Projection of Future Heat Waves in the United States. Part I: Selecting a Climate Model Subset
The widespread increase in global temperature is driving more frequent and more severe local heatwaves within the contiguous United States (CONUS). General circulation models (GCMs) show increasing, but spatially uneven trends in heatwave properties. However, the wide range of model outputs raises t...
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doaj-1857fd61f78b4f089d534850bd1118262020-11-25T03:11:00ZengMDPI AGAtmosphere2073-44332020-06-011158758710.3390/atmos11060587Projection of Future Heat Waves in the United States. Part I: Selecting a Climate Model SubsetJavad Shafiei Shiva0David G. Chandler1Department of Civil and Environmental Engineering, Syracuse University, Syracuse, New York, NY 13210, USADepartment of Civil and Environmental Engineering, Syracuse University, Syracuse, New York, NY 13210, USAThe widespread increase in global temperature is driving more frequent and more severe local heatwaves within the contiguous United States (CONUS). General circulation models (GCMs) show increasing, but spatially uneven trends in heatwave properties. However, the wide range of model outputs raises the question of the suitability of this method for indicating the future impacts of heatwaves on human health and well-being. This work examines the fitness of 32 models from CMIP5 and their ensemble median to predict a set of heatwave descriptors across the CONUS, by analyzing their capabilities in the simulation of historical heatwaves during 1950–2005. Then, we use a multi-criteria decision-making tool and rank the overall performance of each model for 10 locations with different climates. We found GCMs have different capabilities in the simulation of historical heatwave characteristics. In addition, we observed similar performances for GCMs over the areas with a partially similar climate. The ensemble model showed better performance in simulation of historical heatwave intensity in some locations, while other individual GCMs represented heatwave time-related components more similar to observations. These results are a step towards the use of contemporary weather models to guide heatwave impact predictions.https://www.mdpi.com/2073-4433/11/6/587heatwaveglobal warmingdownscaled GCMbest modelmodel performancemulti-criteria decision-making |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Javad Shafiei Shiva David G. Chandler |
spellingShingle |
Javad Shafiei Shiva David G. Chandler Projection of Future Heat Waves in the United States. Part I: Selecting a Climate Model Subset Atmosphere heatwave global warming downscaled GCM best model model performance multi-criteria decision-making |
author_facet |
Javad Shafiei Shiva David G. Chandler |
author_sort |
Javad Shafiei Shiva |
title |
Projection of Future Heat Waves in the United States. Part I: Selecting a Climate Model Subset |
title_short |
Projection of Future Heat Waves in the United States. Part I: Selecting a Climate Model Subset |
title_full |
Projection of Future Heat Waves in the United States. Part I: Selecting a Climate Model Subset |
title_fullStr |
Projection of Future Heat Waves in the United States. Part I: Selecting a Climate Model Subset |
title_full_unstemmed |
Projection of Future Heat Waves in the United States. Part I: Selecting a Climate Model Subset |
title_sort |
projection of future heat waves in the united states. part i: selecting a climate model subset |
publisher |
MDPI AG |
series |
Atmosphere |
issn |
2073-4433 |
publishDate |
2020-06-01 |
description |
The widespread increase in global temperature is driving more frequent and more severe local heatwaves within the contiguous United States (CONUS). General circulation models (GCMs) show increasing, but spatially uneven trends in heatwave properties. However, the wide range of model outputs raises the question of the suitability of this method for indicating the future impacts of heatwaves on human health and well-being. This work examines the fitness of 32 models from CMIP5 and their ensemble median to predict a set of heatwave descriptors across the CONUS, by analyzing their capabilities in the simulation of historical heatwaves during 1950–2005. Then, we use a multi-criteria decision-making tool and rank the overall performance of each model for 10 locations with different climates. We found GCMs have different capabilities in the simulation of historical heatwave characteristics. In addition, we observed similar performances for GCMs over the areas with a partially similar climate. The ensemble model showed better performance in simulation of historical heatwave intensity in some locations, while other individual GCMs represented heatwave time-related components more similar to observations. These results are a step towards the use of contemporary weather models to guide heatwave impact predictions. |
topic |
heatwave global warming downscaled GCM best model model performance multi-criteria decision-making |
url |
https://www.mdpi.com/2073-4433/11/6/587 |
work_keys_str_mv |
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