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RECORD NUMBER: 52 OF 335

OLS Field Name OLS Field Data
Main Title Computationally Efficient Method for the Characterization of Sub-Grid-Scale Precipitation Variability for Sulfur Wet Removal Estimates.
Author Bullock, O. R. ;
CORP Author National Oceanic and Atmospheric Administration, Research Triangle Park, NC. Atmospheric Sciences Modeling Div.;Environmental Protection Agency, Research Triangle Park, NC. Atmospheric Research and Exposure Assessment Lab.
Publisher c1994
Year Published 1994
Report Number EPA/600/J-94/462;
Stock Number PB95-137246
Additional Subjects Precipitation(Meteorology) ; Acid rain ; Computational grids ; Sulfur dioxide ; Sulfates ; Atmospheric models ; Air pollution monitoring ; Networks ; Parametric equations ; Variability ; Canada ; Reprints ; Regional Lagrangrian Model of Air Pollution ; Eastern Region(United States)
Holdings
Library Call Number Additional Info Location Last
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Status
NTIS  PB95-137246 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. NTIS 03/06/1995
Collation 14p
Abstract
The Regional Lagrangian Model of Air Pollution (RELMAP) is a mass conserving, Lagrangian puff model that simulates the concentration and deposition of sulfur dioxide (SO2) and sulfate SO4(2-) over the eastern United States and southeastern Canada. In 1986, a model evaluation showed that the RELMAP over-estimated total sulfur wet deposition for the warm seasons by 25-35%, partly due to sub-grid-scale variability in the observed precipitation fields. Refinement of the model grid to fully resolve the precipitation observation network would increase the computational requirements of the model to unacceptable levels. Instead, a new parameterization of the wet removal fraction was implemented in hopes of reducing the model's sensitivity to precipitation variability. The effects of observed sub-grid-scale precipitation variability on SO2 and SO4(2-) wet removal in the original and updated RELMAP have been isolated and analyzed. Spatial averaging of precipitation to the length scales of the RELMAP grid (approximately 100 km) is shown to increase SO4(2-) wet removal fractions by as much as 400% over those obtained from individual observations. A method of Caregorized Event Distribution (CED) analysis has been developed to characterize sub-grid-scale variability so that more accurate estimates of wet deposition may be made while preserving the ability of the RELMAP to be intensively applied on modest computing facilities. The use of CED analysis of precipitation in the current version of RELMAP is shown to systematically reduce montly domain total sulfur wet deposition estimates by 6-12%, demonstrating that sub-grid-scale precipitation variability must still be addressed.