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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Main Authors: Javad Shafiei Shiva, David G. Chandler
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Atmosphere
Subjects:
Online Access:https://www.mdpi.com/2073-4433/11/6/587
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spelling 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
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