Influence of bias-correcting global climate models for regional climate simulations over the CORDEX-Australasia domain u
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ORIGINAL PAPER
Influence of bias-correcting global climate models for regional climate simulations over the CORDEX-Australasia domain using WRF Karuru Wamahiu1
· Jatin Kala1 · Julia Andrys1
Received: 18 April 2019 / Accepted: 3 May 2020 © Springer-Verlag GmbH Austria, part of Springer Nature 2020
Abstract Regional climate models (RCMs) are used to dynamically downscale global climate models (GCMs) to provide highresolution projections of future climate change to better inform policy and decision making at the regional scale. However, biases from GCMs are transferred to RCMs and this can limit the usefulness of the regional climate projections. This paper investigates the influence of bias correcting 4 GCMs from the Coupled Model Intercomparison Project 3, for regional climate simulations over the CORDEX-Australasia domain using Weather Research and Forecasting. The GCM outputs are bias corrected against ERA-Interim reanalysis as a surrogate truth. Results show that over decadal time scales bias correction removes large systematic precipitation and temperature biases. However, bias correction also introduced biases where there were none, introduced biases of the opposite sign, or enhanced existing biases in other regions in some instances. The dynamical mechanisms driving the changes in the biases are explored. Keywords Australia · CORDEX · Bias correction · Regional climate modeling · Weather research and forecasting model
1 Introduction Regional climate models (RCMs) are used to investigate changes in regional climate by dynamically downscaling global climate models (GCMs) and reanalysis products to provide higher spatio-temporal resolution simulations (e.g., Schmidli et al. (2006), Christensen and Christensen (2007), and Rummukainen (2010)). This has led to initiatives such as the Coordinated Regional Climate Downscaling Experiment (CORDEX) of the World Climate Research Program to promote a consistent method for regional downscaling experiments improving the quality of experiment outcomes
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00704-020-03254-9) contains supplementary material, which is available to authorized users. Karuru Wamahiu
[email protected] Julia Andrys [email protected] 1
Environmental and Conservation Sciences and Centre for Climate Impacted Terrestrial Ecosystems, Harry Butler Institute, Murdoch University, Murdoch, WA 6150, Australia
(Giorgi et al. 2009). RCMs add value by being able to better resolve mesoscale atmospheric processes, such as sea breezes, and account for the influence of topography and land use on regional climatology (Feser et al. 2011). Their ability to add value has been demonstrated in a number of regions, including North America (Mearns et al. 2009), southwest Germany (Feldmann et al. 2008), Southeast Asia (Chotamonsak et al. 2011), southeast Australia (Evans and McCabe 2013), and southwest Western Australia (Kala et al. 2011; Andrys et al. 2015). For example, Evans and McCabe (2010) dynamically downscal
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