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A 1 km daily surface soil moisture dataset of enhanced coverage under all-weather conditions over China in 2003–2019
Earth System Science Data ( IF 11.2 ) Pub Date : 2022-06-08 , DOI: 10.5194/essd-14-2613-2022 Peilin Song , Yongqiang Zhang , Jianping Guo , Jiancheng Shi , Tianjie Zhao , Bing Tong
Earth System Science Data ( IF 11.2 ) Pub Date : 2022-06-08 , DOI: 10.5194/essd-14-2613-2022 Peilin Song , Yongqiang Zhang , Jianping Guo , Jiancheng Shi , Tianjie Zhao , Bing Tong
Surface soil moisture (SSM) is crucial for understanding the hydrological
process of our earth surface. The passive microwave (PM) technique has long been
the primary tool for estimating global SSM from the view of satellites, while
the coarse resolution (usually km) of PM
observations hampers its applications at finer scales. Although quantitative
studies have been proposed for downscaling satellite PM-based SSM, very few
products have been available to the public that meet the qualification of 1 km
resolution and daily revisit cycles under all-weather conditions. In this
study, we developed one such SSM product in China with all these
characteristics. The product was generated through downscaling the
AMSR-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 two
radiometers during 2003–2019. MODIS optical reflectance data and daily
thermal-infrared land surface temperature (LST) that had been gap-filled for
cloudy conditions were the primary data inputs of the downscaling model so
that the “all-weather” quality was achieved for the 1 km SSM. Daily images
from this developed SSM product have quasi-complete coverage over the
country during April–September. For other months, the national coverage
percentage of the developed product is also greatly improved against the
original daily PM observations through a specifically developed sub-model
for filling the gap between seams of neighboring PM swaths during the
downscaling procedure. The product compares well against in situ soil moisture
measurements from 2000+ meteorological stations, indicated by station
averages 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 product
outperforms the SMAP (Soil Moisture Active Passive) and Sentinel (active–passive microwave) combined SSM
product at 1 km, with a correlation coefficient of 0.55 achieved against
that of 0.40 for the latter product. This indicates the new product has
great potential to be used by the hydrological community, by the agricultural
industry, 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).
更新日期:2022-06-08