Performance assessment of general circulation models: application of compromise programming method and global performance indicator technique

Selection of an appropriate ensemble of General Circulation Models (GCMs) is vital to properly assess the impacts of climate change in a region. Several methods exist for the ranking and selection of GCMs. The present study compares the commonly-used Compromise Programming (CP) method and the recent...

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Vydané v:	Stochastic environmental research and risk assessment Ročník 36; číslo 6; s. 1761 - 1778
Hlavní autori:	Deepthi, B., Sivakumar, Bellie
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2022 Springer Nature B.V
Predmet:	Aquatic Pollution Business metrics Chemistry and Earth Sciences Climate change Climate models Computational Intelligence Computer Science Decision making Earth and Environmental Science Earth Sciences Environment Environmental impact General circulation models Indicators Math. Appl. in Environmental Science Original Paper Performance assessment Performance evaluation Physics Probability Theory and Stochastic Processes Rainfall Ranking River basins Statistics for Engineering Waste Water Technology Water Management Water Pollution Control Global performance indicator technique Compromise programming method Kling–Gupta efficiency Ranking General circulation models SPAtial EFficiency metric
ISSN:	1436-3240, 1436-3259
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Abstract	Selection of an appropriate ensemble of General Circulation Models (GCMs) is vital to properly assess the impacts of climate change in a region. Several methods exist for the ranking and selection of GCMs. The present study compares the commonly-used Compromise Programming (CP) method and the recently-developed Global Performance Indicator (GPI) technique for ranking the GCMs. The ability of 20 GCMs to simulate the observed monthly rainfall over the period 1961–2005 in the Upper Godavari River basin in India is assessed, and a grid-wise analysis is performed. The SPAtial EFficiency (SPAEF) metric and Kling–Gupta Efficiency (KGE) are used as the performance indicators to evaluate the 20 GCMs. Further, both the CP method and the GPI technique are applied to integrate the values of the performance indicators into one. The group decision-making (GDM) approach is employed to make a collective decision about the rank of the 20 GCMs considering all the grids. The results from the CP method suggest that the best models are MPI-ESM-P, MPI-ESM-LR, and CNRM-CM5-2, whereas those from the GPI technique indicate that the best-performing GCMs are NorESM1-M, FIO-ESM, and MPI-ESM-LR. An analysis is also performed to examine whether the ranking of the GCMs identified based on the grid-wise analysis also holds true when the average rainfall over the entire basin is considered for ranking. To this end, the average rainfall value across all the 12 grids in the basin is used for the evaluation. The ensemble of GCMs identified by the grid-wise study of GCMs using the CP method provides better SPAEF and KGE values when compared to that using the GPI technique. These results suggest that the GCMs have to be evaluated at the individual grids, and then collective information has to be taken to identify the ensemble of the best-performing GCMs.
AbstractList	Selection of an appropriate ensemble of General Circulation Models (GCMs) is vital to properly assess the impacts of climate change in a region. Several methods exist for the ranking and selection of GCMs. The present study compares the commonly-used Compromise Programming (CP) method and the recently-developed Global Performance Indicator (GPI) technique for ranking the GCMs. The ability of 20 GCMs to simulate the observed monthly rainfall over the period 1961–2005 in the Upper Godavari River basin in India is assessed, and a grid-wise analysis is performed. The SPAtial EFficiency (SPAEF) metric and Kling–Gupta Efficiency (KGE) are used as the performance indicators to evaluate the 20 GCMs. Further, both the CP method and the GPI technique are applied to integrate the values of the performance indicators into one. The group decision-making (GDM) approach is employed to make a collective decision about the rank of the 20 GCMs considering all the grids. The results from the CP method suggest that the best models are MPI-ESM-P, MPI-ESM-LR, and CNRM-CM5-2, whereas those from the GPI technique indicate that the best-performing GCMs are NorESM1-M, FIO-ESM, and MPI-ESM-LR. An analysis is also performed to examine whether the ranking of the GCMs identified based on the grid-wise analysis also holds true when the average rainfall over the entire basin is considered for ranking. To this end, the average rainfall value across all the 12 grids in the basin is used for the evaluation. The ensemble of GCMs identified by the grid-wise study of GCMs using the CP method provides better SPAEF and KGE values when compared to that using the GPI technique. These results suggest that the GCMs have to be evaluated at the individual grids, and then collective information has to be taken to identify the ensemble of the best-performing GCMs.
Author	Sivakumar, Bellie Deepthi, B.
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SubjectTerms	Aquatic Pollution Business metrics Chemistry and Earth Sciences Climate change Climate models Computational Intelligence Computer Science Decision making Earth and Environmental Science Earth Sciences Environment Environmental impact General circulation models Indicators Math. Appl. in Environmental Science Original Paper Performance assessment Performance evaluation Physics Probability Theory and Stochastic Processes Rainfall Ranking River basins Statistics for Engineering Waste Water Technology Water Management Water Pollution Control
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Title	Performance assessment of general circulation models: application of compromise programming method and global performance indicator technique
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