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STUDY OF GRIDDED MIXING HEIGHTS AD CLOUD FIELDS DERIVED FROM THE MESOSCALE METEOROLOGICAL MODEL WITH FOUR DIMENSIONAL DATA ASSIMILATION
Citation:
Ching, J. AND J. Pleim. STUDY OF GRIDDED MIXING HEIGHTS AD CLOUD FIELDS DERIVED FROM THE MESOSCALE METEOROLOGICAL MODEL WITH FOUR DIMENSIONAL DATA ASSIMILATION. U.S. Environmental Protection Agency, Washington, D.C., EPA/600/A-95/129 (NTIS PB96116900), 1996.
Description:
Meteorological data including wind, temperature and moisture variables, as well as boundary layer parameters including surface fluxes, depth of the mixed layer and cloud and precipitation information are integral components of air quality simulations models (AQSMS). QSMs require temporal resolution of these meteorology data fields on hourly basis with temporal averaging to daily, seasonal, and annual periods, and require the range of spatial resolution from land use scale to global scale. egional scale acid rain models require additional spatial and temporal information on clouds and precipitation fields. ir quality related values such as visibility degradation and plume blight depend on accurate and detailed moisture data due primarily to its strong control on aerosol size distributions. n addition to the primary meteorological fields, both data on boundary layer fluxes and turbulence as well as on clouds are important and critical parameters for AQSMS. hese fluxes and mixing processes are dynamically linked with convective cloud fields: convective cloud fields are triggered by heating in the boundary layer; clouds modulate the amount of heat available in the boundary layer needed to produce convection. onsequently, it is expected that the accuracy of the predicted cloud fields in mesoscale meteorological models will be highly dependent on its boundary layer structure and parametric formulations. deally, systems that incorporate modeled meteorology based on hydrodynamic principles and four dimensional data assimilation (FDDA) techniques to constrain model errors should be able to provide the requisite resolution and accuracy of the meteorology information. ne such example is the primitive equation Mesoscale Meteorological Model, Generation 4 (MM,) with Four Dimensional Data Assimilation (FDDA) (Anthes et al.,1987, and Stauffer et al.,1990). This system has been utilized as the meteorological preprocessor for the Regional Acid Deposition Model, RADM, with great success (NAPAP, 1991). his paper investigates the sensitivity of the modeled boundary layer and cloud parameters to different boundary layer parameterizations in the MM,-FDDA system.
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STUDY OF GRIDDED MIXING HEIGHTS AD CLOUD FIELDS DERIVED FROM THE MESOSCALE METEOROLOGICAL MODEL WITH FOUR DIMENSIONAL DATA ASSIMILATION