Dr. Mostafa Karimi, Mis Fatemeh Sotoudeh, Dr. Somayeh Rafati,
Volume 18, Issue 48 (4-2018)
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.
Rahmatollah Shojaei Moghadam, Mostafa Karampoor, Behroz Nasiri, Naser Tahmasebipour,
Volume 18, Issue 51 (7-2018)
Abstract
The purpose of this study is to analyze and analyze Iran's precipitation over the past half-century(1967-2017). For this purpose, the average monthly rainfall of Iran during the statistical period of 50 years was extracted from Esfazari databases (Which is provided using data from 283 stations of Synoptic and Climatology). Regression analysis was used to analyze the trend and to analyze the annual and monthly rainfall cycles of Iran, spectral analysis was used. Investigation and analysis of monthly precipitation trend indicates that except for central Zagros (Lorestan and Chaharmahal va Bakhtiari and Gorgan areas, where rainfall in winter season has increased trend), in other parts of the country and in other seasons, the trend of decline Precipitation is prevalent. The study of Iranian rainfall cycles has been shown that Most of Iran's rainfall cycles are 2 to 4 years old and have a short term course. Meanwhile, there are two middle-cycle 25-year cycles in January-July and two long-term 50-year cycles in March and December, indicating a trend in the March and December rainfall. The two months of February and October lacked a clear cycle. The analysis of the auto-correlation model of rainfall showed that the high spatial auto-correlation model in winter was consistent with the western, southwestern and coastal of the Caspian Sea and covered about 14% of the country's. The low spatial auto-correlation model is found in sparse spots in the southern, central and southeastern regions of the country in winter and spring, and covered about 7.5% of the country's. The results of this study indicate that the overall trend of Iran's rainfall is decreasing trend and only in winter, in the small regions of the country, the increase trend is observed.
Ali Bahri, Younes Khosravi,
Volume 20, Issue 58 (10-2020)
Abstract
Considering the vast application of sea surface temperature in climatic and oceanic investigations, this parameter was studied in Oman Sea from 1986 to 2015. The SST was surveyed using trend analysis and Global and local Moran’s I spatial autocorrelation. In trend analysis, the Mann-Kendall test was used to determine the trend of SST changes and the Sen's Estimator method was used to examine the slope of the changes. Using these methods, it was found that during January, February and December, there was no significant ascending trend in SST values, and only parts of the Strait of Hormuz had a significance descending trend. On the other hand, there was no significant descending trend in March, and the ascending trend in the SST was seen in the southern part of the Oman Sea. Other months of the year had a significant ascending and descending trend in different parts of the Oman Sea, which October had the highest ascending trend. In the annual time scale, it was also found that the southern parts of the Oman Sea had ascending trend in the SST value and Western parts had a descending trend. The occurred changes in the high amounts (positive and negative) were corresponding to the significance ascending and descending trends. The results of Global Moran for the annual time scale indicated an ascending trend of autocorrelation values and cluster patterns of SST data over time, using the local Moran analysis, it was found that warm clusters of SST are increasing in the Oman Sea, and on the other hand, cold clusters of this parameter have been reduced over 30 years. According to the results of trend and spatial autocorrelation analysis, it has been found that SST have been increasing in different parts of the Oman Sea during 30 years, so climate change and global warming may have affected this region.
