آشکارسازی نوسانات اقلیمی با استفاده از روش آزمون همگنی نرمال استاندارد (مطالعه موردی: ایستگاه خرم‌آباد)

دماهای فرین امروزه از مهم ترین پارامترهای ا قلیمی است که برای اثبات تغییر اقلیم در یک منطقه روند آن را طی سال های گذشته مورد ارزیابی قرار می دهند. تحلیل روند سری های زمانی شاخص های حدی دما سبب شناخت بهتر رفتار گذشته و حال تغییرات اقلیمی می شود. پژوهش های انجام شده در جهان نیز به طور عمده نشانگر افزایش تدریجی میانگین دما است. در این تحقیق به منظور شناسایی نوسانات اقلیمی پارامترهای دمای حداقل و روزهای یخبندان از مشاهدات ایستگاه سینوپتیک خرم آباد در دوره آماری 2013 – 1984 استفاده شده است. هدف از این مطالعه در ابتدا آشکارسازی روند دمای حداقل به صورت ماهانه بوده است. از طرف دیگر برای تحلیل روند، سری های زمانی فصلی انتخاب گردید. روش های به کار رفته در این پژوهش برای تحلیل روند دمای حداقل استفاده از آزمون همگنی نرمال استاندارد مطلق ( snht ) بود. برای ترسیم نمودارهای تحلیل روند از آزمون آماری من کندال استفاده شده است. نتایج به دست آمده از روش های آماری استفاده شده در این پژوهش نشان داد که  سری های دما فاقد ناهمگنی معنی دار بودند و فراداده ایستگاه این همگنی را تایید می کند. بیش ترین و کم ترین تغییرات دمای حداقل به ترتیب در فصل زمستان و پاییز رخ داده است. آماره t من کندال برای دوره زمانی مورد مطالعه نشان از افزایش معنی داری دمای حداقل در بیشتر ماه ها داشته است. ولی روند دما در فصل پاییز دارای معنی داری کمتری نسبت به دیگر فصول مطالعه شده می باشد. بر همین اساس با مطالعه روند روزهای یخبندان در طول دوره آماری مورد مطالعه در فصل زمستان نتایج نشان داد که از شدت یخبندان کاسته شده است.

The Clarification of Climactic Fluctuations through SNHT Method (Case Study: Khorramabad Station)

Introduction The purpose of this study is to analyze the temperature trend in Khorramabad station, and an attempt has been made to provide a suitable method to ensure the accuracy of the data, which is the first time that this station is used. The statistical years (20132013) have been that the data in these years have been recorded in a coherent and regular manner and this data has been easier to access. In view of the above, this study intends to identify and modify possible inhomogeneity as much as possible in the first stage while examining the accuracy of data homogeneity before analyzing the trend. In the second stage, the analysis evaluates the trend of minimum temperature over 30 years. Data and Method The SNHT (Standard Normal Homogeneity Test) method is one of the most common methods for examining the homogeneity of temperature and precipitation data, which has been used by many researchers around the world. This method has been proposed by various researchers and for more accurate detection of atmospheric fluctuations from heterogeneity by nonatmospheric factors, this test is used by considering the reference series. In this method, the tested time series is based on the stability of the difference of parameter d between the temperature in the tested station and the reference series. Heterogeneity in the test series is revealed by changes in the d series. To reduce the spatial effect on temperature values, the relation (t ˍˍ t is used, where t is the average temperature value and r is the correlation coefficient between the subject and reference station (for example (t io ˍˍ to) and t jr ˍˍ tj)), respectively, temperature values It is in the test station and in each reference station. The parameter d in each time step i for k reference station is calculated based on the following equation. This test is performed by two methods of absolute standard normal homogeneity and relative normal standard homogeneity. Here, considering that only the time series of a station is examined, the absolute standard normal homogeneity method is used. In fact, this method is a necessity for climate research that must be done before any calculations, and after confirming the homogeneity of the data by the test, the rest of the research studies can be continued (Nassaji Zavareh, 1392: 58). Results and Discussion In this study, due to the lack of adjacent stations during the statistical period in the region, the absolute standard normal homogeneity method has been used to examine the homogeneity of the data. This test was used for monthly time series. The test results showed most of the monthly time series were homogeneous. In a number of months, heterogeneity was observed in the time series. Because the type of test used was an absolute test and the metadata did not confirm this heterogeneity, these heterogeneities could be attributed to natural atmospheric fluctuations. This result is consistent with the research of Peterson et al. (1998). Analysis of the plotted graphs shows that there is no heterogeneity based on this test, which is also confirmed by the metadata in Table (4). Because the meteorological station of Khorramabad city has been moved from the city centre to outside the city since 1981. Therefore, the data recorded from 1981 onwards are standard and acceptable. In this study, the length of the statistical period under study begins in 1984 and ends in 2013. Data homogenization results were performed by absolute homogeneity test for each month separately for 30 years. Altogether two results are obtained from the analyses: Two results are obtained: 1 The temperature of the minimum statistical period of thirty years has acceptable homogeneity. 2. Some inhomogeneity observed in April, May, June and July are due to weather conditions. Conclusion 1. The results of the SNHT test on the data showed that a series of heterogeneity is seen in the data process over 30 years, but it is not related to the displacement of the station, and it is related to the weather conditions. 2 The results of nonparametric IKendall test on the data and during the 30 years of the statistical period showed that the value of Tstatistic is significant in most months and the trend is also positive. 3 According to the Tstatistic of the nonparametric method IKendall, the trend of glacial intensity in Khorramabad station is decreasing, i.e. the days we had in this glacial station are decreasing and it shows the fact that the weather in Khorramabad city has an increasing trend. The results of this study are consistent with the research of other researchers such as Rahimzadeh (2011), and Shiravand et al. (2010). In relation to answering the research questions, it should be stated that this research, according to its title, is an analysis of the trend of minimum temperature and frosty days during 30 years. It is hoped that in other studies, researchers will address this issue in a more comprehensive manner, and these responses have only been proven using the statistical methods studied, if in addition to other atmospheric factors, factors such as The heat island in the city centre, the reduction of green space, the increase of carbon dioxide, etc. have always affected the climate of different regions. Therefore, all factors should be considered in the study of climate change in a region, which in this study, according to its title, is not an opportunity to research and describe the mentioned factors.