Land surface emissivity, which varies widely with surface type, is important for the assimilation of microwave satellite data. The fast radiative transfer model RTTOV-7 developed by ECMWF had been introduced into the Global/regional assimilation and prediction system (Grapes)-3Dvar, a new three dimensional data assimilation system developed by the Research Center for Numerical Meteorological Prediction, Chinese Academy of Meteorological Sciences, to assimilate ATOVS microwave satellite radiance directly. To improve the accuracy of land surface emissivity, the NOAA/NESDIS microwave land surface emissivity model developed by F. Weng is merged into RTTOV-7 and an adjusted parameter scheme is designed to provide the surface parameters for the microwave land surface emissivity model. These surface parameters are produced from a global data assimilation system (GDAS) including a boundary layer model in NOAA/NESDIS. The result shows that the accuracy of land surface emissivity for a variety of land types is improved. It results in the improvement of the accuracy of simulated satellite radiance. Following the satellite microwave radiance operating near the window regions, which are affected strongly by land surface emissivity, could be utilized in the assimilation system to investigate their impact on numerical weather forecast.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.