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RECORD NUMBER: 21 OF 21

OLS Field Name OLS Field Data
Main Title Use of Four-Dimensional Data Assimilation in a Limited-Area Mesoscale Model Part 2: Effects of Data Assimilation within the Planetary Boundary Layer.
Author Stauffer, D. R. ; Seaman, N. L. ; Binkowski., F. S. ;
CORP Author Pennsylvania State Univ., University Park. Dept. of Meteorology.;Environmental Protection Agency, Research Triangle Park, NC. Atmospheric Research and Exposure Assessment Lab.
Publisher c1991
Year Published 1991
Report Number EPA-R-814068-01-0; EPA/600/J-92/141;
Stock Number PB92-166750
Additional Subjects Numerical weather forecasting ; Mesoscale phenomena ; Planetary boundary layer ; Atmospheric models ; Atmospheric temperature ; Atmospheric precipitation ; Barometric pressure ; Wind(Meteorology) ; Four dimensional ; Reprints ;
Holdings
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Status
NTIS  PB92-166750 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. 08/22/1992
Collation 24p
Abstract
A four-dimensional data assimilation (FDDA) scheme based on Newtonian relaxation or nudging has been developed and evaluated in the Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) Limited-Area Mesoscale Model. It was shown in Part I of the study that continuous assimilation of standard-resolution rawinsonde observations throughout a model integration, rather than at only the initial time, can successfully limit large-scale model error growth (amplitude and phase errors) while the model maintains intervariable consistency and generates realistic mesoscale structures not resolved by the data. The purpose of the paper is to further refine the previously reported FDDA strategy used to produce 'dynamic analyses' of the atmosphere by investigating the effects of data assimilation within the planetary boundary layer (PBL). The data used for assimilation include conventional synoptic-scale rawinsonde data and mesoalpha-scale surface data. The main objective of the study is to determine how to effectively utilize the combined strength of these two simple data systems while avoiding their individual weaknesses. Ten experiments, which use a 15-layer version of the model, are evaluated for two midlatitude, real-data cases. (Copyright (c) 1991 American Meteorological Society.)