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 ...
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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
Younes Nikookhesal; ali akbar rasoli; Davod Mokhtari; Khalil valizadeh kamran
Volume 26, Issue 80 , August 2022, , Pages 327-317
Abstract
IntroductionInvestigating the effect of drought on water resources of countries plain is high important at optimal management of water resources in the agriculture and natural resources part. The phenomenon of climate change, affects the amount of water existence in aquifer by changing amount of precipitation. ...
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IntroductionInvestigating the effect of drought on water resources of countries plain is high important at optimal management of water resources in the agriculture and natural resources part. The phenomenon of climate change, affects the amount of water existence in aquifer by changing amount of precipitation. The occurrence of consecutive climate droughts affects ground water resources. Knowing and awareness of the effect of time between two phenomenon of drought and hydrological drought, can help managers and planners of the water sector. Over the years, the effect of drought on ground water resources less attention has been paid. In order to understand the state of groundwater resources and optimum management, it is necessary to carry out a thorough study of groundwater fluctuations. In this research, Marand plain is the purpose of this study. Marand Plain is poor in rainfall and has a rainfall of 450 mm / year and at least 150 mm / year which varies in the plains and mountainous regions. In this research, we have tried to investigate the effect of atmospheric drops, including rainfall, on ground water level in the Marand watershed.MethodologyThe Marand plain with 45 °, 15 to 50 minutes east longitude and 37 ° 7 'to 38 ° 56' north latitude and with an area of 42.517 square kilometer is one of the vast plains in the northwest of East Azarbaijan province. Which is selected as the study area. In this study, in order to study the trend of ground water level changes in the Marand Plain, the static surface data of 23 piezometric wells was used during the 2000 to 2016. First, a common statistical period was chosen to analyze the data series (2000 to 2016). Then in order to reconstruct the statistical defects, the correlation between stations and piezometric wells and linear regression method was used. The IDW method was used to calculate the average rainfall of the plain. Finally, the standard water level index (SWI) and the SPI index for the studied basin were calculated and analyzed. Discussion The aim of this study was to investigate the effects of climate drought on the fell of groundwater level in the Marand plain using SPI and SWI indices. Meteorological drought conditions in the Marand plain were calculated using the SPI index on a 12-month time scale. The results and drought accuracy of the rain gauge stations in the studied basin showed that during the study period, the first period of drought since 2005 started gradually with decreasing atmospheric precipitation and continued until 2007 and after a period of humidity short-term, again, a short period of drought from 2008 to 2009 has been on the ruling area. The SWI index was used to survey the status of groundwater level. This indicator also showed that in terms of time and place, the drought based on this index corresponded to the drought caused by the SPI index.Conclusion Using the SPI index, the drought trend was studied in the region. The results showed that during the study period (2000-2016) three drought periods from winter 2005 to beginning of 2009, summer of 2011 to the end of 2012 and winter of 2015 to summer of 2016 occurred. Drought affected areas included the east and center of the study area and the west of the region witnessed more atmospheric precipitation. The SWI index was used to survey the status of groundwater level. The index showed that in terms of time and place, the drought based on this index corresponded to the drought caused by the SPI index. Data analysis showed that these two indices with a time interval of one season had a correlation of 1%. This means that the hydrological drought after a season has a direct impact on the surface of the water. In general, we can conclude from the results of this study that the trend of ground water surface changes has been consistent with the drought and weathering changes in the region. Therefore, the fall of the ground water level of Marand plain can be largely influenced by weathered droughts.
Climatology
Ebrahim Ahmadzadeh; Khalil Valizadeh Kamran; Davod Mokhtari; ali akbar rasoli
Abstract
IntroductionRecently, high extreme and frequency distribution of higher sequence of precipitation have been attended more. Through this, because of geographical characteristics of each area, diverse and different thresholds have been presented and utilized for the mentioned precipitation’s characteristics. ...
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IntroductionRecently, high extreme and frequency distribution of higher sequence of precipitation have been attended more. Through this, because of geographical characteristics of each area, diverse and different thresholds have been presented and utilized for the mentioned precipitation’s characteristics. Through the present research, for exploring and analyzing the extreme precipitation event in Tehran through the 1983-2016 statistical periods, some of the indexes presented by World Meteorological Organization Committee were utilized.Data and MethodThe study area in the present study is Tehran province. Tehran province is located in the center of Tehran, with an area of about 12981 square kilometers, between 34 to 36.5 degrees north latitude and 50 to 53 degrees east longitude. Data from Abali and Mehrabad synoptic stations were selected daily for use in the present study during the statistical period of 2016-1983. Before analysis, the data were subjected to quality control and homogeneity test. In cases where for any reason there were incomplete data in the data series of each station, they were reconstructed and supplemented.Analysis of non-parametric I-Kendall trend and age slope estimatorIn the present study, in order to study and analyze the trend of limit events, the indexes provided by the National Climate Committee of the World Meteorological Organization and the Acceptable Research and Climate Prediction Research Program, abbreviated as ETCCDMI, are used. These indexes are part of a set of indexes presented by the World Meteorological Organization's Working Group on Climate Change (Peterson et al., 200: 341), which are used by numerous researchers for analysis in different parts of the world.Model of peak values Above the threshold (POT)The POT first fits the set limit and then one above this threshold with the generalized parity distribution. In the present study, the ninety-fifth percentile was considered as the initial threshold (Coelho et al., 2008: 120; Friederichs, 2010, 211). The test threshold was then set to determine whether it was appropriate or inappropriate. In recent years, two visual methods have been developed to select the threshold. In the present study, methods were used to validate the selected threshold. The first method is the description of residual life, also known as conditional excess (Lechner et al., 1992: 229). In the MRL method, the excess rate is plotted from the threshold to the threshold .How to estimate GDP distribution parameters using the maximum likelihood methodFor different estimates, there are several methods such as torques, possible weighted moments, the existence of correct representation, and so on. However, the most efficient performance method is evaluated as the most complete method (Rao and Hamed, 2000: 21). Therefore, in the present study, the correct method of displaying the work was used.Results and DiscussionThe results of man-condensate precipitation statistics at the studied stations. The results obtained from Mann-Kendall test showed that no significant trend in success level was experienced in the studied stations in the statistical period of 1983-2016. Except that in Abali station, the reduction of the number of consecutive dry days and in Mehrabad station, the reduction of the one-day rate (PX1day) at the level of 90% is significant. One day exhibition at Mehrabad station is a downward trend in the level of 90% confidence with the rate of 1.9 days in the last decade.During the statistical period of 2016-1983, no significant trend was experienced in relation to the index of the number of values for 5 consecutive days. The annual show on other days does not make sense. The number of days with more than 10 mm (R10) and the number of days with more than 20 mm (R20) and the number of days with threshold (Rnn) in the two study stations are not significant.In this study, using the Mann-Kendall non-parameter test and sen slope estimator, the final rainfall trend analysis was performed at Abali and Mehrabad stations. According to the results of the Mann-Kendall test, the display of consecutive dry days (CDD) showed a decrease of 8.5 days per decade at Abali station. But on consecutive wet days (CWD) the upward trends are not significant. The Daily Intensity Index (SDII) is also significant without trend. One day exhibition at Mehrabad station is a downward trend in the level of 90% confidence with the rate of 1.9 days in the last decade. In Abali station with confidence intervals (-0.08, -0.11) and Mehrabad station with confidence intervals (-0.09), the figure is zero. Therefore, in these stations, it has a thin sequence with finite torque that is close to producing a show.The study of growth curves showed that in the 34-year statistical period (1983-2016), most events in stations have a return period of 1 to 10 years. In higher return periods, fewer observations are consistent. The confidence bands of the growth curves also showed to some extent that the deviation of the POT model is less even in the return periods. But as the return period increases, the confidence interval increases. This indicates that as the period increases, the uncertainty in the results increases that the extrapolation of the data is in the range beyond the time frame of the statistical period under study (34 years). Reliable bands have shown that return periods of 1000 years are too unreliable to use in practical applications.ConclusionThe aim of this study is to investigate the changes in the intensity and frequency in Tehran province during the period 1983-1916. In this regard, the study of the initial trend of rainfall showed that in relation to the marginal rainfall, most of the backgrounds had a downward trend in the region. The study of the sequence behavior of events and the frequency and intensity of these events, using them, are higher than the thresholds that have increased in frequency in the study areas. The results of this part of the study are highly consistent with the work of Rahimzadeh et al. (2009) who reported negative trends for cold-bounded appearances and thresholds for precipitation and positive trends for warm-range indices in 27 synoptic stations in Iran. . Rahimzadeh and Hedayat Dezfuli (2011) also showed intensification of heating and decrease along with extreme fluctuations and temperature limit power in Hormozgan province and Mohammadi and Taghavi research (2005) increased the frequency of hot limit indices and cold limit index indices in the city. Has stated Tehran. Maroufi et al. (2011) have achieved similar results in studying the trend of borderline events in the northern and southern coasts of Iran. Also, the estimates and severity of precipitation boundary events using the mean time intervals between events (ARIs) indicate return periods of 1 to 10 years for boundary precipitation. Finally, the resulting Q - Q diagrams and Chi - square test (χ 2) showed that the POT model has great potential for modeling precipitation limit events in the study area.
Climatology
Zeynab Jawanshir; Khalil Valizadeh Kamran; Aliakbar Rasouly; Hashem Rostamzadeh
Abstract
Introduction
For the first time, Faddingham presented a geographic weight regression model. He tried to study the aspects of space heterogeneity. After that, Bronson examined the relationship between housing prices and areas. Which encountered a number of issues in relation to the model, which included ...
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Introduction
For the first time, Faddingham presented a geographic weight regression model. He tried to study the aspects of space heterogeneity. After that, Bronson examined the relationship between housing prices and areas. Which encountered a number of issues in relation to the model, which included the selection of variables, bandwidth and spatial correlation errors. Using the GWR, Franklin analyzed the spatial characteristics of the rainfall along with the elevation changes. Elvi also used this model to study the spatial factors that affect land prices. The GWR produces spatial information that expresses spatial variations between variables' relationships. Therefore, the maps produced from these analyzes play a key role in the spatial non-static description and interpretation of variables (Mennis 2006) and an equation Generates a separate regression for each observation instead of calibrating an equation, so it allows the parameter values to be continuously changed in the geographic space. Each of the equations is calibrated using a different weight of the observations contained in the total data. And more relative weights are assigned to closer observations and less or zero weights to those who are far away.
Data and Method
The Surface Energy Balance Algorithm for Land (SEBAL) calculates the surface heat flux instantaneously as well as 24-hour. The latent heat flux shows the energy required for true evapotranspiration and is calculated as the remainder of the equilibrium energy equation (Mobasheri, 2005). In remote sensing estimates of surface Albedo, surface temperature and surface leakage in the thermal infrared region, reflectance is used to calculate spatial variations in short-wave radiation and long-wave radiation emitted from the surface of the earth. A combination of short-wave and long-wave radiation combines the ability to calculate the pure absorbed surface radiation for each image pixel. Each of the equations is calibrated using a different weight of the observations contained in the total data. And more relative weights are assigned to closer observations and less or zero weights to those who are far away. In other words, the GWR only uses geographically close observations to estimate local coefficients. This method of weighting is based on the idea that the use of geographically close observations is the best way to estimate local coefficients. The GWR method not only does not consider the effects of self-variables on the independent variable, but also the effects of neighboring situations. The values of the geographic weighting model can be used to describe the spatial correlation of the factors used. Therefore, we extend the study area to several sections We divide the values of the geographic weight coefficients in each of the sections in relation to each of the environmental parameters. Unlike regular regression models, they provide an equation for describing general relationships between variables. GWR allows the parameter values to be changed continuously in the geographic space. Each of the equations is obtained using a different weight of the observations contained in the total data.
Results and Discussion
The analysis of the relationships between selected indices by geographic weighted regression model and the classification of output values through the normalization of data in seven categories. The values obtained vary between 1 and 1, and the smaller the index, the spatial disjunction is variable, and the larger it shows the presence of spatial clusters. It was found that all three indexes of evapotranspiration, surface temperature and vegetation index have cluster spatial pattern. Therefore, the null hypothesis is based on the spatial correlation itself, and as a result, three of the above indicators can be used for spatial analysis of the actual evaporation. Based on the correlation between the factors affecting the macroeconomic factors, the factor of vegetation index has the most effect on the magnitude of the spatial distribution in the studied area (53% with an area of 471782864 square meters). However, as the results are clear, this number is an overall number and covers the overall situation in the area. And does not refer to spatial features of the area. In the results of weighted regression, the effect of elements can be observed spatially. Accordingly, according to the geographic weighted regression method, the relationship between evapotranspiration and surface temperature was negatively affected and negatively affected. The relationship between dehiscence and vegetation index was studied in different years. The highest digit on the seventh floor is 13/99 and in the area of 266611500, which shows a high positive effect. The relationship between evapotranspiration and the Albedo shows the highest value in the first and second classes. The values of 18 and 10 in the area of 490428000 and 1170753300 m 2, respectively, show a very negative impact and a significant negative effect.
Conclusion
Geographic weighted regression method is a statistical method that is adapted to study local patterns. This method is, in fact, a technical technique that analyzes the relationship between spatial variables in a hypothetical unpopular space. In this research, we tried to express the effect of several indicators on actual evaporation. These indicators are not all indicators that have had an impact on actual evapotranspiration Because actual evapotranspiration is closely related to other climatic factors. Because of the unique ability of spatial weighted regression to identify and analyze the relationships between variables, it is recommended to use it in quantitative analyzes. The Z classes resulting from the GWR analysis of the actual evapotranspiration in different years have different states that indicate the spatial effect of the surface temperature in different conditions.
Climatology
Zeynab Jawanshir; Khalil Valizadeh Kamran; Ali Akbar Rasuly; Hashem Rostamzadeh
Abstract
Introduction Water management has always emphasized the need to abandon water storage in reservoirs and pursue a policy of limiting water consumption. Spatial-spatial information on evapotranspiration helps users understand the evacuation and depletion of water due to evaporation and establish the relationship ...
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Introduction Water management has always emphasized the need to abandon water storage in reservoirs and pursue a policy of limiting water consumption. Spatial-spatial information on evapotranspiration helps users understand the evacuation and depletion of water due to evaporation and establish the relationship between land use, water allocation, and water consumption. Evapotranspiration is the second element of the water cycle (after precipitation) and its accurate estimation on a regional scale is necessary to design appropriate management strategies. Evapotranspiration is a function of the amount of energy available for vegetation and its exchange. Because of this dependence, it can be estimated using the principle of energy conservation. Due to the limited number of meteorological stations in the country and the high cost of collecting ground data, the cost-effectiveness of the use of satellite data is one of its advantages, and the possibility of retrieving data from all levels of the region at one time is its next advantage. Having timely information makes horizontal monitoring of meteorological and environmental parameters possible. The ability of remote sensing to measure some terrestrial parameters has had an important effect on estimating actual evapotranspiration. The SEBAL model is one of the remote sensing algorithms that calculate plant evapotranspiration based on the momentary energy balance at the level of each pixel of a satellite image. The study area of the current research was the eastern cities of Lake Urmia. The reason for studying this section was the impact of recent droughts on these areas and the reduction of surface and groundwater, which has increased the need to manage water resources in these areas. Methodology In the first step of radiometric corrections, the amount of spectral radiance in the thermal band and at the next step, the reflectance in the visible bands, near-infrared, and short-wavelength infrared bands were calculated. As mentioned above, in the SEBAL model, actual evapotranspiration is calculated through satellite imagery and meteorological data is calculated using the surface energy balance. When satellite imagery provides information for its transit time, SEBAL calculates the instantaneous evapotranspiration flux for that time. Landsat 8 images for 2017-2016-2014-2013 years and meteorological data such as Minimum temperature, maximum temperature, dew point temperature, evaporation pan data, sunny hours, and wind speed were analyzed using ENVI 4.8 - Excel 2013- Arc GIS 10.3 software. Results and Discussion SEBAL is an image processing model that measures evapotranspiration and other energy conversions on the Earth's surface using digital data measured by remote sensing satellites that emit visible, near-infrared, and thermal infrared radiation. This method uses surface temperature, surface reflection, and normalized plant differential index (NDVI) and their internal relationships to estimate surface fluxes for different types of land cover. In this section, using the values obtained from latent heat flux and evaporation heat flux, first, the amount of instantaneous evapotranspiration for each pixel was calculated. Then, using Ref_ET software, the total 24-hour evapotranspiration was calculated and the daily evapotranspiration rate was obtained for the whole image. Conclusion The results showed that there was a good correlation between the values estimated by the remote sensing algorithm (SEBAL) and the FAO-Penman-Monteith method as well as the evaporation pan method. The difference between the amount of SEBAL and the FAO-Penman-Monteith method in the reference plant was less than 4.21 mm/day; the largest difference was related to the 22nd of October. In total, SEBAL and Penman-Monteith methods had an average absolute difference of 4.28 mm/day. According to the results of this study, it can be observed that using the SEBAL model, the actual evapotranspiration and water needs of crops and even orchards and rangelands can be calculated on a large scale. This case could prove the suitability of this model for estimating actual evapotranspiration at different levels of the farm and irrigation networks. Therefore, remote sensing has a very high potential to improve the management of irrigation resources in very large areas using various algorithms and providing an estimate of the amount of ET with minimal use of ground data. Using remote sensing technology and GIS, acceptable results can be obtained in estimating the actual evapotranspiration rate, especially in large areas. If the parameters of the energy balance equations and Penman-Monteith could be calculated from satellite images spatially, with a suitable plant coefficient, the two methods would have similar results in estimating the rate of evapotranspiration. Using this method, the plant coefficient, which is one of the important factors in calculating the evapotranspiration of plants, can be accurately determined.
Climatology
Majid Rezaei Banafsheh; saeid Jahanbakhsh; Shoaieb Abkharabat; Aliakbar Rasouli; Mostafa Karimi
Abstract
Introduction 120-day winds of Sistan are considered as one of the significant phenomenon which has a great impact on the morphology and environment of east and southeast of Iran (Figure.1). The common region for these winds is the border of monsoon region in south of Asia which mainly has sunny and cloudless ...
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Introduction 120-day winds of Sistan are considered as one of the significant phenomenon which has a great impact on the morphology and environment of east and southeast of Iran (Figure.1). The common region for these winds is the border of monsoon region in south of Asia which mainly has sunny and cloudless weather during monsoon period. This condition is due to lack of higher humidity divergence accompanied by tangible decrease of the air on the atmosphere (Salighe, 2010). These winds are the most famous advection system in northern hemisphere whose effects are visible in eastern regions of Iran, west and south of Afghanistan, and northwest of Pakistan(Khosravi, 2008). Data and Methodology In order to evaluate the role of the winds, data network of Geopotential height of 850 hPa (hectopascal) level during a 19-year period (1993-2012) from May to the end of September, the period of 120-day winds of Sistan, were found. These data were of those revisited data of 2.5*2.5 NCEO/NCAR during 2480 days. Then, factor analysis and clustering tests were applied on data network of Geopotential height to classify map patterns (Yarnal, translated by Masoudian, 2006: 100). As a matter of fact 5 clusters were recognized in this study presented in table 1. Dynamic method was used in GrADS software in order to find humidity flux of each region in the quintuplet patterns. Discussion Northern Wind Pattern (120-day wind of Sistan) As a matter of fact 120-day winds of Sistan are a part of northern Trade winds which are the most important source of Caspian Sea high pressure. After passing east of Iran, these winds reach Oman Sea and converge with southern Trade winds. Both of them moved toward Indian Subcontinent and finally enter atmospheric monsoon circulation of south of Asia. High pressure of north of Iran is also a tongue of high pressure Azores which is extended over northern regions of Iran and Caspian Sea by Mediterranean and Black sea Basin. Both existing Gang low during hot period of a year in south of Asia and spreading, its tongues over regions of Middle East make Azores high not be able to penetrate the zone in lower levels of atmosphere (from the earth surface to thelevel 850 hPa.). As a result, Azores high has to locate in northern parts especially north of Iran. Analyzing the curves of geo-potential height, figure (2) precisely shows this phenomenon. Gang low not only is weaken among middle levels of atmospheretongue, but also lost its appearance on Iran Plateau and Arabian Peninsula. Therefore, Azores high tongue also can locate in its normal position and appear with maximum pressure on Iran Plateau and Arabian Peninsula. Figure (3) presents the order of synoptic systems in level 500 hPa. of pattern 1. It shows that Gang low has lost its nature in this level, while Azores high tongue obviously is located on Middle East, especially Iran Plateau and Arabian Peninsula. As a matter of fact atmospheric levels of Geopotential height in pattern 1 (figures 2,3, 4) reveal that as we go away from lower levels of atmosphere to middle levels of atmosphere, Gang low gradually is weaken especially over Iran Plateau and Arabian Peninsula. This situation makes Azores high tongue locate in lower latitude. However, in lower levels (earth surface to level 850 hPa.), as a tongue of Gang comes into some parts of Middle East, expanded tongue of Azores high pressure has to locate on higher latitudes than normal latitudes; on north of Iran Plateau and Caspian Sea.Pattern (2) shows the same order as pattern (1), so it will not be repeated here. In the following, the effect of 120-day winds of Sistan on humidity of the region will be investigated, thus humidity flux is calculated between levels 925-1000 hPa. 850-925 hPa. and 850 -700hPa. Figure (5) shows sum of humidity flux for aforesaid levels of synoptic pattern (1). 120-day winds of Sistan with prevailing north direction in this pattern lead to the formation of a core of humidity flux divergence in east and center of Iran and decrease humidity of the region. As previously mentioned, after passing Iran, Sistan winds reach Oman Sea and north of Indian Ocean, and converge with southern Trade winds. Both of them move toward Indian Subcontinent. In fact, convergence of 120-day Sistan winds (northern Trade winds) and southern Trade winds leads to formation of a strong core of humidity flux convergence on Oman Sea and north of Indian Ocean (figure 5). The sum and average of humidity flux convergence and humidity flux divergence in studied region are presented in table (2). Eastern Wind Pattern The other clusters (3, 4, and 5) have different order from 120-day Sistan winds which are introduced as eastern wind pattern. Unlike clusters (1) and (2), in these clusters (table 1) the wind direction is not northern; in other words, the winds blow with prevailing east direction in east and northeast of Iran, however southeast of Iran experience mild weather at the same time. As synoptic order of pressure system and humidity flux system are mainly the same, pattern (3) will be analyzed precisely. The order of synoptic systems of level 850 hPa. in pattern (3) is presented in figure (5). This map reveals that the contrast between high pressure of north and Gang low differs from northern wind pattern, as on the one hand,the strength and breadth of Gang low increase, while on the other hand the strength and breadth of Azores high tongue (high pressure in north of Iran) decrease. In fact, this condition makes most regions of Iran Plateau in lower levels of atmosphere (1000 hPa, 925 hPa and 850 hPa.) be dominated by Gang low. Besides, this order of synoptic systems eliminates 120-day wind conditions of Sistan and make eastern wind conditions in east and northeast of Iran. Since the orders of synoptic systems of levels 925 hPa. and 1000 hPa are the same as level 850 hPa. they will not be presented here. The orders of synoptic systems in middle levels are different, as in level 700 hPa. Azores high tongue comes to Iran Plateau by Arabian Peninsula (figure 7). This layer of atmosphere is a transition layer from dominance of low pressure pattern in lower layers to high pressure pattern in middle levels and upper atmosphere. Moreover, in level 500 hpa. Azores high tongue dominates Iran Plateau and Arabian Peninsula with more power and breadth. The orders of synoptic systems of clusters 4 and 5 are the same as cluster 3. The sum of humidity flux divergence and humidity flux convergence of pattern 3 are presented in figure (9). In this figure, the core of humidity flux divergence, which covers eastern half and center of Iran, is omitted and a core of humidity flux convergence covers east and southeast of Iran. It can be said that both penetration of Gang low into Iran and lack of 120-day winds provide special conditions in which the zone of humidity flux convergence in north of Indian Ocean moves to southeast of Iran leading to moisture condensation. Conclusion In this study 2 patterns of synoptic systems of warm period in east and southeast of Iran were recognized. First pattern (northern wind pattern) makes 120-day winds of Sistan (cluster 1 and 2). In contrast to Gang low tongue, when high pressure of north of Iran and Caspian Sea are in strong mode, it provides the conditions for 120-day winds of Sistan. On the other hand,in contrast to Gang low tongue increasing its influence and spread over Iran Plateau, when the aforesaid high pressure rollbacks of north of Iran and it is weakened, 120-day winds of Sistan stop and second pattern (eastern wind pattern) starts. In this pattern the winds with prevailing east direction cover east and northeast of Iran (clusters 3, 4,and 5). High pressures of Caspian Sea and north of Iran are a tongue of Azores subtropical high pressure which has to move abnormally to higher latitudes due to coming Gang low into lower atmosphere layer. Since Gang low is an inter-tropical convergence zone moving abnormally to higher latitudes in south of Asia, 120-day winds of Sistan are part of northern Trade winds which are flowing from subtropical high pressure (Azores high tongue in north of Iran) to Gang low in south of Asia (inter-tropical convergence zone). After converging with southern Trade winds on north of Indian Ocean, they move toward Indian Subcontinent. 120-day winds of Sistan exclude the entranceof moisture from Oman Sea and Indian Ocean into southeast of Iran (figure 5). However, as 120-day winds of Sistan stop, a core of humidity flux is formed on southeast of Iran providing the entrance of moisture of water areas into southeast of Iran (figure 9). Generally, weakening of Azores subtropical high will help to provide rainfall conditions in southeast by 2 ways: on the one hand, as Azores high pressure is weakened, the influence of decent factors of this high pressure air in levels 700 hPa. and 500 hPa. decreases. As a result ascent conditions are provided in the zone, but on the other hand the weakening of subtropical high pressure in lower levels of atmosphere (1000 hPa to 850 hPa.) also makes expanded Azores tongue weaken and rollback over north of Iran and Caspian Sea leading to stop 120-day Sistan winds. This phenomenon provides appropriate condition to inject moisture from Oman Sea and Indian Ocean to southeast of Iran.
Reza Afrousheh; ali akbar rasoli; Davod Mokhtari; Tahereh Jalali
Abstract
Introduction Changes in occurrence and frequency of extreme events can have more severe and damage effects than changes in the average climatic characteristics (Choi et al, 2008). Therefore, it is important to study the variability and change the behavior of extreme atmospheric events. The main purpose ...
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Introduction Changes in occurrence and frequency of extreme events can have more severe and damage effects than changes in the average climatic characteristics (Choi et al, 2008). Therefore, it is important to study the variability and change the behavior of extreme atmospheric events. The main purpose of this paper is to investigate the temperature extreme events using the distribution of generalized extreme value distribution (GEV) and non-parametric methods in Kermanshah province. The results of this study can be effective in providing the necessary context for assessing the extent of vulnerability and adaptation methods and strategies to deal with it. Methodology The study area in the present study is Kermanshah province. Because to study the extreme events, the length of the statistical period should be long-term, so in this study, the data of Kermanshah synoptic station, which has a statistical period of 56 years (1961-2016), was used. First, the maximum and minimum daily temperature data for the study period were obtained from the Meteorological Organization of the country and after reconstructing the incomplete data, the quality of the data was checked. The data series were first analyzed by trend and then analyzed by frequency of boundary events. To study and analyze the trend of marginal events, the indicators presented by the National Climate Committee of the World Meteorological Organization and the Climate Change and Prediction Research Program, called ETCCDMI, have been used. In total, the group provided 16 main indices with a major emphasis on temperature limits that can be extracted from a series of recorded daily data (Zhang et al., 2006: 2014.( Results and Discussion Generalized Extreme Value Distribution The present study aimed to analyze the changes in temperature extreme events in the study period using generalized extreme value distribution in Kermanshah province. According to the statistics and information of meteorological stations, this region has a drastic change in terms of climate and is affected every year by dry days without successive rains on the one hand or sudden heavy rains on the other, with a sharp rise or fall in temperature. The results of the Maxima block methods showed that in the study area, the intensity and frequency of cold border events decreased and the intensity and frequency of hot border events increased. Warm nights mean an increase in the percentage of days when the minimum daily temperature is above 90 and hot days mean a percentage of days when the maximum daily temperature is above 90 . The incremental trend is the highest annual value of the minimum daily temperature at the 95% level. The slope of the trend line for the index is 0.04 C in the decade. Conclusion The results showed that concerning cold extreme indices such as frost days, ice days, cold days and nights, the direction of change is negative and with hot extreme indices such as summer days, tropical nights, nights and Hot days the direction of change is positive with a confidence level of 99 percent. Since the rate of increase of the minimum temperature was higher than the maximum temperature, the range of the day and night temperature in the region has decreased. Also, graphs of the values of minimum and maximum temperature polynomials in years of return T with a 95 percent confidence interval were plotted. According to the above diagrams, we can estimate the extreme values of the desired parameter for the specified return period.
Climatology
Hashem Rostamzadeh; Aliakbar Rasuly; Majid Wazifedoust; nasser maleki
Abstract
Introduction Floods are a natural occurrence that causes casualties, livestock losses and damage to buildings, facilities, gardens, fields and natural resources every year. Therefore, rainfall estimates have long been considered by researchers in various fields, and along with the advancement of science ...
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Introduction Floods are a natural occurrence that causes casualties, livestock losses and damage to buildings, facilities, gardens, fields and natural resources every year. Therefore, rainfall estimates have long been considered by researchers in various fields, and along with the advancement of science and the emergence of new technologies, many advances have been made in the methods of rainfall estimation and evaluation and validation to achieve the best method. In the last twenty years, there has been a lot of progress in rainfall estimation methods. This advancement is due to the possibility of using a lot of information from different parts of the world, better understanding of atmospheric phenomena, exchanges and atmospheric rotations, improving the performance of models, progress in various surveillance tools such as radar and satellite and computer power. The methods used to estimate precipitation, especially in the short term, have shortcomings and are generally based on numerical forecasting models or the use of empirical analyzes, which are usually not very accurate for multi-hour intervals, so the use of satellite data It has been recommended as a supplement to address this problem, and doing so could greatly help increase the accuracy of numerical models for rainfall estimates. Methodology The study used the physical properties of a cloud of five waves between 2011 and 2015. The data of the second generation of MSG meteorological satellite has good coverage on different regions of Iran. The satellite has 12 channels on the region and produces accurate products. Some of these products are in line with the physical properties of the cloud used in this study. These products are produced daily every 15 minutes and include cloud peak pressure (CTP), cloud peak temperature (CTT), cloud light depth (COT), thermodynamic cloud phase (CPH), and the volume of water in the cloud. Density (CWP) are the effective radius of cloud droplets (REFF) and cloud type (CT). Was obtained. The criterion for the accuracy of the calculations was the two MAE statistics Equation 1: Equation 2: Results and discussion In this study, TRMM satellite data was considered as control data. After receiving TRMM images in MATLAB software environment, programming was performed and precipitation data were extracted from NETCDF files. After extracting TRMM satellite data, Meteosat satellite products were prepared through the CMSAF database and their data were extracted using MATLAB software code. In the study of waves, the coefficient of determination in the GPR model was 0.72 in the experimental section and 0.77 in the training section. In the TD model, the determination coefficient is calculated in the experimental section 0.64 and in the training section 0.87. However, in the neural network model, the coefficient of determination is 0.68 in the experimental section and 0.72 in the training section. The results show a good relationship between the components studied. Investigating the Effects of Cloud Physical Properties: One of the methods for determining the effectiveness of each of the physical properties of the cloud in estimating rainfall is the sensitivity analysis method. After calculating the coefficient of determination and the error coefficient, the sensitivity of each of the physical properties in estimating the precipitation was performed by the method of calculating the sensitivity analysis. Sensitivity analysis was calculated for all waves. Calculations show that the cloud type is most effective, followed by the effective radius of the cloud droplets and then the optical depth of the cloud in the second and third positions, respectively. Among the physical properties studied, the lowest effect is related to the cloud phase. To investigate the relationship between the physical characteristics of the cloud and the amount of precipitation, five waves of pervasive precipitation were selected between 2011 and 2015. Rainfall data from the region's stations were extracted. In order to validate the TRMM data, a comparison was made between the precipitation data of the selected stations and the precipitation of this satellite. Metoost satellite products were used to extract the physical properties of the cloud. After extracting the data, the physical properties of the cloud were matched to the time scale of the data and evaluated using TRMM satellite rain as a control. Conclusion The selection criteria were such that the waves lasted for at least two days and covered the entire area. On the day of the operation, the precipitation information of the meteorological stations of the region was obtained and also the precipitation information of TRMM satellite was extracted. In order to validate the data of TRMM satellite, the information of meteorological stations was compared with TRMM precipitation and obtained the necessary correlation. In order to get a better result, the matching of numbers was done in terms of time scale. In the next step, using the meteosat satellite products, the physical properties of the cloud were obtained for all waves. Data were extracted at all stages for each pixel. Then the data correlation matrix was performed with three models of GPR, TD and MLPBR, the results of which are given in Table One. Due to the use of different models as well as the study of 8 physical properties of the cloud, the results show a high relationship between the components of the study, so that the coefficient of determination in the GPR model for the experimental and training sections was 0.7 and 0.77, respectively. These coefficients for the TD model in the experimental and training sections are 0.64 and 0.87, respectively. In the artificial network model (MLPBR), the coefficients obtained in the experimental and training sections are 0.68 and 0.72, respectively. The numbers obtained indicate a relatively good relationship between the components. Sensitivity analysis was performed. Sensitivity analysis results show that the cloud type feature has the greatest effect on precipitation and then the effective radius of cloud droplets and then cloud light depth are in the second and third positions, respectively. Among the physical properties studied, the lowest effect is related to the cloud phase.
Climatology
mohammad omidfar; Ali akbr Rasouli; Hashem Rostamzadeh; BEHROOZ SARISARRAF
Abstract
Introduction Considering the problem of continuous reduction of the water amount of urmian Lake, Identifying the distribution of rainfall in the basin area of Lake has a particular importance from the point of view of climate and hydrology. Doppler weather radar has an ability of the estimating of intensity ...
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Introduction Considering the problem of continuous reduction of the water amount of urmian Lake, Identifying the distribution of rainfall in the basin area of Lake has a particular importance from the point of view of climate and hydrology. Doppler weather radar has an ability of the estimating of intensity and the accumulation of daily rainfall with suitable spatial and diurnal resolutions. In current study, radar rainfall data, observed at the Sahand station, were evaluated with 10 synoptic weather stations data inside the Urmia Lake Basin exampling some of intensive rainfall events. The compared models show that among synoptic stations Tabriz, Shabestar, Sahand, Urmia, and Bostanabad have a best fit with radar daily rainfall productions, having high-quality conformity in northwest of the study area. In contrast, low level of agreements between two sets of radar has been observed in mountainous area. Due to the problem of continuous decreasing volume of Urmian lake water, accurate identification of the temporal distribution of rainfall can be very important from climatic and hydrological points of view. There are various ways to measure or estimate rainfall. Synoptic stations have a relatively low efficiency compared to radar and satellite due to their point and number limitation, relative to the area of the study area and other influential factors such as weather and human error. Tabriz Doppler Radar is one of the 12 radars of the National Radar Network of the Meteorological Organization of Iran, which works in the frequency band of Doppler C-type radars. The aim of this study was to investigate the efficacy and accuracy of radar-distance measurement tools in the study of heavy precipitation, which due to the infancy and lack of similar studies, the results can be used in future research. Methodology The accumulative precipitation data of synoptic stations in the studied area and the product of the daily accumulative precipitation of Tabriz Doppler radar, which is produced by the radar equation, by converting the echo-return intensity of precipitation, have been used. In this study, the data of accumulative precipitation of synoptic stations of the study area and the product of daily accumulative precipitation of Tabriz Doppler radar have been used. With the help of radar software, the product of surface precipitation intensity is produced in a 24-hour period and its temporal resolution is 15 minutes. Other product specifications such as start time, spatial resolution, and maximum distance, frequency of repetition of sent waves, name of the saved file, color scale of the data and the name of the radar site next to the product are listed. Radar accumulative rainfall on the most severe rainy day in Urmia Lake basin , the distance from the site of the radar site (concentric circles with a distance of 50 km from each other) and the location of the stations studied. Also, to compare the difference in estimation between radar and stations, error estimation indicators such as: mean error, absolute error mean, mean square error and Pearson correlation coefficient were used. Results and discussion The October 14 to 21, 2014 heavy rainfall in Urmia Lake basin has been studied by various radar products and among them 24-hour collective rain product, due to compliance with the cumulative rainfall data of stations, for 10 synoptic stations around Lake Urmia. Due to the collision of the waves with mountains, the topography of the area has a significant impact on the accuracy of radar estimation. They are considered invisible spots; these points causes a lot of errors (in some cases even up to 100%). Therefore, to compare radar data with the station, the accuracy of the separate precipitation estimate at different stations was examined. Conclusion The 24-hour accumulative precipitation comparison of the stations northwest of Urmia (for the cities of Tabriz, Sahand and Shabestar)with radar estimates on the days of heavy rains in October 2014, was highly consistent and the only difference in radar estimates on 20 and 21 days, was about 5 mm that less than Measured by synoptic stations. The correlation coefficient between the data is 0.996, which confirms the closeness of the measurement values of the two methods. The remarkable point in the chart is the significant difference and jump in rainfall on October 19 compared to other days. An examination of the graphs of the cities of Salmas and Urmia in the west and Bostanabad in the east of Urmia Lake shows less accurate but acceptable estimates of rainfall and differs. Conclusion: The comparative graph of rainfall in the Ajabshir city, despite its proximity to the radar site (50 km from the radar), shows a relatively large difference between the radar estimates and the stations. The most important cause of the error is the orientation of the southern Sahand Mountain. In moving to the more southern areas, the radar accuracy is lower, but the comparative rain chart of Ajabshir city, despite its proximity to the radar site, shows a significant difference. Overall, the results shows that: the southern regions, both due to the large distance from the radar and blocking effect of radar waves, almost all of the return waves are weakened from the targets and the radar estimates the amount of precipitation zero.
Climatology
ali akbar rasouli; elnaz ostadi; mohammad reza aziz zade
Volume 23, Issue 69 , December 2019, , Pages 87-103
Abstract
The consequences of climate change in drought areas such as Iran, temporal and spatial changes are the distribution and concentration of rainfall, which can affect water resources. On the other hand, increasing the concentration of rainfall can causing hazards such as floods . The importance of the issue ...
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The consequences of climate change in drought areas such as Iran, temporal and spatial changes are the distribution and concentration of rainfall, which can affect water resources. On the other hand, increasing the concentration of rainfall can causing hazards such as floods . The importance of the issue of distribution and concentration of rainfall has encouraged researchers to study in this regard. Concentration Index (CI) is a method which is used to study the distribution and concentration of rainfall. This study was performed to calculate and analyze 23 station daily precipitation concentration index in Northwest of Iran during 1951 to 2015. In this research range of CI values calculated between 0.57 for Khoy station to 0.67 for Maku station and average 0.61 for all station. CI map obtain from values Interpolation and showed that the Northwest part of the study area with Maku station depute, compared to other regions, especially in central areas such as Tabriz station is not uniformly distributed. Also Northwest area with an average of 0.61 compared with an average CI of Iran ( 0.64) is more evenly precipitation distributed throughout the year.
Climatology
khadijeh javan; ali akbar rasuli; mahdi erfanian; behroz sari sarraf
Volume 22, Issue 65 , November 2018, , Pages 83-100
Abstract
Rainfall is one of the most important elements to determine the climate. Therefore, it is important to estimate its value accurately. The main purpose of this study is the evaluation of the TRMM (Tropical Rain Measurement Mission) 3B42 rainfall estimates, an exponential model and conceptual cloud model ...
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Rainfall is one of the most important elements to determine the climate. Therefore, it is important to estimate its value accurately. The main purpose of this study is the evaluation of the TRMM (Tropical Rain Measurement Mission) 3B42 rainfall estimates, an exponential model and conceptual cloud model in Lake Urmia Basin. Therefore, this study focuses on the comparison of these methods to identify and select the most appropriate model for rainfall estimation in Lake Urmia Basin. The comparison are performed during the period 2007 to 2011 and the hourly rainfall, temperature, barometric pressure and dew point temperature, the three-hourly rainfall rate of TRMM 3B42-V6 at 0.25° resolution and thermal infrared images (TIR) of Meteosat 7 at six-hour intervals are used. The results indicated acceptable match of estimated rainfall with rain-gauge data. Comparison of three methods of rainfall estimation shows that exponential model has the determination coefficient (equal to 0.61). In addition to the high correlation, due to low levels of RMSE and MAE (respectively 1.58 and 1.01), has a good performance to estimate rainfall in this basin. Therefore, this model can introduced as the most appropriate model for estimating rainfall in Lake Urmia basin.
Hamid Ebrahimy; ali akbar rasoli; Davod Mokhtari
Abstract
Abstract Marand city is located in very dangerous zone in terms of seismicity status, Therefore the problem of temporary settlement and optimization of the population settlements in the occurrence of earthquake is very important. This study has been implemented with the aim of identifying and spatial ...
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Abstract Marand city is located in very dangerous zone in terms of seismicity status, Therefore the problem of temporary settlement and optimization of the population settlements in the occurrence of earthquake is very important. This study has been implemented with the aim of identifying and spatial modeling of temporary settlement area in order to manage the earthquake crisis. Eight effective criteria in modeling temporary settlement has been extracted by studying research theoretical foundations and using the opinions of experts, then by using two models; Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Inference System (FIS), the area with proper conditions for temporary settlement in earthquake disaster management was determined. By comparing the results from the two models Based on expert’s opinions and Feasibility, optimization and practical of the Suggested zones among the zones with very good condition in Fuzzy Inference system, 232723 square meters And in the Fuzzy Analytical Hierarchy Process Model 44995 square meters, are Confirmed by experts and have most proper condition. The results indicates more accuracy in results of fuzzy inference system In comparison with fuzzy analytic hierarchy process.
Climatology
Ali Mohammad Khorshiddoust; Ali akbar Rasouli; Ali Slajegheh; Mojtaba Nassaji Zavareh
Abstract
One of the important arguments in variability and climate change assessment is the accuracy of climatic time series analysis. Therefore time series to be used should be homogeneous. Annual and seasonal maximum and minimum temperatures of 5 synoptic stations that contain long time series have been assessed ...
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One of the important arguments in variability and climate change assessment is the accuracy of climatic time series analysis. Therefore time series to be used should be homogeneous. Annual and seasonal maximum and minimum temperatures of 5 synoptic stations that contain long time series have been assessed in this study. For so doing, we utilized direct and indirect methods. We used metadata through indirect method and absolute and relative standard normal homogeneity test through direct routine. Results showed inhomogeneity which was identified by statistical methods corresponding to metadata. Relative standard normal homogeneity test is more suitable than absolute standard normal homogeneity test in this concern. Assessment of homogeneity between annual and seasonal minimum and maximum temperatures indicates that the parameter of minimum temperature has more inhomogeneity in the data. Comparison of homogeneity results between temperature of warm and cold season reveals that the temperature is more stable during relocation and other changes in cold season than in warm season. Relocation of many stations was not proved to be the cause of inhomogeneity in annual and seasonal maximum temperatures.
Tahere Jalali Ansaroodi; Aliakbar Rasouli; Fatemeh Sarafrouzeh; Marzieh Esmaeilpour
Volume 19, Issue 51 , April 2015, , Pages 171-191
Abstract
In this paper, Nisan rainfalls of East Azerbaijan Province in the period of 1980 to 2009 were investigated. Initially changes of Nisan rainfalls trend were analyzed using the non-parametric Mann-Kendall test and Sen's estimator slope that are the most common methods of non-parametric tests. In order ...
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In this paper, Nisan rainfalls of East Azerbaijan Province in the period of 1980 to 2009 were investigated. Initially changes of Nisan rainfalls trend were analyzed using the non-parametric Mann-Kendall test and Sen's estimator slope that are the most common methods of non-parametric tests. In order to predict changes of Nisan rainfalls in the next years, ARMA time series model was used. The results indicated that according to non-parametric tests in the study period, time series of Nisan rainfalls have no trend in none of the stations except Azarshahr. After reviewing of different patterns of ARMA model, proportional model for each station was selected based on Akaike information criterion (ACI) and, the Nisan rainfalls in East Azerbaijan Province were predicted for next 10 years. The accuracy of models was confirmed based on normality tests for residuals of the model and RMSE
