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

中文翻译：

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两组经过偏差校正的 2018 年英国区域气候预测 (UKCP18)，内容涉及英国的温度、降水和潜在蒸散量

摘要。英国气候预测 2018 (UKCP18) 区域气候模型 (RCM) 12 公里区域扰动物理系综 (UKCP18-RCM-PPE) 是英国气象局制作的最新英国国家气候预测的三个部分之一。它已被广泛应用于气候影响评估。在这项研究中，我们报告了原始 UKCP18-RCM 模拟中存在的重大偏差，如果不进行调整，影响评估可能会恶化。使用两种方法来纠正 UKCP18-RCM 的偏差：使用经验分位数的非参数分位数映射，以及为旨在保留气候变化信号的部门间影响模型比对项目 (ISIMIP) 第三阶段开发的变体。具体来说，对 12 个集合成员的 1981 年至 2080 年每日气温和降水模拟进行了调整。还使用 Penman-Monteith 公式估算了同一时期的潜在蒸散量，然后使用后一种方法进行偏差校正。这两种方法都成功地纠正了一系列每日温度、降水和潜在蒸散指标的偏差，并在较小程度上减少了多日降水指标的偏差。对预计未来变化的探索性分析证实了冬季更加湿润、温暖和夏季更加炎热、干燥的预期，并显示了气温和降水分布的不同部分的不均匀变化。两种偏差校正方法几乎同样好地保留了气候变化信号以及预测变化之间的传播。变化因子方法被用作降水量的基准，我们发现它无法捕捉一系列变量的变化，使其不足以进行大多数影响评估。通过比较两种偏差校正方法之间以及 12 个集合成员内部的差异，我们表明气候模型参数化引起的未来降水和温度变化的不确定性远远超过选择这两种偏差校正方法之一所引入的不确定性。最后，我们提供了有关使用偏差校正数据集的指导。使用 ISIMIP3BA 调整的数据集偏差可在以下存储库中公开获得：降水和温度的 https://doi.org/10.5281/zenodo.6337381（Reyniers 等人，2022a）和 https://doi.org/10.5281 /zenodo.6320707 潜在蒸散量（Reyniers 等人，2022b）。使用分位数映射方法进行偏差校正的数据集可在 https://doi.org/10.5281/zenodo.8223024 上获取（Zha 等人，2023）。