Open AccessForecasting of Air Maximum Temperature on Monthly Basis Using Singular Spectrum Analysis and Linear Autoregressive Model
Author(s) -
Nabeel Saleem Saad Al-Bdairi,
Salah L. Zubaidi,
Hussein Al-Bugharbee,
Khalid Hashim,
Sabeeh Lafta Farhan,
Asad Al Defae
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/877/1/012033
Subject(s) - singular spectrum analysis , autoregressive model , series (stratigraphy) , air temperature , time series , spectral analysis , mathematics , linear model , basis (linear algebra) , econometrics , meteorology , statistics , algorithm , singular value decomposition , physics , geology , paleontology , quantum mechanics , spectroscopy , geometry
In this research, the singular spectrum analysis technique is combined with a linear autoregressive model for the purpose of prediction and forecasting of monthly maximum air temperature. The temperature time series is decomposed into three components and the trend component is subjected for modelling. The performance of modelling for both prediction and forecasting is evaluated via various model fitness function. The results show that the current method presents an excellent performance in expecting the maximum air temperature in future based on previous recordings.