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Weiguo Wang, William J. Shaw, Timothy E. Seiple, Jeremy P. Rishel, and Yulong Xie

Abstract

A U.S. Environmental Protection Agency (EPA)-approved diagnostic wind model [California Meteorological Model (CALMET)] was evaluated during a typical lake-breeze event under fair weather conditions in the Chicago region. The authors focused on the performance of CALMET in terms of simulating winds that were highly variable in space and time. The reference winds were generated by the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) assimilating system, with which CALMET results were compared. Statistical evaluations were conducted to quantify overall model differences in wind speed and direction over the domain. Below 850 m above the surface, relative differences in (layer averaged) wind speed were about 25%–40% during the simulation period; wind direction differences generally ranged from 6° to 20°. Above 850 m, the differences became larger because of the limited number of upper-air stations near the studied domain. Analyses implied that model differences were dependent on time because of time-dependent spatial variability in winds. Trajectory analyses were made to examine the likely spatial dependence of CALMET deviations from the reference winds within the domain. These analyses suggest that the quality of CALMET winds in local areas depended on their proximity to the lake-breeze front position. Large deviations usually occurred near the front area, where observations cannot resolve the spatial variability of wind, or in the fringe of the domain, where observations are lacking. Results simulated using different datasets and model options were also compared. Differences between CALMET and the reference winds tended to be reduced with data sampled from more stations or from more uniformly distributed stations. Suggestions are offered for further improving or interpreting CALMET results under complex wind conditions in the Chicago region, which may also apply to other regions.

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Jerome D. Fast, William I. Gustafson Jr., Elaine G. Chapman, Richard C. Easter, Jeremy P. Rishel, Rahul A. Zaveri, Georg A. Grell, and Mary C. Barth

Abstract

The current paradigm of developing and testing new aerosol process modules is haphazard and slow. Aerosol modules are often tested for short simulation periods using limited data so that their overall performance over a wide range of meteorological conditions is not thoroughly evaluated. Although several model intercomparison studies quantify the differences among aerosol modules, the range of answers provides little insight on how to best improve aerosol predictions. Understanding the true impact of an aerosol process module is also complicated by the fact that other processes—such as emissions, meteorology, and chemistry—are often treated differently. To address this issue, the authors have developed an Aerosol Modeling Testbed (AMT) with the objective of providing a new approach to test and evaluate new aerosol process modules. The AMT consists of a more modular version of the Weather Research and Forecasting model (WRF) and a suite of tools to evaluate the performance of aerosol process modules via comparison with a wide range of field measurements. Their approach systematically targets specific aerosol process modules, whereas all the other processes are treated the same. The suite of evaluation tools will streamline the process of quantifying model performance and eliminate redundant work performed among various scientists working on the same problem. Both the performance and computational expense will be quantified over time. The use of a test bed to foster collaborations among the aerosol scientific community is an important aspect of the AMT; consequently, the longterm development and use of the AMT needs to be guided by users.

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