تحلیل الگوی فضایی امواج سرد در استان گیلان (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
امواج گرم و سرد، رخدادهای فرین دمایی با پتانسیل بالا برای ایجاد اثرات منفی بر سلامت انسان و سیستم های طبیعی و اجتماعی-اقتصادی بسته به مدت و شدت آنها هستند. استان گیلان هر ساله امواج گرم و سرد با شرایط آب و هوایی مختلف را تجربه می کند. از این رو، در این پژوهش با ارائه تعریف مشخص از آستانه موج سرد، الگوی مکانی و رفتار فضایی آنها در پهنه استان مورد بررسی قرار گرفت. داده های مورد نیاز دمای حداقل از تارنمای ECMWF با قدرت تفکیک مکانی در مقیاس روزانه بمدت 40 سال (1981 تا 2020) تهیه گردید. سپس با اعمال آستانه صدک 10ام و توالی 3 روزه بر روی داده های دمای حداقل روزانه، امواج سرد شناسایی و شمارش فراوانی رخداد آنها با توالی 3، 6، 9 تا 30 روزه انجام شد. در این راستا، از شاخص های آمار مکانی اعم از I موران جهانی و محلی و آزمون t تک نمونه ای برای شناسایی نوع الگو و رفتار زمانی و مکانی آنها استفاده شد. نتایج نشان داد الگوی کلی فراوانی رخداد امواج سرد در تمامی طول موج ها از نوع خوشه ای بوده و رفتار غیرتصادفی بر آنها حاکم است. همچنین نتایج آماره I موران محلی بیانگر آن است که الگوی HH (بالا-بالا) و LL (پایین-پایین) در بیشتر امواج سرد با توالی های 3 تا n روزه وجود دارد و تعداد پهنه های حاوی الگوهای فوق در امواج کوتاه مدت بیشتر از امواج بلندمدت هستند. به عبارت دیگر، الگوی مکانی امواج سرد در طول موج های بلندتر نیز همگن بوده و کل استان از لحاظ فراوانی رخداد آنها دارای رفتار تصادفی می باشد. همچنین آزمون t تک نمونه ای فراوانی رخداد امواج سرد نشان دهنده رفتار غالب غیرتصادفی در توالی های کوتامدت و رفتار تصادفی در توالی های بلند مدت است.Spatial Pattern Analysis of Cold Waves in Guilan Province
Introduction Heat and cold waves are part of atmospheric extreme events that cause severe damage to human life and destroy the environment. A wave is a period that lasts for several days to several weeks. Heat and cold waves are considered extreme events that occur with increasing or decreasing temperature in cold and heat periods. Since temperature is one of the basic elements of climate, its sudden or short-term and long-term variations can change the climate structure of any place. Climatic hazards such as hot and cold waves, heavy snow, lightning, hail, heavy showers, floods and droughts threaten local people and travelers in Gilan province. Therefore, more detailed studies for the purpose of identification, monitoring, classification and spatial distribution of atmospheric hazards in this area are of great importance and it seems necessary to do it. Methodology In order to investigate the cold waves of Gilan province, the minimum daily temperature for 40 years (1980 to 2020) has been used. The minimum temperature data were obtained from the website of the European center for medium-range weather prediction under ERA5 version for 48° 32' to 50° 36' east longitude and 36° 33' to 38° 27' north latitude. The size of each cell is 0.25° × 0.25° and a matrix of 10 x 10 rows and columns was formed, which covers 100 cells in each measurement. In this research, the temperature threshold for detecting cold waves was the 10th percentile of the maximum daily temperature of each cell during 40 years. Based on this, 100 temperature thresholds were identified for 100 cells using the 40-year daily temperature time series. In this regard, two global and local Moran's I statistics were used to analyze the spatial pattern of cold waves. Results The results obtained from the calculation of global Moran’s I index on the frequency of occurrence of cold waves in different months of the year in Gilan province show a cluster pattern in all months and intervals. As a result, the behavior of the frequency of occurrence of cold waves in the area of Guilan province is non-random, and the assumption of randomness of the pattern is also rejected and its non-randomness is confirmed. It should be noted that the cluster pattern of the occurrence of cold waves in different months of the year is established in all three levels of 90, 95 and 99%, and the null hypothesis that the frequency pattern of cold waves is random is rejected and the null hypothesis based on the cluster pattern is accepted. In this regard, the results obtained from the local Moran's I statistic (Anselin) on the sequence of cold waves of 3 to 30 days showed that the high-high cluster pattern (HH) and the low-low cluster pattern (LL), in the form of small areas and large are distributed in Gilan province from the coast to the mountains. Of course, the above pattern in long-term cold wave sequences also have random behavior and the entire province is known as a homogeneous unit. In the case of short-term waves, this issue also indicates the establishment of a non-random and non-homogeneous pattern in Guilan province. Also, the important point that was observed in the single-sample t-test of the frequency of cold waves was that non-random behavior in short-term cold waves turns into non-random behavior towards long-term cold waves. This means that the heterogeneity in the frequency of occurrence of cold waves in shorter wavelengths is greater than in longer wavelengths, and in longer waves the whole area of the province becomes a more homogeneous area. Discussion & Conclusion Heat and cold waves are among the risks that have different effects depending on their duration, magnitude and frequency as well as the exposure of people, goods and the vulnerability of the territory in different climates. In this research, the calculation of global Moran's I index of the frequency of cold waves showed that in different months of the year, a cluster pattern dominates the frequency of cold waves. According to the calculated Z score values and comparing it with the standard Z score values at the confidence level of 90, 95 and 99 or the significance level of 0.1, 0.05 and 0.01, the cluster pattern is proven at all levels. The calculation of the local Moran's I statistic of the frequency of cold waves in different months of the year showed that the cluster pattern of LL and HH is established spatially and temporally in the area of Gilan province. As a result, it should be said that non-random behavior in short-term cold waves has turned into non-random behavior in the direction of long-term warm and cold waves, and the heterogeneity in the frequency of occurrence of cold waves is greater in shorter wavelengths than in longer wavelengths.
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