Dunn-Sigouin, E., Kolstad, E.W., Wulff, C.O. et al. (2 more authors) (2025) Balancing accuracy versus precision: Enhancing the usability of sub-seasonal forecasts. Climate Services, 39. 100594. ISSN: 2405-8807
Abstract
Forecasts are essential for climate adaptation and preparedness, such as in early warning systems and impact models. A key limitation to their practical use is often their coarse spatial grid spacing. However, another less frequently discussed but crucial limitation is that forecasts are often more precise than they are accurate when their grid spacing is finer than the scales they can accurately predict. Here, we adapt the fractions skill score, a metric conventionally used to quantify spatial forecast accuracy by the meteorological community, to help users navigate the trade-off between forecast accuracy versus precision. We demonstrate how this trade-off can be visualized for daily European precipitation, focusing on deterministic predictions of anomalies and probabilistic predictions of extremes, derived from three years of sub-seasonal forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF). Our results show that decreasing precision through spatial aggregation increases forecast accuracy, extends predictable lead times, and enhances the maximum possible accuracy relative to the grid scale, while increased precision diminishes these benefits. Notably, spatial aggregation benefits daily-accumulated forecasts more than weekly-accumulated ones, per unit lead-time. We demonstrate the practical value of our approach in three examples: communicating early warnings, managing hydropower capacity, and commercial aviation planning—each characterized by distinct user constraints on accuracy, spatial scale, or lead-time. The results suggest a different approach for using forecasts; post-processing forecasts to focus on the most accurate scales rather than the default grid scale, thus offering users more actionable information.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2025 The Authors. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Sub-seasonal forecasts, Usability gap, Forecast skill horizon, Climate adaptation, ECMWF, Fractions skill score |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) |
Funding Information: | Funder Grant number Met Office No external Reference |
Depositing User: | Symplectic Publications |
Date Deposited: | 08 Jul 2025 10:04 |
Last Modified: | 06 Aug 2025 12:40 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.cliser.2025.100594 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:228777 |