Bias‐Adjustment Methods for Future Subdaily Precipitation Extremes Consistent Across Durations. Issue 3 (6th March 2023)

• Record Type: Journal Article
• Authors: Van de Vyver, Hans; Van Schaeybroeck, Bert; De Cruz, Lesley; Hamdi, Rafiq; Termonia, Piet
• Is Part Of: Earth and space science. Volume 10:Issue 3(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-03-06
• Subjects: bias correction -- subdaily precipitation extremes -- IDF‐models -- climate change -- regional climate models -- climate model ensemble; Space sciences -- Periodicals; Geophysics -- Periodicals; 500.5
• DOI: 10.1029/2022EA002798
• Languages: English
• ISSNs: 2333-5084

Abstract

Abstract: Model output from climate projections often requires bias‐adjustment to compensate for systematic model errors. A bias‐adjustment method for extreme precipitation intensity is proposed that preserves the scaling equation for different accumulation levels from hourly to daily, using intensity‐duration‐frequency (IDF) modeling. A validation is performed within a pseudo‐reality setting, based on hourly precipitation from 28 regional climate model projections of the EURO‐CORDEX ensemble over Belgium. The scaling‐based adjustment methods improve upon previous methods, an optimal method is identified, and, analytical quantile mapping methods must be avoided due to three identified problems. The ensemble mean of the adjusted extreme precipitation intensity obeys the above‐mentioned scale‐invariance property, which is consistent with observed extreme intensities. We thus show that IDF modeling provides added value in the context of bias‐adjustment, and, that the particular IDF model proposed balances well between accuracy and the preservation of desired properties such as scale invariance and consistency among rainfall durations. Plain Language Summary: Heavy precipitation is known to have major impacts on society, including crop damage, soil erosion, landslides, and increased flood risk. In recent years, there is a growing body of evidence that human‐induced climate change has intensified extreme precipitation on the global scale. Both regional and global climate models predict that this will continue as the climate warms. Nevertheless, trend analysis or climate‐change attribution of local rainfall extremes remains particularly difficult for many reasons including high variability in space and time. Therefore it is essential to use statistical methods that make use of all available information. Climate model simulations are known to exhibit systematic biases. Here, for the first time, we use a well‐established technique in hydrology (intensity‐duration‐frequency modeling) to adjust extreme precipitation intensity as a function of the rainfall duration and event probability. Validation results with a large multi‐model ensemble illustrate that the new method improves upon existing approaches. As an illustration, we present a bias‐adjusted multi‐model climate ensemble for future projections of heavy rainfall statistics over Belgium. Key Points: New bias‐adjustment methods for subdaily extreme precipitation consistent across different precipitation durations Pseudo‐reality cross‐validation shows higher skill than existing bias‐adjustment methods for subdaily extremes Application to regional climate model projections over Belgium shows, despite large uncertainties, consistent future increase in subdaily precipitation extremes