A 3DVAR land data assimilation scheme Part 1: Mathematical design

Lanjun Zou; Wei Gao; Tongwen Wu; Xiaofeng Xu; Bingyu Du; James Slusser

doi:10.1117/12.679994

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27 September 2006 A 3DVAR land data assimilation scheme Part 1: Mathematical design

Lanjun Zou, Wei Gao, Tongwen Wu, Xiaofeng Xu, Bingyu Du, James Slusser

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Proceedings Volume 6298, Remote Sensing and Modeling of Ecosystems for Sustainability III; 62982E (2006) https://doi.org/10.1117/12.679994
Event: SPIE Optics + Photonics, 2006, San Diego, California, United States

Abstract

Land surface states have significant control to the water and energy exchanges between land surface and the atmosphere. Thus land surface information is crucial to the global and regional weather and climate predictions. China has built abundant meteorological stations that collect land surface data with good quality for many years. But applications of these data in their numerical weather and climate prediction models are quite low efficient. To take the advantages of land surface data in numerical weather and climate models, we have developed a three dimension variational (3DVar) Land Data Assimilation Scheme (LDAS). In Part 1 of this paper, we present the mathematical design of the 3DVar LDAS. By assimilating a single point observational datum into a background setup, the LDAS is tested to demonstrate its capability and usage. In the other part of this paper, we will demonstrate the results and error analysis of assimilating China's air temperature observational data of the meteorological stations into ECMWF's model background using the 3DVar Land Data Assimilation Scheme.

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Lanjun Zou, Wei Gao, Tongwen Wu, Xiaofeng Xu, Bingyu Du, and James Slusser "A 3DVAR land data assimilation scheme Part 1: Mathematical design", Proc. SPIE 6298, Remote Sensing and Modeling of Ecosystems for Sustainability III, 62982E (27 September 2006); https://doi.org/10.1117/12.679994

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