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A fine-resolution soil moisture dataset for China in 2002–2018
- Source :
- Earth System Science Data, Vol 13, Pp 3239-3261 (2021)
- Publication Year :
- 2021
- Publisher :
- Copernicus Publications, 2021.
-
Abstract
- Soil moisture is an important parameter required for agricultural drought monitoring and climate change models. Passive microwave remote sensing technology has become an important means to quickly obtain soil moisture across large areas, but the coarse spatial resolution of microwave data imposes great limitations on the application of these data. We provide a unique soil moisture dataset (0.05∘, monthly) for China from 2002 to 2018 based on reconstruction model-based downscaling techniques using soil moisture data from different passive microwave products – including AMSR-E and AMSR2 (Advanced Microwave Scanning Radiometer for Earth Observing System) JAXA (Japan Aerospace Exploration Agency) Level 3 products and SMOS-IC (Soil Moisture and Ocean Salinity designed by the Institut National de la Recherche Agronomique, INRA, and Centre d’Etudes Spatiales de la BIOsphère, CESBIO) products – calibrated with a consistent model in combination with ground observation data. This new fine-resolution soil moisture dataset with a high spatial resolution overcomes the multisource data time matching problem between optical and microwave data sources and eliminates the difference between the different sensor observation errors. The validation analysis indicates that the accuracy of the new dataset is satisfactory (bias: −0.057, −0.063 and −0.027 m3 m−3; unbiased root mean square error (ubRMSE): 0.056, 0.036 and 0.048; correlation coefficient (R): 0.84, 0.85 and 0.89 on monthly, seasonal and annual scales, respectively). The new dataset was used to analyze the spatiotemporal patterns of soil water content across China from 2002 to 2018. In the past 17 years, China's soil moisture has shown cyclical fluctuations and a slight downward trend and can be summarized as wet in the south and dry in the north, with increases in the west and decreases in the east. The reconstructed dataset can be widely used to significantly improve hydrologic and drought monitoring and can serve as an important input for ecological and other geophysical models. The data are published in Zenodo at https://doi.org/10.5281/zenodo.4738556 (Meng et al., 2021a).
- Subjects :
- QE1-996.5
Radiometer
010504 meteorology & atmospheric sciences
Mean squared error
0211 other engineering and technologies
Climate change
Biosphere
Geology
02 engineering and technology
Atmospheric sciences
01 natural sciences
Environmental sciences
Soil water
General Earth and Planetary Sciences
Environmental science
GE1-350
Image resolution
Water content
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Downscaling
Subjects
Details
- Language :
- English
- ISSN :
- 18663516 and 18663508
- Volume :
- 13
- Database :
- OpenAIRE
- Journal :
- Earth System Science Data
- Accession number :
- edsair.doi.dedup.....aad6cbc6a9047fa872f33044b8339e10