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Soil Moisture Dataset of China based on Microwave Data Assimilation Published

The soil moisture dataset of China based on microwave data assimilation for 2002-2011 was published by a research team led by Prof. YANG Kun at Tsinghua University. The results were published in Science China Earth Sciences, in an article entitled “Development of a daily soil moisture product for the period of 2002-2011 in Chinese Mainland”. This dataset considers the constraints of both land-based model simulations and microwave satellite observations, and the results of the assessment indicate that it has higher accuracy and reliability compared to satellite inversion products and land-based process simulations. It can be applied to support regional climate, hydrological and ecological studies.

As one of the key climate variables, soil moisture plays an important role in the water and energy cycle and land-atmosphere interactions. Although several passive microwave satellites have made soil moisture the main target of their inversions, there are still many challenges in obtaining high-precision soil moisture products from satellite remote sensing at regional scales due to the effects of vegetation and surface roughness. Assimilating passive microwave signals in land surface models is an effective way to reduce soil moisture estimation bias, but it also faces problems such as errors in meteorologically driven data, uncertainty in model parameters and how to effectively verify soil moisture accuracy.

Over the past decade, YANG Kun's research team has developed a two-channel data assimilation system that can optimize model parameters, developed a Chinese high-resolution near-surface meteorological dataset that can drive the land surface data assimilation system, and established a soil moisture observation network with more than 100 stations as a validation base with other teams. This new datasets has a spatial resolution of 0.25° and includes daily soil moisture content in the surface, root layer and deep layers. The data has been published online by the National Tibetan Plateau Data Center. It can be used for a variety of purposes, such as to initialize, calibrate, and validate land surface models, to deepen the understanding of land-atmosphere interaction processes, and to support agricultural and ecosystem research and management.

Based on this dataset, the author further finds that: (1) the spatial distribution of soil moisture content is basically consistent with that of precipitation and evaporation, i.e. it is humid in Southeast China and arid in Northwest China; (2) the soil moisture content in some areas of Southwest China is not high, which reflects the characteristics of coarse-grained purple soil dominated and low soil porosity in this area; and (3) the soil moisture has stronger seasonal variation in the climate transition region than in the humid and arid regions, and stronger interannual variability in the relatively arid North China than in the relatively humid South China, and the variability is more obvious in spring and autumn. These findings are helpful to understand the spatial pattern and interannual variability of climate, hydrology and ecology in China.

Spatial variation of precipitation (a), evaporation (b), near-surface soil moisture(c), soil porosity (d) in Chinese Mainland. The values in (a)–(c) are averaged over July of 2002–2011, Figure (d) is modified from Figure S22 of Shangguan et al. (2013). The grids covering large lakes and near-coastal areas are removed. The ellipse circle covers a part of Sichuan Basin and Yunnan-Guizhou Plateau.

This research was funded by the National Key R&D Program (Grant No. 2018YFA0605400).

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