Investigating the variability of GCMs' simulations using time series analysis
Author(s) -
Babak ZolghadrAsli,
Omid BozorgHaddad,
Parisa Sarzaeim,
Xuefeng Chu
Publication year - 2018
Publication title -
journal of water and climate change
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.421
H-Index - 22
eISSN - 2408-9354
pISSN - 2040-2244
DOI - 10.2166/wcc.2018.099
Subject(s) - climatology , environmental science , structural basin , general circulation model , drainage basin , climatic variability , series (stratigraphy) , scale (ratio) , climate change , vulnerability (computing) , time series , principal component analysis , geology , geography , statistics , mathematics , computer science , oceanography , paleontology , cartography , computer security
The natural vulnerability to the climate change phenomenon due to the unique topographic and climatic conditions in the Middle East adds significance to an already important issue of evaluating the simulations of general circulation models (GCMs) in this region. To this end, this study employed time series analysis to evaluate GCMs9 simulations, in terms of the air temperature variable, with regard to the observed climatic behaviors of Karkheh River basin, Iran. Resultantly, each of the GCMs9 time series was broken down into three principal components (i.e., periodicity, trend, and stochastic component), and each component was analyzed accordingly. Results demonstrated that the simulations from different models significantly differed. Even though some models like CSIR-MK3.5 and INGV-SXG outperformed others in representing an accurate estimation of the historical climatic behavior of the southern plains of the Karkheh River, the GCMs could not provide a realistic simulation of the historical climatic behavior for the topographically challenging areas, like the northern mountainous parts of the basin. It should be noted that while the results from such analyses would shed light on the variability of the GCMs9 simulations in regional-scale studies, the results, under no circumstances, provide evidence indicating that one model is more accurate than another.
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