مطالعه ویژگی‌های اقلیمی شمال غرب کشور بر مبنای تحلیل‌های آماری چندمتغیره

Introduction

One of the main goals in climate studies is to do climate classification. Climatic divisions and the identification of the most important factors affecting each area is one way of identifying the climatic profile of the areas. The climate of each area is composed of all the factors and climatic elements of that area and all those factors and elements must be taken into account when segmenting. Only by referring to temperature, precipitation and humidity can one study the climate of an area (Khosravi and Aramesh, 2012). Climate classification has been the focus of climatologists since the early 20th century. So far, three types of climate classification (empirical classification, genetic classification and multivariate classification) have been applied. Today, the advent of computer technology and the advancement of statistics has provided the conditions for expanding climate information basics. Many climatologists have used this method to classify and map climatic elements. Carbajal et al. (2007) demonstrated the ability of factor analysis in zoning by zoning and zoning bioclimatic zones in central and northeastern Mexico. Carvalho et al. (2016) divided the European territory into regions with similar simulated climate change in a study using daily rainfall simulations and minimum and maximum temperatures. There have also been numerous studies on climate zone zoning in Iran. Masoudian (2003) has studied the geographical distribution of precipitation in the country using factor analysis method. Absolute Gratitude and Evening (2006) dealt with climatic analysis of Bushehr province using cluster analysis. .Salehi et al. (2017) In a study, the climatic zoning of Kohgiluyeh and Boyerahmad province was analyzed using factor-cluster analysis and concluded that Kohgiluyeh and Boyerahmad province climate has five main components and eight climatic components.



Materials and methods

The study area includes East Azarbaijan, West Azarbaijan, Ardabil and Zanjan provinces. This part of the country occupies 118670 square kilometers of land area, which covers about 7.5% of the country.

For this purpose, data on 29 climatic variables of 19 synoptic stations were obtained from the Meteorological Organization from 1980 to 2010 and used for climatic zoning of northwest of Iran. After verification and verification of the data as test run and t-student test in SPSS software matrix with 19 * 29 dimensions (19 represents the number of stations and 29 represents the number of climate variables) was prepared. Climatic classification of the Northwest region. Also, due to the differing scale of measurement data, standard score of data was used for analysis. Finally, using Varimax-era factor analysis method to reduce the data matrix dimensions and identify the main climatic components of the northwest region, and the cluster analysis method through the input to the climatic zones of the study area.

Results and discussion

In factor analysis, it first standardized climatic data, then the corresponding analysis was performed using the Equamax rotation method and rotation method. Factor analysis using the basis components and varimax models showed that the 19 climatic elements of the Northwest region can be summarized into six factors with respect to their intrinsic correlation. After analyzing the matrices, climatic elements (factor loadings matrix) of 19 * 5 were obtained indicating that the climate of the Azerbaijan region is mainly the result of six factors, which together account for 92% of the region's climate behavior. These factors are: temperature factor, atmospheric humidity, precipitation, wind and visibility limit, thunderstorm, glacial.

After identifying the important factors in determining the climate of Azerbaijan region, climatic zoning was carried out using climatic and scientific elements. This was accomplished by using different spatial methods of climatic categories that had previously been reduced by analyzing the principal components. Different tree diagrams were drawn using different clustering methods. The northwestern region was divided into eight climatic zones based on 29 climatic components using cluster analysis method

Conclusion

In modern methods, climate classification is a process in which the statistical nature of climatic data largely determines the boundaries of climatic zones, not the individual taste of the researcher. These methods do not limit the number of elements that can contribute to the climatic zoning and therefore, this classification can identify climates in which the magnitude of the spatial differences of many climatic elements is taken into account (Masoudian, 2011). In this regard, applying modern statistical methods such as principal component analysis and cluster analysis to identify sub-climates of northwestern region, compared to traditional or classical methods such as Demarten, Coupon, Ivanov, Ambrose and ... Full advantage of modern statistical methods In identifying the distinct micro-zones they show climatic differences. In the Azarbaijan region, despite the existence of synoptic systems, the role of synoptic systems has been neglected due to various geographical factors such as altitude, altitude orientation, latitude, proximity to Caspian Sea and Lake Urmia. This has caused the destruction of several climates in the study area. In this study, after obtaining data from 19 synoptic stations and 29 climatic variables using factor analysis and cluster analysis and IDW mediation model, the climatic zoning of northwest region was performed. The results showed that the climate of Azerbaijan region is mainly caused by six factors: thermal, atmospheric moisture, precipitation, wind and visibility limit, thunderstorm and frost. These six factors account for about 92% of Azerbaijan's climate behavior. Subsequently, Euclidean interval cluster analysis was applied to six factors and the region was subdivided into eight semi-arid and windy regions, cold and moderately humid, cold and semi-arid, semi-cold and precipitation, semi-cold and relatively rainy. It was subdivided into warm, semi-arid, semi-cold and thunderstorms, and slightly warm and semi-arid. It should be noted that since in some parts of the study area there are synoptic stations for various reasons and no meteorological data is recorded, definitely with the establishment of long-term meteorological stations and the recording of long-term information, more accurate results on climate can be obtained. Reached areas.