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Modeled mesoscale meteorological fields with four-dimensional data assimilation in regional scale air quality models

Technical Report ·
OSTI ID:6575255
The paper addresses the need to increase the temporal and spatial resolution of meteorological data currently used in air quality simulation models, AQSMs. Transport and diffusion parameters including mixing heights and stability used in regulatory air quality dispersion models are currently computed using routinely collected twice daily (00Z and 12Z) upper air sounding data from approximately 100 locations, and hourly surface data from approximately 300 locations spread across the US. The limited resolution data base limits the accuracy, reliability and validity of the derived dispersion parameters for air quality models. The MM4-FDDA (Mesoscale Meteorological model, Version 4 with Four Dimensional Data Assimilation), a state-of-science dynamic modeling system that assimilates routinely available surface and upper air sounding data has been demonstrated to provide accurate and well characterized primary meteorological fields on hourly time intervals, with fine horizontal and vertical resolution. The MM4-FDDA can also provide as outputs, parameters such as surface heat and momentum fluxes which are necessary for computing the stability dispersion parameters. The goal of the study is to generate meteorological data with accuracy of transport, precipitation and dynamic consistency superior to both direct interpolation of synoptic scale analysis of observations and on-site meteorology, and purely predictive-mode model results. This is a demonstration project to produce a one year meteorological data base on an hourly basis for a horizontal grid resolution of 80 km and for 15 vertical layers is underway.
Research Organization:
Environmental Protection Agency, Research Triangle Park, NC (United States). Atmospheric Research and Exposure Assessment Lab.
OSTI ID:
6575255
Report Number(s):
PB-93-167229/XAB; EPA--600/A-93/046
Country of Publication:
United States
Language:
English