Applied Research in Geographical Sciences

Applied Research in Geographical Sciences

The Trend Analysis and Forecasting of Extreme Temperature Parameters in southern part of the Caspian Sea

Authors
Mostafa Karimi 1
Fatemeh Sotoudeh 2
Somayeh Rafati 3
1 Unoversity of Tehran
2 Unoversity of Kharazmi
3 , University of Sayyed Jamaleddin Asadabadi
10.29252/jgs.18.48.79
Abstract
Increasing CO2 emissions and consequently, air temperature causes climate anomalies which affects all the aspects of human life. The purpose of this study was to assess the temperature changes and also to predict the extreme temperatures in Gilan and Mazandaran Provinces. To do this, the SDSM statistical and dynamical model was used. As well, it was applied the Mann-Kendal graphical and statistical technique to analyze the temperature changes and its trend. In this regard, the daily temperature was obtained from Rasht, Ramsar and Babolsar synoptic stations during 1961 – 2010, and also the general circulation models data of HadCM3 and NCEP were collected from related databases. The results revealed a significant positive trend in monthly and annual minimum and maximum temperature in all three stations in the first (1961-2010) and third (1961-2040) periods. There is not a significant trend in extreme temperatures in Ramsar and maximum temperature in Rasht in the second period (2011-2040). The Mann-Kendal graphical test was used for the yearly extreme temperatures in all periods. The results showed that it was occurred both increasing trend and suddenly changes or shifts at the 95% confidence level in all stations. It is occurred the highest of changes in monthly and annual of the minimum temperature at forecasted period (2011-2040). It was predicted extreme temperature to increase about 0.1 to 1.7° C. The short time oscillations and significant positive trend occurred in both the maximum and minimum temperature shows the temperature increase and climate changes in the future. Thus it is obvious the decrease in temperature difference in warm and cold seasons.
Keywords
trend analysis
Forecasting
modeling
Climate Change
Extreme Temperature
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