Journal of Spatial Analysis

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Precipitation is one of the important aspects of the Earth’s climate that has both spatial and temporal variations. Understanding the behavior of this element and analyzing its spatial and temporal variation is importantwhich can lead to a comprehensive and detailed planning for water resource management and agriculture. Geostatistical techniques and spatial autocorrelation analysis are the most widely used techniques in the field of the spatial continuity. Spatial autocorrelation analysis is applied to help researchers understand the spatial patterns in the area.

      The purpose of this study is to identify the heavy precipitation spatial patterns in Guilan Province. For this purpose, the 6- hourly sea level pressure of the network from  0 to 120 Easter longitude and 0 to 80 Northern latitude with 2.5×2.5 degrees spatial resolution were obtained from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) for the period 1979-2010. The daily precipitation data of 21 stations were obtained from the Islamic Republic of Iran Meteorological Organization and Ministry of Energy.

      Guilan province is one of the most humid regions in the country. The heavy rain days were selected as days when more than 30 percent of the all stations had daily rain amount more the 95^th percentile. As a result, 321 days were selected as heavy and widespread rainy days. By using principal component analysis these 321 days were reduced to 9 factors. These factors then were subject to cluster analysis with Ward method and resulted in three surface pressure patterns of heavy rainy days. Within the resulted pressure patterns by using local geostatistical techniques we identified the heavy rain spots and their spatial orientation. These spatial methods include Kriging,  Geostatistical Analysis, and Anselin local Moran index.

According to the results of this research, the first pattern was characterized with a high pressure over northern part of the Black Sea causing the highest Variance of heavy rainfalls. The second pattern is identified as a low pressure on the Black Sea. But the third pattern showed a precipitation distribution with low variation caused by the Siberian high-pressure. The results of Spatial Statistics techniques indicated that heavy rains were clustered in all there patterns. The clusters of heavy rains were localized mostly over the coastal areas and some over the central regions. The clusters of the western high-pressure patterns penetrated somewhat inside the province, while clusters of the Siberian high pressures was located on the shoreline of the province. The precipitation of western migratory high-pressures was heavier than of the Siberian high-pressure. The results of the standard deviation ellipse showed that heavy rain clusters were oriented in the east-west direction and were nonhomogeneous. While the ones oriented in the south east direction were more homogeneous and clustered. Because of this arrangement, the entry of moisture from the Caspian Sea is relatively concentrated on the East or North East. Because of the concentration of heavy rains in the central areas of the coast, the risks of floods and soil erosion is very high in these areas. This study showed that contrary to the popular belief, the heavy rains of Guilan were produced by western systems and the role of the Siberian high pressure is less important and is limited only to the coastline.

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The results of this study indicated that the synoptic patterns that lead to heavy rainfall in 22 March 1996, 24 mar 1995 and 17 November 1994 in the northern portion of FARS province includes: the low pressure that located in eastern part of Mediterranean and Black sea and southern part of Caspian Sea that created by trough that located at the middle level of atmosphere. In addition to this low pressure, the bipolar pattern in of Saudi Arabia  having negative vorticity that lead to transporting moisture from (India ocean, Red sea, Arab sea, Persian gulf and Oman Sea )   and also to be alignment with east Mediterranean sea and black sea low pressure as ascending agent lead to precipitate of rainfall in mentioned days . and also we found that in 29feb 1996 as second patterns rainy day, a strong deep trough transporting moisture from Soudan region and east Mediterranean  low pressure, cause alignment of this atmospheric systems. In fifth patterns (21 mar 2001), existing an low pressure and positive vorticity center in east of Pakistan simultaneously with existing negative vorticity center in central part of Iran, lead to high pressure gradient which cause rainfall events in study area. The main founding of this study were that reveals the role of low pressure of east, north and south of Caspean sea in heavy rainfall events in study area.

Pre-warning of natural hazards events such as heavy rainfall has a significant effect in damage reducing. The analysis of synoptic-dynamic condition of atmospheric circulation patterns, has great importance in recognize affective agents in heavy rainfall events. Especially this heavy rainfall could lead to flash floods suddenly. This study's aim is to analysis and extraction of daily heavy Rainfall lead atmospheric patterns in northern portion of Persian gulf (Helle and Mond Subbasin).

The study area, Helle and Mond basins, with about 21,274, 47653 km2 area,respectively are located in the south of Iran. The Helle basin approximately is between 28° 20'N and 30° 10'N latitudes and between 50° E and 52° 20'E longitudes and Mond basin is between 27° 20' and 29° 55' latitudes and between 51° 15' and 30° 27'E longitudes.These basins are located in sides of a massive sources of moisture, Persian Gulf.

In this study we investigate the data of daily rainfall of 37 synoptic and meteorological station of study area during 1991 to 2011(20 years) to extraction the atmospheric patterns lead top heavy rainfall. In this study in order to archiving heavy rainfall days based on 95 percentile in study area, the data of sea level pressure, geopotantial high of 300 and 500 hp and also data of verticit and stream line and omega in the spatial framework of -10 to 100 longitude and 10 to 70 Latitude has been selected. Then we create the sea level pressure matrix as rainfall associated days, based on Lond method of Correlation to classify days.

Our founding indicated that the main synoptic systems that lead to heavy rainfall is related to low pressure in eastern Mediterranean  and southern part of Caspian sea. So that in detected rainfalls patterns shown that the transporting moisture from nearby sea by high pressure of Saudi Arabia by associating eastern Mediterranean low pressure and deep strong trough in east and southern part of Caspian sea  cause heavy rainfall events in study area. So that the low pressure located in eastern and southern portion of Caspian sea could affect the study area.

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Classifying daily climate circulation patterns has always been considered by climatologists. Investigating climate changes such as rainfall and the temperature in a same single time and place suggests that these changes are strongly influenced by atmospheric circulation patterns.

Regarding so, climate changes, known as variables here, such as rainfall, temperature, and other related phenomena, which are exemplified as flood, drought, glacial, and etc. are associated with special types of climate circulation patterns. The continuity and alternation of the systems are classified or identified climatically, therefore weather classification system is one of the main objectives of the synoptic climatology (Huth, 1996). Since every weather type creates its own special environmental condition, lack of identification in weather type frequencies leads to a difficult environmental explanation and alternation (Alijani, 1380: 64).

Identifying atmospheric circulation patterns different things that can be expressed inductively such as frequency, intensity, and spatial distribution of climate changes in rainfall and its physical causers (VicenteSerrano and LopezMoreno, 2006).

Heavy rainfall in many watersheds, particularly in the basin and sub-basin which involve less time exposure, causes floods and it also damages human, natural resources, infrastructure utilities and equipment. Before the occurrence of this kind of rainfall, it requires a deep understanding of the synoptic systems of their creator. This understanding is only possible through the classification and identification of rainfall patterns which used to cause floods in the studied basins.

The present study also aims at identifying and classifying the synoptic patterns of rainfall during the statistical stage of the study in the basin which caused flood in Taleqhan basin.

Taleqhan basin with area of (65/1242) per square kilometers is located in "36֯, 5', 20" to "36֯, 21', 30" north latitude and "50֯, 36', 26" to eastern longitude "51֯, 10', 18".

The study area is 120 kilometers away from North West of Tehran and located in a relatively high mountainous area in Alborz Mountain. This area is ranging from 1700 meters to 4400 meters above sea level. Average rainfall in this basin ara is 515/16 mm and its annual temperature fits 10.5 centigrade.  About 79 percent of rainfalls occurs from the cold weather period in November to March. It is also know as semi-humid cold weather based on the De Martonne classification.

Circulation algorithm (CA) and pattern clustering algorithm (PCA) were determined based on the daily methods in synoptic scale by applying information from stations in Taleqhan basin (Gateh deh, Dehdar, Dizan, Snkranchal, armouth, Ange, Joostan, Zidasht). In order to classify the weather type, daily average rate of 500 HPa and the sea level pressure (SLP) were extracted and reconstructed over the period (1980-2011) at the 2.5 degree of NCEP. Selected range includes 608 points from latitude of 10 to the 60 of northern degree, and latitude of 10 to 80 of eastern degree.

Principal components method mixes the interrelated points and reduces the matrix size, so 13 main components are remained that they includes 93 percent of the total variance. This study employs S array and Varimax rotation to identify different types of weather. It also makes use of K-Means clustering method to classify daily weather types. And finally, a matrix was formed in 118×608 dimension for 118 common days of rainfall among stations. All days were divided into four groups. They offer the most common climate circulation patterns in the proposed area. At the end, and finally integrated maps of sea level pressure and 500 HPa were drawn for each weather type. 

According to the results from factor analysis, 13 main elements were selected that they included 93% of the total variance of the data. According to the above mentioned method, all days (118 days) during the statistical period (1980-2011) were divided into 4 groups which provide the most climate circulation patterns in the study area. Then, integrated maps of sea level pressure and 500 HPa range were drawn for each of the types. Clusters were numbered according to the K-Means arrangement, and they were named based on the pressure patterns and the way circulation lines were ordered.

The classification shows two different resources for rainfall in this basin.

A: Those rain systems that are entered to the country from the West and South affect this basin. These systems humidity are caused by the Red Sea, the Mediterranean sea, the Black Sea, and the Atlantic Ocean. (B) Some parts of the Caspian coast rainfalls and the northern part of the Alborz mountain that has received their humidity from the Caspian Sea and it has infiltrated northern high-land, causes the rainfalls. It enters the basin from the wide valley of Sefid Rood. According to the rainfall measuring stations data, the least rainfall area is in western, which includes low-land areas. And the most rainfall area is its northern east. Rainfall in this area, in terms of rainfall time distribution in a year, is the Mediterranean. It does not involve a complete dry climate in summer and it takes 3 to 4 percent of the total rainfall.  Rainfall in the basin, respectively, is distributed in winter, spring, fall, and summer.

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Problem statement
The occurrence of terrible floods due to climate change has caused much damages in different parts of the world in recent decades, and the effect of these changes is more pronounced in dry areas. Floods are the most common environmental damage. On average, 60 floods occur annually in Iran, with an average annual flood loss of 141 people, meaning more than 2 deaths per year per flood event.
Research Methodology
The study area consists of six stations located in Hormozgan, Kerman, Yazd, Kohgiluyeh, and Fars provinces. In this study, two types of ground and high data are used as follows:
A) - Using daily rainfall data of the 44 years (1967-2014) statistical stations of the region obtained from the country's Meteorological Organization
B) Use of high-level data. Includes revised data for geopotential heights, sea level pressure, wind direction, meridian wind, omega, and humidity, from the National Center for Environmental Excellence at Colorado. To conduct synoptic analysis, the circular environmental method was used; after observing the daily rainfall during the statistical period of all rainfall over 50 mm in selected stations of Yazd, Jiroft, Shiraz, Bandar Abbas, and Yasuj, 118 heavy rainfall events were investigated. After identifying and separating days, 105 observation systems were identified and analyzed.
After the evaluation and control of the pressure maps of the sea of the systems of landing, 4 patterns were selected and identified.
Explain and interpret the results
The results showed that heavy precipitation occurred in the months of December, December, February, February, and November, respectively. Since November, with the retreat of high-performance dynamic systems to the southern latitudes and the influx of western winds from high latitudes on the area, conditions for the occurrence of heavy rainfall are provided. Most centers with 9 heavy rainwater systems of Sudan's lowland, 6 the moderate Sudanese-Mediterranean component of the Middle East has been on Iraq, and the four satellite systems have been the Mediterranean-Sudan-Mediterranean integration. The most frequent Sudanese pattern in 2-day continuity with 17 cases was Sudan-Mediterranean integration pattern with 7 cases in 3-day continuation, Sudanese-Mediterranean integration pattern in the Eastern Mediterranean, 4-day continuity with 7 events, and equidistant Mediterranean pattern The continuity of 2 to 4 days has been due to the increased load of Mediterranean systems ranging from 70 to 90 mm.
 

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Synoptic analysis of the torrential on Day 21, 1398 (Case study: Zahedan and Qeshm)

Abstract
Rainfall is the most important phenomenon or feature of the environment and so far many studies have been done about its causes. In any place, rainfall occurs when humid air and climbing cause are provided. Both of these conditions are provided by the circulation pattern. The study area is affected by some severe and sudden weather phenomena such as low annual rainfall, short rainfall period and rainfall in the form of heavy showers. Thus, it is possible that the limited and pervasive precipitation of the area is due to a different synoptic pattern. Because the relationship between circulation patterns and precipitation is significant, achieving acceptable results in the field of the relationship between these patterns with the limit and total rainfall of the studying area requires the analysis of synoptic maps. Therefore, the most important purpose of the present study is the synoptic analysis of heavy cloud rainfall of the studying area on Day 1398.
Two sets of data were required for this study: A: Daily precipitation data of study stations on the day of heavy cloud rainfall on 21 Day (January 11, 2020) along with daily precipitation data in the days before the flood (96 hours before the flood) which was received from the main Meteorological Organization of the country.
B: atmosphere data levels including: sea level (SLP), 850 and 500 hPa levels, vertical atmospheric velocity and wind flow levels of 1000, 850 and 500 hPa, specific humidity of 1000 and 700 hPa levels and 250 hPa surface flow winds for study days from the US National Center for Environmental Forecasting / National Atmospheric Research Center (NCEP/NCAR) were provided in the range of 0 to 60 degrees at north latitude and 0 to 80 degrees at east longitude, and finally, maps were drawn and prepared in Gardes software to provide the ability to interpret.
The synoptic analysis of sea level showed that: on the day of the heavy cloud, a low-height closed center with a central core of 1,010 hPa in the northeast-southwest direction covered the entire study area. Then, the high-height with a central core equal to 1030 hPa is located at northwest of Iran, northwest of Europe and on Tibet. According to the location of high-pressure dams around Iran and the location of low-pressure centers on the study area and water resources in the south, a strong pressure has been created. Subsequently, with height increasing, low-height with central core equal to 1440 geopotential meters is located at northeast-southwest direction of entire study area. And the low height of northern Russia extends to the Persian Gulf and provides the conditions for severe ascent and instability in a very large area. The rear dams of Nave transferred the cold air of the high latitudes into the bottom of the Nave located on the study area and have intensified the instability. Also, the geopotential height of 500 hPa level of deep descent is located at the northeast-southwest direction of Iran and core of the Nave covers the Persian Gulf completely, that is the study area in the best condition and in front of the Nave, which is diverged by hot and humid weather. This deepening of the rotation and the penetration of the Nave to the lower latitudes caused the cold air to fall. 
The analysis of the 250-hectopascal-level flow-wind shows that the flow-wind with a core speed of 65 meters per second has covered the entire study area by crossing above the Persian Gulf, and compared to the previous days, the flow-wind is completely meridional.
Synoptic analysis of the vertical velocity at the level of 1000 hPa shows that the maximum negative omega -0.2 to -0.15 Pascal per second in the northwest-southeast direction has covered the study area. The presence of negative omega index values ​​indicates the role of convection in intensifying precipitation in mentioned area and the dynamic ascent of air. The study map shows that compared to other countries in the study map, the maximum of negative omega is located on Iran, which is reduced along to the west of Iran. With increasing altitude, the maximum negative omega has increased to -0.3 Pascal per second and the core of the maximum negative omega is completely located on the study stations (Zahedan and Qeshm). Then, at the level of 500 hPa, the maximum negative omega has reached -0.6 Pascal per second and its value has doubled compared to the level of 850 hPa, which covers the northeast-southwest direction from Zahedan to the Strait of Hormuz. Cold air fall has increased with increasing of omega levels in the middle levels of the atmosphere.In other words, in the middle levels of the atmosphere, with increasing temperature difference between the earth's surface and the level of 500 hPa, the amount of precipitation has increased.
Synoptic analysis of specific moisture level of 1000 hPa shows that the most moisture deposition was from south water sources to the study area, and the amount of moisture equal to 14 grams per kilogram has entered the study area from the Oman Sea and then its amount has been reduced crossing to other regions of Iran. Furthermore, at the level of 700 hPa, the maximum advection of hot and humid air is in front of the upper atmosphere of Nave from the Red Sea over the study area. There is a moisture strip from the southeast to the whole area under analysis. These suitable humidity conditions with the depth of the western wave have been able to cause heavy cloud rainfall. The maximum amount of moisture in the study area is equal to 7 grams per kilogram, which is a large amount compared to heavy rainfalls.

Keywords: heavy rainfall, flood, synoptic, Zahedan, Qeshm