Share Email Print
cover

Proceedings Paper

A 3DVAR land data assimilation scheme Part 2: Test with ECMWF ERA-40
Author(s): Lanjun Zou; Wei Gao; Tongwen Wu; Xiaofeng Xu; Bingyu Du; James Slusser
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

In the first part of this paper, a 3DVar Land Data Assimilation Scheme (LDAS) is presented. With virtue of this land data assimilation system, this part of the paper demonstrates the results and error analysis of assimilating air temperature data observed at various meteorological stations in China into the output of ECMWF ERA-40. The air temperature distribution of sparse observation zones is obtained, which shows the validity of the assimilation procedure. The 3DVar LDAS can greatly improve the ECMWF background estimates with the high quality observations of air temperature from the Chinese meteorological stations. By comparing the assimilated air temperature field and the ECMWF background field to the observations, the assimilation outputs have better agreement with the air temperature variation trend than the ECMWF background. Another advantage of the assimilated result is that it can describe the extreme air temperature more accurately.

Paper Details

Date Published: 28 September 2006
PDF: 7 pages
Proc. SPIE 6298, Remote Sensing and Modeling of Ecosystems for Sustainability III, 62981M (28 September 2006); doi: 10.1117/12.679991
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