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 ...
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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
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 ...
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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.
Yousef Zarei; Ali Mohammad Khorshiddoust; Majid Rezaeebanafshe; Hashem Rostamzadeh
Abstract
Climate change is one of the main problems on Earth today, so predicting these changes in the future and their impacts on water resources, the natural environment, agriculture, and environmental, economic and social impacts is of particular importance. Therefore, in the present study, the effects of ...
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Climate change is one of the main problems on Earth today, so predicting these changes in the future and their impacts on water resources, the natural environment, agriculture, and environmental, economic and social impacts is of particular importance. Therefore, in the present study, the effects of global climate change on different climatic regions of the country were studied in 12 climatic regions. In this study, NCEP data and climatic elements of precipitation, maximum and minimum temperature were used for statistical downscaling with SDSM model. And using the CanEMS2 model output under RCP scenarios for the three statistical periods of 2011-2040, 2041-2070, and 2071-2099 annual climate change data were obtained. Correlation coefficient, determination coefficient and error indexes of RMSE, MSE and MAD were used to evaluate the performance of the model. However, the results showed that the accuracy of the model was different at different stations. In this way, each model performs better than rainfall in simulating minimum and maximum temperatures. The annual long-run results also show that precipitation will decrease in all climates studied in the coming decades, with the largest decrease occurring in semi-warm (35%) and very humid and temperate (32%) desert areas. But minimum and maximum temperature variations will be different in different climatic regions so that under RCP scenarios during all statistical periods at Sabzevar and Tabas stations minimum temperature changes will decrease but in other climatic regions the trend of minimum and maximum temperatures will be incremental. The highest minimum and maximum temperature increases based on RCP scenarios under RCP8.5 scenario during the period 2071-2099 in the cold mountain climatic region will be 3.03, 4.27 ° C, respectively.
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 ...
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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.
All other Geographic fields of studies , Interdisciplinary
Mostafa Karimi; Sousan Heidari; Morteza sharif
Abstract
IntroductionIncrease temperatures and decrease rainfall can lead to the drying up of wetlands, lakes and rivers, the formation of aerosol centers, which directly and indirectly change the structure of society and the ecological conditions of lakes around the world; As a result, it leads to changes in ...
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IntroductionIncrease temperatures and decrease rainfall can lead to the drying up of wetlands, lakes and rivers, the formation of aerosol centers, which directly and indirectly change the structure of society and the ecological conditions of lakes around the world; As a result, it leads to changes in the distribution of animal and plant species, ecological diversity, changes in the plant phonological cycle, factors, growth and organisms, and ecological metabolism. These changes also severely affect vegetation in arid and semi-arid climates. Finally, changes in surface conditions caused by human activities may also affect various hydrological processes. Thus, the twenty-first century is facing many environmental problems, one of the most important of which is the variability of environmental and climatic parameters. Lake Urmia is one of the most important water areas in Iran and one of the largest salt lakes on earth. The lake plays an important role in the climatic, environmental and economic situation and a national and international natural heritage in the northwest of Iran.variability of environmental and climatic parameters is one of the most important challenges for human specific in arid and semiarid environment such as Iran. The purpose of this study is to investigate the changes in environmental and climatic parameters in the catchment of Lake Urmia in the last two decades. The purpose of the above was to answer the question of how the changes in environmental and climatic parameters in the basin and the relationship between these changes in the current conditions of the basin Lake Urmia.Data and methodsResearch data includes six categories: 1) TOPEX and Jason 1 to 3 satellites data to study of changes in altitude level of Lake Urmia, 2) Landsat 7 satellite images of 2000 and Landsat 8 of 2019 for extract lake water area changes and 3) Precipitation data from GPM[1] satellite product (IMERG[2]) 4) Vegetation index products of Modis sensor (Mod13A3 v006) to identify vegetation changes, 5) LST Night and daytime of Modis sensor (MOD11A2 v006) and finally 6) gridded reanalysis data (ERA5) to detect of trend air temperature, were used.First, the changes in the water level of the lake were extracted using the data of TOPEX and Jason 1 to 3 satellites, and in the next step, the trend of changes in its was calculated. Landsat 7 images of 2000 and Landsat 8 of 2019 using the Normalized Differential Water Index (MNDWI) were used to achieve changes in the lake's water area. Then LST (day and night) of MOD11A2 v006 products were converted into monthly data using MATLAB software. Finally, the trend changes in precipitation data, 2 m air temperature, LST (day and night) and vegetation (NDVI) were investigated using Mann-Kendall test (Mann, 1945; Kendall, 1975).ResultsThe highest changes in water level in the last two decades are from 2000 to 2010. The decrease in level is evident from the year 2000, from that year to 2010, the water level of the lake decreased by 4 meters and the highest slope of the decrease in it observed in the same period. The change in the area obtained from the MNDWI index is 2740 km2, which has caused the lake to decrease from 5143km2 to 2400km2 in 2019. The decrease of the lake level in its southern and eastern part has been more than the western and northern part. The trend of monthly precipitation changes shows two different temporal and spatial patterns. It is important to note that there is a monthly decreasing trend every three months in January, August and December in the central and southern parts of the basin. In contrast, in May and July, a marked increasing trend is observed in the eastern and southern half of the basin. Spatial displacement of incremental changes in air temperature indicates a clockwise movement from north to east and then south and west from May to August. The trend of day of the LST changes indicates a spatial contrast between the Lake and around it. This behavioral contradiction is more pronounced with the increase of the lake surface temperature and the decreasing trend in the southern and western regions corresponding to the agricultural areas in August, September and October. Changes in LST at the basin level from November to February, in which scattered and small incremental zones are observed, can also be due to reduced vegetation in the cold period of the year. In contrast to the daytime LST, at night what is most noticeable is large zones of temperature rise, especially from June to September throughout the basin. NDVI in the period 2019-2000 has had an increasing trend in all months, but with varying intensity and extent. Three temporal patterns are understandable in the process of basin vegetation change. Increased from January to May, then start decreasing trend from June to August and again increasing trend that continued until December. The lowest increasing trend is observed during the summer months from June to August.DiscussionLake Urmia has experienced a continuous decrease in water level since 2000, so that during the last twenty years, the water level has decreased by more than seven meters. The results of the present study also showed that there was a significant increasing trend in the NDVI index at the basin, especially with the southern of the basin. However, at the basin level, the trend of rainfall changes in this period (2000-2000) is not generally significant and also due to the occurrence of numerous droughts in the basin, which has also had an increasing trend and the expansion of irrigated lands, Demand for groundwater has increased. Therefore, this issue indicates various reasons other than changes in climatic parameters, especially precipitation in reducing the water level of Lake Urmia. In addition to the above, daytime and nighttime LST have increased during the warm period of the year as well as the air temperature on the lake. This increase increment evaporation, especially during periods when recharge is reduced due to seasonal dry. Although precipitation has increased at the end of spring, but with increasing temperature, precipitation increases with increasing evapotranspiration and water requirement of plants is neutralized. Therefore, the simultaneous change of environmental and atmospheric parameters can be considered as aggravating the conditions of hazardous events in this basin.ConclusionBased on the evaluation done in this study, it can be concluded that the basin of Lake Urmia is vulnerable. Therefore, the three main and significant effects of environmental variability in these areas are increasing ground temperature, vegetation and reducing water resources. The result of these conditions on the one hand and the increase of water needs of plants on the other hand will increase the stress on water resources, especially groundwater. Decreasing the lake surface and increasing consumption and reducing water resources can lead to the spread of bare surfaces and the occurrence of dust.
Climatology
Hossein asakereh; Seyed Abolfazl Masoodian; Fatemeh Tarkarani
Abstract
Introduction
According to previous investigation and examining climatic elements, the hypotheses of global warming and consequently, global climate change is confirmed by majority of climatologists society around the world. The global changes probably continue for the next decades. The changes in climatic ...
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Introduction
According to previous investigation and examining climatic elements, the hypotheses of global warming and consequently, global climate change is confirmed by majority of climatologists society around the world. The global changes probably continue for the next decades. The changes in climatic elements, by and large, categorized into two types; trends and variation. The trends refer to long term changes, whiles variations indicate vary time interval changes including oscillation, phase, jump (sift), and persistence.
Precipitation is one of climatic elements which can properly reflect chaotic behavior of climate system, and illustrate the nature of changes in the system. Trends, Oscillation, and persistence in this element are investigated in national and international scale, whilst the decadal variations as an index of climate variation can contribute to the current literature. In current study we attempted to illustrate an objective feature of precipitation characteristics and its anomalies over four recent decades by using Asfezari National Dataset (AND).
Data and Methods
In the present study, the gridded precipitation data of the third version of AND with spatial resolution of 10×10 km during the time period of 1970/3/21 to 2016/3/19 (46 years including 16801 days) is used. This dataset adopted from 2188 synoptic, climatology, and rain gauge stations and subjected to interpolation by using Kriging interpolation method. The dataset covers an area from N and E. Accordingly, a pixels cover the area for 16203 days. Consequently, the dataset includes dimensions.
General spatial features of Iran precipitation for the whole under investigation period was studied based on climatological annual precipitation. Next, the same characteristics calculated for four decades ending up to 2016/3/19. Finally, for every decade the anomalies of precipitation in compare with the whole understudy period and its previous decades calculated in order to discover the spatial pattern of decadal fluctuation in precipitation.
Discussion
General characteristics of annual precipitation
Annual mean of precipitation over Iran is 250.5 mm. Due to decline in temperature contrast and strength of fronts in the Mediterranean cyclones, as a main source of precipitation in Iran, the annual precipitation over Iran decreases from west to east, and from north to south.
The annual precipitation in 63.2% of Iran is lower than the climatic annual mean. The annual mean of precipitation in this area which generally located in east and south of the country is approximately 150.5 mm. Thus, the total precipitation in this area is equal to the total precipitation in the rest 36.8% of the country which its annual precipitation is more than the annual precipitation in the country, 422 mm. The spatial variation of precipitation is confirm by other statistics, for instance, skewness, kurtosis, the extreme threshold indices. For instance, a large part of Iran (26.73%) includes 100-150 mm annual precipitation, whiles the precipitation in 15.8% of the country reaches to 150-200 mm. Parts of northeast of Iran, and the coast of Persian Gulf and Oman Sea in the south, in addition to southern slops of Alborz mountain chain experience a precipitation amount of lower than 100 mm. In contrast to the above-mentioned dry regions, the (approximately) wet regions include limited areas for each precipitation class. For example, only 9.1% of the country characterized with 500 mm of precipitation, while the classes of 200-300, 300-400, and 400-500 comprise 20.62, 12.64, and 6.11 percents of the country, respectively.
Decadal variation of precipitation
In current section the spatial distribution and statistical features of precipitation in each decades was illustrated. The following list includes our finding of statistical - graphical analysis of precipitation in four successive decades:
1) The difference between spatial mean and median of annual precipitation increased from the first to the last decades. The increasing in this characteristic refers to increase in spatial asymmetrical distribution of precipitation over the country.
2) A comparison between spatial distribution of precipitation maps showed that generally, the areas experienced precipitation above the decadal and whole period average are decreased from the first and last decades.
3) The increase in spatial skewness from the first decade to the last decade is another evidence of increasing in precipitation spatial differences.
4) The last but not the least finding is the changes in the extreme threshold indices. From the first to the last decade, the range of 10th and 90th percentiles have increased.
Conclusion
Previous studies depicted that the amount of Iran precipitation has decreased over recent decades. In order to investigate the role of each decade in the decreasing values, the gridded precipitation data of the third version of AND with spatial resolution of 10×10 km during the time period of 1970/3/21 to 2016/3/19 (16801 days) is used. General spatial features of Iran precipitation for the whole under investigation period was investigated based on climatological annual precipitation. Next, the same characteristics calculated for four decades ending up to 2016/3/19. Finally, anomalies of precipitation in compare with the whole understudy period and previous decades calculated in order to discover the spatial pattern of decadal fluctuation in precipitation.
Our finding showed that by and large, precipitation has decreased over recent decades. The changes has been more pronounced in southern and northern coastal area, western slopes of Zagros mountain chain, and northern slopes of Alborz mountain chains. Previous researchers attribute these changes to changes in humidity advections in recent years.
Climatology
mehdi asadi; Ali Mohammad Khorshiddoust; Abbas Ali Dadashi Roudbari
Abstract
Introduction As the stations measuring precipitation continuously are not regularly available, the best solution should be to investigate the points without statistics using optimal methods. Among these methods, we can mention geostatistical methods. Geostatistical methods have been approved as appropriate ...
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Introduction As the stations measuring precipitation continuously are not regularly available, the best solution should be to investigate the points without statistics using optimal methods. Among these methods, we can mention geostatistical methods. Geostatistical methods have been approved as appropriate ways for studying precipitation data and estimating precipitation regions. Results of many studies have shown that geostatistical techniques are more accurate than conventional interpolation methods. Statistical context can also be used for precipitation variability. Accurate estimation of the spatial distribution of precipitation requires a dense and regular cell network. The spatio-temporal variation of precipitation is one of the most important issues of applied climatology, so the main purpose of this study is to monitor the spatio-temporal variation of precipitation in Iran in seasonal context by the application of the mentioned techniques. Data and Methods In this study, the common statistics of 125 synoptic stations in the country with the statistical period of 30 years (1980-2010) have been used. Also, the station data were generalized to the 15 km cell spaces using the Kriging interpolation method in ArcGIS 10.2.2 software. To speed up the computational process, the capabilities of GS + software were used to fit the variogram, and ArcGIS software was used to map the precipitation regions of the country. In order to study the pattern of precipitation, spatial autocorrelation techniques (local Moran and global Moran) were used. Also, the skewness coefficient (G1) and the peak degree coefficient (G2) were calculated separately for each of the months studied. Cluster and non-cluster analyses and hot spot method were used to study the patterns and spatio-temporal variations of precipitation. Cluster and non-cluster analysis, also known as Moran local Anselin index is an optimal model for showing the statistical distribution of phenomena in space (Anselin et al, 2009: 74). For cluster and non-cluster analyses for each complication in the layer, the value of the local Moran index score, which represents the significance of the calculated index, was also calculated. Results and Discussion The value of the global Moran index for all 4 studied seasons and the annual total is above 0.95, which indicates the pattern of high clusters of precipitation in the country at the level of 95 and 99%. However, the highest Moran index in the world with a value of 0.970356 is related to the winter. Statistics for each of the five decades studied are high, between 255 and 261. Therefore, based on global trends, it can be inferred that the annual changes in precipitation in the country follow a very high cluster pattern. Consequently, due to the high value and low value, the hypothesis of no spatial autocorrelation between data in each of the five decades can be rejected. If precipitation were to be normally distributed in space for different seasons in the country, the global Moran index would be -0.000139. Moran's spatial autocorrelation only determines the type of pattern. For this reason, to show the spatial distribution of the pattern governing the distribution of precipitation in Iran, local Moran has been used during the studied periods. In winter (36.56%) there was no pattern or in other words it lacked spatial autocorrelation. This amount increased by 1.14% for spring and reached 37.70. This amount has increased significantly in summer, so that it has increased by 47.04% compared to spring. It has reached areas with no spatial autocorrelation in autumn (41.92) and winter (36.56). LL precipitation patterns have been distributed in the five studied periods with values of 36.53, 0, 34.64, 35.31 and 38.29% in the country, respectively, and in the form of nationwide spots in the eastern, southeastern and central regions. Precipitation values with negative spatial correlation in summer had the highest value (84.74%) and the lowest annual average (35.06%). However, values with high rate or positive spatial autocorrelation in all five studied periods were limited to the northern regions of the country, the highlands of Alborz, Zagros and had significant fluctuations in some parts of the country. Local Moran Anselin statistics have been able to well determine the process of precipitation (Masoudian, 1390: 97) and the era of windbreak slopes as well as adjacent areas with climatic contrasts such as north-south slopes of Alborz and slopes of east-west Zagros. Due to the complexity of precipitation patterns in the country, spatial statistics can well explain precipitation patterns. The general results of this statistic (local Anselin Moran) indicate that the amount of rainy areas in the country has been reduced during five study periods. It should be noted that most of these reductions were related to the Zagros region, the southeast of the country and the northern regions of Khorasan. Conclusions Iran has special conditions in terms of precipitation due to its vastness with respect to latitude and longitude, the configuration of unevenness and exposure to air masses. The general structure of precipitation in Iran is affected by latitude, altitude and air masses, so that with the change of any of these factors, precipitation will also change. In other words, the general conditions of precipitation are a function of latitude and altitude, and other factors such as water areas and land cover, which are referred to as local factors, play a role in the formation of Iranian precipitation. In the present study, spatio-temporal analysis of Iranian precipitation has been done using a new method of spatial statistics. For this purpose, high and low clustering methods, local and global Moran, hot spots and cluster and non-cluster analyses have been used. The present study focuses on the assumption that precipitation in Iran follows a cluster pattern and the pattern of precipitation distribution is itself a function of internal and external conditions. To achieve this goal, the average seasonal and annual precipitation statistics of 125 synoptic stations in the country during the statistical period of 1980-2010 were used. Then, to apply the methods used in this research, the capabilities of GIS were used. The results of the global Moran method and the K-function of some distances showed that the annual changes in precipitation in Iran follow the pattern of high clusters. According to spatial autocorrelation analyses, the areas with negative spatial autocorrelation in all studied periods are related to the southeast, the coasts of the Oman Sea to Abadan and parts of the northeast of the country. Areas with positive spatial autocorrelation were often located on the southern shores of the Caspian Sea and the Zagros strip. In all the studied periods, less than one quarter of the country's area lacked a significant spatial autocorrelation pattern. Spatial analyses showed that Iran's precipitation patterns are divided into two precipitation spots of southern tabs (low precipitation spot LL), and Caspian coasts west and northwest (precipitation spot HH). The results also indicated that during the period under study, low precipitation spots (negative spatial autocorrelation) had much more frequency than precipitation spots.
Climatology
mahdi narangifard; mehran fatemi; abdolali kamaneh; mohammad sadegh talebi
Abstract
Introduction Recently, issues raised by changes in precipitation, especially problems brought about by floods and droughts, along with the environmental effects of diminished rainfall, have underscored the importance of precipitation studies at different temporal and spatial scales. Due to the pervasive ...
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Introduction Recently, issues raised by changes in precipitation, especially problems brought about by floods and droughts, along with the environmental effects of diminished rainfall, have underscored the importance of precipitation studies at different temporal and spatial scales. Due to the pervasive impact of precipitation parameter in various urban, industrial and agricultural fields with respect to water supply, the identification of fluctuations, changes and precipitation structure is of particular importance, especially in arid and semi-arid regions. The similarity feature in climatic variables allows the use of fractal geometry and analysis of temporal and spatial changes. Accordingly, the use of fractal geometry in predicting the behavior of many natural processes, including precipitation in different regions, has a special place. The goal of this study is to investigate the structure of different time periods of precipitation in Shiraz synoptic stations to explore changes and determine the spatial position of precipitation in the stability and instability period. Methodology In this study, daily precipitation data was received over a period of 58 years (1956-2013) from the Meteorological Organization of Fars Province to investigate the structure governing precipitation parameter. Then, statistical deficiencies were corrected by restructuring using difference ratio and linear regression. The methodology and algebraic logic of calculations in this study are such that in the first step, research parameters are arranged from minimum to maximum in an ascending order. Then, based on the triangular threshold coordinates(2Π), the minimum and maximum were extracted based on linear structures of the desired criteria and algebraic mathematical reference was conducted using Relation (1). Relation (1) F (x) = Then, in order to apply the fractal structure by applying the criterion for mathematical reference using Relation (2), the real structure of the desired meteorological parameters was obtained. Relation (2) Y = m2 × sin (1/m) Finally, by overlapping the output charts of the actual structures and the classical structure of the fractal (Figure 2) in the algebraic ranges of -0.4 to +0.4, the algebraic process of each climatic parameter was evaluated separately. Results and discussion In this study, based on the results, in addition to the daily analysis of the governing structure of precipitation over a 58-year period (1956-2012), which covered 21185 days, the governing structure along with the analysis of equilibrium dynamics of structures and its functions in three time periods (three 20-year periods) of different daily precipitation were also examined separately. The first period began in January 1, 1956 and lasted for 7065 days. The relevant calculations were performed on the data derived from the first period, which based on the findings of this study, precipitation in Shiraz''s synoptic stations do not follow the fractal logic in the first period by applying fractal algebraic structures, Also, in the second period, similar to the first one, the precipitation structure does not comply with a particular fractal logic. In other words, the logic governing precipitation parameter during the first and second periods changes from equilibrium to non-equilibrium. However, unlike the previous two periods, the fractal logic is followed in the third period. Conclusion The self-similarity feature in climatic variables allows the use of fractal dimension and analysis of temporal and spatial changes. Accordingly, the use of fractal geometry in predicting the behavior of many natural processes, including precipitation in different regions, has a special place. The goal of this study was to investigate the structure of different periods of precipitation in Shiraz synoptic station to identify changes and determine the spatial position of precipitation structure in the period of stability and instability. The behavior of meteorological parameters in various parts of the world is a function that never follows uniform algebraic structure. Therefore, the analysis of complex systems and changes in nonlinear climate parameters using chaotic, fractal and fuzzy concepts offers a suitable way to understand the equilibrium state and dynamic analyses of climate fractal changes. The results indicate the dynamic transition of this time period from non-equilibrium to equilibrium. Therefore, according to the three time periods, the equilibrium dynamics of the daily precipitation structure approaches fractal structure.
Climatology
Mostafa Karimi; Faramarz Khoshakhlagh; ali akbar shamsi por; fahimeh noruzi
Volume 23, Issue 69 , December 2019, , Pages 233-255
Abstract
Large-scale circulation patterns are controlling climatic conditions and especially precipitation of the area. The purpose of the study is investigating the relationship between circulation patterns of Arabian subtropical anticyclone and Iran precipitation. For this reason, was used re-analysis data ...
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Large-scale circulation patterns are controlling climatic conditions and especially precipitation of the area. The purpose of the study is investigating the relationship between circulation patterns of Arabian subtropical anticyclone and Iran precipitation. For this reason, was used re-analysis data of geo-potential height form European Center for Medium-Range Weather forecasts (ECMWF), with spatial resolution of 1*1 degree and correlation distance cluster analysis. Circulation patterns at 30 to 80 degrees the East longitudes and5 to 30degrees north latitudes and the period of11years (2000- 2010) was calculated. The results showed that the patterns in terms of occurrence were divided the patterns of the cold period, the warm period and the transition period. During the cold period anticyclone is located at down latitudes on the Arabian sea and Gulf of Aden and have precipitation more areas of Iran that maximum amount of precipitation is related to the second pattern. In the patterns of transition period Arabian anticyclone sent a southwest clockwise current in to the trough East Mediterranean is effective in the occurrence of precipitation in the area of North and Northwest of the country. In the patterns warm period the anticyclone caused the anticyclone conditions on country and has been as a barrier to entry precipitation systems.
Climatology
Mohamad Saligeh; mohammadhosain naserzadeh; ali ghaffari
Volume 22, Issue 64 , September 2018, , Pages 129-147
Abstract
The mechanisms of climbing rainfall in different areas follow different patterns. Identification of those patterns can increase the environmental planning .The stability indicators which are known as instability indicators are relations through which we can study the amount of instability ...
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The mechanisms of climbing rainfall in different areas follow different patterns. Identification of those patterns can increase the environmental planning .The stability indicators which are known as instability indicators are relations through which we can study the amount of instability of convection of the atmosphere in any area for studying and predicting falls. These indicators are used for convection activities and basically are studied by thermodynamics diagrams and Radio sounds data. The main aim of this paper is studying the chronological features of precipitations over 5 mm .and determining convection precipitation parts of Tabriz spring station based on higher layers of atmosphere . the Tabriz station precipitation data were received from the weather organization cartulary regarding the 35 – year statistic periods and precipitation data for over 5 mm .were chosen while the time frequency was studied . After choosing the samples, the skew – T diagrams of precipitation days inadittion to the instability indicators such as (LI -TT – SI – KI – PW - CAPE)were analyzed . The processing of these data in seasonal scale indicate a frequent happening of those instabilities. The maximum occur once of the precipitations for the April with 131 frequency cases and minimum of this precipitator is in June with 35 cases were observed .The results of drawing skew – t diagrams and measuring the instability indicators show that the role of convection factor is important in spring precipitations because the convection factor is only the main factor not only the amount of convection is critical but also the needed instability for rain is provided. In general, after studying 263 rain samples in spring , it turned out that the convection factor has the most important role in rain occurrence in May and June and the hazards of flood threaten the area .
Climatology
amanollah fathnia; hamid rahimi; Shoaieb Abkharabat
Abstract
Siberian high pressure (SHP) is synoptic system that during the autumn and winter seasons on Asia is religious (Msaudian and Kaviani, 2009: 15). In the cold term of the year, the vast Siberian territory due to the clear sky and away from water sources, the more energy through the long wave radiation ...
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Siberian high pressure (SHP) is synoptic system that during the autumn and winter seasons on Asia is religious (Msaudian and Kaviani, 2009: 15). In the cold term of the year, the vast Siberian territory due to the clear sky and away from water sources, the more energy through the long wave radiation loses, thereupon the around air of land gradually adjacent to becomes cold high-pressure center.
Mohamad Darand; Behrooz Ebrahimi
Abstract
To doing this research daily precipitation data from 162 synoptic, climatic and rain gauge stations in and out of province during 21/3/1961 to 31/12/2012 extracted from Kurdistan Regional Water Company and meteorology organizations. By geostatistic Kriging method daily precipitation interpolated on 6×6 ...
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To doing this research daily precipitation data from 162 synoptic, climatic and rain gauge stations in and out of province during 21/3/1961 to 31/12/2012 extracted from Kurdistan Regional Water Company and meteorology organizations. By geostatistic Kriging method daily precipitation interpolated on 6×6 kilometers and one digital map has been created for each days. Then data over province on the 811 pixels that covers whole of province extracted. A database was created in dimensions of 18914×811with time (day) on the rows and pixels (place) on the column. The average, high and low hresholds and standard deviation of waiting time duration calculated for each pixel during different months. To detection thresholds the t-student test has been applied. The thresholds calculated in 99% confidence level. The results showed that Mountains features have important effects on precipitation waiting time duration. The different precipitation waiting time duration observed over Kurdistan province during different months. The distribution of precipitation waiting time during the different seasons of the year shows route of Rain-bearing systems on Kurdistan province. In total, the cores of minimum precipitation waiting time are located on the North-West of province in spring, on the North and North-East of province in summer, and on the North-West and West of province in autumn and winter. The shortest and most prolonged precipitation waiting time is related to the months of February and September respectively. In February on the part of the western and northwestern parts of Kurdish province precipitation waiting time duration is about 3 days. While waiting period in September on the mentioned areas is more than 60 days.
Climatology
Bohlul Alijani; Ali Bayat; Mehdi Doostkamian; yadollah Balyani
Abstract
Precipitation is one of the most essential and variable climate components whose understanding has long been a concern for climatologists. The main objective of the current paper is to investigate and analyze the precipitation cycles in Iran. In order to realize this objective, the annual precipitation ...
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Precipitation is one of the most essential and variable climate components whose understanding has long been a concern for climatologists. The main objective of the current paper is to investigate and analyze the precipitation cycles in Iran. In order to realize this objective, the annual precipitation data of isometric station of Iran were extracted. These data have been collected by the country’s meteorological organization since the establishment of the station until 2008 which adds up to more than 40 years of statistics. Then, in order to investigate and analyze the precipitation cycles, spectral analysis (co-structural analysis) was utilized. Regarding the calculations, the programming utilities of Matlab were used and the Surfer software application was exploited for drawing operations. The results obtained from analyzing the cycles show that there are significant 2 to 3 year cycles, 3 to 5-year cycles, 2 to 6 year cycles and sometimes 11 or more- year cycles governing Iran’s precipitation patterns. Hence, in east and southeast of Iran, 3 to 5-year cycles are prevailing and in west and northwest 2 to 3-year cycles are dominant and finally in north east 2 to 6-year cycles are customary. The most numerous and the most variable cycles happen in south and south east, mainly due to the mountainous regions of Zagros as well as the proximity to Persian Gulf. The north western regions, much like the southwestern regions, indicate variable cycles due to the mammoth mountains of Sabalan and Sahand. Moreover, the presence of those cycles which have a return period equal to the statistical period has been seen in various parts of Iran, which indicates a precipitation trend in this country.
Climatology
nahideh Jahedi; mohammadali Ghorbani
Volume 19, Issue 52 , June 2015, , Pages 63-63
Abstract
Being aware of decreasing or increasing trend of precipitation and discharge in watersheds has very important role in water resources management and the subjects relating to water engineering. In this study, the trend of precipitation and discharge at Qara-su River Basin in Ardebil has been studied in ...
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Being aware of decreasing or increasing trend of precipitation and discharge in watersheds has very important role in water resources management and the subjects relating to water engineering. In this study, the trend of precipitation and discharge at Qara-su River Basin in Ardebil has been studied in monthly, seasonal and annual timescales over the period from 1351 to 1382. For investigation of the existence or absence of a trend, Mann-Kendall test was used by detecting effects of all auto correlations coefficients, and Sen’s estimator was used at different significant level to evaluate the magnitude of the test. The results of the calculated values for precipitation and discharge data set indicated that the trend of the Qara-su River discharge was decreasing for both stations in annual timescale. Also, decreasing trend of discharge dataset was found for seasonal timescale in spring, autumn and winter in which significant trend belonged to winter season. Maximum value of decrease for discharge is for Doustbiglo station in spring (-0.62 m^3/s), and the minimum value of decrease for discharge in summer for this station, too. Furthermore, there was not significant trend for precipitation dataset in monthly, seasonal, and annual timescales.
Javad Behmanesh; Nasrin Azad Talatape
Volume 19, Issue 51 , April 2015, , Pages 41-58
Abstract
One of the atmospheric cycle properties is climatic changes which can cause the fluctuations in meteorological parameters. These fluctuations in many world regions are considerable and water and soil resources are affected by them. To prepare against undesirable effect of climate change and adopt suitable ...
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One of the atmospheric cycle properties is climatic changes which can cause the fluctuations in meteorological parameters. These fluctuations in many world regions are considerable and water and soil resources are affected by them. To prepare against undesirable effect of climate change and adopt suitable development programs and water resources management, it is necessary to investigate the meteorological variable changes. The objective of this research was to investigate the climate change in Urmia region. In this research, the changes trend of temperature, precipitation, relative humidity, sunshine and potential evapotranspiration were studied. To achieve this goal, Urmia synoptic station daily data with 40 years period (1971-2010) were used. The Mann-kendall statistical test at confidence level of 95% was used to investigate the significance of trend in the mentioned parameters. The results showed that the trend slope of maximum, minimum and average of temperature was positive and this trend in 95% confidence level was significant. Urmia precipitation was decreased with slope of -2.26 so that this decrease was significant. The sunshine had positive slope and significant trend, but the negative trend of relative humidity and the positive trend of potential evapotranspiration (0.0068) were not significant. The monthly investigations showed that the average temperature in all months had positive slope, but this slope was not significant in all months. The other parameters in some months had positive or negative slopes.
Ali mohammad Khorshiddoust; Ali asghar Shirzad
Volume 18, Issue 49 , November 2014, , Pages 101-118
Abstract
In this research we used multivariable statistical methods (cluster and discriminative analysis) with the purpose of the recognition of spatio-temporal differences of precipitation in similar areas. We used monthly precipitation of 35 synoptic, climatic, and rain-gauging station data records of Northern ...
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In this research we used multivariable statistical methods (cluster and discriminative analysis) with the purpose of the recognition of spatio-temporal differences of precipitation in similar areas. We used monthly precipitation of 35 synoptic, climatic, and rain-gauging station data records of Northern Iran including three provinces of Golestan, Guilan, and Mazandaran for 1995-2007 periods. For grouping and homogenizing the stations, we initially applied Ward cluster analysis method. Then we used discriminative analysis and Wilk’s Lambda for finding out the validity of cluster analysis calculations. Results obtained from cluster analysis with Euclid interval method indicated that 4 major clusters can be drawn according to the amount and the location of the precipitation in the study area. Discriminate analysis showed that 82.3% of the clusters in our analysis were valid and about 17.7% were incorrect. The Wilk’s Lambda method also proved the differences between the means.
Hossein Asakareh; Ali Bayat
Volume 17, Issue 45 , November 2013, , Pages 121-142
Abstract
Principal Component Analysis (PCA) is an optimum mathematical method to decrease variables into some limited components in order to justify the highest variance of primary variables. In this study some statistical characteristics of annual precipitation of Zanjan city including sum of annual precipitation, ...
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Principal Component Analysis (PCA) is an optimum mathematical method to decrease variables into some limited components in order to justify the highest variance of primary variables. In this study some statistical characteristics of annual precipitation of Zanjan city including sum of annual precipitation, number of rainy days, extreme daily precipitation in a year, the ratio of extreme precipitation to the sum of annual precipitation and some characteristics such as Standard Deviation (SD), Skewness (Sk), Kurtosis (Ku), Absolute Mean Deviation (AMD) and Mean Absolute Interannual Variability (MAIV) were was calculated from monthly precipitation for each year, and were introduced principal component analysis technique. The results show that 95% percent of annual precipitation variations can be explained through 4 components. The first component which indicates the highest data variance (42.6%), represents annual precipitation and absolute variability indices including SD, AMD and MAIV. The second component represents the shape of frequency distribution indices (Sk, Ku), the third component represents extreme precipitations and finally the fourth component represents the number of rainy days. The analysis of the trend of components scores show that first and fourth components scores have a significant decreasing and increasing trend, respectively. Round a lines show a precipitation decrease during the period under study from one hand and having uniform temporal distribution on the other hand.
Hossein Babazadeh; Saeadamir Shamsniya; Fardin Bostani; Elnaz Norozyaghdam; Davood Khodadadydehkardy
Volume 16, Issue 41 , November 2012, , Pages 23-47
Abstract
Stochastic models have been used as one technique to generate scenarios of future climate change. Temperature and precipitation are among the main indicators in climate study. The purposes of this study is analysis of the status of climatic parameters of monthly precipitation and mean monthly temperature, ...
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Stochastic models have been used as one technique to generate scenarios of future climate change. Temperature and precipitation are among the main indicators in climate study. The purposes of this study is analysis of the status of climatic parameters of monthly precipitation and mean monthly temperature, years of drought and years of wetness due to precipitation deficiency, simulation and forecasting using stochastic methods. In this study, the 21 year data on the precipitation and mean monthly temperature at shiraz synoptic station are used and based on ARIMA model, the autocorrelation and partial autocorrelation methods, evaluation of all possible models regarding their invariability, examination of parameters and types of model, the suitable models for prediction of monthly precipitation: ARIMA (0 0 0)(2 1 0) 12 and for forecasting of the mean monthly temperature: ARIMA (2 1 0)(2 1 0) 12 were obtained. After validation and evaluation of the model, the forecasting for the agriculture years 2008-09 and 2009-10 were made. In view of the forecasting made, despite of a continuing drought, it is likely that the precipitation will improve. As regards the mean monthly temperature, the trend of increasing temperature, especially in recent years, has continued and the findings of the forecasting show an increase in temperature along with a narrowing of the range of variations.
Swywd Hossein Mirmousavi; Mina Mirain
Volume 16, Issue 38 , February 2012, , Pages 153-178
Abstract
Ggiven that assessment data often point to be made, are necessary to generalize to the entire region, Interpolation operation have been done on areas of precipitation. In this study using Kriging and inverse weight method, interpolation of rainfall in KermanProvince has been attempted. For this purpose, ...
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Ggiven that assessment data often point to be made, are necessary to generalize to the entire region, Interpolation operation have been done on areas of precipitation. In this study using Kriging and inverse weight method, interpolation of rainfall in KermanProvince has been attempted. For this purpose, the monthly rainfall statistics for 9 synoptic stations in Kerman province and 11 synoptic stations neighboring provinces have been used.
The results of this study indicate that Kriging method with lower error levels is more appropriate for the interpolation of rainfall in this region. Models based on fitted Semivariogram models, Spherical, linear and exponential models provide better facilities for the preparation of a precipitation isomap. Between models in the spherical model for the months January to June and also in December, the exponential model for the month of July and the exponential model for the months August to November show the most appropriate change model views that are detected. Based on maps prepared for different months, while the highest rainfall occurred in winter time change the amount of the highest range 42-13 mm in the season. Spatial gradients of changes in precipitation decrease trend are from south to north. Other seasons in the low average range of precipitation changes also showed no significant fluctuations.
