issue 17, Issue 47 (3-2018)                   researches in Geographical Sciences 2018, 17(47): 0-0 | Back to browse issues page

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keikhosravi G. Simulation and post-procession of temperature and precipitation elements, using output of RegCM4 dynamic model in Great Khorasan. researches in Geographical Sciences. 2018; 17 (47)
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Abstract:   (117 Views)

In this study, precipitation simulated annual and seasonal in north-east of Iran (Great Khorasan) In the period 1987-2011, using RegCM4 dynamic model in two case; with and without using post-processing technique. The required data for RegCM4 model with NetCDf format, received from ICTP center. For the implementation of the main dynamic model, Convective precipitation test scheme and the horizontal resolution, performed for year 2007. According to the test, Kuo Schema had less error than Emmanuel and Gurl schemes in Precipitation and region temperature modeling. Horizontal resolution selected 30 kilometer. After model implementation with Gurl schema and 30 kilometer horizontal resolution, Precipitation and temperature output post- processed using MA model. According to results, in the study area, during 2006-2011 verification period, average annual rainfall raw bias of RegCM4 model was calculated and post-processed equal to 8.3 millimeter and 61.04 respectively. Briefly in the annual time scale, in 75% of studied stations, post-processing is effective and MA model is more efficient. In seasonal scale, bias error of average precipitation is equal to : 54.99 millimeter in the winter, 27011 millimeter in the spring, -3.6 millimeter in the summer and 7.21 millimeter in the fall. Simulation of the temperature data in the stations using RegCM4 and MA model in north-east of Iran, revealed high performance. Bias error of average temperature is equal to -2.78 for RegCM4 model and post-processed equal to -0.05. In all stations, modeled Annual temperature and observational data has difference less than 0/1 ° C. In seasonal scale, the mean bias error range according ° C is equal to: -4.1 in the winter, -4.09 in the spring, -1.8 in the summer and -1.5 in the fall.

Type of Study: Research | Subject: Special
Received: 2016/09/5 | Accepted: 2018/01/26 | Published: 2018/02/7

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