Actions for Retrieving moisture profiles from precipitable water measurements using a variational data assimilation approach [electronic resource].

Email RIS file
Bookmark
Report an Issue

Retrieving moisture profiles from precipitable water measurements using a variational data assimilation approach [electronic resource].

Published
Washington, D.C. : United States. Dept. of Energy. Office of Energy Research, 1996.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
Physical Description
pages 133-137 : digital, PDF file
Additional Creators
United States. Department of Energy. Office of Energy Research and United States. Department of Energy. Office of Scientific and Technical Information
Access Online

Availability

I Want It
I Want It

Finding items...

Restrictions on Access
Free-to-read Unrestricted online access
Summary
Atmospheric moisture distribution is directly related to the formation of clouds and precipitation and affects the atmospheric radiation and climate. Currently, several remote sensing systems can measure precipitable water (PW) with fairly high accuracy. As part of the development of an Integrated Data Assimilation and Sounding System in support of the Atmospheric Radiation Measurement Program, retrieving the 3-D water vapor fields from PW measurements is an important problem. A new four dimensional variational (4DVAR) data assimilation system based on the Penn State/National Center for Atmospheric Research (NCAR) mesoscale model (MM5) has been developed by Zou et al. (1995) with the adjoint technique. In this study, we used this 4DVAR system to retrieve the moisture profiles. Because we do not have a set of real observed PW measurements now, the special soundings collected during the Severe Environmental Storm and Mesoscale Experiment (SESAME) in 1979 were used to simulate a set of PW measurements, which were then assimilated into the 4DVAR system. The accuracy of the derived water vapor fields was assessed by direct comparison with the detailed specific humidity soundings. The impact of PW assimilation on precipitation forecast was examined by conducting a series of model forecast experiments started from the different initial conditions with or without data assimilation.
Report Numbers
E 1.99:conf-9503140--
conf-9503140--
Subject(s)
Other Subject(s)
Note
Published through SciTech Connect.
04/01/1996.
"conf-9503140--"
"DE96010942"
5. atmospheric radiation measurement (ARM) science team meeting, San Diego, CA (United States), 19-23 Mar 1995.
Guo, Y.R.; Kuo, Y.H.; Zou, X.
View MARC record | catkey: 14141233