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. 
 

Probable maximum precipitation (PMP), is the highest rainfall, which occurs at a given time in a basin. Hydrologist calculates the probable maximum flood for the design of overflow dams, by using the PMP, with two methods: statistical and synoptic. The purpose of this study is calculating PMP in the Ghomrood basin by using the synoptic method. For this purpose rain, meteorological data of the Iran’s Meteorological Organization were used. Also, the data on the 850 and 500 hPa levels were analyzed by the National Center for Environmental Prediction and the National Center for Atmospheric Research (NCEP-NCAR). In the following, the required synoptic maps produced and were studied. Iso rain maps were drawn, and depth-area-duration curves were determined. Eventually, PMP was estimated at 24, 48 and 72 hours. So that 24 hours PMP, by calculating 50 and 100 years return period of dew point estimated 51/75 and 54 mm respectively. Also for 48 hours PMP 128/25 and 132/05 mm, and for 72 hours PMP 97/9 and 101/75 estimated.

 In this study in order to monitor snow cover, the Moderate Resolution Imaging Spectroradiometer (MODIS) optical images were used, while for detection of snow covered areas, the  snow index-NDSI, was applied. The results showed - according to the climatic conditions of the region- during the following months: December, January, February and March, most of the area is covered by snow and the maximum extent of snow cover occurred in January. In West Azerbaijan province there is found a negative trend of snow cover with a drastically reduction in January, as well as the provinces East Azerbaijan and Ardebil showed the decreasing of snow cover in this month. The results of this study show that, changes in snow cover imply a rise in temperature in this region leading to the reduction of snow cover in January. This trend represents global warming and climate change impacts on snow cover in the study area. Investigation of extreme indices  confirms the assumption that by taking temperature increase into consideration, regional winter precipitation pattern has been changed from snow to rain, causing the reduction of snow storage in the catchment of study area. In addition ,the extreme temperature index study  in the period of 2011- 2040 and the baseline by considering climate change approach in North West of Iran by using outputs of general circulation models under A2 scenario and downscaling models LARS-WG indicates the number of frost days or the number of  icy days decreased compared to the baseline which is not unexpected according to reports by the Intergovernmental Panel on Climate Change (IPCC) as well as several studies confirmed  global warming. Moreover, indices such as growth period increased, while diurnal temperature variation decreased compared to the baseline confirming   snow cover reduction in the region as a threat of snow storage in the region. 

This research aims to study the impact of temperature and wind in the southern low-pressure system and its associated precipitation in the southern regions of Iran. As The southern low pressure system moves eastward, it crosses the southern regions of Iran, causing medium and heavy rainfall in these areas. In this study, two southern low-pressure systems that caused heavy rainfall on March 11, 2015 and January 17, 2000 in southern Iran were selected, analyzed and simulated using the numerical Weather Research and Forecasting (WRF) model. Since the wind and temperature fields play a significant role in the southern low-pressure systems, four experiments were performed for investigating the effects of temperature and wind on the intensification and weakening of the southern system. The simulation results showed that the simulation for the increased (decreased) temperature caused the weakened (intensified) the southern low pressure in the studied area. This result showed that the vertical structure of the southern low-pressure and its physical characteristics are similar to the mid-latitudes cyclones, and these systems were different from the thermal low pressures. The results of wind speed changes showed that the increased (decreased) wind speed simulation caused an increase (decrease) in relative vorticity, thus the southern low pressure was intensified (weakened). In both cases, the rainfall was decreased by the increased temperature simulation, and decreased temperature caused an increase in rainfall. It was also seen that the increase in wind speed caused the special humidity advection to be increased and then the rainfall increased. Also the amount of rainfall decreased when conditions did not provide for the advection of specific humidity or the wind speed reduced.

During the rainfall, the intensity of precipitation varies. Changes in the amount of precipitation during an event of rainfall are effective in the resulting of flood and its intensity. Knowledge of how rainfall changes over time during rainfall is determined by temporal distribution pattern of rainfall. For this purpose, availability of short-term time scales rainfalls data are important that obtained by rain gauge stations. However, the low density of the rain gauge network and the lack of sufficient data from the time pattern of rainfall have always been a problem in determining storm patterns for executive plans. Therefore, the simulation of WRF numerical weather models can be used. The WRF model is one of the most responsive models for predicting precipitation, temperature and atmospheric elements that used in this study. In this paper, three great storm events on 15 December 2003, 24 - 26 December 2006 and 6-7 March 2007 have been selected in the Parsian dam basin and surrounding areas in south west of Iran. The result of WRF numerical weather prediction model for these great storms compared with data loggers. It showed that the WRF model was able to performance the heavy rainfall and simulates the rainfall pattern in these dates.