Kamal Omidvar, Reza Ebrahimi, Mohammad Kykhsrvy Kayani, Ghasem Lkzashkoor,
Volume 16, Issue 43 (12-2016)
Abstract
The aim of this study was to investigate the effects of global warming on where the slope changes when the monthly temperature in Iranian territory over the coming decades (2050-2015). The simulated temperature dynamic model EH5OM subset Hybrid Models atmospheric circulations (GCM) selection and data model of the Center for Theoretical Physics Salam (Italy) were derived from emission scenarios A1B scenario was chosen given the scenario of 2100 -2001 found that from 2050 to 2015 were used in this study data is then output the data in the fourth edition of the regional climate model (RegCM4) Linux environment was fine scale output data Downscaling model with dimensions of 27/0 * 27 / Degrees latitude is where the dimensions of 30 x 30 km area of approximately cover the average temperature of the matrix deals 13140 2140 * was extracted. Finally, the slope of the average monthly temperature during the period under study by Mann-Kendall slope age and matrix computation in MATLAB software 13140 * 12 respectively. Results show rising temperatures in March and April to June, more than 90% of the country, that it will be spring's warmer. Increasing the temperature in the winter months and spring mountainous parts of the western half of the country is warming the cold regions of Iran. Temperature negative trend in October and November in the northern part of the eastern half of the region's countries could be indicative of colder temperatures in the northern West.
Fatemeh Ghiasabadi Farahani, Faramarz Khoshakhlagh, Aliakbar Shamsipour, Ghasem Azizi, Ebrahim Fattahi,
Volume 18, Issue 48 (3-2018)
Abstract
The present research about the spatial changes of precipitation is mainly focused on western areas of Iran. Precipitation data for three seasons of fall, winter, and spring have been obtained from Esafzari Database, with 15*15 km spatial resolution in the form of a Lambert Cone Image System for the period from 1986 to 2015. To examine the prevailing pattern of precipitation in west of Iran, we have used geostatistical methods of spatial autocorrelation. The changes in precipitation trends have been analyzed using parametric and non-parametric analyses of regression and Mann Kendal. We have used MATLAB for analysis of the data. We have also used ArcGIS and Surfer for drawing maps. The results of inter-decade changes of positive spatial autocorrelation of precipitation in west of Iran have indicated that there has been a decline in spatial extent of the positive spatial autocorrelation pattern in spring and fall, except for winter with a negligible increasing trend. Nevertheless, except for the second period, no considerable spatial changes were observed in the spatial pattern of precipitation in the region. However, there was a decreasing trend in the negative spatial autocorrelation of precipitation in annual and seasonal scales. The results of trend analysis have indicated that there was a decreasing trend in a vast area of the west parts of the country in annual scale and also in winter. Although there was an increasing trend in precipitation in fall and spring, but the trend was not significant in 95 % of confidence interval. The results of Man Kendal test have confirmed the results obtained from linear regression.
Engineer Amenh Khosravi, Doctor Mahmood Azari,
Volume 22, Issue 66 (9-2022)
Abstract
The study of meteorological characteristics and its variability is important in assessing the climate change impacts for water resources management. Trend analysis of hydrological and meteorological time series is a method for determining the change in climate variables that is performed with different parametric and non-parametric methods. In this research, the annual, seasonal and monthly trends were analyzed regarding rainfall and temperature time series for 1986-2017 in 28 stations of Kashafroud basin in the Northeast of Iran. For this purpose, the annual, seasonal and monthly trends were evaluated using non-parametric Mann Kendall and Pettitt test at 95% level significance. The results showed the trend for the monthly maximum temperature in spring and winter and also the annual trend for all stations was increasing, whereas the summer and autumn pattern differed. The trend of minimum temperature in all seasons and stations do not have a uniform pattern. The results of precipitation trend indicated that the annual precipitation of the basin had not changed and did not have a significant trend in 5% level of significance. Precipitation of the basin in the winter decreased. There was an increasing trend in the Southern half of the basin in autumn. The noticeable decrease of precipitation in winter season especially during January and February with an increase in November can be a serious challenge for water resource management of basin during the dry season.
