Comparison of climate change and climate impact metrics over the UK for the UKCP09 and UKCP18 RCM-PPE ensembles, within a broader context of climate modelling uncertainty

This report analyses and compares metrics using processed daily data output from the regional climate model (RCM) perturbed parameter ensemble (PPE) components of two recent UK Climate Projections projects, namely UKCP18 (the most recent UKCP release) and UKCP09 (the previous release). The metrics considered include daily meteorological variables output directly from the RCM-PPEs plus climate indices derived from the daily temperature and precipitation fields, at grid-point scales and aggregated over UK country regions. To place these RCM-PPE results in a broader modelling uncertainty context, results are compared to a multi-model ensemble of 13 selected CMIP5 global projections, analysed in a similar way using available daily data. Where feasible, results are also compared against the probabilistic projections component of UKCP18, to strengthen this context (this is feasible only for time averages of some meteorological variables, but not derived climate index metrics). The analysis considers future changes in the metrics of interest through the 21 Century relative to a present-day baseline of 1981-2000 with a focus on changes at specified global warming levels ranging through 1.5, 2, 3 and 4 °C relative to preindustrial. No bias corrections are applied to any of the input model data but, where possible, we show how the modelled variables compare with observational data taken from a National Climate Information Centre (NCIC) dataset for the present-day baseline period. Present day biases with respect to NCIC are computed and encapsulated in the graphical output for as many metrics as possible to help inform conclusions on the reliability of projected future changes. We also draw some comparisons of results with a recently completed study by Hanlon et al. (2020) that considers an overlapping set of metrics for UKCP18 RCM-PPE results only but (in contrast to the present report) applies bias correction to the daily input data. Conditioned on specified global warming levels, UKCP18 RCM-PPE results exhibit relatively lower regional warming over the UK than UKCP09 RCM-PPE results. Both tend to lie at the high end of the range of CMIP513 regional warmings. Precipitation changes generally exhibit accentuated increases in winter and decreases in summer in UKCP18 RCM-PPE compared to UKCP09 RCM-PPE results. RCM18-PPE shows more potential for winter drying in some regions than UKCP09 RCM-PPE or CMIP5-13 results. The deepest summer lows tend to become somewhat less intense in UKCP18 RCM-PPE as the climate warms. Probabilistic projection results are considered in the comparisons only for metrics involving regional mean time mean response of meteorological variables, for which they generally give the widest ranges of plausible projected outcomes. Notable exceptions to this are for the accentuated spring warming response in UKCP09 RCM-PPE and changes in cloud amount and surface radiation in UKCP18 RCM-PPE through the year, which are mostly outliers relative to the probabilistic projection range. For metrics involving projections of climate indices derived from daily temperature and precipitation, some aspects of the analysis indicate outcomes from UKCP18 RCM-PPE (e.g. increased occurrence of summer and autumn tropical nights in urban conurbations, more dry days in summer and autumn, increased maximum length of dry day spells in autumn, lower average precipitation on wet days in summer) lie outside the ranges of UKCP09 RCM-PPE or CMIP5-13, implying the potential for impacts more severe than in previous assessments. An important caveat to this work is that the RCM-PPEs are not the only modelling component available from UKCP09 and UKCP18. The analysis conducted here, while representative, is not exhaustive and could usefully be extended in various ways. In particular, comparison against results from the UKCP18 convection-permitting ensemble (Kendon et al. 2019) would clearly be a valuable extension to this work. A large downloadable collection of graphics files is available, which compares the metrics considered here across the different source streams in multiple ways (as time series, box plots and maps). It is hoped that this resource will be useful to others. This report shows only a small fraction of the thousands of graphics files that are potentially available for study.