Mrs Somayeh Naderi, Prof. Bohloul Alijani, Prof. Zahra Hedjazizadeh, Dr. Hasan Heidari, Dr. Karim Abbaspour,
Volume 24, Issue 73 (6-2024)
Abstract
Evidence suggests that climate change will create uncertain regional agricultural production stability in the coming decades. This research investigated the impact of climate change on hydrology and sugar beet yield as one of the main crops in the Urmia lake basin using the Soil and Water Assessment Tool (SWAT). To address this, a baseline SWAT model was setup for 1986-2014. Afterward, the output was calibrated (1989-2004) and validated (2005-2014) in the SWAT-CUP software using the SUFI2 algorithm to simulate streamflow of 23 gauging stations and crop yield. The Nash-Sutcliffe efficiency was 0.43 and 0.53 for calibration and validation periods, sequentially. The Percent Bias was 45% and 16% for calibration and validation periods, respectively. As well as the agreement indices of 0.71 and the little Percent Bias (-6% to 10%) for crop production, verified the model's efficiency. The next step was downscaling and bias-correction of the precipitation and temperature data received from 3 climate models, namely GFDL, HadGEM2, and IPSL under RCP4.5 and RCP8.5 using CCT program. Then, the downscaled data were fed to SWAT, and Finally, hydrological fluxes and sugar beet yield were estimated for 2021-2050. Despite a dispersion of precipitation changes ranging from -12% to +35% in most scenarios, results highlight the pivotal role that the warmer temperature (+2.7°C) increases evaporation, resulting in sharpened pressure on water resources and runoff, especially, at the beginning of crop growth season. Finally, the negative impacts on crop productivity (-45%) is not unexpected. This means that sugar beet may suffer from climate change impacts, and the production of this plant will change over the next period in this region.
Keywords: Climate Change, Sugar Beet, Urmia Lake Basin, Sensitivity Analysis, SWAT.
Ms Akram Hedayati Dezfuli, Ms Zahra Ghassabi,
Volume 24, Issue 73 (6-2024)
Abstract
Flood is one of the most destructive natural phenomena. Every year it brings extensive losses to the country’s financial and human resources. In our country, major parts of Iran’s provinces are always at risk of flooding. The Gorgan and Atrak catchments have also become more important, as several floods have occurred in Golestan province in recent years, causing many deaths and economic losses. The purpose of this study was to investigate the synoptic and thermodynamic conditions of the March 2019 flood event in Golestan province in order to atmospheric system that lead to such floods. This study includes statistical analysis of provincial stations (Gorgan, Gonbadkavus, Aliabadkatol, Hashemabad, Kalale, Maravetape and Bandaretokman), calculating of the return period of precipitation during the available statistical period of each station, analysis of synoptic maps on the day of the flood event, the analysis of satellite images of the days involved in the flood, and calculation of instability indices of the Gorgans’s station. Statistical results showed that Gorgan and Gonbadkavus stations, with the highest amount of rainfall in March 2019, had a return period with 800 and 400 years respectively. Also the highest amount index of Gorgan with values of K=26°c, PW= 0.27 cm and TT= 48 was obtained with high relative humidity (about 80%). The analysis of the synoptic maps showed the severe sea level pressure and mid- level height drop with a deep trough in the study area, which led to extreme rainfall.
Key words: Flood, return period, Synoptic maps, instability indices, Golestan province.
Zoleikha Khezerluei Mohammadyar, , Bohloul Alijani,
Volume 24, Issue 73 (6-2024)
Abstract
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.
Hossein Jahantigh, Esmail Rashidi, Abdolhossein Adel Zadeh,
Volume 24, Issue 73 (6-2024)
Abstract
Objectives: The purpose of this article, the relationship between maximum temperature of Kerman province geopotential height at 500 hPa to avoid risks and losses are extreme temperatures.
Method: In this paper, the approach has been used in the circulation to peripheral circulation patterns will be assessed based approach to environmental data. Therefore, we used two databases. First Base event database environment (surface). In this regard, the surface temperature is selected stations Kerman province. The maximum temperature of the stations in the period 01.01.1368 to 01.01.1398 for 30 years to 10957 the number of days were obtained from the meteorological province. Another database contains data that the data of geopotential height at 500 hPa
Dr Zahra Hejazizadeh, Dr Mehry Akbary, Zarin Jamshidiyini,
Volume 24, Issue 74 (9-2024)
Abstract
The present study investigated the impacts of NAO and ENSO on the precipitation in the southern shores of Caspian Sea. The accumulated monthly and annual rainfalls from 5 synoptic stations during the years (1956-2017) were taken through Islamic Republic of Iran Meteorology Organization (IRIMO) and the Multivariate Enso Indices (MEI) and NAO activity years are obtained from National Oceanic Atmospheric Administration. Pearson correlation was used to investigate the relationship between indices and precipitation amounts of selected stations. The results showed that there was a significant relationship between precipitation and NAO index in some months in all stations but this correlation was not following a particular pattern in all the stations. The maximum correlations were observed at Babolsar and Anzali station and the least correlation was found at Gorgan stations. The correlation between precipitation and different phases of NAO showed that there was a positive correlation between precipitation and negative phase of the index in Ramsar station and a negative correlation between precipitation and positive phase in the Gorgan station.The results of the Pearson correlation show a significant correlation between the MEI and rainfall amounts in the autumn in some stations in the early winter. In Review drought and wet periods with both Indicator it was observed that the behavior of the stations in the El Niño period, which was with different phases of the NAO was not entirely harmonious but the coefficient of 89% of rainfall in normal and more than normal during the period of El Niño showed that Elnino is better fitted to normal and more than normal rainfall in these stations also coefficient of 60% of weak to severe droughts in the Lanina period in the selected stations Indicates that the LaNina phase was more related with severe droughts in the under studied period.
Tooba Alizadeh, Majid Rezaei Banafsheh, Hashem Rostamzadeh, Gholamreza Goodarzi, Hedar Maleki, Hamzeh Alizadeh,
Volume 24, Issue 74 (9-2024)
Abstract
The aim of this study was to identify the epicenter and co-occurrence factors of dust storm wave from 1 to 3 November 2017 in Kermanshah. To investigate the synoptic conditions of the causes of this phenomenon, from the European Central Center (ESMWF) mid-term weather forecast data set with a resolution of 0.125 degrees of arc including, geopotential height, omega, sea level pressure, orbital and meridional components, humidity. The Lagrangian method of HYSPLIT model was used to orient the source of dust particles. in this study, dust storm WRF-chem was simulated using a paired numerical weather forecasting model. Finally, through the processing of MODIS satellite images, its scope was determined. Examination of HYSPLIT tracking maps shows that two general paths for dust transfer to the area can be identified. 1- The northwest-southeast route, which passes through dust cores formed in the deserts of Iraq and Syria, transports dust to the western half of Iran. 2- Southwest to west of Iran and Kermanshah, which is the main source of dust on November 2 and 3, The source of the particles is Kuwait, northern Saudi Arabia and part of Iraq. The spatial distribution of the dust interpreted by the MODIS sensor images is consistent with the spatial distribution of the dust concentration simulated by the WRF-chem model.
Maryam Aghaie, Siamak Dokhani, Ebrahim Omidvar,
Volume 24, Issue 74 (9-2024)
Abstract
Rain water harvesting is an appropriate option for storing surface runoff for subsequent uses during periods with limited access to water. The most important step in the application of rainwater harvesting systems (RWH) is the site selection suitable areas. Therefore, by identifying suitable sites for this purpose, time and cost will be saved . In this research, multivariate regression model and GIS were used to site selection in situ (RWH) in Tajare watershed. For this purpose, layers such as crown cover, litter, rock and stones, soil, curve number, rainfall, slope and depth of field as independent variable and infiltration were considered as the dependent variable. Then, according to the maps, their values were calculated in average for each of the 27 sub-basins. Also, to investigate the relationship between these variables and weighting, each of the effective layers of multi-variable regression was used by the stepwise method The results showed that the linear multivariate regression model with an explanation coefficient of 0.993 was able to estimate the penetration factor values well In terms of grade of importance, the curve number variables with a coefficient of -2.433, depth of soil with a coefficient of 0.3488, and rubble and gravel percent with a coefficient of 0.057, were the most important, and other factors were not significant. Comparison of the map from the site selection of multivariate regression in this research with some recommended criteria of various research studies showed that the predicted classes with good in the central parts of the basin and very good in the upstream areas of the basin which in the eastern and southeastern part of the basin fit have a good overlap with the recommended areas with these criteria.
Dana Rahimi, Javad Khoshhal Dastjerdi, Dariush Rahimi,
Volume 24, Issue 74 (9-2024)
Abstract
Among natural disasters, floods have the highest human toll. The economic impacts of floods are greater in developing countries, including Iran, and are particularly severe in the colder months of the year in the west of the country. The purpose of the present study is to analyze the most severe historical synoptic floods that occurred in Karkheh Basin (1 April, 2019). Descriptive - analytical research method and its environmental approach into circulation. Analysis of synoptic systems of large floods such as the April 12, 2019 floods show that Western Europe's high-pressure systems, Black sea, East of the Caspian and low pressure north of the Red Sea, Eastern Mediterranean in harmony with the high-rise systems of Western Europe, Low Mediterranean East with a temperature drop of about 50 degrees Celsius(The temperature at sea level In the eastern Mediterranean and Red Sea about 25 degrees Celsius and in the middle of the atmosphere -25 degrees Celsius) also the climb Humidity from the Arabian Sea, North Indian Ocean, Red Sea, Oman Sea and Persian Gulf and Along with Mid-width cold air loss On the area and the establishment of the Polar jet stream) Core up to 70 m(And the establishment of the front jet stream And positive rotation area On the area shows the structure of the synoptic systems causing the flood in the area.
Mrs Mahnaz Saber, Dr Bromand Salahi, Dr Abbas Mofidi,
Volume 24, Issue 74 (9-2024)
Abstract
In this study, the spatiotemporal variations of evapotranspiration (ET) were investigated in the southern part of the Aras River catchment. For this purpose, the ET networked data of FLDAS Noah model with horizontal resolution of 0.1 * 0.1 degree were used for a period of 38 years (2019-1982). After validating the data, the average annual ET values for the region were determined first. Then the monthly and seasonal distribution of the parameter were analyzed spatially. Subsequently, ET variations and anomalies were evaluated year to year. Also, the spatial distribution of the occurrence frequency of ET was investigated by considering the absolute thresholds of 50, 80, 100 and 120 mm for the Aras basin. The results show that the annual ET in the east of the basin is higher than the west of the basin. In the seasonal scale, spring and summer have the highest ET values, respectively. In the monthly scale, Mayو June, April and March had the highest ET values, respectively. In contrast, the autumn and winter months have the lowest average ET values. Also, the whole basin during the study period has experienced three distinct periods of ET changes that in the eastern and western parts of the basin, despite the same behavior in the second and third periods, a significant difference was observed in the first period. The results also indicate the existence of positive anomalies after 2002 in the whole basin, the highest values occurred in 2018 in the west of the basin. The study of the frequency of occurrence of absolute ET thresholds on the basin shows the high frequency of ET occurrence at all thresholds in the east of the basin. A study of nearly 4 decades of ET values in the Aras River Basin shows an increase in ET values over the last two decades over the entire basin, which can be attributed to the occurrence of global warming.
Mr Mohammad Reza Salimi Sobhan,, Mrs Zahra Beygom Hejazizadeh , Mrs Fariba Sayadi, Mrs Fatemeh Qaderi,
Volume 24, Issue 75 (12-2024)
Abstract
In examining natural hazards, such as hail, statistical analyzes can play a significant role. Due to the great importance of economic and side losses of hail in the northern part of Zagros with maximum frequency and damage, the necessity of studying its temporal and spatial location is felt very distinctly. Therefore, in order to estimate and estimate the probability of occurrence of this phenomenon, 10 hail data data of 10 synoptic stations of the region were used during the statistical period of 2014- 1992. In choosing the best method for calculating the distribution of precipitation probabilities, different types of probability distributions of discrete random variables were tested by means of both Kolmogorov and Anderson-Darling testsThe results showed that the good Poisson distribution test had a good fit for hail occurrence at a high level of 90.99%. Baneh station with the maximum frequency of hail precipitation has the lowest probability (0.023%) and Pearnshahr station has the most probable days without hail (0.39%). Therefore, the probability of occurrence of hail in Baneh has a higher percentage. In the next round, the negative binomial model satisfies the observations of this type of precipitation well. The calculation of probabilistic distributions by these two methods showed that the probability of occurrence of hail with the frequency of 1 to 6 times and more in the region and the highest probability is related to the frequency of 3 occurrences of 0.20%. At a frequency of 1 to 6 times, the probability of occurrence of this phenomenon is 5 times more than the probability that it will not occur, which indicates the region's high vulnerability to this type of climate risk.
.
Saeed Jahanbakhshasl, Ali Mohammadkhorshiddoust, Fatemeh Abbsighasrik, Zahra Abbasighasrik,
Volume 24, Issue 75 (12-2024)
Abstract
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]
Ali Hashemi, Hojjatollah Yazdanpanah, Mehdi Momeni,
Volume 24, Issue 75 (12-2024)
Abstract
This research study aims to investigate the effect of climatic variables, specifically precipitation, temperature, and humidity, on changes in vegetation indices of orange orchards in Hassan Abad, Darab County, using satellite data. Consequently, observational data, including orange tree phenology data and meteorological data from the agricultural weather station, were collected over a period of more than 10 years (2006 to 2016). MODIS images from 2006 to 2016 were referenced based on territorial data and 1:25000 maps from the Iran National Cartographic Center. These images were used to calculate remote sensing vegetation indices, namely the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). The results demonstrated that the variables of maximum humidity, minimum temperature, and precipitation have a significant positive effect on the NDVI variable. Additionally, the variables of maximum temperature and minimum humidity have a significant negative effect on both the NDVI and EVI. To determine the significance of each independent variable in predicting the dependent variables, the artificial neural network method was employed. The findings showed that the climatic elements of precipitation, minimum temperature, maximum temperature, minimum humidity, and maximum humidity had the greatest effect on EVI, with values of 0.39, 0.3, 0.13, 0.1, and 0.06 respectively. Moreover, the effect of these variables on the NDVI index is equal to their coefficients, which are 0.2, 0.28, 0.22, 0.11, and 0.17 respectively. Finally, the ARMAX regression method was used to improve the explanatory power of the model. The results indicated that this method enhanced the explanatory power of the model and reduced the forecasting error.
Hamed Heidari, Darush Yarahmadi, Hamid Mirhashemi,
Volume 24, Issue 75 (12-2024)
Abstract
Human interventions in natural areas as a change in land use have led to a domino effect of anomalies and then environmental hazards. These extensive and cumulative changes in land cover and land use have manifested themselves in the form of anomalies such as the formation of severe runoff, soil erosion, the spread of desertification, and salinization of the soil. The main purpose of this study is to reveal the temperature inductions of the land cover structure of Lorestan province and to analyze the effect of land use changes on the temperature structure of the province. In this regard, the data of land cover classes of MCD12Q2 composite product and ground temperature of MOD11A2 product of MODIS sensor were used. Also, in order to detect the temperature inductions of each land cover during the hot and cold seasons, cross-analysis matrix (CTM) technique was used. The results showed that in general in Lorestan province 5 cover classes including: forest lands, pastures, agricultural lands, constructed lands and barren lands could be detected. The results of cross-matrix analysis showed that in hot and cold seasons, forest cover (IGBP code 5) with a temperature of 48 ° C and urban and residential land cover (IGBP code 13) with a temperature of 16 ° C as the hottest land use, respectively. They count. In addition, it was observed that the thermal inductions of land cover in the warm season are minimized and there is no significant difference between the temperature structure of land cover classes; But in the cold season, the thermal impulses of land cover are more pronounced. The results of analysis of variance test showed that in the cold period of the year, unlike the warm period of the year, different land cover classes; Significantly (Sig = 0.026) has created different thermal impressions in the province. Scheffe's post hoc analysis indicated that this was the difference between rangeland cover classes and billet up cover.
Ms Akram Alinia, Dr Amir Gandomkar, Dr Alireza Abasi,
Volume 24, Issue 75 (12-2024)
Abstract
The main goal of this research is to analyze the time series trend of fire events in natural areas and reveal the relationship between these fire events and vegetation levels in Lorestan province. In this regard, the data of the fire product of the Madis sensor (MOD14A1) and the vegetation product (MOD13A3) of the Madis sensor were used during the statistical period of 2000-2020. The monthly and annual spatial distribution of fires in Lorestan province was investigated. Cross-information matrix analysis and spatial correlation matrix were used to reveal the relationship between fire occurrences and vegetation. The results showed that more than 70% of the total frequency of fire occurrences in natural resources fields (fires with code 2) in Lorestan province is related to June and then July. In terms of the long-term trend, the 21-year trend of the frequency of fire incidents in the province showed that the frequency of incidents in the natural resources areas of the province has generally increased with an annual slope of 3 incidents. The results of the correlation analysis between the monthly vegetation cover and the annual frequency of fire occurrences showed that the fire occurrences in the province showed a significant correlation with the vegetation cover changes in 4 months of the growing period, i.e. from May to August. Cross-matrix analysis between the spatial distribution of fire occurrence foci and NDVI index, both of which were products of MODIS measurement, indicated that, in general, the highest frequency of fire occurrences in Lorestan province in the period from May to August corresponds to Greenness range was 0.15 to 0.22. This range of vegetation generally corresponded to rainfed lands, weak pastures and low-density forest patches
Shamsallah Asgari, Tayeb Razi, Mohamadreza Jafari, Ali Akbar Noroozi,
Volume 25, Issue 76 (3-2025)
Abstract
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.
Zeinab Mokhayeri, Ebrahim Fatahi, Reza Borna,
Volume 25, Issue 76 (3-2025)
Abstract
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.
Mohammad Baaghideh, Motahhareh Zargari,
Volume 25, Issue 76 (3-2025)
Abstract
The performance of broiler chickens is directly influenced by temperature changes and the occurrence of heat stress, whether it is cold or hot. The present study aims to assess the cooling and heating degree days in different stages of broiler chicken production in Khorasan Razavi province. To achieve this objective, daily average temperature data were collected from 13 synoptic stations during the statistical period of 1988-2018. Cooling and heating degree days were calculated for each week of production using specific thresholds, and their spatial distribution was analyzed. Furthermore, the relationship between cooling and heating degree days and geographical features was evaluated. The findings indicate a decrease in cooling degree days and an increase in heating degree days as latitude increases. The northern and western regions of the province exhibited a greater need for heating throughout all stages of broiler chicken production, whereas the eastern and southern regions had higher cooling requirements at different production stages. Overall, the northeastern, southern, and western marginal areas of the province, including Khaf, Gonabad, Kashmar, Sarakhs, and Sabzevar, exhibited the lowest cooling and heating needs during the 6-week period of broiler chicken production, making them suitable climates for this economic activity.
Doc. Zahra Ghassabi, Doc. Hoshang Ghaemi, Mr. Ebrahim Mirzaei,
Volume 25, Issue 76 (3-2025)
Abstract
The structure of deep moist convection can be influenced by various factors, including wind shear, available potential energy of convection, relative humidity, and vertical distribution of these variables. Among these factors, wind shear plays a more significant role in the creation of convection. The interaction between large-scale and synoptic-scale processes, along with the adjustment of available potential energy for convection and the presence of convection inhibitors, creates conditions suitable for the development of convection. The large-scale average reduces the convection inhibitor, while even small vertical velocities, such as a few centimeters per second, can have a noticeable impact on the environment's sounding. The presence of potential instability is also considered an important factor in initiating deep moist convection. When the temperature reaches the critical point and the convection inhibitor is removed, moist deep convection begins. If an air parcel rises above the lower stable layer with low relative convective inhibition energy and high relative free convective potential energy, it supports the development of deep moist convection. The initiation of updrafts by warm air masses and the subsequent development of convection depend on parameters like vertical wind shear and the inversion cap of the environment, among others. Large-scale convective systems can be triggered with less forcing due to the significant uplift of the air mass from the surface to the convection level along the front.
Dr Abolhassan Gheibi, Mr Ali Soleymani, Hossein Malakooti,
Volume 25, Issue 76 (3-2025)
Abstract
Nitrogen dioxide is a significant factor affecting air quality in various regions worldwide. The aim of this study is to examine the concentration and trends of nitrogen dioxide pollution between 2005 and 2018, and explore its association with precipitation levels in the region. Based on data derived from the OMI sensor in Iran, the average vertical column concentration of nitrogen dioxide during this period revealed that the highest concentration was observed in the troposphere. Megacities, particularly Tehran metropolis, exhibited elevated levels of nitrogen dioxide due to the high population density and extensive road transportation. Analyzing the annual changes in nitrogen dioxide concentration in the troposphere alongside the average annual precipitation in Iran, it was observed that the pollutant concentration increased from 2005 to 2016 and subsequently decreased from 2016 to 2018, primarily due to population growth. However, when considering the overall trend, there was an upward trend with a slope of 3.53× -2. In contrast, the time series analysis of average annual precipitation in Iran demonstrated a declining trend with a slope of (-0.159 mm × ). Comparing the trends of these two variables, it can be deduced that they exhibit a negative correlation.
Mohammadsaleh Ekhlasi, Dr. Somayeh Soltani-Gerdefaramarzi, Dr. Abolfazl Azizian, Morteza Gheysouri,
Volume 25, Issue 76 (3-2025)
Abstract
In this study, we examined the impact of climate change on the virtual water content of key crops in Kerman province for future periods. Specifically, we utilized the climatic data from the HadCM3 model under the RCP4.5 radiative forcing scenario. The model was calibrated and validated for the base period of 1991-2011. We predicted the precipitation levels, as well as the maximum and minimum temperatures, for selected stations from 2011 to 2070 using data from LARS-WG. These predictions were then compared to the base period. The virtual water content was calculated for three selected crops: alfalfa, barley, and wheat. Our findings indicate that climate change has a significant impact on evapotranspiration and the performance of these crops, consequently affecting future agricultural water productivity. As we project an increase in average temperature during the growing season due to climate change, it is worth noting that the maximum temperature parameter will be more affected by this phenomenon than the minimum temperature. This, in turn, will lead to increased water requirements and plant evaporation-transpiration during this period. Our research also reveals a decrease in precipitation during hot seasons and an increase during cold seasons across all study stations. Notably, the virtual water content for all crops studied demonstrates an upward trend, with barley and wheat showing the greatest average increase in the future period. Specifically, the Kerman station exhibits a substantial increase in virtual water content for barley and alfalfa products, at a minimum of 30% higher than the base period.
