INTERCOMPARISON OF METEOROLOGICAL MODELS APPLIED TO THE ATHENS AREA AND THE EFFECT ON PHOTOCHEMICAL POLLUTANT PREDICTIONS

Citation
P. Grossi et al., INTERCOMPARISON OF METEOROLOGICAL MODELS APPLIED TO THE ATHENS AREA AND THE EFFECT ON PHOTOCHEMICAL POLLUTANT PREDICTIONS, Journal of applied meteorology, 35(6), 1996, pp. 993-1008
Citations number
23
Categorie Soggetti
Metereology & Atmospheric Sciences
ISSN journal
08948763
Volume
35
Issue
6
Year of publication
1996
Pages
993 - 1008
Database
ISI
SICI code
0894-8763(1996)35:6<993:IOMMAT>2.0.ZU;2-N
Abstract
In this study, four different meteorological models, one diagnostic an d three prognostic, are used to develop meteorological inputs for a ph otochemical model, as applied to the peninsula of Athens, Greece. The comparison of meteorological models results pointed out significant di fferences in the calculated wind fields, mainly during the night perio d. These differences are linked to specific aspects of the models, suc h as model vertical resolution, hydrostatic versus nonhydrostatic form ulation, and numerical diffusion. During the day hours, models produce quite similar wind fields, which agree correctly with the available o bservations related to the Athens center area. Using the different win d fields as input to a photochemical air quality model led to similar urban ozone levels in the Athens area. Outside of the city, the differ ent wind fields transport the urban plume in different directions in a range of 50 degrees. The more primary pollutants, for example CO and NO2 concentrations, varied significantly due to the different wind vel ocities predicted by meteorological models. The effect of the atmosphe ric deposition can be near zero or can go up to 25% for ozone and to 4 5% for NO2. The determination of the most appropriate wind field to be used for the photochemical modeling would have required a more compre hensive set of observed data. Therefore, when data are scarce, it may be recommended to use different wind field modeling techniques to asse ss the sensitivity and the robustness of the predicted concentrations.