Abstract
Abstract. General circulation models (GCMs) are the primary tools for evaluating the possible impacts of climate change; however, their results are coarse in temporal and spatial dimensions. In addition, they often show systematic biases compared to observations. Downscaling and bias correction of climate model outputs is thus required for local applications. Apart from the computationally intensive strategy of dynamical downscaling, statistical downscaling offers a relatively straightforward solution by establishing relationships between small- and large-scale variables. This study compares four statistical downscaling methods of bias correction (BC), the change factor of mean (CFM), quantile perturbation (QP) and an event-based weather generator (WG) to assess climate change impact on drought by the end of the 21st century (2071–2100) relative to a baseline period of 1971–2000 for the weather station of Uccle located in Belgium. A set of drought-related aspects is analysed, i.e. dry day frequency, dry spell duration and total precipitation. The downscaling is applied to a 28-member ensemble of Coupled Model Intercomparison Project Phase 6 (CMIP6) GCMs, each forced by four future scenarios of SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5. A 25-member ensemble of CanESM5 GCM is also used to assess the significance of the climate change signals in comparison to the internal variability in the climate. A performance comparison of the downscaling methods reveals that the QP method outperforms the others in reproducing the magnitude and monthly pattern of the observed indicators. While all methods show a good agreement on downscaling total precipitation, their results differ quite largely for the frequency and length of dry spells. Using the downscaling methods, dry day frequency is projected to increase significantly in the summer months, with a relative change of up to 19 % for SSP5–8.5. At the same time, total precipitation is projected to decrease significantly by up to 33 % in these months. Total precipitation also significantly increases in winter, as it is driven by a significant intensification of extreme precipitation rather than a dry day frequency change. Lastly, extreme dry spells are projected to increase in length by up to 9 %.
Highlights
The distribution of the relative error for total precipitation adjusted by bias correction (BC) is generally shifted towards higher values for higher level scenarios
As for dry spells, quantile perturbation (QP) can be considered the best method for the number of very short to large dry spells
The difference between the skills of the four methods is small for the number of very short and short dry spells, while it becomes bigger as the spells become longer
Summary
Since the mid-20th century, global warming has been observed (IPCC, 2014). The atmosphere and oceans have warmed, ice and snow volumes have diminished and the sea level has risen. Climate change is linked to a variety of recent weather extremes worldwide. We entered the current decade with Australia’s immense bushfires empowered by severe droughts (Phillips, 2020) and devastating mud slides triggered by extreme precipitation in Brazil (Associated Press, 2020). Nature and human communities all over the world are feeling the impact of global warming, which is projected to become more pronounced in the future (Tabari, 2021). Projections of how global warming will evolve in the coming decades and centuries would be extremely valuable to humankind in order to adapt efficiently
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.