In order to recognize Isfahan WEATHER TYPES, in this research 22 variables including temperature, precipitation, atmospheric humidity and wind were studied in Isfahan synoptic station from Dey, 11th, 1339 (January, 1st, 1960) to Dey, 11th, 1383 (December,31st,2004). A Cluster analysis on the Euclidean distance of standardized matrix of data and linking days on the basis of ward method showed that Isfahan has 9 WEATHER TYPES (WT) including: 1.Cold, frosty, calm WT, 2.Very cold, frosty, calm, foggy WT, 3.Rainy WT, 4.Cold, frosty, dry WT, 5.Cold, windy WT, 6.Windy WT, 7.Moderate WT, 8.Warm, dry WT and 9.Hot, dry WT. Based on this research's results, hot and dry WT is the most dominant and durable, and rainy WT is the least frequent and short-lived WEATHER type.

In order to recognize WEATHER TYPES, in this research 7 variables were studied in Zahedan synoptic station from Farvardin, 1st, 1358 to Esfand, 29th, 1382. Cluster analysis on the standardized matrix of data (stnd9088, 18) and linking days on the basis of Ward method showed that, Zahedan has 6 WEATHER TYPES (WT) including: 1. Moderate WT, 2. Cold and calm WT, 3. Warm and dry WT, 4. Hot, dry and windy WT 5- Very cold WT 6- Very cold, Low rain and foggy WT. Based on this research results, hot, dry and windy WT is the most dominant, durable, cold and calm WT is short-lived WEATHER TYPES of Zahedan. For every type one day was selected as the representative day. Monthly and yearly frequency of each type was estimated. It was found that the yearly frequency of TYPES has changed since three decades ago.

In this paper, the main aim is the identification of WEATHER TYPES in Arak station. In this study we used 18 daily climatology variables including dry temperature between hours (15- 09-03), wet bulb between hours (15- 09-03), relative humidity (15- 09-03), wind speed (15- 09-03), wind direction (15- 09-03), daily precipitation amount, max and min temperature during the years of 1984/3/21 to 2004/3/19 in 20 years, two decades, for Arak station. At first a data base was provided in MATLAB software. This data base consisted of all the events whose number of variables was recorded in it. For data analysis, one of the shapes eigenvector named P was used for typing. In fact P arrangement is an arrangement of data matrix on which the climate variables are shown on columns and days on lines. Then the data were standardized so that each of the variables has an equal share in typing. At the end, on the standardized data, a cluster analysis with the method of Ward link was carried on. Then a total dendrogram for station was drawn. With regard to the main dendrogram for Arak station, four main TYPES were obtained. The type of warm and dry are the most frequent, most endurable, most dominant and the most homogeneous; it has grown in the recent years. The type of cold and humid is the most frequent and the most heterogeneous. The moderate type is the most harmonious, the least lasting and the most sporadic. The very cold and raining type is the least frequent and has the longest period of waiting for recurrence. In recent years, rainfall has occurred relatively. On the whole, the dominance of WEATHER TYPES has been illustrative of the dominance of various climatic seasons. Then for each type, frequency, occurrence, nonoccurrence, diversity, day representative and time period in the last two decades have been investigated so that frequency of WEATHER type changes becomes known.

In this study we used of 18 daily climatological variables including dry WEATHER, wet WEATHER, humidity, wind speed and direction, dept ,maximum and minimum temperatures between the solar years of 1363/1/1 to 1382/12/29 in 20 years for Bushehr station. At first a data base was created in MATLAB software. This data base was consisted of all the events that their amount of variables was recorded in it. For data analysis one of the shapes eigenvector named P was used for typing. In fact P arrangement is an arrangement of data matrix that climate variables are shown in columns and days in rows. Then the data were standardized so that each of the variables had an equal share in typing. After standardized data, a cluster analysis was Pretoria using the method of Ward link. Then drawn a tree diagram for each station. With regard to the main tree diagram for Bushehr Station3 main TYPES were obtained. And for each obtained type, variety of everyday synoptic typing, frequency, occurrences, unoccurrences, representative day and time, yearly and monthly period in the previous 2decades were determined so that WEATHER TYPES and frequency of changes were established.

Understanding the daily WEATHER TYPES of any specific location is crucial for identifying its long-term climate patterns. In this study, we utilized the Wos classification method in conjunction with a comprehensive climatological approach to analyze key variables, including minimum, average, and maximum temperatures, as well as cloud cover and daily precipitation. Data from 1985 to 2021 were collected from 39 synoptic stations, which exhibited a well-distributed representation across the country and provided complete datasets. WEATHER TYPES were identified using established coding techniques. The findings indicated that the predominant temperature TYPES in the country are primarily categorized as hot and very hot, with sub-codes reflecting generally low to moderate cloud cover and negligible precipitation. Furthermore, the application of Ward's clustering method facilitated the identification of three distinct climatic groups. The geographical characteristics of each location, including factors such as altitude, latitude, proximity to the sea, and synoptic influences, play a significant role in the regional differentiation of these groups within the country. The outcomes of this research can be instrumental in developing WEATHER calendars for various regions, with implications for numerous sectors including agriculture and tourism.

In this research a data base has been provided using daily observations for seven climatic variables including relative humidity, daily rain, wet temperature, dry temperature, maximum temperature, minimum temperature, the wind speed and direction during 1358-1382. At first, a data base of the investigating variables was established in "mat lab" software. Considering the goal of the research, which was WEATHER type recognition, the researcher prepared a matrix with "P" decoration. "P" decoration is a decoration of data base matrix in which the rows are time and the columns are the indicators of climatic elements. Having chosen the classification method, the researcher carried on a cluster analysis with combination method on standardized Bam station. For every type, one day was selected as the representative day. Monthly and yearly frequency of each type was estimated. It was found that the yearly frequency of TYPES has changed since the last three decades. At the end, the relationship of these TYPES to circulation patterns of the middle level of atmosphere was investigated. Based on the findings, it was found that the event of each type is affected by the specific circulation pattern.

The writers of this research have studied seven variables including: precipitation, relative humidity, sunny hours, temperature average, temperature minimum, temperature maximum and sea level pressure, at Sanandaj Air Station during 1964-1994. Sanandaj Air Station has nearly 10966 days of complete data for these variables. A principal component analysis (PCA) has been applied on this data; then five principal components have been selected that explain more than 1% variances. A cluster analysis has been applied on this matrix (10966*5) and five synoptic TYPES have been obtained. Synoptic TYPES one and five, showed a large amount of within group variance. So a PCA was applied to the members of these two TYPES and three synoptic subTYPES have been obtained for synoptic type one and five synoptic subTYPES for synoptic type five.

Introduction: Iran is due to the diversity of wildlife and beautiful nature itself among the world's countries. Due to geographical conditions in north of the country, such as Alborz and Azarbaijan mountainous and forested areas of north west river are probe the most abundant natural tourist attractions and ecotourism in the northern half of the country.

In order to determine the TYPES of rain producing WEATHER in Tehran, the rainy days of the station (days with more than or equal to 1 millimeter) were identified during the 1990-95 period. The 12 GMT pressure and height data of the area 200-47.5° and 35°-67.5°E were -extracted from the NCEP Reanalysis file for the grid points 2.50 apart. The synoptic systems and flow directions were determined according to the objective method of computing vorticity. The results first showed 24 pressure patterns for the three groups of light, moderate, and heavy precipitation days. Then these patterns were re-grouped according to their similarities into 10 WEATHER TYPES. These TYPES consist of two cyclonic and anticyclonic, and 8 directional TYPES corresponding to 8 geographical directions. The most frequent type was the Easterly and the most important rain producing type was the cyclonic type. The anticyclonic type was the least rain producing type. CyclonicTYPES were more dominant and developed mostly in winter. The anticycloicTYPES showed lower frequency and concentrated in spring.This study showed that the vorticity computation method is very effective and accurate and capable of quantifying the power of the WEATHER TYPES. The 500 hpa level had more significant effect on the precipitation than the surface pressure changes. The Syrian trough was the most important upper level system which controls the precipitation of Tehran.

One of the things done in the field of synoptic climatology is air typology. An air typology represents TYPES of air that are similar enough in terms of particular atmospheric variables. The emergence of an air type in a certain area, on one hand, depends on the air masses entering to the area, and on the other hand, reflects the geographic conditions (roughness, adjacency to the masses of water, etc. ) of that area. Since the geographic conditions of each area are usually constant, the difference in air TYPES that come and go in the region is a function of the air masses that enter the area. Characteristics of the air masses while moving and crossing different areas, change, adjust and turn into another air. Given the fact that the repetition of air TYPES determines the climate in an area, it is very important to identify the TYPES of air. This is because without knowing the TYPES of air dominating an area, management and planning will be very difficult and even impossible. This is while by identifying air TYPES, it will possible to identify possible TYPES of natural disasters in different sectors of agriculture, industry, etc. and prevent its damages. Since each type is related to circulation patterns, recognizing the characteristics, severity, and frequency of each type can show us their remaining time and duration of their domination, and help us in planning.