چکیده:
در این پژوهش از دادههای روزانۀ ارتفاع ژئوپتانسیل تراز 500 هکتوپاسکال با تفکیک مکانی 1 درجه از پایگاه دادة ECMWF برای جنوبغرب آسیا و دادههای ایستگاهی بارش از سازمان هواشناسی کشور (1979 تا 2018) بهرهجویی شده است. تکنیک بکار رفته تحلیل مؤلفة اصلی و تحلیل خوشهای است. با این تحلیلها 9 الگوی گردشی شناسایی شدند. تغییرات الگوها در سطح 95 درصد معنا-داری، بوسیلة آزمون ناپارامتری منکندال آزموده و برای برآورد میزان تغییرات از تخمینگر شیب سن بهره گرفته شد. آزمون معناداری روند برای الگوهای زمستانی در فصل بارشهای ایران، روند معنادار افزایش ارتفاع ژئوپتانسیل؛ که منجر به کاهش شیو فشار و کاهش ناپایداری و نهایتاً تضعیف الگوهای بارشی زمستانی گردیده است را آشکار ساخت. روندهای معنادار مثبتِ ارتفاع ژئوپتانسیل، تداوم این شرایط را برای الگوهای تابستانی (افزایش پایداری، کاهش چرخندگی وکاهش بارش) نشان دادند. از 9 الگوی شناخته شده تنها برای یک الگوی فصل گذار روند معنادار منفی بر روی کشور مشاهده شد. این الگو با اندکی افزایش بارندگی بیانگر شکلگیری شرایط ناپایدار است که در صورت مهیا بودن رطوبت میتواند منجر به بارشهای فصل معتدل گردد. یافتهها نشان دادند که یک الگوی زمستانی بارشزا در دو دهۀ اخیر حذف شده و بجای آن یک الگوی تابستانی ظاهر گردیده است.
Extended AbstractIntroductionAtmospheric circulation patterns play an important role in the emergence of environmental phenomena, that is why the classification of weather systems is one of the main goals of synoptic climatology. With the advent of computers and advanced mathematical algorithms, such as principal component analysis (PCA) and cluster analysis (CA), as well as the availability of digital data, quantitative methods replaced manual methods. Most of the methods used and discussed for the classification of circulation patterns are based on the use of multivariate statistics, principal component analysis and clustering techniques. In this research, the same method is used to classify atmospheric circulation patterns. Due to the large amount of data, MATLAB software was used in this research. Materials and methods The statistical population of this research includes the precipitation station data of the National Meteorological Organization from 1979 to 2018, which were converted to grid data (2491 cells) with a resolution of 0.25 degrees using the kriging interpolation technique. For typification of daily geopotential height data of 500 hpa for the frame (coordinates) zero to seventy degrees east longitude and ten to sixty degrees north latitude from ECMWF medium-term atmospheric prediction center of Europe, ERA-INTERIM project from 1/1 It has been used for 14610 days from 1979 to 12/31/2018. The data were divided into two 20-year periods for a two-decade comparison. This framework was considered large enough to properly represent the circulation patterns affecting Iran's climate.Finally, the data matrix was prepared with two matrices with dimensions of 3621 x 7305. Then principal component analysis was performed on these two matrices. The purpose of this analysis is, on the one hand, to reduce the amount of data, and on the other hand, to classify and identify the most important patterns and changes in geopotential height of 500 hpa in the last two decades. To identify the types of weather and classify them, twelve components of the S matrix with a level of 500 hpa were used as the required input for the next step of classification. Then, 9 patterns or weather types were identified by cluster analysis. With the help of the Menkendall test and the Sen Slope estimator, the process of pattern changes was done both on time and on places (pixels).Results and Discussion Correlation coefficient parameter was used to identify similar patterns in two periods. In this way, three winter patterns, three temperate season patterns and two summer patterns were identified. Pattern 3 from the first period is a winter pattern and pattern 7 from the second period is a pattern with the features of the warm season, and no suitable pair was identified. These two patterns had the lowest correlation coefficient with each other. It is clearly seen that the CTA3 pattern, which was a winter pattern with heavy rainfall, was removed in the second period and the CTB7 pattern, which is a spring-summer pattern with little precipitation, was born instead.The Menkendall trend test on the patterns did not show a negative trend in the time series for any pattern. Two pairs of winter patterns have a significant positive trend, and pattern number 3 was removed. Two pairs of the temperate season pattern and two pairs of the summer pattern showed a significant positive trend, and the 7 summer pattern appeared in the second period. The trend test on the pixels of the region for the 1st winter pattern showed all of Southwest Asia with significant positive trends, which indicates the weakening of this pattern with warmer winters. The 2nd winter pattern in the eastern half of the country shows the weakening of the second cold season pattern with wide positive trends. Another noteworthy point is the significant negative trends for the pair of moderate CTA5B4 pattern significantly and widely over our country, which can lead to rain if other conditions are available.The two pairs of the summer pattern have covered almost the same range in terms of the significance of the trend and its values. Significant positive trends (increase in geopotential height) for summer patterns provide conditions for increasing stability, reducing vorticity and reducing precipitation.The analyzes carried out show that under the influence of climate change, a hotter and drier climate prevailed in our country in the last two decades. Figure 5 shows the rainfall maps of the country related to the circulation patterns obtained in this research. For all patterns, the expansion of low rainfall areas can be clearly seen. The comparison of the rainfall maps of the country related to the pair of winter patterns PA1, PB1 and PA2, PB2 and PA9, PB3 shows that in addition to the decrease in the rainfall of these patterns, their spatial distribution has also undergone significant changes and the core of the maximum rainfall is from The west of the country has shifted to the southwest.ConclusionA side-by-side comparison of the models showed significant changes for the models. The patterns that are associated with ridges on all or a large part of Iran are more frequent, which is consistent with the results of Masoudian's research (2006). The significant positive trend on the Sudan and Mediterranean circulation systems, which play an important role in the rains of the winter and autumn seasons of our country, revealed the weakening of these systems in the last two decades. These results are in harmony with the research of Alizadeh (2013) and Darend (2014). Another result of this research is that the patterns of Iran's rainy seasons (winter and autumn) have weakened significantly in the past two decades. Significant positive High geopotential trends for summer patterns showed increasing stability and strengthening of these patterns.Significant positive High geopotential trends for summer patterns showed increasing stability and strengthening of these patterns. Also, the CTA4B5 seasonal pattern pair showed significant negative trends over a wide part of the country, the nature of this pattern determined that with the establishment of the CTB5 pattern (second period pair) in case of access to moisture, it is possible to have widespread rains in the country. provided Correlation coefficients identified two inconsistent patterns. The CTA3 pattern is a winter pattern with heavy rainfall that has not occurred in the last two decades and can be said to have disappeared, and instead the CTB7 pattern is a summer pattern that has appeared with a frequency of 10.7% in the last two decades.