Two sets of bias-corrected regional UK Climate Projections 2018 (UKCP18) of temperature, precipitation and potential evapotranspiration for Great Britain

Earth system science data, Год журнала: 2025, Номер 17(5), С. 2113 - 2133

Опубликована: Май 20, 2025

Abstract. The United Kingdom Climate Projections 2018 (UKCP18) regional climate model (RCM) 12 km perturbed physics ensemble (UKCP18-RCM-PPE) is one of the three strands latest set UK national projections produced by Met Office. It has been widely adopted in impact assessment. In this study, we report biases raw UKCP18-RCM simulations that are significant and likely to deteriorate assessments if they not adjusted. Two methods were used bias-correct UKCP18-RCM: non-parametric quantile mapping using empirical quantiles a variant developed for third phase Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) designed preserve change signal. Specifically, daily temperature precipitation 1981 2080 adjusted members. Potential evapotranspiration was also estimated over same period Penman–Monteith formulation then bias-corrected latter method. Both successfully corrected range temperature, precipitation, potential metrics reduced multi-day lesser degree. An exploratory analysis projected future changes confirms expectation wetter, warmer winters hotter, drier summers shows uneven different parts distributions both precipitation. bias-correction preserved signal almost equally well, as well spread among changes. factor method benchmark show it fails capture variables, making inadequate most assessments. By comparing differences between two within members, uncertainty stemming from parameterization far outweighs introduced selecting these methods. We conclude providing guidance on use datasets. datasets bias-adjusted with ISIMIP3BA publicly available following repositories: https://doi.org/10.5281/zenodo.6337381 (Reyniers et al., 2022a) https://doi.org/10.5281/zenodo.6320707 2022b). datasets, method, at https://doi.org/10.5281/zenodo.8223024 (Zha 2023).

Язык: Английский

Correcting biases in regional climate model boundary variables for improved simulation of high-impact compound events

iScience, Год журнала: 2023, Номер 26(9), С. 107696 - 107696

Опубликована: Авг. 21, 2023

Although climate models have been used to assess compound events, the combination of multiple hazards or drivers poses uncertainties because systemic biases present. Here, we investigate multivariate bias correction for correcting in boundaries that form inputs regional (RCMs). This improves representation physical relationships among variables, essential accurate characterization events. We address four types events result from eight different hazards. The results show while RCM simulations presented here exhibit similar performance some event types, broadly compared no univariate correction, particularly coincident high temperature and precipitation. with uncorrected tends produce a negative return period these suggesting tendency over-simulate respect observed

Язык: Английский

An improved statistical bias correction method for Global Climate Model (GCM) precipitation projection: A case study on the CMCC-CM2-SR5 model projection in China’s Huaihe River Basin

Journal of Hydrology Regional Studies, Год журнала: 2024, Номер 57, С. 102146 - 102146

Опубликована: Дек. 21, 2024

Язык: Английский