Potential Dispersion Modeling Uses of Archived NOAA Forecast Model Data

A newly-developed generation of air quality simulation models has the potential to use profiles of wind, temperature, and turbulence, as well as improved mixing height determination, measures of surface heat flux, and a host of other meteorological parameters. Several numerical weather prediction models that generate these comprehensive data sets are routinely being run by the National Oceanic and Atmospheric Administration (NOAA) to support forecast operations of the National Weather Service (NWS). The Eta model (named after the Greek letter h, which is used to denote vertical coordinate) is being run to make forecasts out to 48 hours (including precipitation) over this period. In order to provide input data for each forecast run, assimilation of the many types of meteorological data collected by NOAA is done over a three-dimensional grid. Another model, Rapid Update Cycle (RUC), is also being applied. This model primarily supports short-range forecasts (out to six hours) with three-hour updates. Data assimilation is also used to provide input for the RUC model. The creation of a three-year (April 1995 to April 1998) archive of analyses and forecasts from these two models, plus data from the Canadian Regional Finite Element (RFE) model, is underway. Archived data include vertical profiles of temperature, wind, and turbulent kinetic energy (TKE). Surface heat flux, cloud cover, and precipitation are also available. A grid with 40-kilometer horizontal spacing with 30 to 40 vertical levels is being used. The data of greatest interest to air pollution meteorologists are the analyses resulting from the data assimilations rather than the forecasts. Since assimilated data for a large number of parameters and gridpoints are continuously being collected, the size of the archive upon completion will be enormous, making it impractical for small-scale usage such as dispersion modeling. How a subset of the data archive can be utilized in conjunction with the new generation of air quality models, as well as how the subset might be organized to best serve the interests and needs of the dispersion modeling community, are discussed.

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