نشریه نیوار
پیاپی 127-128 (بهار و تابستان 1404)

Rainfall, as a random variable, is one of those climatic elements that have significant changes in duration and location. Meanwhile, investigating the temporal and spatial distribution of precipitation in a place is of particular importance. In this research, the daily rainfall data of 38 synoptic stations during the 30-year statistical period (1981-2010) have been used to analyze the temporal and spatial changes of Iran's autumn rainfall with the non-parametric Mann-Kendall, ShibSense, and cluster analysis methods. The results of the research show that in the time series of the average autumn rainfall stations in Iran, the increasing trend in October at the Saqez station is at the 95% probability level. In October, the rainfall at Bojnord station decreased by 4.6 mm, and in December at Kermanshah station, it decreased by 16.5 mm. The annual trend of fall season rainfall in Qazvin and Khoi stations has decreased by 24.2 and 21.1 mm in the last decade, respectively. The analysis of autumn rainfall trends using the Mann-Kendall test also showed that Saqez station had a significant increase in rainfall in November, and Bojnord, Kermanshah, Qazvin, and Bojnord stations experienced sudden changes, either increasing or decreasing, during the statistical period. have experienced, but they do not show a significant trend. The results of the cluster analysis also showed that the mentioned region includes low rainfall, high rainfall and medium rainfall, so that the month of December has the highest share of autumn rainfall and the month of October has the lowest share. Autumn rain has taken its place.

The Persian Gulf is a semi-closed sea that leads to the Gulf of Oman and open waters through the Strait of Hormuz. the main inflow is the Indian Ocean Surface Water (IOSW), which after circulating in the Persian Gulf, Persian Gulf Water (PGW) is created. It was used 11 stations of a valid data set, temperature and salinity, of wintertime ROPME1992 Crouse, which was prepared from the National Oceanographic Research Institute to investigated temperature and salinity changes by measurements and density, sound speed, and water column stability changes caused by software calculations (Ocean Data View) due to the inflow and outflow of Persian Gulf. The measured stations started from Iranian Waters (Lavan Island) and continued until the United Arab Emirates (Sir Bani Yas Island). The results showed water temperature changes in winter between 17.56°C and 20.25°C, salinity changes from 38.48 psu to 43.93 psu, potential density anomaly changes from 27.47 kg/m3 to 19.32 kg/m3 and the changes of sound speed are 1521.7 m/s to 1528 m/s. Southern shallow waters have lower temperature, higher salinity and density. In density changes, the role of salinity is greater than temperature, but in the changes of sound speed, temperature has a greater contribution in the north of the Persian Gulf and in the south of it, salinity has a greater contribution. The highest speed of sound is related to the north and the lowest is related to the middle and south of the Persian Gulf. Near the coasts of Iran, at the depth more than 30 meters, a subsurface flow of warm water is observed, which is not affected by the surface layers that have cooled in winter, and still has the effected by Indian Ocean Surface Water (IOSW). The presence of CE1 eddy, at station 4, at a depth of about 30 meters is completely visible, which is due to the return of the IOSW flow. Although the water column from station 5 to 9 is mixed and relatively homogeneous, it is horizontally heterogeneous. Also, the results clearly show that the two different flow of IOSW (in the north) and PGW (in the south) cause different water column stability regimes, so that in the northern stations, the diffusive regime and in the southern stations, the finger regime plays a greater role in creating double diffusion convection. In the southern stations, layers consisting of static instability are seen more than layers consisting of double diffusion convection in the water column. In conclusion, the diffusive regime generally plays a greater role in creating double diffusion convection in this cross section of The Persian Gulf in winter.

Floods are among the most common natural phenomena in different parts of the world and they have claimed many lives over the years and left irreparable destructive effects. The Khordad 1402 rainfall in Ardabil Province has caused extensive damage to property and the lives of people in urban and rural areas by destroying bridges and rural communication roads between northern cities of the province, destroying orchards and livestock farms, and destroying residential houses. Therefore, understanding the flood phenomenon and being aware of its effects are among the most important issues that should be considered in flood monitoring. There are various methods for flood monitoring, among which the use of applied techniques such as satellite remote sensing using synthetic aperture radar (SAR) provides good support for flood monitoring and reducing their effects on a global scale. Therefore, in this study, to determine the flood areas and the extent of the resulting water for Khordad 1402 in Ardabil province, SAR synthetic aperture images were used before and after the flood. For this purpose, in the first step, pre-processing operations were performed on the images in the SNAP software, in the second step, postprocessing operations were performed on the classified binary raster data in the ENVI 5.3 environment, and in the last step, and the final map was imported into the ArcGIS environment for conversion to a vector file and analysis. The results showed that based on the rainfall in June 1402, the flooded areas of the province were about 1603 hectares, with the largest area of flooded areas being in the north of the province, especially in Bilehsavar County with 593 hectares. In the study area, the most flooded areas were seen in grasslands and lands with a slope of less than 20 percent and an altitude of less than 1000 meters, which was influenced by various factors such as topographic features such as slope and lowland of the region .

Airborne particles have a significant effect on the characteristics of precipitation and directly affect the climate of the region and human life. Aerosols, which play an essential role in cloud formation and radiation balance regulation, can affect the intensity, frequency, geographical distribution, extent, and timing of precipitation. However, due to variations in aerosol properties, different types of precipitation, vertical distribution of aerosols, and meteorological conditions, discrepancies are observed among the results of current studies. Scientific advances in recent research have produced significant developments, but understanding the effects of aerosols on precipitation remains challenging and complex. In this research, the AOD index and geographically weighted regression model have been used to investigate the relationship and possible impact of aerosols on precipitation in Iran. For this purpose, the daily data of the Modis Mod08 product and the daily rainfall data during the statistical period of 2000-2022 were used. Also, to reveal the type of aerosols affecting precipitation, daily data of the MERRA-2 model and multivariate regression method model were used. The results showed that considering all three cases, i.e. the relationship between AOD index values with precipitation on the same rainy day, AOD index values one day before precipitation with precipitation the next day, and AOD index values two days before precipitation with precipitation on the given day. Opinion, there is a correlation between these two variables in all three situations at a minimum of 0.3 to a maximum of 55.7. The results of analyzing the spatial distribution of significant pixels showed that this distribution has a special pattern in such a way that most of these pixels are located in the three regions of the southeast (Kerman, Sistan and Baluchistan, and Hormozgan provinces), the western region (Kurdistan province, Hamadan and Lorestan) and the northeast region (Khorasan, Semnan and the eastern part of Mazandaran) are concentrated. In the investigation of the types of aerosols effective in precipitation, it was found that the most effective types of aerosols in precipitation in these areas were dust particles with diameters of PM10 and PM2.5. Also, comparing the amount of precipitation with the AOD index on a rainy day shows that on the days when the index value is high (values close to 1 and more), the amount of precipitation that occurred in one day has increased significantly. In other words, with the increase in the density of aerosols, more intense rains have occurred.

 Fars province is one of the agricultural hubs of the country, due to the dependence of its water resources on annual precipitation, the change of precipitation regime can impact the pattern of cultivation and production in this province. This research intends to investigate and analyze the trend of spatial and temporal changes in precipitation in Fars province during the thirty-year period (1985-2014), using one of the CMIP6 climate models (namely CanESM5) under SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 scenarios to project the annual and monthly changes of precipitation in the coming decades (2026-2096). To carry out this research, the monthly and annual precipitation of the fars province synoptic stations and the data of the CanESM5 climate model, which is one of the most widely used global atmospheric general circulation model, were used. The results showed that there is a possibility of an increase in the annual precipitation of Fars province in all scenarios; Thus, the SSP126 scenario projected the least increase and the SSP370 scenario predicted the highest increase in precipitation compared to the base period. Accordingly, it was estimated that the increasing trend of projected predicted precipitation will be insignificant under the SSP126 scenario, but will be significant under the other scenarios. Also, the examination of the monthly precipitation regime of Fars province showed that in almost all SSP scenarios, there is a decrease in precipitation in the relatively hot months of the year, i.e. August, September or October, and in the case of the SSP126 and SSP245 scenarios, a decrease in precipitation in the early months of the year (January and February) is also predicted. On the other hand, a probable increase in the spring precipitation of Fars province was predicted, compared to the base period and in all scenarios, as well. The results of this research indicate the necessity of planning to make maximum use of the changes in the monthly precipitation regime of Fars province for spring crops and observing the necessary precautions and measures for autumn crops and considering the possibility of a decrease in autumn precipitation of this province. In addition, it is suggested that future studies utilize a variety of GCM models and different downscaling methods to quantize the uncertainties in precipitation projections arising from three sources: the model, the downscaling method, and the emission scenarios.

This study aims to investigate the heavy rainfall and flooding that occurred in May 2024 in Khorasan Razavi . In this research, an analysis of the rainfall data for May 2024 in Khorasan Razavi revealed that the peak of the heavy rainfall occurred on the 16, 17, and 18 of May, which were selected for further study. To analyze the synoptic conditions of this heavy rainfall, daily maps of surface pressure, 500 hPa, Omega, Vorticity, and moisture flux at 850 hPa were used. Satellite images from the Sentinel mission in Google Earth Engine were also employed to identify flood-prone areas and conduct a detailed analysis. The results showed that a low-pressure system in southeastern Iran and northwestern Pakistan directed warm and moist air from the southern regions towards northeastern Iran. On May 18, 2024, this system transported moist air towards northeastern Iran, leading to increased humidity in the region. This rise in humidity, combined with higher temperatures, resulted in further temperature increases and intense rainfall. The 500 hPa maps also showed the development of a deep trough in western Iran and weak subsidence in northeastern Iran. Gradually, the subsidence in northeastern Iran strengthened, and isobaric lines converged, creating instability. The moisture flux followed a west-east trajectory, moving towards northeastern Iran through the Caspian Sea. Additionally, Sentinel satellite imagery indicated an increase in rainfall due to atmospheric instability and the movement of low-pressure systems, especially in the central, eastern, and southern parts of the province. The estimated area affected by the flooding was 6,822.9 square kilometers, which had a significant impact on the hydrology and geography of the region and could have important consequences for agriculture, infrastructure, and ecosystems in Khorasan Razavi.

To investigate the changes in atmospheric circulation in the Northern Hemisphere, geopotential height data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) was analyzed from 1948 to 2020. A trend test was conducted on the geopotential height data to examine these changes. The results indicated significant alterations over the 70-year period in the polar regions, mid-latitudes, and other latitudes. In winter, particularly in December, a negative core of decreased geopotential height at the 10-hectopascal level was observed over the polar cap, reaching a minimum of -8 geopotential meters. Conversely, the North Pacific Ocean exhibited a maximum core of the geopotential height trend, exceeding 4.5 geopotential meters. This pattern was also evident in January and February, with a decreasing trend noted in northern Europe and the Eurasian region. In spring, a downward trend in geopotential height was observed in the area affected by the polar vortex, extending towards northeastern Russia. The analysis revealed that the most significant changes in the polar hemisphere during the first 37 years occurred in November and December. In contrast, the most substantial decreases in the polar sphere during the subsequent 37 years were noted in November, December, and March. Changes in November and March were nearly identical across both periods, with the first 37 years showing an increase in the polar hemisphere and a peak geopotential height of 140 geopotential meters in November. In the latter 37 years, a decline in the polar sphere was evident.

Tourism is a major part of the global economy which is heavily affected by weather. Therefore, it is very important to investigate the climatic conditions of a region in terms of the physiological comfort of tourists and to determine suitable periods for tourism elements, including planning, implementation and stay of tourists, especially in the hot and dry climates of the south of the country. In this study, we examined the spatial-temporal distribution of tourism comfort climate along the southern coastal regions of Iran in four provinces: Khuzestan, Bushehr, Hormozgan, and Sistan and Baluchestan, which are among the major ecotourism destinations. This research is descriptive-analytical in nature, aimed at examining climatic conditions and determining suitable times for tourism along the southern coasts of Iran. According to the results of tourism climate index during the years 1990-2022, the most favorable weather conditions for tourism in the region are in \months of November, December, December, February and March. In addition, the results of the neurotic pressure index showed that the most favorable time for tourism in the southern coasts of Iran can be seen in the months of November and March, and the results of the effective temperature index also indicate that the most suitable The months for tourists to visit this area are November, December, February and March. Therefore, among the studied indicators, the favorable and common months for tourism can be seen in November and March. The results of the present study, considering the climatic conditions of the southern coasts of the country, help decision makers and tourism planners to determine the optimal time for tourism and the presence of visitors in this region by choosing the appropriate climate index. It also improves our understanding of the correlation of the tourism climate index with the time of presence and the number of visitors during different months of the year in the region so that managers can make more informed decisions and plan appropriately in order to implement the sustainable development of tourism in this region.

In the past few decades, minimum and maximum temperatures have shown different behaviors. The difference between these two variables, known as the diurnal temperature range (DTR), is one way to detect climate change in a region. Therefore, in this study, the DTR trend in West Azerbaijan province was examined in order to show the spatial and temporal of these changes in the statistical period (1992-2021) on annual and seasonal scales. For this purpose, the Mann-Kendall test was used to examine the trend, and the Sen's Slope Estimator was used to examine the intensity of the changes. The results of the spatial distribution of DTR changes in the studied period showed that the range of diurnal temperature changes in West Azerbaijan province is between 8 to 14.3 0C. The trend of seasonal changes also indicates an increase in the diurnal temperature range in most regions of the province except for the Piranshahr and Khoy stations, especially in the summer and autumn seasons. According to the results, the highest rate of trend and changes in terms of time was observed in the summer season and the lowest in the autumn season. In terms of temporal, the highest intensity of changes is related to the southeastern and central regions of the province, and the lowest intensity of changes is related to the southwestern and northwestern regions of the province. The detection of DTR changes on an annual basis also showed that changes have become significant in all regions of the province except for Mako. These significant changes also have an increasing trend in other regions except for the Piranshahr and Khoy stations, which are decreasing. The annual change intensity rate is also between -0.01- 0.031 0C per year in the study period.

Climate change and rapid urbanization, particularly in cities with inadequate infrastructure, have significantly increased the frequency and intensity of destructive floods. Beyond the devastation of physical infrastructure, floods pose grave threats to human health and the environment. Addressing these challenges necessitates the adoption of hydrological modeling and simulation to predict and manage floods effectively. This research explores the potential of metaverse technologies in flood modeling and visualization. Virtual reality (VR) and augmented reality (AR) tools offer highly precise simulations of flood scenarios, enabling planners, citizens, and stakeholders across communities to make informed, practical decisions based on complex datasets. These technologies facilitate more effective risk mitigation and damage reduction strategies. By offering more immersive and realistic simulations, metaverse technologies greatly enhance predictive accuracy and decision-making in flood crisis management. Consequently, they hold a transformative role in reducing vulnerabilities and strengthening community resilience against natural disasters.

This study aims to assess the tourism climate indices of Khalkhal city and their implications for ecotourism planning. Due to its geographical location and unique climatic conditions, Khalkhal is considered a favorable tourism destination during the warm seasons. In this research, climatic data including temperature, humidity, precipitation, sunshine hours, and wind speed—were collected from the Khalkhal synoptic station over a 30-year statistical period (1991–2020) and analyzed using tourism climate indices, including the Tourism Climate Index (TCI), Wind Chill Index (WCI), Terjung Index, and Olgyay Index. The results indicate that Khalkhal enjoys favorable climatic conditions for tourism from June to September, whereas from December to February, a significant decline in temperature, increased precipitation, and strong winds impose considerable limitations. The analysis of climate indices demonstrates that TCI aligns most closely with summer tourism suitability, while WCI and Olgyay indices highlight the constraints of winter tourism. Additionally, higher precipitation levels in autumn and winter significantly reduce tourist comfort, underscoring the need for specialized infrastructure planning to support tourism activities during these periods. To enhance seasonal tourism management and promote sustainable ecotourism, equipping tourist areas with heating facilities, developing a seasonal tourism calendar, and adapting tourism programs to climatic conditions are recommended. Furthermore, engaging local communities in tourism planning and implementation can contribute not only to strengthening the local economy but also to preserving natural resources and optimizing seasonal tourism policies. The findings of this study highlight that utilizing tourism climate indices can serve as an effective decision-making tool for enhancing tourism management, improving efficiency, and fostering sustainable development in climate-sensitive tourism destinations.