Correcting biases in regional climate model boundary variables for improved simulation of high-impact compound events
Summary: Although climate models have been used to assess compound events, the combination of multiple hazards or drivers poses uncertainties because of the systemic biases present. Here, we investigate multivariate bias correction for correcting systemic bias in the boundaries that form the inputs...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-09-01
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| Series: | iScience |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S258900422301773X |
| _version_ | 1797706894930870272 |
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| author | Youngil Kim Jason P. Evans Ashish Sharma |
| author_facet | Youngil Kim Jason P. Evans Ashish Sharma |
| author_sort | Youngil Kim |
| collection | DOAJ |
| description | Summary: Although climate models have been used to assess compound events, the combination of multiple hazards or drivers poses uncertainties because of the systemic biases present. Here, we investigate multivariate bias correction for correcting systemic bias in the boundaries that form the inputs of regional climate models (RCMs). This improves the representation of physical relationships among variables, essential for accurate characterization of compound events. We address four types of compound events that result from eight different hazards. The results show that while the RCM simulations presented here exhibit similar performance for some event types, the multivariate bias correction broadly improves the RCM representation of compound events compared to no correction or univariate correction, particularly for coincident high temperature and high precipitation. The RCM with uncorrected boundaries tends to produce a negative bias in the return period of these events, suggesting a tendency to over-simulate compound events with respect to observed events. |
| first_indexed | 2024-03-12T05:59:07Z |
| format | Article |
| id | doaj.art-f901c6b672e04de8b2eea8a82734fc90 |
| institution | Directory Open Access Journal |
| issn | 2589-0042 |
| language | English |
| last_indexed | 2024-03-12T05:59:07Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj.art-f901c6b672e04de8b2eea8a82734fc902023-09-03T04:24:21ZengElsevieriScience2589-00422023-09-01269107696Correcting biases in regional climate model boundary variables for improved simulation of high-impact compound eventsYoungil Kim0Jason P. Evans1Ashish Sharma2School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW, AustraliaClimate Change Research Centre and ARC Centre of Excellence for Climate Extremes, University of New South Wales, Sydney, NSW, AustraliaSchool of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW, Australia; Corresponding authorSummary: Although climate models have been used to assess compound events, the combination of multiple hazards or drivers poses uncertainties because of the systemic biases present. Here, we investigate multivariate bias correction for correcting systemic bias in the boundaries that form the inputs of regional climate models (RCMs). This improves the representation of physical relationships among variables, essential for accurate characterization of compound events. We address four types of compound events that result from eight different hazards. The results show that while the RCM simulations presented here exhibit similar performance for some event types, the multivariate bias correction broadly improves the RCM representation of compound events compared to no correction or univariate correction, particularly for coincident high temperature and high precipitation. The RCM with uncorrected boundaries tends to produce a negative bias in the return period of these events, suggesting a tendency to over-simulate compound events with respect to observed events.http://www.sciencedirect.com/science/article/pii/S258900422301773XAtmospheric scienceClimatologyEarth sciences |
| spellingShingle | Youngil Kim Jason P. Evans Ashish Sharma Correcting biases in regional climate model boundary variables for improved simulation of high-impact compound events iScience Atmospheric science Climatology Earth sciences |
| title | Correcting biases in regional climate model boundary variables for improved simulation of high-impact compound events |
| title_full | Correcting biases in regional climate model boundary variables for improved simulation of high-impact compound events |
| title_fullStr | Correcting biases in regional climate model boundary variables for improved simulation of high-impact compound events |
| title_full_unstemmed | Correcting biases in regional climate model boundary variables for improved simulation of high-impact compound events |
| title_short | Correcting biases in regional climate model boundary variables for improved simulation of high-impact compound events |
| title_sort | correcting biases in regional climate model boundary variables for improved simulation of high impact compound events |
| topic | Atmospheric science Climatology Earth sciences |
| url | http://www.sciencedirect.com/science/article/pii/S258900422301773X |
| work_keys_str_mv | AT youngilkim correctingbiasesinregionalclimatemodelboundaryvariablesforimprovedsimulationofhighimpactcompoundevents AT jasonpevans correctingbiasesinregionalclimatemodelboundaryvariablesforimprovedsimulationofhighimpactcompoundevents AT ashishsharma correctingbiasesinregionalclimatemodelboundaryvariablesforimprovedsimulationofhighimpactcompoundevents |