نشریه نیوار
پیاپی 116-117 (بهار و تابستان 1401)

The presence of fog reduces the horizontal visibility to less than 1000 meters and disrupts air transport services and can make it impossible for aircraft to land and take off. Climatology of fog can help better diagnosis and prediction of fog. In this study, METAR data from 2011 to 2020 were used to detect fog events at Ardebil Airport and according to the classification algorithm of Tardif and Rasmussen (2007), the types of events were determined. Then the fog climate was studied during the period. The results showed that the most common type of fog at Ardebil Airport is radiation fog and the rarest type is precipitation fog. In terms of duration of fog event, radiation fog was the longest fog event and precipitation fog was the shortest fog event. The highest incidence of fog during the study years was at 3 and 4 GMT. The monthly distribution of radiation fog showed that events often occurred in autumn and early winter (September to December). In terms of annual changes in the occurrence of fog, there was no significant trend in the number of fog hours during the studied years, except for the last three years which had a decreasing trend.

Despite the important role of soil surface moisture in the management of water and soil resources, unfortunately in Iran, there is no national network for monitoring soil moisture and the spatial distribution of measuring stations is limited. Therefore, in the present study, an attempt was made to extract and analyze the spatial and temporal distribution maps of soil moisture from SMAP products during the period 2015 to 2021 in Iran. The results showed that the average 7-year soil moisture at a depth of 5 cm in Iran varies between 0.005 to 0.5388 m3/m3, and the temporal average of soil moisture is 0.137 m3/m3. Evaluation of monthly average soil moisture maps by SMAP showed that the highest and lowest long-term average soil moisture in February and August occurred at 0.192 and 0.079 m3/m3, respectively. The spatial assessment also shows that the highest average annual soil moisture values are concentrated in the northern and western regions, and the lowest values are concentrated in the central and southeastern regions. Evaluation of the results based on the provincial scale shows the highest average annual soil moisture in the provinces of Gilan, Mazandaran, Kohgiluyeh and Boyer-Ahmad, and Alborz, respectively 0.294, 0.243, 0.216, and 0.209 m3 / m3. While the lowest values in Sistan and Baluchestan, South Khorasan, and Yazd provinces are 0.076, 0.091, and 0.096 m3 / m3, respectively. The results of this study can help the management of soil and water resources by knowing the amount of soil moisture in different areas.

This article aims to investigate the effects of climate change on tropical cyclones. The present study has been carried out by using and examining the available library resources. The results show that ocean surface warming leads to more intense tropical storms. On the other hand, with the rise of the ocean water level, the destructive power of storms in coastal areas will increase. The rise of the sea level itself is caused by climate change. On the other hand, the proportion of very intense tropical cyclones (Category 4 and 5) is projected to increase, even though most climate model studies predict that the total number of tropical cyclones per year will decrease or remain nearly constant. Also, models predict that as the Earth warms in the coming decades, some regions will experience an increase in the rate of intensification, a poleward shift of the geographic latitude of the maximum intensity, or a decrease in tropical cyclone forward motion.

Climate change, which poses a serious threat to natural ecosystems and the sustainable development of natural resources with global warming, and the negative effects of climate change on the environment and the country's economy. In this paper, we present a positive mathematical planning model for evaluating adaptive measures of climate change on rural farmers' incomes and natural resource management in the Tarshiz Plain. First, the trend of temperature and precipitation changes in Tarshiz plain during the years 1083-2020 was studied. Then, using regression analyzes the effect of average temperature and annual rainfall variables on yield and area under cultivation of selected crops in this plain was investigated. The results showed that climate change had a positive effect on the income of the farmer household on improving the improvement of the cultivation pattern. To achieve sustainable development in the field of climate change, sustainable development of natural resources under environmental protection (rangeland conservation and vegetation) must be increased. On the other hand, the yield of most selected crops has a negative and significant effect and leads to a decrease in the area under irrigated wheat, saffron and eggplant in the crop pattern of Tarshiz plain. With the occurrence of climate change, the total gross yield of rural farmers in Tarshiz plain decreases by 11.17% and the total water consumption in the cultivation pattern decreases by 5.77% compared to the base year conditions.

Reference crop evapotranspiration and its accurate estimation play an essential role in irrigation planning, irrigation interval determination and in studies related to water balance modeling in each region. Valiantzas method is one of the newest methods for calculating reference evapotranspiration, the advantages of which include simple application in regional calibration and hydrological applications. In this study, in order to evaluate the accuracy of five different models of Valiantzas method, monthly reference evapotranspiration during the years 1999 to 2018, in nine meteorological stations of Lorestan province (Azna, Aleshtar, Aligudarz, Boroujerd, Poldakhtar, Khorramabad, Dorod, Kuhdasht, Noorabad) were calculated and the results were compared with the FAO-56 reference method. The results showed that based on RMSE and CRM statistics, Valiantzas 2 model and based on R2 statistics, Valiantzas 4 model recorded the best performance in estimating reference evapotranspiration. By station as well, the Valiantzas 4 model in five stations and the Valiantzas 2 model in four stations provided the most accurate performance, and as a result, the Valiantzas 4 and 2 models can be suggested for use in Lorestan province. In addition, in four stations the Valiantzas 5 model, in four stations the Valiantzas 3 model and in one station the Valiantzas 1 model by the weakest performance, indicated that they are not suitable for use in Lorestan province. In general, despite the under estimation in the reference evapotranspiration calculation, all five models of Valiantzas method had an acceptable closeness with FAO-56 method and the results of this method can be considered reliable.

 One of the results of climate change is the lack of fresh water and as a result land destruction or desertification, increase in wind erosion and the occurrence of dust storms. Although by implementing desertification operations, an attempt is made to control the destructive effects of dust storms, but identifying the causes of erosion, the temporal distribution of storms, and the location of the start zones of storms can be effective in the effectiveness of projects and reducing damages caused by storms. In this regard, this research was conducted with the aim of knowing the effective atmospheric factors in the activity of dust centers with domestic origin in Isfahan province. Knowing the existence of internal focuses and their location, the date of occurrence of local, intense and short-term dusts at the focal point was investigated. The results showed that convective conditions played a significant role in these cases and the occurrence of such internal dusts due to the timeframe of occurrence and locality requires thermodynamic information, especially cin, cape, TT, ki, ko, li and tools such as Skewet diagram. Also, due to the scale of these phenomena, companion maps do not help much and output of microscale models such as wrf, satellite imagery and if radar access is required

In this study, the dust sources and factors affecting the occurrence of dust storms in the southeast of Iran have been investigated. For this purpose, the observational data from Sistan-Balochistan province synoptic stations, ERA5 reanalysis data and satellite data in the period of 2009-2018 have been used. Using the GOCART model, the amount of vertical dust from different areas has been estimated. To determine how dust is transferred, the synoptic systems over the region have been examined seasonally. The seasonal average of the SAVI index is presented to investigate the vegetation cover in the study area and its seasonal changes. The results showed that there are four dust sources in Sistan-Balochistan province and two sources in Afghanistan and Pakistan which affect this province. One of the main factors for the activation of dust sources is the strong winds blowing on these areas, especially in the summer season, so that the average wind speed on the border of Iran and Afghanistan reaches more than 10 meters per second. The existence of low-pressure systems over the east of Iran and west of Afghanistan and high-pressure over the Hindu Kush causes a significant pressure gradient in the border region of the two countries. The investigation of a severe dust event in the studied area showed that the dust particles were emitted from the areas around Hamon Lake and the Afghanistan-Pakistan border and entered the areas of Afghanistan, Pakistan and Southeast Iran under the influence of the north and northeast currents.

In this study, considering the importance of temperature and salinity parameters in recognizing marine phenomena, changes of these parameters were investigated using WOA13 data and the conditions of each of these parameters were determined at different seasons and at different depths. Therefore, by selecting WOA13 historical data, which is the seasonal mean of temperature and salinity over the period 2005 to 2012, IDW interpolation maps of salinity and temperature at the surface, 5, 20 and 50 m were performed. In order to understand how these parameters change in depth, vertical profile cross sections maps have been created in 6 different lines. Also, the results are compared with the studies in the study area. According to the data and results it can be concluded; As the seasons change from winter to summer, salinity and temperature increase from the Oman Sea to the northern part of the Persian Gulf and decrease with autumn, This well describes the thermohaline cycle of the region. It also experiences the highest and lowest salinity in the northern part of the Persian Gulf and the Oman Sea, respectively. And, the highest and lowest temperatures, respectively, are in the central part of the Persian Gulf (summer season) and the northern part of the Persian Gulf (in winter and spring).

Implementing sustainable development of regions requires careful planning based on talents and resource constraints, and the climate of each region is one of the most important factors determining the development potential of the place. In this regard, climatic characteristics and its dominant elements that play a decisive role in the dispersal and formation of vital phenomena (plants, animals, humans) are considered as one of the most important natural-environmental factors. If the guarantee of complete success of most agricultural development plans, industry, irrigation projects, transportation, health, etc. is achieved when it is accompanied by knowledge of the climate and the use of its various potentials. The purpose of this study is to classify the climate of Khuzestan province based on litany-skiing method. The litany-skiing method uses the three basic elements of temperature, precipitation and coefficient. This method uses auxiliary indicators for comprehensive classification, which include three indicators of compliance, dry season duration and solar radiation status.To calculate meteorological data index including precipitation, minimum temperature, maximum temperature and relative humidity of 13 meteorological stations including Ahvaz, Izeh, Andimeshk, Mahshahr, Behbahan, Dezful, Azadegan, Ramhormoz, Shushtar, Masjed Soleiman, Omidieh, Shadegan and Shousha during 1991. Collected until 1397. Excel and SPSS software were used to calculate and analyze the indicators. The results showed that the climatic situation of Khuzestan cities was divided into 4 groups based on the coefficient of lithium ski index.

Improving agriculture, water resources management, flood management, and preventing environmental damage in future periods requires predicting climate data and adapting management and macro decisions to these changes. Today, it is possible to predict this data by using models and web databases. For this purpose, in the present study, the data obtained from the web database DKRZ and LARS-WG model, under three variables (minimum temperature, maximum temperature and precipitation) of Qazvin synoptic station in five public circulation models of the fifth IPCC report (EC-EARTH, GFDL-CM3, HadGEM2-ES, MIROC5, MPI-ESM-MR) under two release scenarios (4.5 and 8.5) in future periods (2021-2040, 2041-2060, 2061-2080, 2081) -2100 and 2021-2100) were calculated and compared. The differences of the variables in each period compared to their mean in the base period (1991-2020) were examined. The highest and lowest rates of climatic variables during future periods and the general circulation model of the atmosphere and its scenario were introduced. In the period 2021-2100, LARS-WG-RCP4.5, LARS-WG-RCP8.5 and DKRZ-RCP8.5 models, 0.65, 0.8, 0.63° C increase the minimum temperature compared to the base period and DKRZ- RCP4.5 reports 0.61° C minimum temperature decrease compared to baseline. LARS-WG models predict maximum temperature rise under scenarios of 4.5 and 8.5, 0.75 and 0.86° C. DKRZ database models under maximum scenarios of 4.5 and 8.5 report maximum temperature drop of 2.53 and 1.16° C, respectively. According to the results of the models, the precipitation is LARS-WG-RCP4.5, LARS-WG-RCP8.5, DKRZ-RCP4.5 and DKRZ-RCP8.5, 16/35, 24/13, 146 and 145/97 mm, respectively. It increases value in the base period.

The current study deals with the monitoring and evaluation of soil moisture and vegetation changes using remote sensing technique and its relationship with the standardized precipitation-evapotranspiration index in Bandar-Dij and Kol-Mehran watersheds in Hormozgan province. For this purpose, soil moisture data at a depth of 0-10 cm was calculated from GLDAS satellite images and standardized soil moisture drought index (SMDI) and standardized normalized difference vegetation index (SNDVI) were used to calculate changes in vegetation cover. The results of the correlation between SPEI and Standardized Moisture Drought Index (SMDI) showed that in all sub-basins, the correlation coefficients increase with the increase of the time scale, and the highest correlation is related to the Minab sub-basin (R=0.764) in the 12-month time scale. Examining the characteristics of drought (severity-duration and magnitude) showed that SPEI showed more intensities in shorter periods of time than SMDI, so it shows more magnitudes of drought. The investigation of the standardized vegetation cover index showed that in most of the sub-basins, since 2012, the decreasing trend of vegetation cover is evident. Investigating the relationship between SPEI and SMDI and SNDVI showed that SNDVI has a high correlation with SPEI and SMDI in a long-term time scale. A comparison of historical droughts between the three indices showed that, although all three indices often showed drought conditions, SPEI always showed extreme conditions compared to changes in soil moisture and vegetation, indicating a delayed response to changes in soil moisture. and vegetation to meteorological drought.

The Arabian Sea is a region of the northern Indian Ocean. The Arabian Sea's surface area is about 3,862,000 km2. The maximum width of the sea is approximately 2,400 km, and its maximum depth is 4,652 meters. The biggest river flowing into the sea is the Indus River. The Persian Gulf is a semi-enclosed epicontinental water body that is located at the northwestern corner of the Indian Ocean. The basin is connected to the Arabian Sea and the Gulf of Oman via the Strait of Hormuz. These water bodies were called Pars Sea. Sea surface temperatures of Persian gulf can exceed 35°C in summer ,while in winter the temperature can fall to <10°C. These regions contributes significantly to current climate change, and suffers deeply from the consequences of this phenomenon. Changes in sea surface temperature (SST) and sea level rise (SLR) affect all forms of life. Therefore, this research aims to project the sea temperature changes of the Arabian Sea and the Persian Gulf, as well as the changes in the sea level of the Persian Gulf and the Oman Sea, based on the output of the CMIP6 under SSPs scenarios for the period 2021-2040.