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Published on: October 16, 2018
Implementation and evaluation of WRF simulation over a city with complex terrain using Alos-Palsar 0.4 s topography
Marco Andrés Guevara Luna1,2,3, Alejandro Casallas4, Luis Carlos Belalcázar Cerón5
1Grupo de Investigación de Calidad del Aire (GICA), Universidad Nacional de Colombia, Bogotá, 111071, Colombia. maguevaral@unal.edu.co.
Abstract:
Air quality modeling requires an accurate representation of meteorology, and in cities with complex topography, the performance of meteorological modeling can be improved by using an alternative global digital elevation model (GDEM) such as Alos-Palsar 0.4 s instead of the default elevation data. Bogotá is a city with complex topography geographically located over the Andes Mountains at 2600 m.a.s.l. A reliable meteorological simulation model is critical for performing a suitable air quality modeling in any case of study. Previous researches have been developed using the standard Weather Research and Forecast (WRF) topography (GTOPO 30 s). These studies have been developed with different configurations for the representation of meteorology. The aim of this study is to evaluate Alos-Palsar 0.4 s topography with WRF, and two domain configurations with horizontal spatial resolutions up to 1000 m, to establish a reliable and accurate way to simulate the meteorology in the city of Bogotá. The evaluation quantitative parameters: IOA, r (Pearson), RMSE, MGE, and MB were calculated for the quantitative evaluation of temperature, relative humidity, wind speed, wind direction, and solar radiation. An additional evaluation using Taylor diagrams was performed. Spatial differences were identified in the same locations as well the differences between the elevation from Alos-Palsar 0.4 s and GTOPO30. The results and evaluation suggest that simulations based on Alos-Palsar 0.4 s topography lead to a significant improvement in the meteorology representation by WRF in a region with complex topography such as Bogotá, Colombia.
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Levels of Use of a GIS
Design Example: Analyzing Capacity Contours for Flood Risk Assessment
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