Climatology
saeid Jahanbakhshasl; Behrouz Sari Sarraf; Hossein asakereh; soheila shirmohamadi
Abstract
Introduction Climate extreme events have expanded and intensified during the 21st century. Extreme precipitation event annually leads to severe damage in agriculture, environment, infrastructures and even the human loss. Therefore, identification of the behavior of such events is one of the pivotal aspects ...
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Introduction Climate extreme events have expanded and intensified during the 21st century. Extreme precipitation event annually leads to severe damage in agriculture, environment, infrastructures and even the human loss. Therefore, identification of the behavior of such events is one of the pivotal aspects of climatic change and the increase of information about extreme precipitation is tangibly necessary for the society especially with regard to those, living in the areas with high risk of flood. extreme precipitation events can be defined as significant deviations from the precipitation mean. As a result, to identify such precipitations, a criterion was needed to evaluate the rate of precipitation values’ deviation from mean. Importantly, given the different types of indicators and thresholds proposed for extracting extreme precipitation, choosing an appropriate threshold with climatology conditions of the study region which could also be capable of identifying extreme precipitation optimally in terms of amount and frequency, requires high precision. The present study aimed at identifying the extreme precipitation events in the west of Iran through introducing the appropriate threshold and spatial scale for the extraction and investigation of these events.Data and MethodsThe west of Iran with the areaof 230760 square kilometers includes about 14% of total area of Iran. Zagros Mountains, stretching from northwest to southeast, are the most important feature of the west of Iran. Two databases have been used in this study. The first database regardsthe precipitation data of 1129 synoptic stations, climatology and rain gauge in the west of Iran. The stations statistics have been checked in terms of existence of any outlier. Ultimately 823 stations out of 1129, were used for producing gridded data. The gridded data, are the results from the interpolation of daily precipitation observations since January 1st 1965 to December 31st 2016, using Kriging interpolation method and spatial separation of 6*6 kilometers. the final base, a matrix possessing the dimensions of18993*6410 (representing time on the rows and place on the columns) was developed. The second database referred to the Sea-level pressure patterns (Hectopascal).To identify such precipitations, in addition to the main threshold that includesthe mean of precipitation more than 75th percentile for each pixel per day of a year, a second threshold including the standard deviation of these precipitations (with the values of one, two, and three times more) has been also added to the mean. Accordingly, three groups of extreme precipitation were identified in the region which were separated according to the spatial zone that had been covered. Moreover, the sea-level pressure patterns were extracted with regard to these precipitations for each zone andthen classified using clustering analysis technique.Results and Discussionthree groups of precipitations with different coverage zoneswere identified: 1- 83 days with equal to or more precipitation than the mean of precipitations more than 75th percentile plus one time standard deviation which cover more than 40% of the region. 2- 144 days with equal to or more precipitation than the mean of precipitations more than 75th percentile plus two times standard deviation which cover more than 20% of the region. 3- 82 days with equal to or more precipitation than the mean of precipitations more than 75th percentile plus three times standard deviation which cover more than 20%The maps of 7 participation groups of the first type in comparison with 6 precipitation groups of the second and third type contain common and repetitive patterns. Each precipitation maps of the second and third types explains a type of patternand there is minimum overlapping in the maps. Therefore, the precipitations are obtained from the most particular and distinct atmospheric patterns. considering the three properties of 1- equality of precipitation groups of type two and three (both include 6 groups of atmospheric patterns). 2- repeating the atmospheric patterns of precipitation of type two prominently in the precipitations of type three. 3- the formation of the most optimum atmospheric modeling for the precipitations of both thresholds in the zones of 20% and higher, in the west of Iran, the extreme precipitations refer to those with higher means of recipitations more than 75th percentile plus two times standard deviations,have mostly occurred in the zone of 20% and higher of the region.
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
Daryush Yar ahmadi; Saeed Basati; Behroz Nasiri; Somayyeh Rafati
Volume 22, Issue 65 , November 2018, , Pages 301-321
Abstract
Consequences and threats of climate hazards and opportunities such as water resources, agriculture and other economic sectors has caused Convective systems of precipitation are considered in recent years. Therefore, in this study, the dynamic conditions of mesoscale convective systems in the months warm ...
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Consequences and threats of climate hazards and opportunities such as water resources, agriculture and other economic sectors has caused Convective systems of precipitation are considered in recent years. Therefore, in this study, the dynamic conditions of mesoscale convective systems in the months warm and cold and their accumulation convective precipitation is investigated. After obtaining Geostationary satellites images, Meteosat and GOES, the most comprehensive of mesoscale convective systems without merge and split with the brightness temperature threshold of 224 K and area thresholds were determined and through the RegCM4, dynamic behavior and their accumulation convective precipitation was investigated. The results showed formation location of systems has been in southern Iraq and northern Saudi Arabia. The systems flows pattern of cold months of the year has been affected by altitudes pattern. So that positive vorticity in the region has been created on the collision of the elevation. Also the cores of dynamic quantities has been weakened after Zagros Mountains in months of December- January. Vorticity and convergence has been in April convective systems stronger and more intense than the months of December to January.
Climatology
Aliakbar Shamsipoor Shamsipoor; Seyfolah Kaki; Ayob Jafari; Seyd Maysam Jasemi
Volume 22, Issue 64 , September 2018, , Pages 149-167
Abstract
The aim of the research is recognizing mechanisms of the heavy rainfalls in the west and southwest of Iran using synoptic and thermodynamic method. For analysis of case study at April 2016, At first was obtained and calculated hourly rainfall data from 70 weather stations in the research area and 10 ...
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The aim of the research is recognizing mechanisms of the heavy rainfalls in the west and southwest of Iran using synoptic and thermodynamic method. For analysis of case study at April 2016, At first was obtained and calculated hourly rainfall data from 70 weather stations in the research area and 10 weather stations bordering the research area. Then rainfall amounts in stations were calculated and zoned using Arc/Map10. After that Ki, Li, TTi, Cape and SWEAT instability indexes was calculated for Kermanshah and Ahwaz weather stations. Finally, the synoptic maps were analyzed. According to instability indexes, mostly atmospheric instability has been moderate and favorable conditions could be observed for convection and thunder storm, lightening and snow fall. The analysis of the sea level synoptic maps have shown that a few days before the rainfall, the study area has been under the influence of the Siberian high, and simultaneously cyclones centers were formed above the Mediterranean Sea. Their eastern-ward movements created the condition for instability and rainfall in the area. Cold air downfall from high-pressure centers toward the backside of the Mediterranean trough and lower latitudes beside the dislocation of warm humid air to the fore side of the trough created the front and resulted in intensifying the rainy system that finally resulted in heavy rainfall in the area. The atmospheric physical and dynamic indexes show that during the rainfall, voracity positive values, jet stream wind and negative omega figures were in their maximum.
Ali Mohammad Khorshiddoust; Gholam Hasan Mohammadi; Atefeh Hosseini Sadr; Khadijeh Javan; Abolfazl Jamali
Volume 17, Issue 46 , February 2014, , Pages 47-66
Abstract
The effective synoptic systems on dust events was investigated in the west of Iran based on observed dusty days at 50 meteorological stations using principal component analysis (PCA) and geographical information system (GIS). Results showed that the first 5 components explained 69.11% of spatial variability ...
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The effective synoptic systems on dust events was investigated in the west of Iran based on observed dusty days at 50 meteorological stations using principal component analysis (PCA) and geographical information system (GIS). Results showed that the first 5 components explained 69.11% of spatial variability of dust event variance. For detecting of affective synoptic systems, the computed correlation coefficient of stations with each component (Rotated Component Matrix) was transferred to the GIS environment, and synoptic patterns that affected spatial variability of dust events were simulated through Kriging interpolation method. It was shown that Azores high pressure system has the most effective role in frequency of days with dust in the west of Iran through the creation of surface thermal low pressures.
