Impact of bias correction of regional climate model boundary conditions on the simulation of precipitation extremes
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Impact of bias correction of regional climate model boundary conditions on the simulation of precipitation extremes Youngil Kim1 · Eytan Rocheta1 · Jason P. Evans2 · Ashish Sharma1 Received: 8 April 2020 / Accepted: 12 September 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract An accurate description of changes in extreme rainfall events requires high resolution simulations. Regional climate models (RCMs), where GCM data are used to provide input boundary conditions, are widely used as a way to resolve finer spatial scale phenomena. A problem with this, however, is that the inherent systematic biases within the GCM simulation are transferred to the RCM through the model boundaries. In this work we focus on the impact of bias correction of lateral and lower boundary conditions on simulated extreme rainfall events. Here three bias correction approaches are investigated. In increasing order of complexity, these are corrections for the mean, mean and variance, and the nested bias correction (NBC) approach that also corrects for lag-1 autocorrelations at nested timescales. These corrections are implemented on six-hourly GCM data taken from the GCM simulations which are used to drive the RCM along the RCM lateral boundaries. To evaluate the performance of bias correction on simulation of extreme rainfall events, daily precipitation extremes indices from the World Meteorological Organization (WMO) Expert Team on Climate Risk and Sectoral Climate Indicators (ET-CRSCI) are used. The results show that bias correction on the boundary conditions produce the results in significant improvement in extremes indices. It is clear that sea surface temperature (SST) plays an important role in driving the simulation. The results indicate that within the domain (far from boundaries) the errors in precipitation extremes are strongly dependent on the RCM, with a smaller effect coming from changes in the lateral boundary conditions. Keywords Regional climate model · Boundary conditions · Bias correction · Extreme rainfall
1 Introduction The analysis of precipitation extremes has become increasingly important since both observations and model simulations indicate that rainfall intensity and variability are increasing on a global scale (Singleton and Toumi 2013). Managing risks from extreme rainfall events has become a key component in climate change adaptation pathways (Rojas et al. 2011; Kim et al. 2020). Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00382-020-05462-5) contains supplementary material, which is available to authorized users. * Ashish Sharma [email protected] 1
School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW 2052, Australia
Climate Change Research Centre and ARC Centre of Excellence for Climate System Science, University of New South Wales, Sydney, NSW, Australia
2
To inform adaptation studies, accurate assessments of changes in extreme rainfall events in high resolution simulations are ne
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