisture uncertainty at 0-10 cm depth Additional information for each variable are given in the netCDF attributes. Version Changelog Changes in v9.2: The COMBINED product of v9.2 is used as input. The period was extended to 12-2024. 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 exist 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 Related Records This record and all related records are part of the ESA CCI Soil Moisture science data records community. European Space Agency 03wd9za21