Articles | Volume 7, issue 4
https://doi.org/10.5194/gmd-7-1641-2014
https://doi.org/10.5194/gmd-7-1641-2014
Methods for assessment of models
 | 
14 Aug 2014
Methods for assessment of models |  | 14 Aug 2014

Influence of high-resolution surface databases on the modeling of local atmospheric circulation systems

L. M. S. Paiva, G. C. R. Bodstein, and L. C. G. Pimentel

Abstract. Large-eddy simulations are performed using the Advanced Regional Prediction System (ARPS) code at horizontal grid resolutions as fine as 300 m to assess the influence of detailed and updated surface databases on the modeling of local atmospheric circulation systems of urban areas with complex terrain. Applications to air pollution and wind energy are sought. These databases are comprised of 3 arc-sec topographic data from the Shuttle Radar Topography Mission, 10 arc-sec vegetation-type data from the European Space Agency (ESA) GlobCover project, and 30 arc-sec leaf area index and fraction of absorbed photosynthetically active radiation data from the ESA GlobCarbon project. Simulations are carried out for the metropolitan area of Rio de Janeiro using six one-way nested-grid domains that allow the choice of distinct parametric models and vertical resolutions associated to each grid. ARPS is initialized using the Global Forecasting System with 0.5°-resolution data from the National Center of Environmental Prediction, which is also used every 3 h as lateral boundary condition. Topographic shading is turned on and two soil layers are used to compute the soil temperature and moisture budgets in all runs. Results for two simulated runs covering three periods of time are compared to surface and upper-air observational data to explore the dependence of the simulations on initial and boundary conditions, grid resolution, topographic and land-use databases. Our comparisons show overall good agreement between simulated and observational data, mainly for the potential temperature and the wind speed fields, and clearly indicate that the use of high-resolution databases improves significantly our ability to predict the local atmospheric circulation.

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