Assimilating multi-source data into land surface model to simultaneously improve estimations of soil moisture, soil temperature, and surface turbulent fluxes in irrigated fields

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• 作者：Chunlin Huang^a ; ^e ; ^{huangcl@lzb.ac.cn} ; Weijing Chen^b ; Yan Li^a ; ^c ; Huanfeng Shen^b ; Xin Li^a ; ^d
• 关键词：Data assimilation ; Ensemble Kalman Smoother ; Soil moisture ; Soil temperature ; Surface turbulent fluxes ; Common Land Model
• 刊名：Agricultural and Forest Meteorology
• 出版年：2016
• 出版时间：15 December 2016
• 年：2016
• 卷：230-231
• 期：Complete
• 页码：142-156
• 全文大小：5874 K
• 卷排序：230

文摘

An EnKS-based data assimilation scheme is developed toward Multi-source observation. Profiles of soil moisture and soil temperature are improved by assimilating multi-source observation. Latent and sensible heat fluxes are improved by assimilating multi-source observation. Assimilation of multi-source observation can reduce the influence of absence of irrigation information.