Updated Moving Forecasting Model of Air Maximum Temperature

Khalid Hashim,Saleem Ethaib,Sabeeh L Farhan,Nabeel Saleem Saad Al-Bdairi,Hussein Al-Bugharbee,Salah L Zubaidi

doi:10.1088/1755-1315/877/1/012032

Abstract

In the current study, a moving forecasting model is used for the purpose of forecasting maximum air temperature. A number of recordings are used for building the AR model and next, to forecasting some temperature values ahead. Then the AR model coefficients are updating due to shifting the training sample by adding new temperature values in order to involve the change in temperature time series behaviour. The current work shows a high performance all over the temperature time series, which considered in the analysis.

Highlights

Global warming and the variability of climate are likely to cause a substantial problem for the ecosystem and go worst based on different scenarios of climate change[1, 2]
The AR model coefficients are updating due to shifting the training sample by adding new temperature values in order to involve the change in temperature time series behaviour
The current work shows a high performance all over the temperature time series, which considered in the analysis

Summary

Introduction

Global warming and the variability of climate are likely to cause a substantial problem for the ecosystem and go worst based on different scenarios of climate change (i.e., the temperature increased)[1, 2]. The current work shows a high performance all over the temperature time series, which considered in the analysis. 1. Introduction Global warming and the variability of climate are likely to cause a substantial problem for the ecosystem and go worst based on different scenarios of climate change (i.e., the temperature increased)[1, 2].

Results

Conclusion