Evaluation of Dynamically Downscaled CMIP6‐CCAM Models Over Australia
Abstract High‐resolution climate change projections are increasingly necessary to inform climate policy and adaptation planning. Downscaling of global climate models (GCMs) is required to simulate the climate at the spatial scale relevant for local impacts. Here, we dynamically downscaled 15 CMIP6 G...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-11-01
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| Series: | Earth's Future |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2023EF003548 |
| _version_ | 1827378938945470464 |
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| author | Sarah Chapman Jozef Syktus Ralph Trancoso Marcus Thatcher Nathan Toombs Kenneth Koon‐Ho Wong Alicia Takbash |
| author_facet | Sarah Chapman Jozef Syktus Ralph Trancoso Marcus Thatcher Nathan Toombs Kenneth Koon‐Ho Wong Alicia Takbash |
| author_sort | Sarah Chapman |
| collection | DOAJ |
| description | Abstract High‐resolution climate change projections are increasingly necessary to inform climate policy and adaptation planning. Downscaling of global climate models (GCMs) is required to simulate the climate at the spatial scale relevant for local impacts. Here, we dynamically downscaled 15 CMIP6 GCMs to a 10 km resolution over Australia using the Conformal Cubic Atmospheric model (CCAM), creating the largest ensemble of high‐resolution downscaled CMIP6 projections for Australia. We compared the host CMIP6 models and downscaled simulations to the Australian Gridded Climate Data (AGCD) observational data and evaluated performance using the Kling‐Gupta efficiency and Perkins skill score. Downscaling improved performance over host GCMs for seasonal temperature and precipitation (10% and 43% respectively), and for annual cycles of temperature and precipitation (6% and 13% respectively). Downscaling also improved the fraction of dry days, reducing the bias for too many low‐rain days. The largest improvements were found in climate extremes, with enhancements to extreme minimum temperatures in all seasons varying from 142% to 201%, and to extreme precipitation of 52% in Austral winter and 47% in summer. The ensemble average integrated skill score improved by 16%. Temperature and precipitation biases were reduced in mountainous and coastal areas. CCAM downscaling outperformed host CMIP6 GCMs at multiple spatial scales and regions—continental Australia, Australian IPCC regions and Queensland's regions—with integrated added value ranging from 9% to 150% and higher over densely populated regions more exposed to climate impacts. This data set will be a valuable resource for understanding future climate changes in Australia. |
| first_indexed | 2024-03-08T13:04:02Z |
| format | Article |
| id | doaj.art-343d607065ed477282b17745cc11e119 |
| institution | Directory Open Access Journal |
| issn | 2328-4277 |
| language | English |
| last_indexed | 2024-03-08T13:04:02Z |
| publishDate | 2023-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | Earth's Future |
| spelling | doaj.art-343d607065ed477282b17745cc11e1192024-01-18T22:26:39ZengWileyEarth's Future2328-42772023-11-011111n/an/a10.1029/2023EF003548Evaluation of Dynamically Downscaled CMIP6‐CCAM Models Over AustraliaSarah Chapman0Jozef Syktus1Ralph Trancoso2Marcus Thatcher3Nathan Toombs4Kenneth Koon‐Ho Wong5Alicia Takbash6Department of Environment and Science Queensland Government Brisbane QLD AustraliaSchool of the Environment The University of Queensland Brisbane QLD AustraliaDepartment of Environment and Science Queensland Government Brisbane QLD AustraliaCSIRO Environment Melbourne VIC AustraliaDepartment of Environment and Science Queensland Government Brisbane QLD AustraliaQueensland Fire and Emergency Services Queensland Government Brisbane QLD AustraliaCSIRO Environment Melbourne VIC AustraliaAbstract High‐resolution climate change projections are increasingly necessary to inform climate policy and adaptation planning. Downscaling of global climate models (GCMs) is required to simulate the climate at the spatial scale relevant for local impacts. Here, we dynamically downscaled 15 CMIP6 GCMs to a 10 km resolution over Australia using the Conformal Cubic Atmospheric model (CCAM), creating the largest ensemble of high‐resolution downscaled CMIP6 projections for Australia. We compared the host CMIP6 models and downscaled simulations to the Australian Gridded Climate Data (AGCD) observational data and evaluated performance using the Kling‐Gupta efficiency and Perkins skill score. Downscaling improved performance over host GCMs for seasonal temperature and precipitation (10% and 43% respectively), and for annual cycles of temperature and precipitation (6% and 13% respectively). Downscaling also improved the fraction of dry days, reducing the bias for too many low‐rain days. The largest improvements were found in climate extremes, with enhancements to extreme minimum temperatures in all seasons varying from 142% to 201%, and to extreme precipitation of 52% in Austral winter and 47% in summer. The ensemble average integrated skill score improved by 16%. Temperature and precipitation biases were reduced in mountainous and coastal areas. CCAM downscaling outperformed host CMIP6 GCMs at multiple spatial scales and regions—continental Australia, Australian IPCC regions and Queensland's regions—with integrated added value ranging from 9% to 150% and higher over densely populated regions more exposed to climate impacts. This data set will be a valuable resource for understanding future climate changes in Australia.https://doi.org/10.1029/2023EF003548Australian climateCMIP6conformal cubic atmospheric modelregional climate modeldynamical downscalinghigh‐resolution projections |
| spellingShingle | Sarah Chapman Jozef Syktus Ralph Trancoso Marcus Thatcher Nathan Toombs Kenneth Koon‐Ho Wong Alicia Takbash Evaluation of Dynamically Downscaled CMIP6‐CCAM Models Over Australia Earth's Future Australian climate CMIP6 conformal cubic atmospheric model regional climate model dynamical downscaling high‐resolution projections |
| title | Evaluation of Dynamically Downscaled CMIP6‐CCAM Models Over Australia |
| title_full | Evaluation of Dynamically Downscaled CMIP6‐CCAM Models Over Australia |
| title_fullStr | Evaluation of Dynamically Downscaled CMIP6‐CCAM Models Over Australia |
| title_full_unstemmed | Evaluation of Dynamically Downscaled CMIP6‐CCAM Models Over Australia |
| title_short | Evaluation of Dynamically Downscaled CMIP6‐CCAM Models Over Australia |
| title_sort | evaluation of dynamically downscaled cmip6 ccam models over australia |
| topic | Australian climate CMIP6 conformal cubic atmospheric model regional climate model dynamical downscaling high‐resolution projections |
| url | https://doi.org/10.1029/2023EF003548 |
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