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| DOI | 10.5194/gmd-17-1249-2024 |
| ibicus: a new open-source Python package and comprehensive interface for statistical bias adjustment and evaluation in climate modelling (v1.0.1) | |
| 发表日期 | 2024 |
| ISSN | 1991-959X |
| EISSN | 1991-9603 |
| 起始页码 | 17 |
| 结束页码 | 3 |
| 卷号 | 17期号:3 |
| 英文摘要 | Statistical bias adjustment is commonly applied to climate models before using their results in impact studies. However, different methods based on a distributional mapping between observational and model data can change the simulated trends as well as the spatiotemporal and inter-variable consistency of the model, and are prone to misuse if not evaluated thoroughly. Despite the importance of these fundamental issues, researchers who apply bias adjustment currently do not have the tools at hand to compare different methods or evaluate the results sufficiently to detect possible distortions. Because of this, widespread practice in statistical bias adjustment is not aligned with recommendations from the academic literature. To address the practical issues impeding this, we introduce ibicus, an open-source Python package for the implementation of eight different peer-reviewed and widely used bias adjustment methods in a common framework and their comprehensive evaluation. The evaluation framework introduced in ibicus allows the user to analyse changes to the marginal, spatiotemporal and inter-variable structure of user-defined climate indices and distributional properties as well as any alteration of the climate change trend simulated in the model. Applying ibicus in a case study over the Mediterranean region using seven CMIP6 global circulation models, this study finds that the most appropriate bias adjustment method depends on the variable and impact studied, and that even methods that aim to preserve the climate change trend can modify it. These findings highlight the importance of use-case-specific selection of the method and the need for a rigorous evaluation of results when applying statistical bias adjustment. |
| 语种 | 英语 |
| WOS研究方向 | Geology |
| WOS类目 | Geosciences, Multidisciplinary |
| WOS记录号 | WOS:001190456000001 |
| 来源期刊 | GEOSCIENTIFIC MODEL DEVELOPMENT
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/289376 |
| 作者单位 | University of Reading; University of Exeter; European Centre for Medium-Range Weather Forecasts (ECMWF) |
| 推荐引用方式 GB/T 7714 | . ibicus: a new open-source Python package and comprehensive interface for statistical bias adjustment and evaluation in climate modelling (v1.0.1)[J],2024,17(3). |
| APA | (2024).ibicus: a new open-source Python package and comprehensive interface for statistical bias adjustment and evaluation in climate modelling (v1.0.1).GEOSCIENTIFIC MODEL DEVELOPMENT,17(3). |
| MLA | "ibicus: a new open-source Python package and comprehensive interface for statistical bias adjustment and evaluation in climate modelling (v1.0.1)".GEOSCIENTIFIC MODEL DEVELOPMENT 17.3(2024). |
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