Showing 5 results for Synoptic Analysis
Mohammad Darand,
Volume 15, Issue 37 (9-2015)
Abstract
The aim of this study is synoptic analysis of heavy precipitations in Kurdistan Province during 1/1/1961 to 31/12/2010(18263days). By using two thresholds of extensively and intensity of precipitation, 107 days have been recognized. In temporal view, the selected days occurrences in wet seasons of year that start from October to June. By applying the principle component analysis on the sea level pressure during the 107 days, the results showed that 12 components explain about 93 percent of sea level pressure variation. The results of the applying cluster analysis on the component score showed that two circulation patterns result in occurrence of extreme and heavy precipitations in Kurdistan province. In order to recognize heavy precipitation in dry season (June to October), the area mean precipitation for the province have been calculated. According to the 99 percentile threshold and extensively of precipitation the heavy phenomena recognized. By two thresholds 32 days selected and same as to the wet season precipitation the sea level pressure data from NOAA extracted. The data analyzed by Principle Component Analysis and 11 components extracted that explain the 93 percent of variation sea level pressure in the frame study. By doing cluster analysis on the 11 components, one pattern recognized for the sea level pressure. The results showed that in lower atmospheric levels (1000, 925 and 850 hpa) occurred highest convergence on the study region during wet season. The source of humidity in the lower levels is Arabian, Red, Oman, Persian Gulf and Mediterranean Seas. In the high level atmosphere, the value of convergence is low. The sources of humidity in high levels atmosphere are Red and Mediterranean Seas. In the mid level atmosphere (500 hpa) the presence of trough results in nutrition of the instability on the study region. Also during dry season, the highest moisture flux convergence occurred in the low levels but the resource of the moisture is Caspian Sea. In the upper levels (from 700 hpa to up) in addation to Caspian Sea, Mediterranean and Red sea are the resource of heavy precipitations.
Ali Reza Karbalaee Doree, Sayyed Mohammad Hosseini, ,
Volume 17, Issue 47 (12-2017)
Abstract
Air pollution is one of the most important natural hazards in cities that is one of the priorities of climate research. In this research, synoptic situation of days polluted by ozone in Tehran have been studied and by environmental to circulation approach and cluster analysis. At first, was formed a matrix in 2417*41. Rows are indicated days and columns represent the number of stations. by cluster analysis and Ward method eight different clusters were identified. The results showed that the frequency of the ozone days have a seasonal trend and more can be seen in the first half of year in these cases the establishment subtropical high pressure in Iran. Therefore, cause the persistency of pollution in Tehran.
Mrs Zahra Hejazizadeh, Mr Farshad Pazhoh, Mr Fardin Ghadami, Mrs Haniyeh Shakiba,
Volume 22, Issue 65 (6-2022)
Abstract
The aim of this study is to synoptic analyze of the number of frost days in a year of Khuzestan province. For this purpose, using the minimum daily temperature data of 12 stations during the statistical period of 1992 to 2017, the Meteorological Organization of the country, 54 days of frost was identified. Sea level pressure, Geopotential Height, Zonal and meridian wind and temperature of 500 hPa data with size of 2/5 * 2/5 degree arc from the National Oceanic and Atmospheric United States of America were extracted. On the matrix of the variance of sea level pressure data in 54 days, the analysis of the basic components was performed and 10 components which identified 83% variance of the sea level pressure. Then, by applying the hierarchical cluster analysis method, the integration method was applied to the scores of the 10 components and 5 patterns of sea level pressure were identified. The results showed that frost phenomenon in Khuzestan province occurs from November to march and its trend is decreasing during the statistical period. Also northern and western parts of the province have allocated the most frequency of frost. Also the synoptic condition analysis of troposphere showed that 5 sea level pressure pattern with different make ups lead to pervasive frosts of Khuzestan province. Weak and moderate frosts formed by the influence of Siberian and European cold high pressure systems. But severe frosts occur with spread of Iceland low pressure to Iran, along with strong cold pressures. Meanwhile, the powerful Siberian high pressure is present in most of the patterns, which its interaction with sub polar and Icelandic low pressure, plays the most role in the most severe frost in the province of Khuzestan. Also in the middle level of troposphere penetration of deep troughs from northern latitudes and east European huge blockings has the most role, which has advection of cold air from the side west of troughs on the country and during the intensity of the frost added to its continuity.
Hadi Zerafati, Yousef Ghavidel, Manuchehr Farajzadeh,
Volume 24, Issue 72 (6-2024)
Abstract
In this study, for statistical studies to determine days whit temperature above 50°c, the reanalyzed data of the nineteenth, twentieth and twenty-first centuries for the West Asia region (12 to 42.5 degrees north latitude and 36 to 63.5 degrees east longitude) have been used. Also, for synoptic analysis of extreme temperatures, HGT, AIR, UWND, VWND and SLP data were used. To conduct this research, first, extreme temperature data above 50° during the last 185 years were extracted for the study area in the hot season (June, July, August and September). After identifying days whit above 50° c, HGT data at the level of 500 hp were extracted and WARD clustering was applied. Finally, after identifying the clusters, the days whit the highest temperature that occurred in each cluster were selected for synoptic analysis. It can be said that all altitude patterns of geopotential meters (HGT) at the level of 500 hp show that the main cause of occurrence and distribution of temperatures above 50°c in West Asia are high-altitude (high-pressure) subtropical West Asia, which due to the location of its high-pressure core on the Zagros and sometimes the Arabian Peninsula, it has been referred to as the Zagros or Saudi high-pressure in terms of interest and taste. What is certain, however, is the high-pressure independent identity of the subtropical Azores, which has been mentioned in numerous articles and is known to be the main cause of the heat in the West Asian region, especially Iran.
Dana Rahimi, Javad Khoshhal Dastjerdi, Dariush Rahimi,
Volume 24, Issue 74 (12-2024)
Abstract
Among natural disasters, floods have the highest human toll. The economic impacts of floods are greater in developing countries, including Iran, and are particularly severe in the colder months of the year in the west of the country. The purpose of the present study is to analyze the most severe historical synoptic floods that occurred in Karkheh Basin (1 April, 2019). Descriptive - analytical research method and its environmental approach into circulation. Analysis of synoptic systems of large floods such as the April 12, 2019 floods show that Western Europe's high-pressure systems, Black sea, East of the Caspian and low pressure north of the Red Sea, Eastern Mediterranean in harmony with the high-rise systems of Western Europe, Low Mediterranean East with a temperature drop of about 50 degrees Celsius(The temperature at sea level In the eastern Mediterranean and Red Sea about 25 degrees Celsius and in the middle of the atmosphere -25 degrees Celsius) also the climb Humidity from the Arabian Sea, North Indian Ocean, Red Sea, Oman Sea and Persian Gulf and Along with Mid-width cold air loss On the area and the establishment of the Polar jet stream) Core up to 70 m(And the establishment of the front jet stream And positive rotation area On the area shows the structure of the synoptic systems causing the flood in the area.
