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Modeling Urban Land surface temperature at the local scale.

Urban areas are home to millions of people who are exposed to the climatological conditions of their environment every day. They are continuously facing too many problems in day-to-day life. A city competitive is an important part of successful urbanization, because it creates jobs, raises productivity, and increases people’s wages. They should have good land use management and strong institutions for a better lifestyle and future. So, the urban climate and its study are becoming increasingly important as these regions because it shows a significantly high rate of population growth and development which will exacerbate the environmental challenges already present.

ENVI-met is a 3D model designed for a wide range of temporal and spatial inquiries and can reveal credible urban geometry differences by capturing their impacts on microclimatic conditions. It also has the capacity to analyze the wide array of spatial scales from as small as a courtyard to as large as an entire city. The software will help to minimize heat stress, air pollution, and many more by providing up-to-date numerical simulation techniques. A more holistic approach can resolve the dynamic interaction between plants, buildings, and the atmosphere using ENVI met software. The main input parameters for ENVI-met include meteorological data, initial soil wetness, and temperature profiles, structure, and properties of ground surfaces, vegetation elements, and buildings. 1D boundary model (from the ground level to 2500 m height) is used for the initialization of the model and for the 3D atmospheric model the different elements (e.g.; buildings) are included. The software allows simulating (Wind speed and direction, air and soil temperature, air and soil humidity, turbulence, radiative fluxed, and gas and particle dispersion). (Juan A. Acero 2016). The ENVI-met model is one of the most widely employed dynamic simulation tools. As a non-hydrostatic model that simulates surface-plant-air interactions inside urban environments on a three-dimensional rectangular grid with variable spacing in x, y, and z directions. It was developed to simulate meteorological variables in urban areas with a typical grid resolution of 0.5 to 10m. (Bruse and Fleer 1998).

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Map Credits: Mira Shivani Sankar

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