Post-processing of Precipitable Water from WRF Prediction Model with used of Genetic Algorithm and Met-8(IODC) Data over non-radiosound station points
Message:
Abstract:
The precipitable water is the integrated water content in the whole column of the atmosphere that has the potential to precipitate. In more precise terms prediction of PW is one of the common issues of meteorology and hydrology. Countries facing water scarcity require an advanced management of water resources that one of the management tools in this area being knowledge of the total precipitable water content (TPW) in the atmosphere. Also accurate estimation of this quantity in many meteorological issues such as prediction of rainfall, time, dams overflow and also prediction of flood occurrence is beneficial. Iran's roughness is one of the main factors in the heterogeneous distribution of precipitable water in the atmosphere. So that most researchers believe that the main reason for the existence of many Iranian leeward deserts is the roughness such as Zagros. With the discovery of new remote sensing technology, it is possible to estimate the amount of precipitated water vapor by absorbing water vapor bands and thermal bands at any time and place and at any scale.In the first we compare the precipitable water values of two European and Chinese satellites, METEOSAT and FENGYUN respectively, with corresponding parameter of radiosound that calculated for Mashhad and Tehran airport stations. By comparing precepitable water data for about two years from two meteorological satellites and radiosound for two mentioned station, there is a good aggrement between precipitable water parameter of the METEOSAT European satellite and radiosounds. But the FY-2E Chinese satellite doesn’t have good correlation with the Mashhad and Tehran airport radiosound station. So in this article we use MET-8 satellite to post-processing precipitavle water of WRF Model in non-observational points. Finally, we compared the post-processed values and compared the MSG1 satellite values in 6 different Iranian cities with different climatic conditions.
Language:
Persian
Published:
Pages:
41 to 44
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