A 1 km daily surface soil moisture dataset of enhanced coverage under all-weather conditions over China in 2003–2019

[摘要] Surface soil moisture (SSM) is crucial for understanding the hydrologicalprocess of our earth surface. The passive microwave (PM) technique has long beenthe primary tool for estimating global SSM from the view of satellites, whilethe coarse resolution (usually > ∼ 10  km) of PMobservations hampers its applications at finer scales. Although quantitativestudies have been proposed for downscaling satellite PM-based SSM, very fewproducts have been available to the public that meet the qualification of 1 kmresolution and daily revisit cycles under all-weather conditions. In thisstudy, we developed one such SSM product in China with all thesecharacteristics. The product was generated through downscaling theAMSR-E/AMSR-2-based (Advance Microwave Scanning Radiometer of the Earth Observing System and its successor) SSM at 36 km, covering all on-orbit times of the tworadiometers during 2003–2019. MODIS optical reflectance data and dailythermal-infrared land surface temperature (LST) that had been gap-filled forcloudy conditions were the primary data inputs of the downscaling model sothat the “all-weather” quality was achieved for the 1 km SSM. Daily imagesfrom this developed SSM product have quasi-complete coverage over thecountry during April–September. For other months, the national coveragepercentage of the developed product is also greatly improved against theoriginal daily PM observations through a specifically developed sub-modelfor filling the gap between seams of neighboring PM swaths during thedownscaling procedure. The product compares well against in situ soil moisturemeasurements from 2000+ meteorological stations, indicated by stationaverages of the unbiased root mean square difference (RMSD) ranging from 0.052 to 0.059 vol vol −1 .Moreover, the evaluation results also show that the developed productoutperforms the SMAP (Soil Moisture Active Passive) and Sentinel (active–passive microwave) combined SSMproduct at 1 km, with a correlation coefficient of 0.55 achieved againstthat of 0.40 for the latter product. This indicates the new product hasgreat potential to be used by the hydrological community, by the agriculturalindustry, and for water resource and environment management. The new product is available for download at https://doi.org/10.11888/Hydro.tpdc.271762 (Song and Zhang, 2021b).

[学科分类] 眼科学