Climatology
shahriar khaledi; Esmaeil Bakhshi; Mahmoud Ahmadi; Abbasali Dadashi Roudbari
Abstract
From urbanization, the phenomenon of the urban temperature island follows which the city rises and increases from energy to cool. In this research, the role of local factors in the creation and development of heat islands in the city of Ahvaz during the hot period from 2000 to 2015 was investigated using ...
Read More
From urbanization, the phenomenon of the urban temperature island follows which the city rises and increases from energy to cool. In this research, the role of local factors in the creation and development of heat islands in the city of Ahvaz during the hot period from 2000 to 2015 was investigated using Landsat 7 and 8 satellite data. In order to evaluate the biophysical changes of the land surface in Ahvaz city, the changes of vegetation difference indices were taken by Tokanga-Tag threshold method. By using the kriging method and the low speed zones of Ahvaz, the thresholds of the closest and maximum temperature of Ahvaz city, it appears that this change can cause a change in the local climate. The results of Moran's spatial autocorrelation are a confirmation of the lack of spatial correlation of ground surface temperature in Ahvaz. The evaluation of the northern maps showed that as we move from the southern regions to the northern regions, the temperature increases due to the increase of green space and the increase of barren lands. There is a sharp temperature difference between the central and suburban areas of the city, because of the establishment of industrial companies, District 8 has formed the most stable islands in this area of the city. Residential areas have had less impact on the creation and expansion of thermal islands than industrial and barren areas.
Climatology
Hassan Rezaei; Gholamabbas Fallah Ghalhari
Abstract
Understanding the climatic potentials of the regions is very important for the diversity and talent of agricultural products. Barberry, one of the products of Iran, suffers from climate change and anomalies. In the present study, the phonological stages of barberry tree without any basis of field observations ...
Read More
Understanding the climatic potentials of the regions is very important for the diversity and talent of agricultural products. Barberry, one of the products of Iran, suffers from climate change and anomalies. In the present study, the phonological stages of barberry tree without any basis of field observations in Ghaen synoptic meteorological station were determined. To measure the accumulation of cooling needs based on the cold clock model and the Utah unit, the statistics of 18 valid meteorological stations from 1987 to 2017 on an hourly and daily time scale were used. The results showed that barberry needs six phonological stages to complete the growth period from early April to late November. The highest temperature requirement occurs in the ripening stage until fruit development. The cooling requirement of barberry tree in different stations varies from 1050 to 1960 hours depending on climatic conditions. Field observations showed that seedless barberry does not take on a full and commercial color if it does not meet the need for sufficient cooling. The study area was zoned according to the models of the cold clock and the Utah unit, based on which Ghaen and Zahedan stations have the highest cooling needs. Based on the validation indices of different models estimating the need for cooling, the root mean square criterion was used and the results show that the cold hour (CH) model has a higher performance due to the fact that the root mean square (RMSE) is less than the other model.
Climatology
Ali Mohammad Khorshiddoust; Mustafa Tahani Yazdali; farahnaz khoramabadi; Aazam Samadi; Farideh Ansari Maleki; Mohammad Hossein Pourghorban
Abstract
Problems caused by climate change are one of the most important environmental crises and threats of human society, especially in urban environments. In the city of Tabriz and in recent years, due to the growth of the population, a lot of migration from other cities, traffic, the development of industries ...
Read More
Problems caused by climate change are one of the most important environmental crises and threats of human society, especially in urban environments. In the city of Tabriz and in recent years, due to the growth of the population, a lot of migration from other cities, traffic, the development of industries and production centers have caused an increase in the production and distribution of pollutants. Based on this, in this research, attention has been paid to the evaluation of the quality of dust occurrence in the years 2019 and 2018. The concentration of dust particles in different areas of the studied places varies depending on the geographical location, topographical, climatic conditions and also their origin, both internal and external. Based on the results obtained from the analysis of laboratory results and field studies, in the Tabriz region and during the research period, the concentration of lead metal in dust is moderate for adults and severe for children, and the risk of mercury metal for both the elderly and children. It has been intense. The adverse effects of cadmium metal have been very severe in children and adults. On the other hand, the high air temperature in the city center and the formation of thermal islands in it causes local winds from the suburbs to the city center. With the transfer of pollution from the suburbs to the city center by these winds, the pollution situation in the city center also increases.
Climatology
Fatemeh Taghavi nia; Batool Zeinali; Abbasali Dadashi Roudbari
Abstract
Climate change is a key factor in most weather-related disasters worldwide. Regarding its distinctive geographical location and diverse climate, Iran has the most variable climate in the world. The present study aims to investigate the effectiveness of the MPI-ESM-LR model from the CMIP5 model series ...
Read More
Climate change is a key factor in most weather-related disasters worldwide. Regarding its distinctive geographical location and diverse climate, Iran has the most variable climate in the world. The present study aims to investigate the effectiveness of the MPI-ESM-LR model from the CMIP5 model series in predicting the monthly temperature of Iran under representative concentration pathway scenarios (RCPs) with the CORDEX-WAS project. In this research, for the historical period of 1980-2005, the daily air temperature data of 49 synoptic stations of the country and the MPI-ESM-LR model under the CORDEX project were used. Likewise, for the future period, from the predicted temperature data of RCP 8.5, RCP 4.5, and RCP 2.6 scenarios of the mentioned model in three periods of the near-future (2021-2050), mid-future (2051-2075) and far-future (2076-2100) was used. Validation of the model was done with three statistical indices: r, RMSE, and MBE. The results revealed that the model has a good performance. The slope of the temperature trend in station data and model data has been increasing in the historical period and the future period in RCP8.5 and RCP4.5 in all months, the temperature trend slope has been observed in every decade. In all months, the maximum anomaly of temperature under the scenarios studied in all three future periods can be seen in the northwest and western highlands. The eastern and southeastern regions of Iran have indicated minimum temperature anomalies, except in RCP 2.6 and RCP 8.5, respectively, the southern coasts and the northeastern heights of the country also show minimum temperature anomalies. In the cold half of the year, the minimum area of temperature anomaly has been extended to the north-western heights and low-altitude interior regions of the country.
Climatology
khadijeh javan; mohammadreza Azizzadeh
Abstract
The outputs of general circulation models (GCMs) usually have a bias compared to observational data, and some corrections must be made before using them to develop future climate scenarios. The bias correction methods are the standard statistical methods for processing the output of climate models. In ...
Read More
The outputs of general circulation models (GCMs) usually have a bias compared to observational data, and some corrections must be made before using them to develop future climate scenarios. The bias correction methods are the standard statistical methods for processing the output of climate models. In this research, the effect of five bias correction methods on the projected precipitation of the GFDL-ESM4 model in the Lake Urmia basin has been evaluated. The methods used in this research include linear scaling (LS), local intensity scaling (LOCI), power transformation (PT), distribution mapping (DM) and delta change factor (DC). Statistical metrics such as the correlation coefficient, root mean square error (RMSE) and percentage bias (PBias) have been used to evaluate the accuracy of the corrected data in the period of 1990-2014 compared to the observational data and to choose the best method for correcting the data of future scenarios. research results showed that the delta change method significantly improved the raw estimates after correction; Therefore, this method was used to correct the data of scenarios SSP1-2.6, SSP2-4.5 and SSP5-8.5. In addition, the projection of the mean annual precipitation shows a decrease between 2 and 9 percent in SSP1-2.6, between 5 and 17 percent in SSP2-4.5, and between 8 and 26 percent in SSP2-8.5 compared to the observed data.
Climatology
Atefeh Hoseini Sadr; bromand salahi; Gholam Hasan Mohammadi
Abstract
The aim of this study is to investigate the long-term fluctuations and trend in horizontal visibility in the northwest of Iran. For this purpose, hourly horizontal visibility data from 7 synoptic stations were used for the period of 1951-2020. The Koschmieder approach was used to calculate the extinction ...
Read More
The aim of this study is to investigate the long-term fluctuations and trend in horizontal visibility in the northwest of Iran. For this purpose, hourly horizontal visibility data from 7 synoptic stations were used for the period of 1951-2020. The Koschmieder approach was used to calculate the extinction coefficient. Moreover, the Mann-Kendall and Rdit tests were applied to examine the trend of horizontal visibility. Also, the percentages of very good visibility (>19 km) compared with bad (<10 km) visibilities. Based on the results the annual average of horizontal visibility in northwest of Iran is ~13 km. This study showed three different fluctuation periods in the regional average of horizontal visibility: the first period (1951-1985) showed a sharp decrease in the visibility, the second period (1987-2005) was characterized by a low and stable visibility, and the third period showed a recent relative improvement. The regional average of horizontal visibility (extinction coefficient) exhibited a significant decreasing (increasing) trend of -0.167(0.0017) km per year at a confidence level of 0.01. The significant decreasing trend was confirmed in all stations except for the Ardabil station. The most severe decreasing trend was detected in Sanandaj and Zanjan stations with rates of 0.183 and 0.179 km year-1, respectively. The region-average of Rdit statistic in northwest Iran in the early 1950s was ~0.85, but it decreased to around 0.3 in the 1990s. Despite the recent improvement in horizontal visibility, reaching the reference distribution (i.e. Rdit=~0.5), the decreasing trend of horizontal visibility was still confirmed. The percentage of trend analysis of very good and bad visibility showed an increase in bad visibilities (from 5% to 25%) and a decrease in very good visibilities (from 80% to 5%), which confirms the decreasing trend in horizontal visibility. Hazy condition with 38.7% was the most influential weather phenomenon in visibility degradation.
Climatology
Hassan Zareh; Saeed Movahedi; Dariush Rahimi
Abstract
Reduction in productivity of horticultural and agricultural products, increase in pests, reduction in quality of agricultural products, and threat to food security are the consequences of climate change. The impact of climate change on agriculture leads to an increase in risk and risk-taking in the field ...
Read More
Reduction in productivity of horticultural and agricultural products, increase in pests, reduction in quality of agricultural products, and threat to food security are the consequences of climate change. The impact of climate change on agriculture leads to an increase in risk and risk-taking in the field of agricultural activities. The results of the observational data review confirm the occurrence of climate change. The annual temperature anomaly of Bushehr province indicated an increase in the frequency of years with temperatures above the average from 1996 to 2021. According to the Pettitt's test, this increase is about 1.2 c˙. In addition, the significant increase in temperature at the 95% confidence level and Z values ≥ 2(in Mann-Kendall test) confirmed the occurrence of climate change in Bushehr province. The estimated data of the model for the future period confirm the continuation of the increasing trend of olive temperature thresholds for the period (2014-2040). The findings of the research indicated that with the increase in temperature for at least the following 20 years, the olive tree's cooling needs will not be met and the flowering season will occur in March instead of April. In the future, more areas will have an annual temperature of more than 26 °C. Therefore, in the future, the olive growing period will increase from 90 days to 150 days. With the increase in the number of days with temperatures above 40°C, the fruit burns more and the quality of olives decreases. Therefore, in addition to Asalouye and Dashtestan counties (1994-2019), Kangan, Jam, Deir and Dashti counties, the northern foothills of the province, and parts of Dilam (2017-2040) are added to the unsuitable olive areas. The favorable areas for olive cultivation will be moved to the west of the province.
Climatology
Yagob Dinpashoh; Saeid Jahanbakhsh-Asl; Asma Azadeh Garebagh
Abstract
In this study the values of potential reference crop evapotranspiration were calculated using the FAO-56 Penman Monteith method in six stations located in southern shores of Caspian Sea. Trends in annual ET0 values of the stations were analyzed using the Mann-Kendall test. Then to determine the relative ...
Read More
In this study the values of potential reference crop evapotranspiration were calculated using the FAO-56 Penman Monteith method in six stations located in southern shores of Caspian Sea. Trends in annual ET0 values of the stations were analyzed using the Mann-Kendall test. Then to determine the relative importance of climatic variables on ET0 in a certain station factor analysis conducted. To do this, correlation matrix (R) of seven variables also called similarity matrix was constructed. The significance of correlation coefficients were tested. Results of trends in ET0 showed that in all the stations (except Noshahr) trends of annual ET0 were upward and significant. The slopes of trend lines were positive in all the stations. Factor analysis showed that the first two factors accounted the total variance in the range of 56.5 per cent in the Rasht to 79.6 per cent in the Sari. The largest loading of the first factor is attributed to sunshine hours in the station Rasht, however, it was maximum air temperature in all other sites. In the case of the second factor, the largest loading belonged to wind speed (in Rasht, Gorgan, Sari and Noshahr) and precipitation (in Ramsar and Astara). The findings of this study can be helpful in optimum management of regional water resources.
Climatology
Roghayeh Maleki Meresht; Bromand Salahi; Mahnaz Saber
Abstract
The current research was carried out to analyze the changes in precipitation in northwest Iran during the coming decades based on GCM models. For this purpose, first, the precipitation of 1985-2014 was trended based on the Mann-Kendall test. Then, the daily precipitation data for each of the studied ...
Read More
The current research was carried out to analyze the changes in precipitation in northwest Iran during the coming decades based on GCM models. For this purpose, first, the precipitation of 1985-2014 was trended based on the Mann-Kendall test. Then, the daily precipitation data for each of the studied stations was simulated in SDSM6.1 software for 1985-2014. Then, under the scenarios (SSP2-4.5) and (SSP5-8.5) of CanEsm5 and MPI-ESMI-2HR models, the precipitation of 2015-2043 was predicted. To evaluate the performance of CMIP6 models and compare the basic and predicted values, MSE, RMSE, and MAE statistical measures were used. According to the results of the Man-Kendal test, the precipitation of the base period in the stations of Tabriz, Ardabil, Urmia, Takab, and Maragheh has a decreasing trend and in the stations of Meshginshahr, Sardasht, Mako, Khalkhal, Sarab, Jolfa, and Parsabad it has an increasing trend. Among the 12 investigated stations, only the Maragheh station had a significant decreasing trend. In other stations, precipitation trends were not significant. According to the predictions made based on the mentioned models, under the medium scenario (SSP 2-4.5), the precipitation will decrease in late winter and early spring. In other months, especially summer and autumn months, the percentage of precipitation will be higher. Based on the SSP5-8.5 scenario, the highest percentage of precipitation decrease in the MPI model was predicted by 33% in Jolfa, Sardasht, and Maragheh stations, and in the CanESM5 model, about 33-35% in Jolfa, Takab, and Urmia stations. According to the results, although both models predicted precipitation with a relatively high error, the MPI model had a lower error and more accuracy in predicting precipitation than the CanESM5 model.
Climatology
vahideh abtahi; Saeed jahanbakhsh; hashem rostamzadeh; hasan lashkari
Abstract
Heavy rainfall is considered one of the climatic features of precipitation that can occur in any climate, but its occurrence in arid and semi-arid climates, due to the lack of adequate and appropriate infrastructure, is associated with greater damage. These rains occur under different synoptic conditions. ...
Read More
Heavy rainfall is considered one of the climatic features of precipitation that can occur in any climate, but its occurrence in arid and semi-arid climates, due to the lack of adequate and appropriate infrastructure, is associated with greater damage. These rains occur under different synoptic conditions. In this study, the role of atmospheric rivers in the formation of heavy rainfall has been investigated. For this purpose, heavy rainfall data from stations in the west and northwest of the country were extracted for a 33-year period. Then, precipitation systems were separated in conjunction with atmospheric rivers. In the next step, using weather maps and the troposphere's underlying layer levels, synoptic patterns that lead to the formation of atmospheric rivers were identified. The results showed that atmospheric rivers were responsible for heavy rainfall in the study area, following three general patterns. The Sudanese low-pressure pattern and the combined pattern of Sudanese low-pressure and Mediterranean cyclone were responsible for the most significant role in the formation of atmospheric rivers leading to heavy rainfall, respectively. In the Sudanese low-pressure pattern, two to three days earlier, a broad tongue of Siberian high pressure spreads over the warm waters of the Oman, Arabian, and Aden seas, passing through Afghanistan, Pakistan, and the eastern part of Iran. This tongue, with the rotation of moisture, escapes from the Sudanese system. The Mediterranean trough deepens over western Asia and northeast Africa, and this moisture is strengthened along the southern currents and, by passing over the mountains,leads to the formation of atmospheric rivers. In the combined pattern, with the expansion of the Sudanese low-pressure tongue to the eastern Mediterranean and western Asia, the southern warm waters' moisture is released onto this region with the transport of moisture from the Mediterranean, it is strengthened, leading to the formation of atmospheric rivers.
Climatology
narges samadi; ali akbar rasouli pirouzian; davood mokhtari; Khalil Valizadeh Kamran
Abstract
The main aim of the current study was to detect changes in snow cover within the Western watersheds of Lake Urmia, situated in the Silvaneh mountain range, using the processing of multi-sensor and multi-spectral satellite images for high-precision identification of snow-covered areas. Sentinel-2 and ...
Read More
The main aim of the current study was to detect changes in snow cover within the Western watersheds of Lake Urmia, situated in the Silvaneh mountain range, using the processing of multi-sensor and multi-spectral satellite images for high-precision identification of snow-covered areas. Sentinel-2 and Landsat (8 and 9) satellite images were acquired and underwent preprocessing operations, such as atmospheric and radiometric corrections, using ENVI software version 1/10. Projects for the May months of the years 2016 to 2023 were then established. Initially, normalized difference snow indices were employed to independently generate snow cover maps for Landsat and Sentinel images for the entire watersheds of Nazluchay, Ruzechay, Shahrchay, and Barandozchay. In the next stage, an optimized color-sensitive object-based approach, based on object-oriented functions, was applied to the main bands of the Sentinel-2 sensor. To enhance the accuracy of the final results, Landsat images were fused with Sentinel images through a coordinated fusion method, producing various products, especially high-resolution optimized color images and classified scene maps. Ultimately, high-precision snow cover maps for temporal series were extracted for each of the mentioned watersheds through processing the fused images. Examination of the snow cover maps revealed that despite its smaller area compared to the Nazluchay and Barandozchay watersheds, the Shahrchay watershed has a higher snow accumulation coefficient, allowing for greater snow cover storage. Additionally, the comparison of the snow cover density map (years 2016 to 2023) with the elevation model of Alouspalsar at a resolution of 5/12 meters indicates a significant distribution of snow cover in higher elevations above 2300 meters in the study area. Therefore, accurate identification of snow cover, even on a daily and weekly scale, can provide essential and precise information for proactive water resource management, resulting from snowmelt, with multiple objectives in the watersheds surrounding Lake Urmia.
Climatology
Hashem Rostamzadeh; Saied Jahanbakhsh asl; Mir kamel Hosseini; Mohammad Omidfar
Abstract
AbstractChanges in the incidental behaviors are among the most important aspects of global climate change with significant consequences on human society and the environment. Monitoring and measuring heavy rainfall events are important for understanding the nature of severe weather fundamentals and future ...
Read More
AbstractChanges in the incidental behaviors are among the most important aspects of global climate change with significant consequences on human society and the environment. Monitoring and measuring heavy rainfall events are important for understanding the nature of severe weather fundamentals and future assessment. In this study, Global Precipitation Measurement (GPM) experiments with ground station data were performed at 20 synoptic stations for intense daily detection (25 mm and above) of precipitation over an 8-year period (2021-2014). Statistics such as coefficient of determination (R2), correlation coefficient (R) and root mean square error (RMSE) were used to compare and evaluate the observational and satellite data. Comparison of the maps obtained from GPM satellites and ground stations showed that the spatial distribution of precipitation from two similar bases is the same and the low and high rainfall areas correspond to the region. GPM satellite detected precipitation zones well so that the spatial correlation coefficient between GPM satellite and observed was 0.81. The results of the ANOVA test between the observational data and the GPM satellites showed that due to the low significance level of p-value of 0.000, the assumption that the average precipitation is the same between the two databases is rejected. There is a significant relationship between the average precipitation at ground and satellite stations. Also, the results of Kolmogorov-Smirnov test showed that since the obtained p-value (0.819) is a number higher than the error value of the test (0.05), so the null hypothesis based on the equality of precipitation values recorded at ground stations and modeled are the same and the null hypothesis is confirmed.
Climatology
Ali Mohammad Khorshiddoust; saeed jahanbakhshasl; zahra abbasighasrik; fatemeh abbasighasrik
Abstract
Today, long-term forecasting of climate variables has received much attention in order to be aware of the extent of change and, consequently, to take the necessary measures to mitigate the adverse effects of climate change. In this study, minimum temperatures in Kurdistan province were predicted using ...
Read More
Today, long-term forecasting of climate variables has received much attention in order to be aware of the extent of change and, consequently, to take the necessary measures to mitigate the adverse effects of climate change. In this study, minimum temperatures in Kurdistan province were predicted using LARS-WG6 downscaling for the next three 20-year periods (2040-2021, 2060-2041, 2080-2061). For this purpose, the HadGEM2-ES general circulation model and three scenarios of RCP8.5, RCP4.5 and RCP2.6 were used. To generate the time series of future periods, daily data for the statistical period 1989-2019 were used and the trend of its changes was analyzed using Mann-Kendall test. The results showed that LARS-WG6 software simulates the minimum values of the minimum temperature well with low error indicators. Also, based on the results of the HadGM2-ES global model output in the study area, the minimum temperature in the future period will be higher than the base period in all scenarios and periods. The intensity of this increase under the RCP8.5 scenario is related to the last period of the century (2080-2061) and its lesser extent is related to the period (2060-2041) under the RCP4.5 scenario. Examination of seasonal averages also shows that spring has a lower temperature increase and autumn has a higher temperature increase. The trend of changes shows that the trend is positive and negative in both directions, so that in most stations and scenarios in different forecast periods, spring will have the most positive trend and autumn will have the most negative trend. Therefore, it can be concluded that the temperature will increase in future periods and the effect of cold waves will decrease.
Climatology
Mojtaba Nassaji Zavareh; Hossein Hokmabadi; Alireza Asadolahi
Abstract
Late spring frost cause a lot of damage to the agricultural sector every year. Prediction of this phenomenon is needed to active protection of plants. In this research, using FAO experimental method, daily and hourly data of two meteorological stations were used to determine the coefficients of the experimental ...
Read More
Late spring frost cause a lot of damage to the agricultural sector every year. Prediction of this phenomenon is needed to active protection of plants. In this research, using FAO experimental method, daily and hourly data of two meteorological stations were used to determine the coefficients of the experimental model for prediction radiation frost in Qazvin Plain. also, in order to investigate the climatic condition of spring frost, the daily minimum temperature data of Qazvin and Buinzahra stations were used. The analysis of sixty years data in Qazvin stations showed that the intensity of frost has decreased during these years, but frequency of frost in Ordibehesht month has increased. Air, dew-point at two hours after sunset and minimum temperature relate 25 events of radiation frost at Simorgh station were used for regional coefficient calculation based on two models. These models were evaluated using 14 events of radiation frost at Tat stations. The mean absolute error(MAE) for testing and evaluating of Model1 was 0.71℃ and 1.21℃ and for Model2 was 0.67℃ and 1.09℃. The findings also showed that both models have acceptable accuracy in estimating the minimum temperature of the next day. It is proposed that these two models can be used for prediction of radiation frost in other regions.
Climatology
Mehdi pourahmad; mostafa karampour; behroz nasiri
Abstract
The aim of this study was to reveal the relationship between land cover changes and changes in aerosol optical depth index in the Middle Zagros. In this regard, two categories of MODIS sensor remote sensing products were used. First, land cover changes in the study area were performed using MODIS sensor ...
Read More
The aim of this study was to reveal the relationship between land cover changes and changes in aerosol optical depth index in the Middle Zagros. In this regard, two categories of MODIS sensor remote sensing products were used. First, land cover changes in the study area were performed using MODIS sensor land use classification derivative product. In the second part of the research, the trends of dust events were investigated based on the station data of the dust codes of 4 stations of Khorramabad, Shahrekord, Yasuj and Abadeh. In addition, the trend of Aerosol Optical Depth Index (AOD) was examined using MOD04-L2 Madis sensor product for the statistical period 2000 to 2020. The results showed that there were 6 layers of rangeland, forest, agricultural, urban, residential, barren and water areas in the Central Zagros, in which the forest floor has decreased by about 123 square kilometers per year. Rangeland cover, which is the main cover of the study area, has remained relatively stable, and agricultural land uses have increased significantly, from 7% in 2000 to 9.5% in 2020. Urban and residential lands had also increased. On the other hand, a review of the 21-year time series trend of the AOD index indicates an upward trend over the last 21 years. Among the land use classes, the two categories of pastures and forests, which in fact occupy more than 90% of the study area, have shown an inverse relationship with the AOD index. But the class of agricultural lands was directly related to the AOD index. Therefore, the decreasing trend of forest floor in the region has been significantly associated with the increasing trend of AOD in the region and on the other hand, the increasing trend of agricultural land has been associated with the increase of AOD in the region.
Climatology
behrouz sobhani; minoo ahmadyan; Saeed jahanbakhsh
Abstract
the statistics of the ECMWF database were used for the observation data of the two stations of Semiram and Urmia during a 21-year period (1996-20016).In order to investigate the effects of climate fluctuations, the daily data of dynamic micro-rotation of the CORDEX project was used for the output of ...
Read More
the statistics of the ECMWF database were used for the observation data of the two stations of Semiram and Urmia during a 21-year period (1996-20016).In order to investigate the effects of climate fluctuations, the daily data of dynamic micro-rotation of the CORDEX project was used for the output of the ICHEC-EC-EARTH model under the RCP8.5 and RCP4.5 radiative forcing (RCP) scenarios for the period (2017-2037). By using the data of the stations and the outputs of the micro scale model, and by using the perceptron neural network and linear regression, the performance was simulated. Then, to evaluate the efficiency of the models, R, R2, MSE, RMSE, and NRMSE statistics were used, and the non-parametric Menkendall test and age slope were used for the performance trend. The result of comparing the output of artificial neural networks with the linear regression model shows that the error rate of the neural network is less and the simulated results are close to the real observations to a very acceptable extent. The phenological stages, including bud blooming to fruit ripening in the stations under both scenarios, and in all the phenological stages in the future period will be completed earlier than the base period, and the length of the growth period will also decrease. The amount of future yield in Urmia station under RCP4.5 and RCP8.5 scenarios respectively yield 3.7 and 2.2 tons per hectare and in Semiram station yield 1.4 and 3 respectively tons per hectare will decrease. The results show that in the future in the study areas, with the change in the time of occurrence of the length of the growth period, all the phenological stages as well as the declining performance of apple trees will be subject to climatic fluctuations
Climatology
Shirin Mahdavian; Batool Zeynali; Bromand Salahi
Abstract
Climate diversity and land use / land cover change have a significant impact on hydrological regimes, especially in arid and semi-arid regions with critical water shortage problems. Therefore, estimating and evaluating climate change and land use and its consequences in each catchment is essential. This ...
Read More
Climate diversity and land use / land cover change have a significant impact on hydrological regimes, especially in arid and semi-arid regions with critical water shortage problems. Therefore, estimating and evaluating climate change and land use and its consequences in each catchment is essential. This study examined the climate change of Kiwi Tea Basin using the data of four models of the Fifth Climate Change Assessment Report (CMIP5) under both optimistic and pessimistic scenarios (RCP8.5 and RCP4.5) using the LARS-WG6 microcirculation model. Changes in precipitation and temperature during three different periods (2040-2021, 2060-2041 and 2080-2061) compared to the base period (2019-1987) have been studied and for calibration and validation of LARS-WG6 model, observational data and output data of models with The use of F and T tests as well as RMSE, MSE, MAE and R2 indices were compared and evaluated. Based on the results of most of the models and the average of the studied models, in general, it is expected that the amount of precipitation and the minimum and maximum temperature in all the studied models will increase compared to the base period. Also, the results of evaluating land use changes with object-oriented classification showed that rangeland use with an area of 1224.18 and 1046.59 square kilometers, respectively, covered the largest area in both periods, while in 1987, residential use with an area of 3.66 square kilometers and in In 2019, water use with an area of 3.77 square kilometers had the lowest area. Also, the most modified use of rangeland use was dryland agriculture (181 square kilometers), which indicates thedestruction of rangelands
Climatology
shahnaz Rashedi; Saeed jahanbakhsh; Ali Khorshiddoust; Gholam Hasan Mohammadi
Abstract
For this purpose, data on the type, amount, and height of different cloud layers and daily precipitation of 36 synoptic stations located on the southern coast of the Caspian Sea were received from the Meteorological Organization. MODIS images were used to investigate the relationship between precipitation ...
Read More
For this purpose, data on the type, amount, and height of different cloud layers and daily precipitation of 36 synoptic stations located on the southern coast of the Caspian Sea were received from the Meteorological Organization. MODIS images were used to investigate the relationship between precipitation and cloud microphysical parameters (CTT, CTH, COT, CER, CWP). ERA5 and NCEP/NCAR data were also used to identify synoptic patterns leading to cloud formation. Finally, HYSPLIT model and regression method were used to identify the path of moisture flow. The results of observational data showed that Caspian clouds were observed in the form of low Stratus clouds and middle clouds of Altocumulus type in the region. So that among the low clouds, the heights of 750 and 900 meters and among the middle clouds, the heights of 2700 meters had the highest frequency. The results of Caspian clouds rainfall showed that in most areas, 1 to 5 mm of precipitation has occurred. Correlation results showed that precipitation was positively correlated with CTH,COT, CER and CWP, and negatively correlated with CTT. Multivariate regression predicted 17% of precipitation by cloud parameters. The results of the study of synoptic maps showed that with the establishment of a 1012 hPa high pressure core in the north of the Caspian Sea, the north-south wind flow along with the transfer of sea moisture to the south shore of the Caspian Sea, ascending the air mass and the formation of clouds and limited rainfall in the region. Vertical profiles showed maximum specific humidity in the lower levels of the atmosphere (1000 to 900 hPa). The results of HYSPLIT model moisture flow path showed that the main source of regional moisture was the Caspian Sea.
Climatology
Mohammadreza Rafighi; Mehry Akbary; Mohammad Hassan Fakharnia; Mohammad Hassan Vahidnia
Abstract
IntroductionAlthough the air layer adjacent to the earth's surface - the boundary layer - is a small fraction of the entire atmosphere, the processes that take place on a small scale are very important to human life and activites. Among living organisms, plants and especially trees have undeniable effects ...
Read More
IntroductionAlthough the air layer adjacent to the earth's surface - the boundary layer - is a small fraction of the entire atmosphere, the processes that take place on a small scale are very important to human life and activites. Among living organisms, plants and especially trees have undeniable effects on surface temperature and especially in urban environments have several balancing effects. This research was carried out using Landsat 8 satellite imagery and with Arc GIS software to compare the surface temperature of the earth in two areas with vegetation of coniferous trees (Chitgar Park) and broadleaf trees (Shahid Chamran Park). The values of Radiance, Reflectance, Brightness Temperature, Normalized Difference Vegetation Index, Proportion of Vegetation and Emissivity and then Land Surface Temperature were calculated and generated. A total of 1700 points were harvested from Chitgar Park and 800 points from Chamran Park. In SPSS software, Leven test (F) statistics was used to prove the homogeneity of variances of the samples and parametric tests (T with two independent samples) were used to prove the significant difference between the surface temperature of the earth in the mentioned areas. According to Leven test, the value was Sig = 0.409 (P_value), which confirms the homogeneity and equality of variance of the studied samples. Also, in the T test, the value was Sig = 0.000, which is less than 0.05, which means a significant difference. Therefore, the difference between the surface temperature data of the two parks was proved. Also, by comparing the graphs of LST values in the two groups, we found that Chitgar Park has a higher surface temperature than Chamran Park. In the current dilemma of the century, global warming, knowing these local realities and providing logical solutions to reduce surface temperature at the regional and regional scales as a whole can effectively solve the problem of global warming on a global scale.Data and Method The data used in this study is a Landsat 8 satellite imagery with the acronym: 8 (LC08_L1TP_165035_20190706) is LANDSAT.Retrieved July 6, 2019 from the USGS website.Production of component images for Shahid Chamran Parks in Karaj and Chitgar in Tehran: The surface temperature image was generated step by step using the Landsat 8 satellite image using the Raster Calculator command in the ArcMap software environment. First, relevant and effective indicators in calculating the surface temperature of the earth, Top of atmospheric radiance, reflectance, Brightness Temperature, normalized difference vegetation index, proportion of vegetation, emission coefficient (emissivity), calculation and their images are produced and then the land surface temperature, It was calculated and produced according to the following mathematical formulas.Step 1: Produce a spectral radius image from above the atmosphere To obtain the brightness temperature, the image must first be converted to radius. Therefore, the gray DN values of bands 10 and 11 of the Landsat 8 satellite TIRS sensor should be converted to high atmospheric radius separately with the help of the MTL file, which is an extension of the Landsat image (Tables 1, 2 and 3).Formula (1) :Calculate the radius of the upper atmosphere TOA (Lλ) = ML * Qcal + ALLλ = (Watts / (m2 * srad * μm)) The radius of the atmosphere in terms ofML = Multi-band radius_ 10 bandStep 2: Produce an image of the light temperature above the atmosphere After converting the DN values of bands 10 and 11 to high atmospheric radii, we converted these two corrected bands to Brightness Temperature.BT = (K2 / (ln (K1 / L) + 1)) - 273.15 Formula (2): Calculation of Brightness Temperature BT = Atmospheric Brightness Temperature (° C)Lλ = (Watts / (m2 * srad * μm)) Radius of the atmosphere in terms ofBT = (1321.0789 / Ln ((774.8853 / “% TOA%”) + 1)) - 273.15K1 = K1 Constant Band (No.), K2 = K2 Constant Band (No.)Step 3: Produce vegetation index image formula (3): normalized difference vegetation index image was generated usingNDVI = (Band 5 - Band 4) / (Band 5 + Band 4)Step 4: Produce a proportion of vegetation imageThe proportion of vegetation image was generated using normalized difference vegetation index.formulas (4):Calculate the proportion of vegetation PV = (NDVI - NDVImin / NDVImax- NDVImin) 2PV = Square (("NDVI" - 0.216901) / (0.632267 - 0.216901))Step 5: Produce the Emissivity image Emissivity image was generated using formula (5)ε = 0.004 * PV + 0.986 Formula (5): Calculate the Emissivity coefficientStep 6: Produce an image of the earth's surface temperature Land surface temperature image was generated using formula (6).Formula (6) :Calculate ground land surface temperatureLST = (BT / (1 + (0.00115 * BT / 1.4388) * Ln (e)))Results and Discussion Text Comparison of surface temperature phenomena (LST) According to Table (6), the highest land surface temperature with 44.42 ° C belongs to Chitgar Park, which is covered with coniferous trees, and the lowest in Shahid Chamran Park, in Karaj with 28.09 ° C with broadleaf trees. Has been. According to Tables (7) and (8), the lowest temperature of Chamran Park is 28.09 ° C and the highest is 36.51 ° C and the lowest temperature of Chitgar Park is 34.74 ° C and the highest is 44.42 ° C. . According to Figure (22), Chitgar Park with an average surface temperature of 38.92 ° C is warmer than Shahid Chamran Park with an average land surface temperature of 31.39 ° C. Figure (23) shows a red graphic showing the surface temperature of the ground in Chitgar Park with coniferous species (pine) and the blue diagram shows the surface temperature of Shahid Chamran Park in Karaj with broadleaf species. It is clear that the temperature is significantly higher in Chitgarh Park. The range of temperature fluctuations in Shahid Chamran Park is between 36.51 - 28.09 ° C and in Chitgar Park is between 42 / 44-74 / 34 which is exactly shown in the diagram. The fact that the red chart is higher than the blue chart explains this correctly. This is due to the lower density of trees in Chitgarh Park as well as the predominant tree species (needle-shaped) due to less shading and more input radiation. T test with two independent samples: This test, which is a parametric test, was used to prove a significant difference between the earth's surface temperature in areas with coniferous and deciduous trees. Leven test (F) was used to prove the homogeneity of sample variances and t-test with two independent samples was used to examine the homogeneity of the means of the two statistical populations, which resulted in the following results. As can be seen in Table (12), the value = 0.409 Sig, which is the same value as P_value, is greater than 0.05, ie the variance of the communities is homogeneous and equal. 0.05 is less, which means that the difference is significant. Due to religion, the difference between the land surface temperature data of Shahid Chamran and Chitgar parks is proved.ConclusionAccording to all the findings, Chitgar Park has a higher land surface temperature than Chamran Park, which is due to the lower density of trees and also the type of dominant tree species (needle-shaped). Coniferous species that take up less space than broadleaf species and have less shading. They also make it possible for the sun to collide with the ground due to the fact that the leaves of the adjacent trees do not meet, and this is an important factor in raising the surface temperature in the mentioned park. Species compatible with the climate of the study areas are broadleaf species because they have more leaves shading and care than coniferous species and ultimately cause more climate adjustment. The difference in temperature between the two parks confirms this fact. In the current dilemma of the century, global warming, knowing these local realities and providing logical solutions to reduce surface temperature at the regional and regional scales as a whole can effectively solve the problem of global warming on a global scale.
Climatology
abdolreza hosseini; sayed mohammad hosseini; Rahman Zandi; hasan hajimohammadi
Abstract
IntroductionSnow, as one of the important climatic-hydrological parameters, has a significant role in providing the world's water resources for industrial, agricultural and drinking purposes. At the same time, the dangerous consequences of heavy snowfall, avalanches, destruction of rural housing, disruption ...
Read More
IntroductionSnow, as one of the important climatic-hydrological parameters, has a significant role in providing the world's water resources for industrial, agricultural and drinking purposes. At the same time, the dangerous consequences of heavy snowfall, avalanches, destruction of rural housing, disruption of road transport and communication and numerous other consequences that it has on the natural and human environment are significant for environmental scientists (Shakiba et al, 2015: 88). However, heavy snowfall, especially in the lowlands and lowlands of the middle latitudes, is unexpected and somewhat surprising. So that its continuation for a few days in these areas will have negative effects on practically all living standards of the residents of these areas (Hosseini, 2014: 101). In recent years, the use of satellite data in natural, hydrological and water resource management has grown significantly, and in this regard, MODIS sensor images due to acceptable spatial resolution and fast temporal retrieval power with a variety of bands. Spectral has put it in a good position. Also, due to the very high albedo of snow, it is possible to measure the level of snow cover using satellite data. MethodologyIn the present study, the environmental approach to circulation was used to investigate the relationship between circulation patterns and heavy snowfall. Thus; first, the days of heavy snowfall in the studied stations were identified and then the synoptic patterns and atmosphere of the representative days were analyzed. In this regard, after receiving snow altitude data from the Meteorological Organization, heavy and widespread rainfall events were identified in three western provinces of the country, including Hamadan, Kurdistan and Kermanshah in the form of 16 synoptic stations, during the years 2000 to 2019. In order to study and analyze the synoptic patterns of days with heavy snowfall, by referring to the website of the National Center for Environmental Forecasting / Atmospheric Sciences (NCEP / NCAR), daily data on Sea Level Pressure (SLP), High Geopotential (HGT), zonal wind (UWND) and meridianal wind (VWND), air temperature (Air) and instability index (Omega) were extracted at the intersection of 2.5 * 2.5 and the relevant maps were drawn using GRADS software. Also, the area covered by snow was obtained from MODIS satellite images. MODIS data are of level1b type, which was calculated based on the parameters in the header, radiance and reflectivity. Reflective and thermal parameters for bands 4 and 6 were also used to apply the NDSI (Normalized Difference Snow Index). Results and DiscussionAfter 20 years of study, 8 days were identified that heavy and heavy snow had fallen in the area. On February 4, 2011, in the middle of the atmosphere, a deep trough formed in the western Mediterranean and North Africa, with a strong positive vorticity. This situation has affected the study area.The location of this trough in the Mediterranean provides the moisture needed for snowfall from the Mediterranean Sea. ConclusionsThe results showed in the ground formed a powerful cyclone on Iraq and turbulent weather caused chaos for the region. This condition causes the air to cause accelerated the rise of the package and water vapor in the atmosphere with his quick ascent to the seed quickly convert hexagonal snow. Creates a pressure gradient that causes more than 12 HPa in the region was to create a strong front will be formed in the region. In the high latitudes of cold air and warm air in front of it is the lower latitude. Has caused more than 60 to 70 percent of the study area are covered by snow. A deep trough of cold air loss in middle levels at depths greater than 25 degrees latitude has been. With extreme vorticity and air along rapid ascent has been closed. NDSI index showed the results of actions by deploying the most weather systems has gone down snow-covered forests of western Iran.
Climatology
Seyyed mahmoud Hosseini seddigh; masoud jalali; Hossein Asakereh
Abstract
IntroductionThe results of the study showed that the correlation headley cell and subtropical jet on the atmosphere Iran at the level 200 hPa has a positive correlation with a value of 0.4-0.7 to 35 ° latitude and also regression analysis showed that in latitudes between 15 35 degrees north of the ...
Read More
IntroductionThe results of the study showed that the correlation headley cell and subtropical jet on the atmosphere Iran at the level 200 hPa has a positive correlation with a value of 0.4-0.7 to 35 ° latitude and also regression analysis showed that in latitudes between 15 35 degrees north of the subtropical jet 1(m/s) is higher than normal, although in 2017 up to latitudes 30 degrees north showed an increase of 2(m/s), which had a negative effect on rainfall.Data and MethodThe relationship between Hadley cell and olr in the southern, southwestern and southeastern regions of Iran with a value of 0.4 and the Zagros and northwestern heights of Iran with a value of 0.7 and regression with a value of (w/m2) 0.01 more than normal.Results and DiscussionIt acts as a tangible source of heat in the middle Wordspehr and the heat is added directly to the middle Wordspehr and causes heating of the upper half of the Wordspehr.ConclusionRegression 2 to 1 is shown. Low relative humidity along with the dried air mass is located below the descending branches of the headley cell, which has ruled the drought conditions (-0/7) showed that it creates conditions for lack of rainfall and drought.
Climatology
Behrooz Sarisarraf; Hashem Rostamzadeh; Mohamad Darand; Omid Eskandari
Abstract
Precipitation is one of the most important and variable climatic elements that changes in time and place. Critical rainfall at various time scales, especially daily, causes severe damage to human communities in densely populated urban areas and natural ecosystems and affects many arid economies. Earth ...
Read More
Precipitation is one of the most important and variable climatic elements that changes in time and place. Critical rainfall at various time scales, especially daily, causes severe damage to human communities in densely populated urban areas and natural ecosystems and affects many arid economies. Earth outgoing long-wave radiation is studied as a significant parameter to detect clouds and estimate this type of precipitation. The current study aims to examine the relationship and analysis of outgoing long-wave radiation variables and precipitation values in Arc GIS software environment for the four cold months 17 statistical years in Iran using AIRS sensor products of Aqua satellite and GPM satellite. Correlation and regression models and confidence interval estimation were used to measure the correlation of long-wave radiation output in predicting precipitation patterns and their changes. According to the results obtained in all months studied, In the whole country, except Caspian Sea basin in January, parts of the central and eastern plateau of eastern Iran, there is a negative correlation of 10 to 92%, Which indicates that the country's atmosphere is humid and prevents the release of outgoing long-wave radiation. In the western rainfall areas of the Zagros Mountains, negative correlations above 70% and outgoing long-wave radiation is less than 260 W⋅m−2 which is due to cloudy and humid atmosphere with precipitation.In December and February, the rainfall areas north of the Caspian Sea basin range have negative correlations of above 50% and OLR less than 235 W⋅m−2 of rainfall and the reason for the lower numerical value north of the Alborz mountain range to predict is the existence of high relative humidity in the region, which is the cause of less outgoing long-wave radiation output of the earth.
Climatology
younes nikookhesal; Ali Akbar Rasouli; Davod Mokhtari; Khalil Valizadeh Kamran
Abstract
IntroductionThe water cycle in nature is directly related to the climate of that region. Reasonable and correct use of water resources requires accurate quantitative and qualitative knowledge and collection of appropriate climate data and information. Depletion of groundwater reservoirs, drying of canals ...
Read More
IntroductionThe water cycle in nature is directly related to the climate of that region. Reasonable and correct use of water resources requires accurate quantitative and qualitative knowledge and collection of appropriate climate data and information. Depletion of groundwater reservoirs, drying of canals and springs and even semi-deep wells and reduction of deep well discharge, change of groundwater flow direction, salinization of aquifers, salinization of soil due to irrigation with saline water, barren The emergence of fields, soil erosion, etc. has put most of the plains of the country at risk of further desertification (Tavousi, 2009: 14).Atmospheric precipitation is the main source of surface and groundwater and the study area is poor in terms of atmospheric precipitation and its amount is between 150 to 450 mm per year, which varies in plain and mountainous areas. The climate of the region is semi-arid and cold and is mostly influenced by the Mediterranean climate. Due to the fact that groundwater is the most important source of water consumption in the study area, the impact of climate change, especially precipitation on the water table of wells in the area was investigated in this study.Materials and methodsTo study the trend of groundwater level changes in Marand plain, water table data of 23 piezometric wells and data of 8 rain gauge stations during the last 16 years of 1395-1395 were used. After using the correlation matrix method to select rainfall stations and considering the complete statistical data and appropriate coverage of the area by these stations, 4 stations were selected for the study and for each station, a piezometric well was selected within the station. This research was first calculated using precipitation data and water table of piezometric wells SPI and SWI values and then NRMC values for each index, respectively, in each method are briefly referred to:Calculate SPI and plot seasonal SPI variations of selected stationsThe standardized rainfall index was provided by McKay et al. (1993, 1995) to provide a warning and help assess drought severity and is calculated by the following formula: Relation 1: SPI = (X_ij-X_im) / σIn the above relation, X_ij is the seasonal rainfall at rainfall station i, with j number of observations, X_im is the long-term average rainfall and σ is the standard deviation.Calculate SWI and plot the seasonal SWI of selected wells The standard water level index was presented in 2004 by Bui Yan et al. (2006) to monitor fluctuations in groundwater aquifers in the study of hydrological droughts, which is calculated by the following formula:Relation 2: SWI = (W_ij-W_im) / σWhere W_ij is the seasonal average of the water table of observation wells i to j, W_im is the long-term seasonal average and σ is the standard deviation.Calculate the NRMC values of each indicator and plot the normalized distribution curveIn this method, seasonal normalized distribution curves were adjusted for both SPI and SWI indices. Cumulative normalized curve is a kind of condensation diagram of a climatic or hydrological variable (such as precipitation and water table) that is extracted from the subtraction of each observation in the statistical series of the long-term average and its division by the average according to the following formula. (Rasooli, 1994)Relation 3: NRMC xi = ( (Xi-X m) / ({(Xi-X ̅m) / X ̅m}) ) * 100 In the above formula, Xi represents the amount of each rainfall observation or the amount of water table and X ̅m is the long-term average in the series of observations.Results and DiscussionInvestigation of normalized distribution curves showed a correlation between precipitation changes and groundwater level in Marand plain. This correlation has a higher significance with a delay season. Shamsipoor (2003) in Hamedan plain achieved a 9-month delay between precipitation and water table. Mohammadi et al. (2012) in Arak plain expressed the impact of groundwater resources from drought with a delay of two months. The results of the study (Rudel and Lee 2014) in the study of groundwater drought index in the United States showed that the SPI drought index with a delay of 12 and 24 months had the highest correlation with the SWI index.ConclusionConsidering the more fluctuations of the water table than the fluctuations of the rainfall, it can be concluded that human factors such as uncontrolled harvesting is an effective factor on the water level of wells. Komasi et al. (2016) stated the effect of human factors on the decrease of groundwater level before the factor of climate change in Silakhor plain. Calculations showed that the value of correlation for both SPI and SWI indices in the nonlinear multivariate equation is higher than the value of the linear equation, which indicates the effect of several other factors in addition to precipitation fluctuations on the groundwater level. According to the results of the study, it seems that the groundwater level in addition to precipitation depends on other factors such as geology, lithology, tectonic morphology, the shape of the aquifer, the distance of aquifers to the feeding site and .... And to achieve more complete results, it seems necessary to address these factors in future research.
Climatology
naser pouyanfar; Gholam Ali Mozafari; Kamal Omidvar; Ahmad Mazidi
Abstract
IntroductionPistachio, like many subtropical fruit trees, need a cold period in their annual cycle to allow the buds to bloom naturally after the right conditions are in place. There are several models to calculate the chilling needs of pistachio, of which the chilling hours model, Utah and Utah positive ...
Read More
IntroductionPistachio, like many subtropical fruit trees, need a cold period in their annual cycle to allow the buds to bloom naturally after the right conditions are in place. There are several models to calculate the chilling needs of pistachio, of which the chilling hours model, Utah and Utah positive are the most important of these models. The studied geographical area is Yazd-Ardakan plain located in Yazd province.Materials and methodsIn this study, according to statistical tests based on meteorological variables, the chilling hours model was selected for modeling. To conduct this research, three-hour temperature data of Yazd Synoptic Station during the statistical period of 1367-1396 were used to model and estimate the total monthly chilling hours of pistachio and The daily temperature data of this station during the statistical period of 1961-2005 were used for the SDSM model and the monthly temperature statistics of the years 1385-1397 were used to evaluate the downscaling data of the CanESM2 model under different RCP scenarios and finally modeling for the years 1400 -1429 was done.Result and discussionResults indicate that there is a significant correlation between monthly cumulative hours of temperatures between zero and 7.2 ° C and monthly temperature parameters such as mean minimum temperature, mean maximum temperature and mean monthly temperature, which in the absence of data hourly temperature can be used to model and determine monthly cumulative hours.ConclusionFindings show that the chilling needs of Kalle-Ghuchi, Owhadi and Ahmad- Aghaei species will be met in the coming years and Akbari and Fandoghi species will not be met.
Climatology
Monir Shirzad; Hajar Feyzi; Majid Rezaei Banafsheh
Abstract
Introduction Reference evaporation and transpiration is one of the important elements of the hydrological cycle, which plays an important role in agricultural studies, water resource management plans, irrigation and drainage network design and water structures (Nuri et al., 2013, Volume twenty, ...
Read More
Introduction Reference evaporation and transpiration is one of the important elements of the hydrological cycle, which plays an important role in agricultural studies, water resource management plans, irrigation and drainage network design and water structures (Nuri et al., 2013, Volume twenty, number five, page 12). Due to the small amount of precipitation and the limitation of water resources in Iran, the correct management of water resources is very important and it is necessary to be careful in using water.Data and MethodIn order to carry out this research, daily climatic data during the years 2014 to 2015 of East Azerbaijan (four stations of Maragheh, Midane, Jolfa and Ahar) were prepared from the regional meteorological organization. After normalization and determination of correlation, the data were used in MATLAB software with artificial neural network method with Lunberg-Marquardt training to 70-30 combination for training and simulation. The input data for the simulation of evaporation and transpiration (temperature, sunshine hours, humidity, wind speed) and the work evaluation criteria are RMSE, R2 and MAE, which we gave priority to the data with less error. Results and DiscussionIn this research, the method based on artificial intelligence (ANN) and three experimental models (Penman Monteith Fau (PMF56), Blaney Kridel (B-C) and Kimberly Penman (K-P) were used to model the non-linear transpiration evaporation system of the reference plant. The results showed that the artificial intelligence method has better accuracy and speed in estimating ET0 compared to experimental methodsConclusionThe results showed that the artificial intelligence method has better accuracy and speed. Also, comparing the method of artificial neural networks with classical methods, the results indicate the appropriateness of the performance of artificial neural networks.
