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Title

AN EXPERIMENTAL MODEL DESIGN, FOR ANALYSIS OF PERCEPTIBILITY OF SYNOPTIC PATTERNS (PSP)

Pages

 Start Page 1 | End Page 30

Abstract

 According to the computational and physical simplifications used in regional climate models and NUMERICAL WEATHER PREDICTION models, none of them can predict the weather and climate accurately. A fully statistical technique, named MaS, has been recently used for calibration and decreasing of the errors in numerical models. Physiographic characteristics, climatic behavior and regional synoptic climatology are not included in this technique. For overcome to this deficiency, an empirical model, named PSP\ including topographic, climatic and synoptic behavior of the region under study has been developed for DOWNSCALING of numerical models outputs in to computational grid-points for determination of daily precipitation. Daily 2.5*2.5 degree GFS2 data from NOAA3 has been used for running the model. More than 85 weather systems has been studied in the period of 2002-2007 and coefficients of the model has been determined gradually by using statistical regression between model and observed precipitation. Model outputs in surface and 500hpa levels have been used as input of the PSP model during each weather system affecting IRAN. Then we compared model outputs with actual weather data reported by synoptic stations. A CLIMATIC AND PHYSIOGRAPHIC INDEX named CPI1 defined for all of synoptic stations of IRAN. Monthly mean precipitation, monthly mean temperature, monthly number of days with precipitation, station latitude and height of station from sea level are included in CPI index. CPI index was used for determination of daily precipitation amount of synoptic stations. CPI can be used for climate classification and climate change issues as well. Using PSP parameters in each station under study then plots the PSPs charts. Finally using regression equation between model PSP and actual precipitation can compute daily precipitation amount in millimeters.

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