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Journals / Gazi University Journal of Science / 2015 / Cilt: 28 - Sayı: 4

A Time Series Approach for Precipitation in Turkey

Mesut BALIBEY
Serpil TÜRKYILMAZ
Pages
549–559
Publication Date
2015-01-06
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In conclusion, it is observed that the sinusoidal model predictions are more appropriate than ARIMA techniques and usual generalized linear model (GLM) techniques.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The climate that has a dynamic structure varies continuously.
📊
Key Findings & Data:In this study, statistical analysis is applied to historical data set consisted of monthly precipitation totals (mm.) which are provided by the Turkish State Meteorological Service(TSMS) for 1999-2010 period in Turkey.
💡
Conclusion & Impact:In conclusion, it is observed that the sinusoidal model predictions are more appropriate than ARIMA techniques and usual generalized linear model (GLM) techniques.
🔬Design:Modeling & Simulation
📍Scope:2010 Verileri
⚙️Variables:Precipitation · Periodicity · Time Series Model

Abstract

The climate that has a dynamic structure varies continuously. Basic climatological features of any region depend on many meteorological variables, such as precipitation and temperature records. The changes in these two variables reveal important clues about climate variations. Turkey is one of the sensitive areas for climate variation around the world. In this study, statistical analysis is applied to historical data set consisted of monthly precipitation totals (mm.) which are provided by the Turkish State Meteorological Service(TSMS) for 1999-2010 period in Turkey. Furthermore, a sinusoidal model for each region obtained by using a time series method is proposed in order to obtain a sinusoidal form for the precipitation to each region. Besides a basic form of Frequency Domain Techniques, usual Box-Jenkins ARIMA approach is applied in this study. In conclusion, it is observed that the sinusoidal model predictions are more appropriate than ARIMA techniques and usual generalized linear model (GLM) techniques.

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Cite This Article

BALIBEY, M., TÜRKYILMAZ, S. (2015). A Time Series Approach for Precipitation in Turkey. Gazi University Journal of Science, Cilt: 28 - Sayı: 4, 549–559. https://ajindex.com/articles/254523

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References (14)

  1. Karabulut, M. and Cosun, F. (2009). Kahramanmaraş İlinde Yağışların Trend Analizi, Coğrafi Bilimler Dergisi, 7(1), 65-83.
  2. Shi, C., Wang, H. and Yin, F. (2011).
  3. Monthly Rainfall Periodicities, The 6th International Forum on Strategic Technology, 1239-1242. with Hidden Bahadır, M. and Özdemir, M.Ali, (2011). Trabzon ve Rize’ de Yağışın Mevsimsel Değişimlerinin Marginal ve Matrix Yöntemleri ile Belirlenmesi ve Trend Araştırmalar Dergisi, Cilt:4, Sayı:7, 457-473. arası Sosyal [4] Bahadır, M. (2011). Türkiye’ de İklim Değişikliğinin İklim Bölgelerine Yansımasında Kuzey-Güney Yönlü Sıcaklık ve Yağış Değişim Öngörüleri, Uluslararası Hakemli Sosyal Bilimler E-Dergisi, 26, 1-18.
  4. Tularam, G.A. and Ilahee, M. (2010). Time Series Analysis of Rainfall and Temperature Interactions in Coastal Catchments, Journal of Mathematics and Statistics, 6(3), 372-380.
  5. Türkeş, M., Koç, T. and Sarış, F. (2009). Spatiotemporal Variability of Precipitation Total Series Over Turkey, International Journal of Climatology, 29, 1056-1074.
  6. Çiçek, İ. and Ataol, M. (2009). Türkiye’ nin Su Potansiyelinin Belirlenmesinde Yeni Bir Yaklaşım, Coğrafi Bilimler Dergisi, 7(1), 51-64.
  7. Stathis, D. and Myronidis, D. (2009). Principal Component Analysis of Precipitation in Thessaly Region, Global NEST Journal, Vol.11, No.4, 467- 476. Beare, S., Chambers, R. and Peak, S. (2009). Statistical Modelling of Rainfall Enhancement, Centre for Statistical and Survey Methodology Working Paper, 1-32.
  8. Unkasevic, M. and Tosic, I. (2009). Statistical Analysis of Precipitation in Belgrade and Nis, Geophysical Research Abstracts, Vol.11, EGU, 2009-2824.
  9. Türkeş, M., Koç, T. and Sarış, F. (2007). Türkiye’ nin Yağış Toplamı ve Yoğunluğu Dizilerindeki Değişikliklerin ve Eğilimlerin Zamansal ve Alansal http://dergiler.ankara.edu.tr/dergiler/33/830/10494. pdf, 5(1), 57-73.
  10. Çözümlemesi, Afriyie, K.O. and Adukpo, D.C. (2006). Spectral Characteristics of the Annual Mean Rainfall Series in Ghana, West Africa Journal of Applied Ecology, 9, 1-9.
  11. Partal, T. and Kahya, E. (2006). Trend Analysis in Turkish Processes, 20, 2011-2026.
  12. Data, Hydrological Brunetti, M. (2004) Changes in Daily Precipitation Frequency and Distribution in Italy over the Last 120 Years, Journal of Geophysical Research, Vol.109, 1-16.
  13. Gil-Alana, L.A. (2004). A Fractionally Integrated Model for Some Indian Monthly Rainfall Data, J. Indian Inst. Sci., 84, 1-20.
  14. Türkeş, M. and Erlat, E. (2003). Precipitation Changes and Variability in Turkey Linked to the North Atla