RESUMENUna representación apropiada de las fuentes de polvo es necesaria para predecir adecuadamente la concentración de partículas en simulaciones de resuspención de polvo. El modelo Weather Research and Forecasting with Chemistry (WRF/Chem) incluye un mapa de erosionabilidad basado en la topografía del terreno, originalmente desarrollado para simulaciones de escala global, y que en consecuencia no representa apropiadamente la distribución geográfica de fuentes de polvo en Argentina. Por lo tanto, en este trabajo se desarrolla un método para obtener un mapa de erosionabilidad de alta resolución apropiado para simulaciones de escala regional o local con el modelo WRF/Chem. Presentamos dos aproximaciones independientes basadas en métodos globales para estimar la erosionabilidad del suelo a partir de información satelital; una basada en un modelo topográfico de la Shuttle Radar Topography Mission (SRTM) y la otra basada en reflectancia del suelo del instrumento Moderate Resolution Imaging Spectroradiometer (MODIS). Se utilizó la simulación de un evento severo de viento Zonda en la zona árida del centro-oeste de Argentina para analizar estos métodos. La concentración de material particulado simulada se comparó con mediciones realizadas en la ciudad de Mendoza. Además, se utilizó información de espesor óptico de aerosoles (AOD, por sus siglas en inglés) para estudiar el desempeño del modelo para reproducir la distribución espacial de las emisiones de polvo. El mapa basado en reflectancia de MODIS mejora la representación de las características en pequeña escala y mejora las predicciones de inyección de aerosoles con relación al mapa original. La simulación realizada con dicho mapa arrojó valores de concentración que coinciden con las mediciones puntuales y la distribución espacial de AOD.
ABSTRACTA proper representation of dust sources is critical to accurately predict atmospheric particle concentration in regional windblown dust simulations. The Weather Research and Forecasting model with Chemistry (WRF/ Chem) includes a topographic-based erodibility map originally conceived for global scale modeling, which fails to identify the geographical location of dust sources in many regions of Argentina. Therefore, this study aims at developing a method to obtain a high-resolution erodibility map suitable for regional or local scale modeling using WRF/Chem. We present two independent approaches based on global methods to estimate soil erodibility using satellite retrievals, i.e. topography from the Shuttle Radar Topography Mission (SRTM) and surface reflectance from the Moderate Resolution Imaging Spectroradiometer (MODIS). Simulation results of a severe Zonda wind episode in the arid central-west Argentina serve as bases for the analysis of these methods. Simulated dust concentration at surface level is compared with particulate matter measurements at 12 P. G. Cremades et al.one site in Mendoza city. In addition, we use satellite aerosol optical depth (AOD) retrievals to investigate model performance in reproducing spatial...
The Weather Research and Forecasting (WRF) model was used to simulate two mesoscale events of Zonda winds that occurred in August 2010 and April 2011. The model was applied on a complex terrain area of high mountains in Mendoza, western Argentina. The WRF numerical model performance was evaluated for two reanalysis datasets and two land use and land cover databases in order to verify the influence of forcing conditions and to find the configuration that best reproduces these severe conditions. Results were evaluated using meteorological data from three surface stations and two stations with radiosondes for the following variables: temperature, dew point, and meridional and zonal winds components. Upper air data were analyzed for standard pressure levels. Results clearly showed a better performance from the locally adapted model in predicting surface variables. Furthermore, distinct tendencies were found with regard to the preferred configuration for upper air variables at different levels of pressure, both in the use of land use and land cover databases and of reanalysis data.
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