Improving numerical weather forecast using multi-frequency passive microwave satellite observations and data assimilation methods

Author

Rasmy, Mohamed ; Koike, Toshiaki

Author_Institution

Dept. of Civil Eng., Univ. of Tokyo, Tokyo, Japan

fYear

2013

fDate

21-26 July 2013

Firstpage

2254

Lastpage

2257

Abstract

A multi-frequency passive microwave data assimilation system (CALDAS) was developed to physically introduce the satellite observed land and atmospheric moisture information into a mesoscale model to enhance the capability of numerical prediction. CALDAS merged information from AMSRE´s lower-frequency observations with that from higher frequencies, and therefore facilitated passive microwave remote sensing to obtain atmospheric information over land surfaces. They system was applied over a mesoscale domain of Niger, Africa. The results showed that CALDAS improved the cloud representation and land-atmosphere feed back mechanism, significantly. Detailed validations will be carried out in the near future to asses the full potential of the system.

Keywords

atmospheric boundary layer; atmospheric humidity; weather forecasting; AMSR-E lower-frequency observations; Africa; CALDAS; Niger; data assimilation methods; land-atmosphere feed back mechanism; mesoscale model; multifrequency passive microwave satellite observations; numerical prediction; numerical weather forecast; passive microwave remote sensing; satellite observed atmospheric moisture information; satellite observed land information; Atmospheric modeling; Clouds; Data assimilation; Land surface; Microwave theory and techniques; Predictive models; Satellites; data assimilation; land-atmosphere interactions; microwave remote sensing; numerical prediction;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International

Conference_Location

Melbourne, VIC

ISSN

2153-6996

Print_ISBN

978-1-4799-1114-1

Type

conf

DOI

10.1109/IGARSS.2013.6723266

Filename

6723266