Share Email Print

Proceedings Paper

A 3DVAR land data assimilation scheme Part 1: Mathematical design
Author(s): Lanjun Zou; Wei Gao; Tongwen Wu; Xiaofeng Xu; Bingyu Du; James Slusser
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper 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.

Paper Details

Date Published: 27 September 2006
PDF: 8 pages
Proc. SPIE 6298, Remote Sensing and Modeling of Ecosystems for Sustainability III, 62982E (27 September 2006); doi: 10.1117/12.679994
Show Author Affiliations
Lanjun Zou, Nanjing Univ. of Information Science and Technology (China)
China Meteorological Administration (China)
Wei Gao, Nanjing Univ. of Information Science and Technology (China)
Colorado State Univ. (United States)
Tongwen Wu, China Meteorological Administration (China)
Xiaofeng Xu, China Meteorological Administration (China)
Bingyu Du, Nanjing Univ. of Information Science and Technology (China)
James Slusser, Colorado State Univ. (United States)

Published in SPIE Proceedings Vol. 6298:
Remote Sensing and Modeling of Ecosystems for Sustainability III
Wei Gao; Susan L. Ustin, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?