Thunderstorm is one of the most severe atmospheric disturbances in the world and also in Iran, which is characterized by rapid upward movements, abundant moisture, and climatic instability. Since this phenomenon is usually accompanied with hail, lightning, heavy rain, flood and severe winds, it can cause irreparable damage to the environment. Investigation of spring thunderstorms has a great significance regarding the irreparable damages can cause by them and also because of the higher frequency of this phenomenon in the spring and the necessity for preparedness and disaster mitigation actions. To identify the locations of the major thunderstorm risk areas, the entire country with an area of 1648195 square kilometers, which is located between the 25°-40° north latitude and 44°-63° east longitude is considered. Spatial distribution of the occurrence of hazardous spring thunderstorms was analyzed using a series of monthly thunderstorm frequency data obtained from 25 synoptic stations over a 51-year-long period (1960-2010). Ward's hierarchical clustering and Kriging methods were used for statistical analysis. Initially, total number of thunderstorms in April, May and June were considered as the frequency of occurrence of thunderstorm in different stations in the spring. Measure of central tendency and dispersion which consists of the sum, minimum, maximum, range and coefficient of variation, standard deviation, and skewness were used to clarify the changes of thunderstorms and to determine the spatial and temporal climatic distribution of spring thunderstorms. An appropriate probability distribution function was chosen to determine the distributions of the data. Due to the large volume of data and the uneven distribution of stations, cluster analysis and kriging methods were used to classify different regions into homogeneous groups for zoning and spatial analysis of spring thunderstorms, respectively. The statistical characteristics of spring thunderstorms were reviewed and fitted with a 3-parameter Weibull distribution. Regions considered for this study were classified in four separate clusters according to the simultaneity of thunderstorms in the spring. After zoning, it was found that the highest rates of thunderstorm took place in the northwest and west of country. The northeast of Iran has the second highest number of thunderstorm occurrence. The least number of thunderstorm event had happened in the central and southern half of the country. According to the descriptive statistics parameters, maximum number of thunderstorms occurred in May.. Based on the results of the cluster analysis, there is a similar trend in the central and eastern regions, the rest of the country was clustered into five distinct homogeneous regions, including the northwestern, western, southern, northern, central northern and northeastern regions. Zoning results indicate that the highest number of the occurrence of this phenomenon in the country is concentrated in the northwestern and western regions. Higher frequency of occurrence of thunderstorms in the northwestern and western regions may be attributed to local topographic conditions like high mountains, orientation of the terrain, solar radiation on slopes and existence instability conditions, hillside convection, the presence of water resources and specific climatic conditions in these areas. In addition, as a result of a continuous surface obtained by the method of interpolation with the least amount of systematic error and also the use of correlation functions for recognizing the spatial structure of the data and estimating the model error when using the Kriging method, the weights are chosen in order to have a more optimized interpolation function. Also the cluster analysis may significantly reduce the volume of operation without affecting the results and will help in finding a real band due to more appropriate classification of different geographic areas with greater spatial homogeneity and minimal variance within the group. Based on the results of the spatial analysis, it is clear that Kriging and Ward cluster analysis methods are appropriate for thunderstorm zoning and classification of different regions according to occurrence of thunderstorm, respectively.
Climate is one of the important natural factors that affect all stages of life, particularly human exploitation. Selection of the type of clothing, housing, cultures, architecture, civil engineering, and settlements are influenced by climatic factors. It can be said that the climatic circumstances of the surface of the earth and atmospheric circulation patterns have an important role in shaping and organizing the environment (Alijani, 2009). In some cases, the normal weather conditions become abnormal and cause many damages, which are mostly catastrophes rooted in climatic changes, such as hail, frost, heat and cold waves, floods, storms and so on. Blizzard is one of the atmospheric phenomena, which happens as the result of snow combined with wind (15 meters per second), and low temperatures (below zero°C), and it causes severe losses.
Due to its special geographical location, Iran is placed in the transition region of the large-scale patterns of common tropospheric circulation, and is the intersectional place of the of extra-tropical and tropical circulation system. This feature along with its complex topography caused the land to have a considerable climatic diversity. The climatic diversity makes the various climatic phenomena to be observed with intensity, energy, and different frequencies, therefore, the climatic phenomena with high intensity always causes damage to natural resources and the human civilization. This undesirable phenomenon is called climatic risks. Since the West Azerbaijan Province is located in mountainous areas and high latitudes, the feature is triggered many climatic risks such as flood, hail, snow, snow storm, and so on. Therefore, snowstorm is one of such phenomena that have occurred every year or every few years due to the specific characteristics of the region and have caused damages in the fields of transportation, energy, livestock, closeness of schools and offices.
The purpose of this study is the statistical and synoptic analysis of snowstorm in west Azerbaijan province. Therefore, the data related to the present weather codes were collected during the period 1986 to 2009 from the National Meteorological Agency. The data related to the weather codes entered in Excel, and data related to the snowstorm were selected through Filter tool and isolation of codes related to the strong snowstorms (codes 37and39) and weak snowstorms (codes 36 and 38). Then the data related to the snowstorm was entered in SPSS, and the statistical analysis was performed. In the next step, three cases of the strong and common snowstorm (code 37 and 39) were selected for synoptic analysis. Then, the synoptic maps of the different layers of the atmosphere were selected as the samples for strong snowstorm for the days before the event of the phenomenon, the day of event, and the day after the event of the phenomenon by the using of the accuracy of 2.5 degrees from cdc.noaa.gov website. The study area has been selected in 10 to 80 degrees north latitude, and 15 to 90 degrees east longitude for identifying the patterns that affect West Azerbaijan Province. The data was received on wind speed and direction in digits from the National Center for Environmental Prediction. Then, the maps of the wind direction and speed were provided in Grads. Finally, the daily analysis and interpretation of pressure (500hPa at sea level), instability (700hPa level and the ground level), Earth's surface temperature, wind speed and direction maps for 700hPa level, and identification of patterns that have caused snowstorm in West Azerbaijan province were carried out. Statistical and synoptic analysis of snowstorm phenomenon in West Azerbaijan province during was performed in the period 1986 to 2009. To do this, using codes 36 to 39, which represent a variety of snowstorm (weak and strong), the frequency of snowstorm days on monthly and annual average, distribution of the snowstorm in the extracted stations, the frequency of strong snowstorms (codes 37and39), weak snowstorms (codes 36 and 38), all types of snowstorms (codes 36 to 39), and the frequency of storms in the station level were compared. Out of 322 snowstorms occurred during the period 1986 to 2009 in seven synoptic stations 108 have been determined as strong snowstorm and 214 as weak snowstorm. In order to analyze the synoptic snowstorm in West Azerbaijan province, in the first place, the strong snowstorms were identified, and then five of the strong and comprehensive storms were selected for the synoptic analysis. The snowstorms of choice are as follows: On 18 January 1986, on January 19, 2000, on February 7, 1992, on February 5, 1997, and on December 25, 1990.
For applying the study, pressure maps, Omega (700hp level at ground level), Earth's surface temperature, and wind speed and direction at 700hPa were analyzed, and patterns and conditions that are causing this phenomenon in the West Azerbaijan province were identified.
In this study, to perform statistical and synoptic analysis of snowstorm in Western Azerbaijan province, the statistical data were examined during the period 1986 to 2009 from 7 stations, and the results of the statistical analysis showed that:
• Out of a total 322 snowstorm event days of 7 synoptic stations during the period 1986 to 2009, 108 and 214 days were strong and weak snowstorms, respectively.
• Review the annual and monthly snowstorm during the study period showed that the 1992, 1997, and 1989 with a total of 69, 29, and 25 days, as well as the 1999, 2006 and 2007 with 0, 1, and 1 day have the most and the fewest days of snowstorm, respectively. The statistical analysis showed that the snowstorm phenomena happened in January, February, March, April, November, and December. January had the most and April had the fewest snowstorms with 119 and 3 days, respectively. February with 39 days, and April and November, with the number 0 and 1 had the most and the fewest days of strong and constant snowstorms.
• Distribution of the snowstorms in the stations indicated that out of the studied seven synoptic stations, which had a great impact on the synoptic situation of the region, topography, and height, Sardasht-Maku station had the most, and stations of Khoy, Mahabad, and Orumiyeh by having no snowstorms had the fewest days of snowstorm.
• The results of the maps of the different levels of the atmosphere and Earth’s surface in the days before the storm, event day and the day after the snowstorm were selected for the snowstorm pattern, which indicated that the snowstorm in the winter due to low compliance pressure formed in the earth's surface with synoptic patterns of middle levels of the atmosphere have provided the conditions for the event, in a way that among the sample cases of the strong snowstorms occurred in the West Azerbaijan Province two circulation patterns were involved in the formation of natural hazards: The Caspian Sea low pressure pattern- Eastern Europe high pressure pattern and the north of the Black Sea low pressure pattern.
Understanding the climate of a region as a first step and most immediate action is considered research for development projects Climatic phenomena such as floods every year irreparable damage to the soil, pastures, forests, urban and rural facilities, human and animal import Climatic phenomena such as floods every year irreparable damage to the soil, pastures, forests, urban and rural facilities, human and animal import. The first factor in causing flood is rainfall intensity that occurs at a certain time. Therefore necessary infrastructure projects, and one of the main issues in hydrological and hydro-climate is awareness of the occurrence and amount of rainfall, most likely for different periods.
In order to implement the model of Synoptic convergent in this research and estimated probable maximum precipitation in the South West region of the Caspian
1: The 1:50,000-scale Digital Mapping the location of all stations in the study area, Climatology, rainfall and hydrometric surveys in selected were identified on the map.
2: The maximum instantaneous discharge rate of the highest daily rainfall stations selected surveys (1976-2011) are also studied.
3: collection of the highest daily rainfall statistics selected stations, monthly and annual precipitation data for the period (1986-200),Facts about the daily atmospheric phenomena (cloud, wind speed, dew point temperature, air pressure) with an interval of 3 hours to 3 hours, Statistics continuing 12-hour maximum dew point of the surface (in degrees Celsius) and wind speed times (NAT) for the stations of Anzali, Rasht, Astara, Ramsar, Ardabil, Pars Abad For the first 10-day period, 10-day and 10-day return period for calculating the 50-year-old third, 80-year and 100-year and monthly statistics on the average pressure of the selected stations establishment station.
4: Select the desired storm rainfall in 24 hours and 48 hours to obtain a return period of 50 years, 80-year and 100-year 12-hour maximum dew point and wind speed persistence for long periods, the separation of each month, and the resolution of each decade, through software SMADA and HYFA.
5: Purvay of Rain maps and DAD chart is also the main stages of this work.
6: Finally, weather maps, humidity maps and omega air maps at ground level, 700 level and 850 hp prepared from
Days prior to completion until the day of rain showers in the stormy period from the NCEP / NCAR site and was ready in GRADS software environment.
In order to realize the adiabatic saturation warmest period of the most intense storms in 1355-1390The maximum instantaneous rate of discharge and daily rainfall statistics, the most comprehensive and stations on their occurrence in the previous chapter, was studied.So the four pervasive hurricane was selected. Then, rain storms map were plotted in the GIS software environment and use of IDW method and Using data from the windy days selected on rainfall stations in the study area. In order to obtain the rainfall in the whole region,were regressed between the two parameters: precipitation and elevation; and was estimated average of rainfall in the cumulative area and rainfall amount in during of the storm days. Based on the height - area tables of each storm separately, DAD curves was drawn based on average rainfall in columns cumulative and cumulative area. Then we reviewed and interpreted weather maps at ground level, elevation Maps, humidity maps and omega maps at 850 hPa level. Survey maps showed Tongue of immigrant anticyclons in North West Europe that usually is deployed on the Black Sea will advection cold air from the above widths on the Caspian sea and is transmited very wet weather to the south and West south Caspian Sea. After analyzing weather maps, the next step is obtain to water for showers.To calculate the rain water the best way is getting the hottest adiabatic saturation that occurs with the maximize the dew point temperature and wind speed. After obtaining the maximum dew point and wind speed factor, we would like to calculate the coeffcient storm. After obtaining the coefficients of the storm,obtained its P.M.P by multiplying the amount of rainfall for each storm.
According to the obtained PMP,was adopted rainfall continued for 24 hours with the numbers 276/95. PMP obtained showed that the storm dated 2/10/2001 of 24-hour duration, has been most intense and pervasive from the two other samples.
Dust particles consist of important aerosols and resulting in blowing strong winds on the surface of desert areas. These particles enter the atmosphere under the influence of different factors including: weather condition (wind, precipitation and temperature), land surface (topography, humidity level, roughness and vegetation), soil features (texture, density, composition and land use (agriculture).
Today powerful dust storm destroys people lives and causes severe damages to their life and also causes financial problems in most regions of the world especially in west and southwest of Asia. Dust storm is one of the most important natural phenomena and also a kind of severe natural disaster that influence Iran and its west and southwest part. The location of Iran on the desert belt is accompanied by frequent increasing of sand and dust storm. Integral prediction of dust storm phenomena can be useful in decreasing damages caused by these storms. So synoptic-dynamic analysis of dust storms and their simulation play an important role in achieving to this goal.
In this research, we investigate severe dust storm in August 2005 that affected a large area of our country. Select of dusty days were based on minimum visibility and maximum durability of that dust storm. At first, we show the minimum of daily visibility table. These data has been provided by Meteorological Organization in 5 western cities. The synoptic maps were related to these phenomena derived from NOAA website and synoptic and dynamic interpretation has been done. We have got the data with resolution of 2.5 degree from NOAA website.
Then 700 hpa relative vorticity maps were drawn. We investigate MODIS images instrument on Aqua satellite and evaluate the amount of mass concentration of dust particles. Then the Lagrangian Integrated Trajectory Model has been used to determine the backward trajectory of dust particles. We run HYSPLIT model by GDAS data with a resolution of 0.5 degrees. At last we investigate the output of the WRE-CHEM model. This model was run to simulate dust storms in 7-10 August and FNL data with a resolution 1 degree use for initial and boundary conditions. WRF-CHEM is used to simulate dust condition and transmission. As a part of WRF model, its main application is the study of atmosphere chemistry.
At 500 hpa a very strong ridge entered Iran from the southwest. It covered all areas of our country which prevents the transference of dust to high levels of atmosphere. In 700 hpa relative vorticity maps show one day before dust storm reach to Iran a Positive voriticity is located in Iraq and Syria. So dust comes up to higher levels of the atmosphere and in dusty days in our country. There is a negative voriticity located in our country and because of downside movement of the air, dust storm happen in Iran.
Dust loading and friction velocity of outputs of the model has been drawn in dusty days. The time series of dust concentration of output models for Tabriz are compared with the concentration data of Environmental Organization of visibility data. Result show that a low pressure system is located over the Oman sea that its blaze has been extended to the northwest of Iran. On the other hand a high pressure center is located in the Europe that extended to the east of Mediterranean. So strong pressure gradient were in Iraq and Syria and they caused the creation of strong winds in their deserts which caused dust emission.
Friction velocity related to the model outputs show that the velocity of wind is high in dusty days in Iraq and Syria. So conditions are suitable for dust raining. Satellite images showed that WRF/CHEM model is simulated very well in emission, source, diffusion and the extent of the areas covered with dust. Comparing MP10 concentration of the model output with and Environment Organization data of Tabriz city show that WRF/CHEM model forecast daily changes well. But model underestimate significantly in quantity of concentration. This error may be due to a model considering only dust quantity but other pollutants affected on visibility. In general it can be said that in this event, dust concentration has been underestimated by WRF/CHEM model especially in maximum amount of PM10 concentration.
Dust particles are important atmospheric aerosol compounds. The particles are resulting performance of strong winds at the soil surface desert areas. Sources of dust are 2 types: 1- Natural Resources 2- Human Resources. Iran is located in the desert belt which this problem cause increased the frequency of dust storms, especially in South East (Sistan) and South West. China Meteorological Administration Center classifies storms based on particles type, visibility and speed storms to 4 kind: Floating Dust, Blowing Dust, Sand/Dust Storm and Sever Sand/Dust Storm. In general, the effects of dust storms in 7 of Environment (particles into remote areas, the effect of dust particles on the material, climate, oceans and deserts), public health and health (increase of respiratory diseases , cardiovascular problems, digestive, eye, skin, reduced hearing, infections, reduced life expectancy and premature death, etc.), economic (unemployment, road accidents, damage to communication lines, air, land, sea, increase water turbidity in water utilities, creating uncertainty for all economic activities, etc.), Agriculture and Livestock (negative effect on the growth of plants and animals, reduced productivity and diversification, intensification of plant and animal pests and diseases, rising costs maintenance of livestock, etc.), socio-cultural (poverty and the loss of local jobs, destruction of subcultures, rural migration to the cities, closure of educational premises, industrial units, services, etc.) and military-security (disabling weapons, food and beverage contamination, the threat of sensitive electronics and power transmission systems, and reduce the useful life sitting on warehouse equipment, logistics cargo weight gain, etc.) can be evaluated. One way to identify, evaluate and forecast dust storm modeling. Dust cycle consists of 3 parts, dust emissions, dust and subsidence transfer dust that can be simulated by models.
In this study using the WRF_Chem model with FNL[1] input data and GOCART schema, sever dust storm in Sistan region was simulated to date 14 & 15 July 2011. Satellite images of the event was received by the MODIS sensor. Dust concentration data was received from the Department of Environment. The dust storm code, minimum visibility data and maximum wind speed data was received from the, Meteorological Organization.
The results of the simulation for dust concentration which peak amount of dust was for 21Z14July2011 and 03Z15 July 2011. Model output showed maximum wind speed 20 m/s with North to South direction in the study area. The model predicts maximum dust concentration for the latitude 31 degree North and longitude 54 degree East to 66 degree East (Within the study area). MODIS sensor images showed clearly the sever dust storm. Simulated time series in Figure 3-1 Changes in dust concentration during the event show in the Sistan region. As can be seen from the peak of the concentration of dust in 21 hours on 14 July (350 micrograms per cubic meter) and 03 hours on 15 July (425 micrograms per cubic meter) 2011 was created. Model simulation and satellite images indicated which the Sistan region, especially dry bed of Hamoun wetland in East of Iran was main source of sand and dust storm. Also, based on the model output blowing wind direction from North to South on Iran which converging these currents in East Iran caused by strong winds in the lower levels (According to the meteorological data), arise dust, increasing the dust concentration (According to Department of Environment data), increasing the dust and being transferred to the Southern regions, especially Oman sea. To identify the source of the sand and dust storm, the path of the particle and anticipated this event cant actions and warned to stop and reduce effects its. . Simulation of dust particles in the resolution of 10 and 30 kilometers, the plains of Sistan in Iran's East region as the main source screen. The findings suggest that compliance with the maximum concentration limits on known sources of particles (especially Sistan plain dry bed of plain wetlands) is. Check drawings wear rate showed that the source of dust in the Sistan region, particularly the high potential of our wetlands dry bed of soil erosion in wind activity 120 days during the hot and dry conditions, and silt and clay up to thousands of kilometers away from their source transfers. Vector lines on maps wear rate, indicative of converging flow north-south and severe dust storms in history is this. It is better than models forecast dust events and rapid alert
[1] Final Reanalysis
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