https://www.ims-jmas.net/ Journal of Meteorology and Atmospheric Science en daily 1 Mon, 22 Jun 2026 00:00:00 +0330 Mon, 22 Jun 2026 00:00:00 +0330 https://www.ims-jmas.net/article_254310.html The aim of this study is to comprehensively investigate the climatic factors affecting precipitation in the Urmia Lake basin during the 20-year period from 2003 to 2022. For this purpose, a set of satellite and reanalysis data including CHIRPS, MODIS, ERA5-Land, PM2.5 concentrations, and NAO and SOI teleconnection indices were used. The trend of the time series was assessed using the Mann-Kendall test and the age-slope estimator. The relationships between precipitation and climatic-environmental variables were examined using Spearman correlation, simultaneously and considering time lags (−3 to +3 months). Subsequently, the random forest model was used to identify the relative importance of the variables. The results showed that most climatic and surface variables, including precipitation, temperature, soil moisture, and NDVI, lacked a significant trend during the study period, while PM2.5 concentrations and SLP showed a significant increasing trend. Synoptic analysis of winter precipitation showed that the rainy years were accompanied by the weakening of the Siberian high pressure and the strengthening of the Mediterranean low pressure and troughs. The examination of time lags and correlations shows that soil moisture and relative humidity have the greatest relationship with precipitation and play a short-term precondition role in its occurrence. Based on the results of the random forest model, the soil moisture of the current month is the most important factor controlling precipitation. Overall, the findings show that precipitation plays an important role in surface–atmosphere processes. However, the long-term effects of lake drying and human interventions have weakened this relationship. As a result, the direct link between precipitation variability and both lake conditions and air quality has declined. Consequently, even in years with high rainfall, the drying trend of Lake Urmia has not been reversed. https://www.ims-jmas.net/article_255145.html The increasing frequency and intensity of climate extremes in recent decades highlight the need for reliable tools like Global Climate Models to project future changes in temperature, precipitation, and extreme climate indices at local and regional scales. Given the coarse spatial resolution of GCMs, downscaling approaches (statistical and dynamical) are widely applied to generate station-scale climate information. This study evaluates the performance of the latest version of the stochastic weather generator, LARS-WG8.0, in simulating temperature, precipitation, and climate extreme indices, and subsequently projects their future changes for the near-future period (2031–2050). To this end, daily observed minimum and maximum temperature and precipitation data from Mehrabad synoptic station, Tehran, were obtained from the IRIMO for the baseline period (1981–2010). The comparison of ETCCDI extreme indices revealed that LARS-WG8.0 adequately reproduces the central values and variability of the majority of extreme indices (approximately 12 out of 16 indices) for the study station. However, the most pronounced discrepancies were observed for indices associated with persistent and highly extreme events, including WSDI, CSDI, ID, and R99p. Future projections, derived from the outputs of five CMIP6 models under SSP1-2.6 and SSP5-8.5 scenarios, indicate that the number of summer days (SU) and tropical nights (TR20) will increase by 10–23 days and 12–30 days, respectively, relative to the baseline period. Moreover, maximum 1 day precipitation (RX1day) is projected to increase by up to 19% under the SSP5-8.5 scenario, while no significant changes are anticipated for the consecutive dry days index (CDD). These findings provide valuable insights for climate change adaptation planning and weather-related risk management in the Tehran metropolitan area. https://www.ims-jmas.net/article_255146.html In recent years, destructive floods in South Baluchistan have caused many human and financial losses. The extremely heavy rainfall that have led to major floods in South Baluchistan occur under certain conditions. In this research, two case studies of widespread and severe floods in the southern region of Sistan and Baluchistan province in Dec 2020, and Apr 2024 have been investigated based on the data of provincial stations and Chabahar and Kanarak stations. The statistics recorded in the meteorological stations of Sistan and Baluchistan province show that Sistan and Baluchistan province has had unprecedented rainfall compared to the last 60 years. The statistical results of 24-hour heavy rainfall, based on the latest information received from 16 rain gauge stations, the amount of rainfall received in the province is reported to be more than 100 mm, which is equivalent to the rainfall of one agricultural year this year. Long-term in the statistical analysis section of the Q-Q charts, the observed values, histogram and probability density function related to the observed maximum show that the cumulative rainfall return period of 24, 48, 72, 96 and 120 hours are related to similar return periods. Events in consecutive years are short. The plot of P-P probability or theoretical probability versus the probability values obtained from the fitted probability cumulative function corresponding to each annual maximum observed cumulative rainfall also has an increasing trend. Based on these statistical results, in Chabahar station, the probability of rainfall is more than 40 mm in every 12 years, and the analysis results of Q-Q diagrams and P-P probability diagram in the catchment area of South Baluchistan also show that the probability of daily rainfall is 35 mm every ten years. And every hundred years the probability of rainfall about 50 mm in one day is not far from expected. The results of synoptic analysis in all cases indicate the existence of a low pressure system and a long trough in the upper levels of the atmosphere at the levels of 500, 300, 700 and 850 Hectopascal in the south of the province. The extreme gradient of temperature and wind speed along with vorticity fields are also clearly evident in the region. Heavy rainfall and torrential rain, momentary gusts, 10-degree drop in air temperature and night frost were among the most important phenomena that caught Sistan and Baluchistan province during floods