Journal of Statistical Theory and Practice

, Volume 11, Issue 4, pp 604–633 | Cite as

Seasonal time-series modeling and forecasting of monthly mean temperature for decision making in the Kurdistan Region of Iraq

  • Tara Ahmed Chawsheen
  • Mark BroomEmail author


A generalized structural time-series modeling framework was used to analyze the monthly records of mean temperature, one of the most important environmental parameters, using classical stochastic processes. In this article we are using the SARIMA Box-Jenkins model and obtain a medium-term (10 years) forecast of the mean temperature in Erbil. A prediction of the monthly mean temperature during the past 287 months (≃24 years) using the SARIMA(0,1,2)(0,1,1)12 model predicts that the average temperature in the governorate of Erbil, Iraq, will be stable for the next 10 years. The evaluation of prediction accuracy shows that our model performs equally well when applying it to different periods of time for which data is available. The method used here could easily be applied by the decision makers responsible for providing water and electricity in the Kurdistan Region.


Climate change forecasting Fourier method Kurdistan Region of Iraq SARIMA model stochastic process 

AMS Subject Classification



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© Grace Scientific Publishing, 20 Middlefield Ct, Greensboro, NC 27455 2017

Authors and Affiliations

  1. 1.Department of MathematicsCity, University of LondonLondonUnited Kingdom

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