The purpose of this article is to analyze the frequency and severity of the one to six days of rainfall in Iran. The trend of frequency changes and severity of each course was identified using my-candle test and the slope estimator during the 1968-1988 period. Then, using the main component analysis method and cluster analysis method, the entire stations were categorized in five clusters (abundance) and four (intensity) based on the annual changes of frequency indicators and intensity of precipitation. Cluster 1 and 2 stations represent the frequency of precipitation periods with a severe or without trend. The two clusters were mostly established in the southern half of Iran. Cluster 4 and 5 stations represent the frequency of precipitation periods with a positive (mild) trend, mainly in the northern part of the country. Cluster 3 stations represent the frequency of precipitation periods with decreased (mild) trends, which are mostly focused on west and southwestern Iran. The clustering results of the stations based on the intensity index of precipitation periods, contrary to many results; do not show a specific pattern. But in the cluster, there has been a severe decrease in the last half century. The stations of this cluster are mostly concentrated in the northern parts of the country. Other clusters are scattered in almost all parts of the country. Accordingly, it can be concluded that the frequency of precipitation periods in the northern latitudes of incremental processes (average or weak) and the severity of precipitation periods in these latitudes (north of the country) had severe declining trends.

Keywords: Frequency of precipitation, intensity of precipitation, analysis of main components, clustering, process.
 

 Assessing and predicting future climate change is of particular importance due to its adverse effects on water resources and the natural environment, as well as its environmental, economic and social effects. Meanwhile, rainfall is also an important climatic element that causes a lot of damage in excess conditions. West Azerbaijan Province is no exception. The aim of this study is to model and predict 30 years of rainfall in West Azerbaijan province. The statistical period studied is 32 years (2019-1987). Selected stations in the province include Urmia, Piranshahr, Takab, Khoy, Sardasht, Mahabad and Mako stations. Average slider time series models, Sarima (seasonal Arima), Health Winters were used for analysis and prediction and also linear regression and Mann-Kendall test were used to determine the data trend. The results show an increasing trend of precipitation in Urmia, Piranshahr, Khoy, Sardasht and Mako stations and a decreasing trend in Takab and Mahabad stations. According to the results of comparing the models used, the Health Winters model with the least error in the absolute mean of deviations, mean squared deviations and the percentage of absolute mean errors was introduced as the best precipitation forecasting model for West Azerbaijan province. province.                                     [A1] 

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Due to the significance of forests in both the natural and human environment, this study aims to investigate the impact of meteorological drought on oak forest dieback in Ilam province. Specifically, the study seeks to determine the relationship between Zagros Forest drought and droughts in this particular region. The analysis utilizes the Standard Precipitation Index (SPI) to identify the frequency of droughts during different time periods. The results indicate that the years 2007, 2008, 2011, 2015, and 2016 experienced the highest occurrence of droughts. Additionally, remote sensing data from MODIS images were employed to examine the trend in tree greenness (NDVI) from 2000 to 2016. The analysis reveals a significant correlation (R2 = 0.9999) between the greenness trend and the drought index (SPI). Moreover, a land survey of oak drying points and simulation using Landsat satellite images, with a 15×15 pixel output from GIS software, indicate that approximately 17,894 hectares of forests in the region experienced drying and destruction between 2000 and 2016. By combining the oak forest drying layer with the output layers derived from drought zoning, visual indicators were created, and statistical analysis was conducted for three 5-year time series. The results demonstrate a correlation coefficient of 96.6% and an explanation coefficient of R2 = 0.985 for the 2002-2006 time series, a correlation coefficient of 95.4% and an explanation coefficient of R2 = 0.980 for the 2007-2011 time series, and a correlation coefficient of 98.8% and an explanation coefficient of R2 = 0.995 for the 2012-2016 time series. These findings illustrate the influence of drought and its variations in terms of intensity and duration on oak forests in the Zagros region of Ilam. Based on the study results, it is predicted that if the drought persists with the same trend, approximately 1,118.4 hectares of oak forests in Ilam province will dry up and be destroyed annually.

To conduct this research, data on monthly synoptic and hydrometric precipitation observations from the National Meteorological Organization and the Ministry of Energy were obtained for a 30-year period (1976-2005). To assess future changes in rainfall, historical data from the period (1976-2005) and simulated climate data from the period (2021-2050) using two models (CM3 and CSIRO-Mk3.6) from the CMIP5 series were used. These simulations were based on four scenarios (RCP2.6, RCP4.5, RCP6, and RCP8.5) with a spatial resolution of 0.5 x 0.5 using the BCSD method. A mean-based (MB) strategy was employed to correct any bias in the model outputs.  The results of the AOGCM models indicated that the CSIRO-Mk3.6 model had a lower error coefficient than the GFDL-CM3 model when simulating precipitation in the Large Karoun case. The average future rainfall (2021-2050) across the entire basin, compared to the average observed rainfall during the statistical period of 1976-2005, exhibited a significant decrease in both the amount and extent of precipitation in both basins for all models and scenarios. In the Great Karoun Basin, heavy rains were consistently concentrated east of the basin across all scenarios and models, with the central foothills experiencing the highest rainfall and the southwest and southeast regions receiving the lowest amounts.  The findings of this study estimate rainfall to range between 83-116 mm, with the highest rainfall expected in the Greater Karoun Basin under the rcp4.5 and rcp2.6 scenarios for both models.

Extratropical cyclones, characterized by their frequency, duration, and intensity, serve as the primary drivers of mid- and high-latitude precipitation across the Mediterranean during the winter and autumn months. For this research, climatic variables obtained from the ECMWF network, featuring a temporal resolution of 6 hours and a spatial resolution of 0.25° × 0.25°, spanning from 1979 to 2016, were utilized. Additionally, precipitation data from four basin stations sourced from the Asfezari database for the same period were analyzed. Initially, geopotential height, temperature, humidity, and jet stream data for rainy days were extracted using MATLAB. Subsequently, a cyclonic center extraction algorithm was applied to identify cyclonic centers from the geopotential height data, based on the conditions that the geopotential height is at a minimum and the geopotential gradient is at a maximum. From the geopotential height matrix of rainy days (361×441×498), four distinct atmospheric patterns were identified through cluster analysis. The temporal and spatial frequency of these patterns, as well as the average temperature of cyclonic centers, were analyzed for the cold season months. The results indicated that the first pattern, identified as the Mediterranean trough pattern, is the most frequent, occurring 42% of the time. This pattern is characterized by the presence of a high-level system acting as a barrier, which deepens the low-level Mediterranean system and extends its axis toward the Red Sea. The interaction between low-level and high-level systems enhances instability, resulting in the highest precipitation levels among the identified patterns. Conversely, the fourth pattern, termed the western wind trough pattern, exhibits the lowest frequency at 10%. This pattern is characterized by a trough over the Caspian Sea; however, a high-level system in the southern region inhibits the entry of low-level systems, thereby confining cyclonic activity to the northern portion of the study area. Consequently, the isobars in the northern region assume a more orbital configuration, leading to a decreased influx of cyclones and, as a result, lower precipitation amounts compared to the other patterns. The analysis further revealed that cold-core cyclones accounted for 60% of occurrences in winter and 40% in autumn, while hot-core cyclones constituted 62% in winter and 38% in autumn. Notably, the frequency of hot-core cyclones increased relative to cold-core cyclones in winter, whereas an inverse trend was observed in autumn. Over the past decade, both the frequency and intensity of cyclones have diminished compared to the preceding two decades. In terms of cyclogenesis locations, the western part of the study area has consistently emerged as the most active region. Moreover, cyclogenesis activity exhibits a gradual increase from autumn to winter as the cold season progresses. These findings underscore the dynamic nature of extratropical cyclones and their significant role in shaping precipitation patterns across the Mediterranean region.