Added value analysis of a CMIP6-based downscaling ensemble for Australian climate projections

By using finer resolution modelling and locally representative model physics, regional climate models (RCMs) have the potential to improve the information provided by global climate models (GCMs). However, RCMs have their own biases and limitations due to remaining unresolved processes. It is therefore necessary to carefully assess RCM outputs through added value analyses. An ensemble of CMIP6-based 12–17-km regional climate projections has been produced for the Australian Climate Service (ACS) based on the Bureau of Meteorology’s regional climate modelling system (BARPA) and CSIRO’s Conformal Cubic Atmospheric Model (CCAM). The historical and potential future added value of this ensemble is assessed, focusing on extremes (cold, hot, wet and dry). Despite variations in added value across different GCM–RCM experiments, quantities, seasons and regions, BARPA and CCAM generally improve on their driving models for the historical period. Added value over ERA5 is generally small, and often negative for wet and dry extremes, especially for CCAM. The most consistent improvements in all GCM–RCM pairs are found for quantities containing daily minimum temperature, whereas hot days above 40°C show the least improvements. CNRM-ESM2-1-CCAM appears to have significant issues in most analysed quantities, especially related to maximum temperature and might not be recommended for downscaling or use by the community. Additionally, RCMs often predict different climate change signals than their driving models, for example the Murray Basin, which combined with the historical added value indicate plausible improvements in future climate projections.

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Publication Details

Journal
Journal of Southern Hemisphere Earth System Science
Published
2025-11-26
DOI
https://doi.org/10.1071/es25014
Primary Topic
Climate variability and models
Type
article
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article

Added value analysis of a CMIP6-based downscaling ensemble for Australian climate projections

Emma Howard, Benjamin Ng, Marcus Thatcher, Chun‐Hsu Su et al.
Journal of Southern Hemisphere Earth System Science
Climate variability and models
article

Added value analysis of a CMIP6-based downscaling ensemble for Australian climate projections

Emma Howard, Benjamin Ng, Marcus Thatcher, Chun‐Hsu Su, H. Ye, Christian Stassen
article en

Abstract

By using finer resolution modelling and locally representative model physics, regional climate models (RCMs) have the potential to improve the information provided by global climate models (GCMs). However, RCMs have their own biases and limitations due to remaining unresolved processes. It is therefore necessary to carefully assess RCM outputs through added value analyses. An ensemble of CMIP6-based 12–17-km regional climate projections has been produced for the Australian Climate Service (ACS) based on the Bureau of Meteorology’s regional climate modelling system (BARPA) and CSIRO’s Conformal Cubic Atmospheric Model (CCAM). The historical and potential future added value of this ensemble is assessed, focusing on extremes (cold, hot, wet and dry). Despite variations in added value across different GCM–RCM experiments, quantities, seasons and regions, BARPA and CCAM generally improve on their driving models for the historical period. Added value over ERA5 is generally small, and often negative for wet and dry extremes, especially for CCAM. The most consistent improvements in all GCM–RCM pairs are found for quantities containing daily minimum temperature, whereas hot days above 40°C show the least improvements. CNRM-ESM2-1-CCAM appears to have significant issues in most analysed quantities, especially related to maximum temperature and might not be recommended for downscaling or use by the community. Additionally, RCMs often predict different climate change signals than their driving models, for example the Murray Basin, which combined with the historical added value indicate plausible improvements in future climate projections.

Journal of Southern Hemisphere Earth System ScienceVol. 75(3)
Bureau of Meteorology (AU), Department of Environment and Natural Resources (PH)
Openalex Percentile: Top 65%
Climate variability and models
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