Downscaling Tehran’s Temperature Field Using Machine Learning Algorithms and Geospatial Interpolation, M.Sc. Thesis Sharif University of Technology ; Moghim, Sanaz (Supervisor)
Abstract
Due to climate change and the increase in the emission of greenhouse gasses, the temperature of the large cities is increasing. Tehran, which is the capital of Iran and the most populated city of it, is no exception. One of the significant tools for characterizing heat in the cities is having access to the temperature field of the region. Different tools can be used for achieving the temperature field. Two methods for doing so are remote sensing and numerical models. Each one of the mentioned methods has their own strength and weaknesses. In this research, the WRF-ARW model (version 3.7) is used for deriving meteorological fields for the city of Tehran. One of the many merits of using...
Cataloging briefDownscaling Tehran’s Temperature Field Using Machine Learning Algorithms and Geospatial Interpolation, M.Sc. Thesis Sharif University of Technology ; Moghim, Sanaz (Supervisor)
Abstract
Due to climate change and the increase in the emission of greenhouse gasses, the temperature of the large cities is increasing. Tehran, which is the capital of Iran and the most populated city of it, is no exception. One of the significant tools for characterizing heat in the cities is having access to the temperature field of the region. Different tools can be used for achieving the temperature field. Two methods for doing so are remote sensing and numerical models. Each one of the mentioned methods has their own strength and weaknesses. In this research, the WRF-ARW model (version 3.7) is used for deriving meteorological fields for the city of Tehran. One of the many merits of using...
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