Behroz Sobhani; Leyla Jafarzade Aliabad; Vahid Safarian Zengir
Abstract
The aim of the current research is to study and predict hazardous extreme temperatures in some cities of central Iran, for this purpose the minimum and maximum temperature data of 15 meteorological stations (cities: Esfahan, Shahreza, Natanz, Nain, Ardestan, Semnan, Shahroud, Garmsar, Damghan, Yazd, ...
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The aim of the current research is to study and predict hazardous extreme temperatures in some cities of central Iran, for this purpose the minimum and maximum temperature data of 15 meteorological stations (cities: Esfahan, Shahreza, Natanz, Nain, Ardestan, Semnan, Shahroud, Garmsar, Damghan, Yazd, Bafaq, Gariz, Meibod, Qom and Salafchagan) were collected for the time period (1999 - 2019) and analyzed using the innovative method of hybrid artificial neural network and ANFIS adaptive neural network model. Finally, Topsis and Saw multi-variable decision-making models were used to prioritize more exposed areas of temperature increase. The results of this study showed that according to ANFIS modelling for predicting station temperatures, the lowest mean educational error and the average error of validation for the minimum temperature, with a value of 0.010 was for the station Yazd and 1.66% for Damghan station. The lowest mean educational error and the mean error of validation for the maximum temperature curve were obtained at 0.016 for Garmsar station and 9.39% for Shahroud station, respectively. The maximum temperature fringe based on the Topsis model of two stations of Garmsar and Bafgh with a percentage of 1 and 0.96, will be in higher priority with increasing temperature. Based on the Saw model, Garmsar and Salafchegan stations with the highest percentages i.e., 1 and 0.98, respectively, were exposed to higher temperatures.
environment
Behroz Sobhani; vahid safarian zengir; Rabab dyhm
Abstract
Thunderstorms rainfalls are a kind of unstable storms that are caused by an extremely strong abnormal state of atmospheric displacement and are one of the most important climatic phenomena in the northwest of the country.The aim of this study was to determine the spatial distribution of thunderstorms ...
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Thunderstorms rainfalls are a kind of unstable storms that are caused by an extremely strong abnormal state of atmospheric displacement and are one of the most important climatic phenomena in the northwest of the country.The aim of this study was to determine the spatial distribution of thunderstorms rainfalls in Ardabil province by using satellite images and Estimation of perceptible water. In this study, synoptic stations data, satellite imagery and MODIS bands 17 and 18 for Estimation of perceptible water were used. Images of thunderstorms rainfalls on 05.10.2010 and 18.06.2012 in ENVI4.4 software was processed and then they were interpolated in ArcGIS. Also, the results of interpolated field data revealed that the highest thunderstorms rainfalls are at Khalkhal station and lowest occurs in Meshkinshar station. In addition, thunderstorms rainfalls in the province in the spring and early summer lightning occurs. The results of the analysis of ground data and satellite imagery indicated this fact that the thunderstorms rainfalls derived from satellite imagery is far more accurate than data that obtained from the harvest of the earth. Also, maps of thunderstorms rainfalls can be extracted quickly and accurately, as well as using in the prediction of atmospheric hazards and optimal water resources planning in Ardabil province.
