10 September 2008 Numerical simulation by the Common Land Model (CLM) of the soil moisture over China during the summer of 2006
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Abstract
The Common Land Model (CLM) has been validated by observation experiments over different land surfaces in various climate zones throughout the world. These experiments have shown that CLM simulates the characteristics of land-atmosphere interactions over different land surfaces, except in the East Asian monsoon zone where complex land surface conditions exist. China lies on this East Asian monsoon zone which consists of complex terrain, various vegetation types, and specific land surface conditions, and experiences frequent drought and flood disasters. It is important to study how varying land surfaces affect the interaction of energy, mass, and momentum between land and atmosphere. Owing to poor simulation of soil moisture by most land surface models, CLM has chosen to simulate the distribution of soil moisture over China. Meanwhile, station-observed soil moisture, drought monitoring data from a pole orbit meteorology satellite, and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) remote-sensed soil moisture are used to verify the capability of CLM simulation, especially for surface and soil moisture at a 20 cm depth. The results show that the surface soil moisture distribution and variation trend of CLM simulation coincides with pole orbit meteorology satellite monitoring and AMSR-E, and that soil moisture at a 20 cm depth coincides with station observation products from the National Climate Center. It also illustrates that CLM can reasonably simulate the distribution and variation of soil moisture over China. It is meaningful to study the climate response of the lack of soil moisture on soil moisture data. Key words: CLM, soil moisture, drought, AMSR-E
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Lanjun Zou, Lanjun Zou, Wei Gao, Wei Gao, Tongwen Wu, Tongwen Wu, Qifeng Lu, Qifeng Lu, Yanwu Zhang, Yanwu Zhang, } "Numerical simulation by the Common Land Model (CLM) of the soil moisture over China during the summer of 2006", Proc. SPIE 7083, Remote Sensing and Modeling of Ecosystems for Sustainability V, 708314 (10 September 2008); doi: 10.1117/12.794448; https://doi.org/10.1117/12.794448
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