16.1 What Issues are Involved in the Generation and Acquisition of

Meteorological Modeling Data?

The recommended approach for generating the meteorological data needed to conduct the

attainment demonstration is to apply dynamic meteorological models with FDDA. These models

use the fundamental equations of momentum, thermodynamics, and moisture to determine the

evolution of specific meteorological variables from a given initial state. When modeling past

events, the use of data assimilation helps to "nudge" solutions so that they do not diverge greatly

from the actual observed meteorological fields. A major benefit of using dynamic

meteorological models is that they provide a way of consistently characterizing meteorological

conditions at times and locations where observations do not exist. Examples of frequently used

meteorological models are listed below:

• The Penn State University / National Center for Atmospheric Research mesoscale model

known as MM5 (Grell, 1994),

• The Regional Atmospheric Modeling System (RAMS) (Pielke, 1992), and

• The Weather Research and Forecasting Model (WRF) (Skamarock, 2005).

Recent advances in relatively low-cost computational power have resulted in widespread

use of MM5 and similar models for air pollution applications over the past decade (Olerud,

2000; Doty, 2001; Johnson, 2003; Baker, 2004b). EPA expects that the large majority of future


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