|  درخواست عضويت  |  رمز خود را فراموش کرده ايد؟  |  ورود اعضا [Sign in]
جستجوي پيشرفته مطالب   |  
 جستجو:  
بكارگيري تبديل موجك گسسته براي تحليل روند و شناسايي الگوهاي نوساني دما (مطالعه موردي: ايستگاه سينوپتيك مشهد)
magiran.com >  نشريه آب و خاك >سال بيست و نهم، شماره 1 > متن
مشخصات نشريه
آخرين شماره
آرشيو شماره هاي گذشته
جستجوي مطالب
سايت اختصاصي
تماس با نشريه
ارسال الکترونيکي مقاله
شماره جديد اين نشريه
سال سي و دوم
شماره 2
خرداد و تير 1397


 راهنمای موضوعی نشريات
اين نشريه در گروه(های) زير قرار گرفته است:
1 آب و خاک

خدمات سايت




 


Journal of water and soil, 2015(Issue 1)



Title:
Using Discrete Wavelet Transform for Trend Analysis and Oscillatory Patterns Identification of Temperature (Case Study: Mashhad Synoptic Station)


Author(s):
A.R. Araghi* , M. Mousavi Baygi , S. M. Hasheminia

Paper language: Persian


Abstract:
Introduction: Studying long-term trend changes of meteorological parameters is one of the routine methods in atmospheric studies, especially in the climate change subject. Among the meteorological parameters, temperature is always considered as one of the most atmospheric elements and studying it in order to gain a better understanding of the climate change phenomenon, has been effective. In addition to identifying trends, extraction of oscillatory patterns in the atmospheric phenomena and parameters occurrence can be an applicable and reliable method to explore the complex relations between atmospheric-oceanic cycles and short term or long term consequences of meteorological parameters.

Materials and Methods: In this paper, monthly average temperature time series in Mashhad synoptic station in 55 years period (from 1956 to 2010) in monthly, seasonal, annual and seasons separately (winter, spring, summer and autumn) have been analyzed. Discrete wavelet transform and Mann-Kendall trend test were the main methods for performing this research. Wavelet transform is a powerful method in signal processing and it is an advanced version of short time Fourier transforms. Moreover, it has many improvements and more capabilities compared with Fourier transform. In the first step, temperature time series in various time scales (which was mentioned above) have been decomposed via discrete wavelet transforms into approximation (A) and detail (D) components. For the second step, Mann-Kendall trend test was applied to the various combinations of these decomposed components. For detecting the most dominant periodic component for each of the time scales datasets, results of Mann-Kendall test for the original time series and the decomposed components were compared to each other. The nearest value indicated the most dominant periodicity based on the D component’s level. To detect the similarity between results of the Mann-Kendall test, relative error method was employed. Additionally, it must be noted that before applying Mann-Kendall test, time series has to be assessed for its autocorrelation status. If there are seasonality patterns in the studied time series or lag-1 autocorrelation coefficient of data is significant, then some modified versions of the Mann Kendall test have to be employed.

Results and Discussion: Results of this study showed that the temperature trend at every time scaled dataset (monthly, seasonal, annual and seasons separately) is positive and significant. Autocorrelation coefficients indicated that only seasonal time series and winter datasets did not have significant ACFs. On the other hand, monthly and seasonal datasets had seasonality pattern. Based on these results, Hirsch and Slack’s modified version of Mann-Kendall test was employed for monthly and seasonal time series and for the winter temperature data, the original version of the Mann-Kendall test was applied. For the remaining time series, the Hamed and Rao’s modified version of the Mann-Kendall trend test was employed. Dominant periodicities in monthly, seasonal and annual, confirmed the oscillatory behavior of each other. However, in the seasons, it seems that periodic patterns with the same temperature ranges are more similar. On the other hand, due to the greater similarity between the results of the Mann-Kendall test in the warmer seasons and the data with monthly, seasonal and annual time scale, it seems that yearly warm period has more noticeable impacts on the positive and significant trend of temperature in the study area. It must be noted that in any of the studied time series, results of the Mann-Kendall test for detail (D) component was not significant and after adding approximation (A) component, Mann-Kendall statistics turned to a significant value. This happens because the long term variations or trends appear in approximation components in most of the time series.

Conclusion: In this study, a powerful signal processing method called wavelet transform was employed to detect the most dominant periodic components in temperature time series in various time scales, in Mashhad synoptic station. Results showed that using frequency-time analysis methods has more benefits compared with the use of only classic statistical methods, since one can explore any time series with more accuracy. Because most of the meteorological variables have periodic structures, it seems that using advanced signal processing methods like wavelet for analysis of these variables can have many advantages compared with linear-based methods. It can be suggested for future studies to use and employ signal processing methods for exploring the large scaled phenomena (e.g. ENSO, NAO, etc.) and discovering the relationship between these phenomena and climate change in recent decades.








Keywords:
Discrete wavelet transforms, Mann, Kendall test, Oscillatory pattern, Trend
 

دوست گرامي:

    با تشکر از همراهي شما به اطلاع مي رساند مطالعه متن مقالات نشريات و خدمات اختصاصي اين سايت تنها براي اعضا و با پرداخت حق عضويت (اشتراک طلايي) امکان پذير است.

  هزینه حق عضویت سالانه(اشتراک طلایی):

  • مشترکان داخل کشور     250.000 ريال (100 مقاله اعتبار اولیه) پرداخت با همه کارتهای بانکی
  • مشترکان خارج از کشور   50 دلار  (100 مقاله اعتبار اولیه) پرداخت با  Paypal
  اگر عضو سايت هستيد:
     شناسه کاربري:
     رمز عبور:

  اگر عضو سايت نيستيد:
شما با تکميل فرم عضويت و تاييد نشاني ايميل خود در سايت "بانک اطلاعات نشريات کشور magiran.com"  مي توانيد از امکانات اختصاصي اين سايت به شرح زير استفاده نماييد.:
  • دسترسي به متن مقالات پس از پرداخت حق عضويت و فعال سازی اشتراک طلايي
  • استفاده از  فروشگاه سايت و سفارش اينترنتي اشتراک نسخه چاپي نشريات با 10 درصد تخفيف
  • ايجاد فهرست نشريات مورد علاقه براي دسترسي سريع
  • اطلاع از انتشار نشريات مورد علاقه از طريق پست الکترونيکي
  • دريافت روزانه سرخط مطالب روزنامه هاي عضو بر اساس کلمات انتخابي خودتان تا سقف 10 عنوان


آيا مايل به عضويت در بانک اطلاعات نشريات کشور هستيد؟ 
(رايگان)

          

 



 

 

 
 
ارسال مطلب به دوستان
نظر بدهيد
ثبت در فهرست علائق

معرفی سايت به ديگران
گزارش اشکال در اطلاعات
اشتراک نشريات ديگر
 جستجوی مطالب
کلمه مورد نظر خود را وارد کنيد

جستجو در:
آرشيو اين مجله
همه مجلات عضو
مجلات علمی مصوب
متن روزنامه های عضو
    
جستجوی پيشرفته



 

اعتماد
ايران
جام جم
دنياي اقتصاد
رسالت
شرق
كيهان
 پيشخوان
فصلنامه انديشه ديني
متن مطالب شماره 66، بهار 1397را در magiran بخوانيد.

 

 

 

سايت را به دوستان خود معرفی کنيد    
 1397-1380 کليه حقوق متعلق به سايت بانک اطلاعات نشريات کشور است.
اطلاعات مندرج در اين پايگاه فقط جهت مطالعه کاربران با رعايت شرايط اعلام شده است.  کپی برداري و بازنشر اطلاعات به هر روش و با هر هدفی ممنوع و پيگيرد قانوني دارد.
 

پشتيبانی سايت magiran.com (در ساعات اداری): 77512642  021
تهران، صندوق پستی 111-15655
فقط در مورد خدمات سايت با ما تماس بگيريد. در مورد محتوای اخبار و مطالب منتشر شده در مجلات و روزنامه ها اطلاعی نداريم!
 


توجه:
magiran.com پايگاهی مرجع است که با هدف اطلاع رسانی و دسترسی به همه مجلات کشور توسط بخش خصوصی و به صورت مستقل اداره می شود. همکاری نشريات عضو تنها مشارکت در تکميل و توسعه سايت است و مسئوليت چگونگی ارايه خدمات سايت بر عهده ايشان نمی باشد.



تمامي خدمات پایگاه magiran.com ، حسب مورد داراي مجوزهاي لازم از مراجع مربوطه مي‌باشند و فعاليت‌هاي اين سايت تابع قوانين و مقررات جمهوري اسلامي ايران است