نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشجوی دکتری اقلیم شناسی دانشگاه لرستان، ایران
2 استادیار و مدیر گروه علوم جغرافیایی دانشگاه لرستان، ایران
3 استادیار علوم جغرافیایی دانشگاه لرستان، ایران
چکیده
برف، باران، تگرگ و باران ریزه از مهم‌ترین انواع بارش هستند که تغییرات آن‌ها باعث آثار و بازخوردهای منفی و مثبت در سایر پارامترهای اقلیمی می‌شوند که به دنبال آن تغییر در چرخه هیدرولوژیکی، منابع آب، سکونت‌گاه‌های انسانی و جانوری ایجاد می‌گردد. لذا با توجه به نگرانی‌های موجود، این پژوهش تغییرات تعداد روزهای بارشی مانند تگرگ، باران، برف و باران‌ریزه را در طول دوره آماری 1981-2010 برای ایستگاه کرمانشاه و ارتباط آن‌ها با دما و رطوبت نسبی را مورد واکاوی قرار داده است. جهت اطلاع از وضعیت نرمال بودن داده‌ها از آزمون کلموگروف- اسمیرنوف و آزمون شاپیرو ویلک استفاده شد و برای محاسبه ارتباط بین تعداد روز انواع بارش با دما و رطوبت نسبی از همبستگی پیرسون و روند تغییرات آن‌ها از من کندال، ضریب همبستگی پیرسون و تحلیل رگرسیون استفاده‌شده است. ضرایب تعیین تحلیل در مدل برف، نشان می‌دهد که 48 درصد از تغییرات برف در ایستگاه کرمانشاه به وسیله متغیرهای مستقل توجیه می‌شود. این رقم برای باران 37 درصد و باران‌ریزه 40 درصد برآورد شده است. آزمون‌های من کندال و رگرسیون نشان دادند که تعداد روزهای انواع بارش دارای روندی کاهشی بوده‌اند. تعداد روزهای باران از 7/65 درصد در دهه اول به 4/77 در دهه سوم رسیده است و از سهم سایر انواع بارشی کاسته شده است. کاهش دما بیش‌ترین تأثیر را بر فراوانی بارش برف و باران‌ریزه و افزایش دما باعث افزایش فراوانی باران و تگرگ در هنگام ورود توده‌های باران‌آور شده است.
کلیدواژه‌ها
عنوان مقاله [English]
Study of changes in the precipitation forms and clarify the relative humidity and temperature effects on them (Kermanshah station)
نویسندگان [English]
- saed Basati 1
- D. Yarahmadi 2
- B. Nasiri 3
چکیده [English]
The changes and oscillations of form and type of precipitation have positive and negative effects; therefore they play an important role in different dimensions of human life; moreover; their changes create secondary positive and negative feedbacks in other climate parameters; then they followed by hydrological cycle; water supplies; natural and artificial echosystem;human and animal inhabitance;security and economic change. Precipitation disorder and climate dryness are two main features of dry and semidry climate regions of climate regions of the world and specifically consequently, the continuous effects of climate changes have created worries for scientists, politicians, and public .In alliance with this, paying attention to the regime, severe and changes in precipitation form has got particular importance. Materials and methods First of all, hourly data of day numbers of precipitation forms, hail, rain, snow, and drizzle which are meteorology codes (WW) and daily precipitation of Kermanshah meteorology station were prepared. To study the normality of remainders Kolmogrove- Esmirnove test and shapir wilk test were used. By using the diagrams the constant of remainders variance was studied, since the data analysis used para meter testsand regression analyses it needs the data normality, enhance to use parameterric and Man Kendall, and non-parametric tests, Kolmogrove- Esmirnove test was used. The relation rate between the variables of precipitation forms day numbers and relative humidity was measured through pearson correlation method. To determine the process direction , type and time of change by tha use of Man Kendall statistic and graphic test, the MATLAB software was used, where first the statistics was calculated, and then the statistic aggregation abundance after that mathematics Ei and variance vi and man kendall index based on next relation were calculated. Results and discussion The highest deviant of measure among them relates to rain days numbers is 9.8, which snows that rain days numbers has the highest scattering. On the contrary , the temperature has the least measure deviation. The days with drizzle had the highest changeable coefficient of 124.5 in the statistic period. Which snows the changes of thisprecipitation form in statistic period are very high and forecasting the number of precipitation days is difficult. Also, ther is a fairly strong and firm correlation between precipitation forms eith the temperature and relative humidity, which is mainly significiant at 0.1 level and it justifies the hhigh validity and strong power among them and high effect rate of temperature and relative humidity on precipitation forms. The negative process was perceived for all precipitation forms in the all following three pearson ,regression and man Kendal tests in Kermanshah station during the statistic period. Regression coeficients show to some extent strong justification of changes in number of snow days by temperature and relative humidity parameters, namely 0.48 changes of number of snow days that will be determined by linear relation,where as the power of this test prediction hail with 0.2 showes the weakest rate, and it is a sign of weak power and validity of this test model in forecasting the hail changes. Maybe its cause relates to hail forming atmosphere different temperature layers. Temperature increase process and days nombers of precipitations forms have followed a converse linear grade, in other words, with the temperature increase in whole statistic period , precipitation days have been decreasethis relation of precipitation days nombers and relative humidity is aligned and direct. Conclusion The analysis determining coeficients in snow modelo shows that 0.48 of snow changes in Kermanshah station are justified by independent variables. This figure is estimated 0.37 for rain and 0.40 for precipitation. Man kendall and regression tests showed that day numbers of precipitation forms had reduction process.precipitation days numbers from 0.65 in first dacade have reached to 0.77 in third dacade, and other precipitation forms shares have been reduced as well. The temperature reduction has the highest effect on snow and precipitation abundance and temperature increase causes the rain increases and hail abundance during the arrival of rainy clouds.
کلیدواژه‌ها [English]
- Rain forms
- Regression
- Man kendall
- Kermanshah
- Kolmogrove- Esmirnove
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