مطالعات جامع آب و هوايي مكران (حوضه بلوچستان جنوبي)

Indian Monsoon Data Assimilation an‎d Analysis , MODIS Data , Principal Component Analysis , Cluster Analysis , Trend Test , Southern

University of Isfahan Faculty of Geographical Sciences an‎d Planning Department of Physical Geography

جغرافياي طبيعي

The Southern Balochistan Basin is located in southeastern of Iran an‎d on the border with Pakistan. The Sea of Oman, which covers half of the Iranʹs southern coast, is located to the south of this basin. These coasts play a very decisive role in ensuring Iranʹs national security. Identifying the capacities an‎d limitations of this region requires awareness of its climatic potentials an‎d limitations. Therefore, a comprehensive study of the climate of the southern Balochistan basin is one of the main goals of this research. To achieve the research objectives, MODIS data (2002 to 2019), the Indian Monsoon Weather Database (1979 to 2020), an‎d station data (1986 to 2020) were used. Principal component analysis was used to process data an‎d analyze spatial an‎d temporal patterns, cluster analysis was used for spatial regionalization an‎d temporal seasonality, an‎d trend testing was used in the MATLAB environment to examine temporal an‎d spatial changes. Principal component analysis an‎d cluster analysis were performed for the variables of aerosol optical depth, precipitable water, cloud fraction, sea level pressure (SLP), lan‎d surface temperature (LST), an‎d albedo. In principal component analysis, the influential components in each of the variables under study were identified, an‎d the spatial distribution pattern so map an‎d the temporal change pattern so chart were analyzed. Among the aforementioned variables, aerosol optical depth, precipitable water, an‎d LST have a greater impact than other variables in the studied basin. Studies showed that spatial patterns follow the structure of the ruggedness configuration an‎d latitude, an‎d spatial changes have an orbital arrangement pattern. Trend analysis was conducted on data from the Indian database, including maximum temperature, minimum temperature, sea level pressure, an‎d precipitation. In this study, precipitation did not show a significant trend, but an increasing trend was observed for minimum an‎d maximum temperatures, especially in the middle parts of the basin. A weak decreasing trend was also observed for SLP data. The climatic regionalization of the basin was also carried out using the cluster analysis method, which identified four regions including coastal, plain, foothill, an‎d mountainous. This regionalization largely corresponds to environmental realities, especially the structure of the ruggedness configuration an‎d the distance from the sea. The identification of the basinʹs weather types was also carried out using daily data of 26 variables using cluster analysis based on Euclidean distance an‎d Wardʹs linkage method, based on which six weather types were identified. These types include: semi-warm, low-rainy, an‎d relatively humid type. Temperate, semi-rainy, an‎d semi-humid type. Semi-temperate, rainy, an‎d humid type. Cool, dry, an‎d low-windy type. Hot, humid, an‎d low-rainy type. Very hot, humid, low-rainy, an‎d windy type.

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