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Recent extreme weather events have had severe impacts on UK crop yields, and so there is concern that a greater frequency of extremes could affect crop production in a changing climate. Here we investigate the impacts of future climate change on wheat, the most widely grown cereal crop globally, in a temperate country with currently favourable wheat-growing conditions. Historically, following the plateau of UK wheat yields since the 1990s, we find there has been a recent significant increase in wheat yield volatility, which is only partially explained by seasonal metrics of temperature and precipitation across key wheat growth stages (foundation, construction and production). We find climate impacts on wheat yields are strongest in years with compound weather extremes across multiple growth stages (e.g. frost and heavy rainfall). To assess how these conditions might evolve in the future, we analyse the latest 2.2 km UK Climate Projections (UKCP Local): on average, the foundation growth stage (broadly 1 October to 9 April) is likely to become warmer and wetter, while the construction (10 April to 10 June) and production (11 June to 26 July) stages are likely to become warmer and slightly drier. Statistical wheat yield projections, obtained by driving the regression model with UKCP Local simulations of precipitation and temperature for the UK's three main wheat-growing regions, indicate continued growth of crop yields in the coming decades. Significantly warmer projected winter night temperatures offset the negative impacts of increasing rainfall during the foundation stage, while warmer day temperatures and drier conditions are generally beneficial to yields in the production stage. This work suggests that on average, at the regional scale, climate change is likely to have more positive impacts on UK wheat yields than previously considered. Against this background of positive change, however, our work illustrates that wheat farming in the UK is likely to move outside of the climatic envelope that it has previously experienced, increasing the risk of unseen weather conditions such as intense local thunderstorms or prolonged droughts, which are beyond the scope of this paper.

Recent extreme weather events have had severe impacts on UK crop yields, and so there is concern that a greater frequency of extremes could affect crop production in a changing climate. Here we investigate potential future impacts of climate projections on wheat, the most widely grown cereal crop globally, in a temperate country with currently favourable wheat-growing conditions. Past and projected climate conditions are considered for key wheat growth stages (Foundation, Construction and Production). Historically, following the plateau of UK wheat yields since the 1990s, we find there has been a recent significant increase in wheat yield volatility, which is partially explained by seasonal metrics of temperature and precipitation, including mean, extremes, and intra-seasonal variability. Strong associations between climate and yield anomalies occur during years with cumulative climate impacts across growth stages, when climate extremes ‘escape’ the ability of farmers to adapt through agronomic means. We then analyse the latest 2.2 km UK Climate Projections for the UK’s three main wheat-growing regions. Climate projections indicate that on average across the three regions, the Foundation growth stage (broadly 1st October to 9th April) is likely to become warmer and wetter, while the Construction (10th April to 10th June) and Production (11th June to 26th July) stages are likely to become warmer and slightly drier. An analogue approach, comparing historical climate conditions with future climate projections, reveals a mixed picture of future climate conditions for UK crop yields. Projected warmer winter night temperatures are likely to prove beneficial in the Foundation stage, but concurrent increases in heavy rain may be detrimental. Similarly, warmer and drier mean conditions may enhance yields during the Production stage, but increases in high temperatures and heat variability may increase plant stress, while decreases in rainfall may also threaten adequate water supply. Since future climatic conditions are likely to move outside the historically observed range, there may be challenges for agriculture to adapt management practices to realise any potential benefits.

The flooding in South Yorkshire in the United Kingdom (UK) in autumn 2019 saw one fatality, at least 500 properties flooded and 1 200 households evacuated. The worst of the flooding occurred after very high 24-h rainfall totals of up to 82 mm fell on already saturated ground. This followed very high 24-h rainfall totals in the region just two weeks earlier of up to just under 50 mm. In the light of anthropogenic climate change, it is expected that extreme rainfall events are set to become more intense as a result of increased global mean temperatures and the Clausius-Clapeyron relation. Here we investigate the change in risk of such extreme rainfall events in the UK in autumn using a new index R50mm_OND, representing the mean number of daily precipitation totals in excess of 50 mm in October–December each year. Using high resolution regional model datasets and observations we show that extreme rainfall totals for the UK are increasing exponentially as a result of anthropogenic climate change. Observations show that the frequency of extreme daily precipitation in the form of R50mm_OND has already increased by 60% (95% CI: 44–76) in the UK between the beginning of the 20th and 21st centuries. R50mm_OND is projected to increase even further between 2019 and 2080, by 85% (95% CI: 73–97) according to a Representative Concentration Pathway (RCP) 8.5 scenario of anthropogenic emissions. While higher resolution models (12 km spatial resolution) were able to capture the observed changes, lower resolution models were not. This underlines the importance of high-resolution models for modelling extreme precipitation seen in late autumn and early winter, not just for convective rainfall in the summer. A more specific analysis of the November 2019 event looked at the mean of the two highest daily precipitation totals in October–November in the South Yorkshire region. This found a long-term shift to higher daily rainfall totals for this mean with an increase in intensity of the top 10% of events, suggesting that the South Yorkshire region in autumn is more at risk of flooding in the future without effective adaptation measures.

We evaluate a 12-member perturbed parameter ensemble of regional climate simulations over Europe at 12 km resolution, carried out as part of the UK Climate Projections (UKCP) project. This ensemble is formed by varying uncertain parameters within the model physics, allowing uncertainty in future projections due to climate modelling uncertainty to be explored in a systematic way. We focus on present day performance both compared to observations, and consistency with the driving global ensemble. Daily and seasonal temperature and precipitation are evaluated as two variables commonly used in impacts assessments. For precipitation we find that downscaling, even whilst within the convection-parameterised regime, generally improves daily precipitation, but not everywhere. In summer, the underestimation of dry day frequency is worse in the regional ensemble than in the driving simulations. For temperature we find that the regional ensemble inherits a large wintertime cold bias from the global model, however downscaling reduces this bias. The largest bias reduction is in daily winter cold temperature extremes. In summer the regional ensemble is cooler and wetter than the driving global models, and we examine cloud and radiation diagnostics to understand the causes of the differences. We also use a low-resolution regional simulation to determine whether the differences are a consequence of resolution, or due to other configuration differences, with the predominant configuration difference being the treatment of aerosols. We find that use of the EasyAerosol scheme in the regional model, which aims to approximate the aerosol effects in the driving model, causes reduced temperatures by around 0.5 K over Eastern Europe in Summer, and warming of a similar magnitude over France and Germany in Winter, relative to the impact of interactive aerosol in the global runs. Precipitation is also increased in these regions. Overall, we find that the regional model is consistent with the global model, but with a typically better representation of daily extremes and consequently we have higher confidence in its projections of their future change.

Pan-Africa convection-permitting regional climate model simulations have been performed to study the impact of high resolution and the explicit representation of atmospheric moist convection on the present and future climate of Africa. These unique simulations have allowed European and African climate scientists to understand the critical role that the representation of convection plays in the ability of a contemporary climate model to capture climate and climate change, including many impact-relevant aspects such as rainfall variability and extremes. There are significant improvements in not only the small-scale characteristics of rainfall such as its intensity and diurnal cycle, but also in the large-scale circulation. Similarly, effects of explicit convection affect not only projected changes in rainfall extremes, dry spells, and high winds, but also continental-scale circulation and regional rainfall accumulations. The physics underlying such differences are in many cases expected to be relevant to all models that use parameterized convection. In some cases physical understanding of small-scale change means that we can provide regional decision-makers with new scales of information across a range of sectors. We demonstrate the potential value of these simulations both as scientific tools to increase climate process understanding and, when used with other models, for direct user applications. We describe how these ground-breaking simulations have been achieved under the U.K. Government’s Future Climate for Africa Programme. We anticipate a growing number of such simulations, which we advocate should become a routine component of climate projection, and encourage international coordination of such computationally and human-resource expensive simulations as effectively as possible.

A large number of recent studies have aimed at understanding short-duration rainfall extremes, due to their impacts on flash floods, landslides and debris flows and potential for these to worsen with global warming. This has been led in a concerted international effort by the INTENSE Crosscutting Project of the GEWEX (Global Energy and Water Exchanges) Hydroclimatology Panel. Here, we summarize the main findings so far and suggest future directions for research, including: the benefits of convection-permitting climate modelling; towards understanding mechanisms of change; the usefulness of temperature-scaling relations; towards detecting and attributing extreme rainfall change; and the need for international coordination and collaboration. Evidence suggests that the intensity of long-duration (1 day+) heavy precipitation increases with climate warming close to the Clausius–Clapeyron (CC) rate (6–7% K −1 ), although large-scale circulation changes affect this response regionally. However, rare events can scale at higher rates, and localized heavy short-duration (hourly and sub-hourly) intensities can respond more strongly (e.g. 2 × CC instead of CC). Day-to-day scaling of short-duration intensities supports a higher scaling, with mechanisms proposed for this related to local-scale dynamics of convective storms, but its relevance to climate change is not clear. Uncertainty in changes to precipitation extremes remains and is influenced by many factors, including large-scale circulation, convective storm dynamics andstratification. Despite this, recent research has increased confidence in both the detectability and understanding of changes in various aspects of intense short-duration rainfall. To make further progress, the international coordination of datasets, model experiments and evaluations will be required, with consistent and standardized comparison methods and metrics, and recommendations are made for these frameworks. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.

Short-duration (1–3 h) rainfall extremes can cause serious damage to societies through rapidly developing (flash) flooding and are determined by complex, multifaceted processes that are altering as Earth’s climate warms. In this Review, we examine evidence from observational, theoretical and modelling studies for the intensification of these rainfall extremes, the drivers and the impact on flash flooding. Both short-duration and long-duration (>1 day) rainfall extremes are intensifying with warming at a rate consistent with the increase in atmospheric moisture (~7% K−1), while in some regions, increases in short-duration extreme rainfall intensities are stronger than expected from moisture increases alone. These stronger local increases are related to feedbacks in convective clouds, but their exact role is uncertain because of the very small scales involved. Future extreme rainfall intensification is also modulated by changes to temperature stratification and large-scale atmospheric circulation. The latter remains a major source of uncertainty. Intensification of short-duration extremes has likely increased the incidence of flash flooding at local scales, and this can further compound with an increase in storm spatial footprint to considerably increase total event rainfall. These findings call for urgent climate change adaptation measures to manage increasing flood risks. Short-duration rainfall extremes are determined by complex processes that are affected by the warming climate. This Review assesses the evidence for the intensification of short-duration rainfall extremes, the associated drivers and the implications for flood risks.

High resolution regional climate models are needed to understand how climate change will impact extreme precipitation. Current state-of-the-art climate models are Convection Permitting Models (CPMs) at kilometre scale grid-spacing. CPMs are often used together with convective parameterised Regional Climate Models (RCMs) due to high computational costs of CPMs. This study compares the representation of extreme precipitation events between a 12 km resolution RCM and a 2.2 km resolution CPM. Precipitation events are tracked in both models, and extreme events, identified by peak intensity, are analysed in a Northern European case area. Extreme event tracks show large differences in both location and movement patterns between the CPM and RCM. This indicates that different event types are sampled in the two models, with differences extending to much larger scales. We visualise event-development using area-intensity evolution diagrams. This reveals that for the 100 most extreme events, the RCM data is likely dominated by physically implausible events, so called 'grid-point storms', with unrealistically high intensities. For the 1000 and 10,000 most extreme events, intensities are higher for CPM events, while areas are larger for RCM extreme events. Sampling extreme events by season shows that differences between RCM and CPM in intensity and area in the top 100 extreme events are largest in autumn and winter, while for the top 1000 and top 10,000 events differences are largest in summer. Overall this study indicates that extreme precipitation projections from traditional coarse resolution RCMs need to be used with caution, due to the possible influence of grid-point storms.

N. Ban et al., Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of ∼3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution (∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from ∼ −40% at 12 km to ∼ −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales., Open access funding provided by University of Innsbruck and Medical University of Innsbruck., The ETH team, MZ, CNRM IPSL, ICTP, SMHI, Met-Office, DMI, CMCC, HZG, KNMI acknowledge funding from the HORIZON 2020 EUCP (European Climate Prediction System) project (https://www.eucp-project.eu, grant agreement No. 776613). AL-G acknowledges support by the Spanish government through grant BES-2016-078158 and MINECO/FEDER co-funded project MULTI-SDM (CGL2015-66583-R).

We investigate the effect of using convection-permitting models (CPMs) spanning a pan-European domain on the representation of precipitation distribution at a climatic scale. In particular we compare two 2.2 km models with two 12 km models run by ETH Zurich (ETH-12 km and ETH-2.2 km) and the Met-Office (UKMO-12 km and UKMO-2.2 km). The two CPMs yield qualitatively similar differences to the precipitation climatology compared to the 12 km models, despite using different dynamical cores and different parameterization packages. A quantitative analysis confirms that the CPMs give the largest differences compared to 12 km models in the hourly precipitation distribution in regions and seasons where convection is a key process: in summer across the whole of Europe and in autumn over the Mediterranean Sea and coasts. Mean precipitation is increased over high orography, with an increased amplitude of the diurnal cycle. We highlight that both CPMs show an increased number of moderate to intense short-lasting events and a decreased number of longer-lasting low-intensity events everywhere, correcting (and often over-correcting) biases in the 12 km models. The overall hourly distribution and the intensity of the most intense events is improved in Switzerland and to a lesser extent in the UK but deteriorates in Germany. The timing of the peak in the diurnal cycle of precipitation is improved. At the daily time-scale, differences in the precipitation distribution are less clear but the greater Alpine region stands out with the largest differences. Also, Mediterranean autumnal intense events are better represented at the daily time-scale in both 2.2 km models, due to improved representation of mesoscale processes.

This paper is a contribution to the special issue on Advances in Convection-Permitting Climate Modeling, consisting of papers that focus on the evaluation, climate change assessment, and feedback processes in kilometer-scale simulations and observations., A recently launched project under the auspices of the World Climate Research Program’s (WCRP) Coordinated Regional Downscaling Experiments Flagship Pilot Studies program (CORDEX-FPS) is presented. This initiative aims to build first-of-its-kind ensemble climate experiments of convection permitting models to investigate present and future convective processes and related extremes over Europe and the Mediterranean. In this manuscript the rationale, scientific aims and approaches are presented along with some preliminary results from the testing phase of the project. Three test cases were selected in order to obtain a first look at the ensemble performance. The test cases covered a summertime extreme precipitation event over Austria, a fall Foehn event over the Swiss Alps and an intensively documented fall event along the Mediterranean coast. The test cases were run in both “weather-like” (WL, initialized just before the event in question) and “climate” (CM, initialized 1 month before the event) modes. Ensembles of 18–21 members, representing six different modeling systems with different physics and modelling chain options, was generated for the test cases (27 modeling teams have committed to perform the longer climate simulations). Results indicate that, when run in WL mode, the ensemble captures all three events quite well with ensemble correlation skill scores of 0.67, 0.82 and 0.91. They suggest that the more the event is driven by large-scale conditions, the closer the agreement between the ensemble members. Even in climate mode the large-scale driven events over the Swiss Alps and the Mediterranean coasts are still captured (ensemble correlation skill scores of 0.90 and 0.62, respectively), but the inter-model spread increases as expected. In the case over Mediterranean the effects of local-scale interactions between flow and orography and land–ocean contrasts are readily apparent. However, there is a much larger, though not surprising, increase in the spread for the Austrian event, which was weakly forced by the large-scale flow. Though the ensemble correlation skill score is still quite high (0.80). The preliminary results illustrate both the promise and the challenges that convection permitting modeling faces and make a strong argument for an ensemble-based approach to investigating high impact convective processes., IG and LS have been supported by the Croatian Science Foundation (HrZZ) project CARE (no. 2831). JF acknowledges support by the Spanish R + D programme through MINECO/FEDER co-funded project INSIGNIA (CGL2016-79210-R). AL-G is supported by the Spanish government though grant BES-2016-078158 and MINECO/FEDER co-funded project MULTI-SDM (CGL2015-66583-R). JM and KW-S gratefully acknowledge the support by the German Science Foundation (DFG) through project FOR 1695. DM, MP, and HT gratefully acknowledge the support received via the Austrian Science Fund (FWF) project NHCM-2 (no. P24758-N29) and the projects HighEnd:Extremes and EASICLIM, funded by the Austrian Climate Research Programme (ACRP) of the Klima- und Energiefonds (nos. KR13AC6K10981 and KR16AC0K13160, respectively). SS and TL acknowledge the support of NOTUR project no. NN9280K and the Research Council of Norway and its basic institute support of their strategic project on Climate Services. RMC and PMMS gratefully acknowledge the support of the SOLAR project (PTDC/GEOMET/7078/2014) financed by the Portuguese Foundation for Science and Technology. EJ Kendon gratefully acknowledges funding from the Joint Department of Energy and Climate Change (DECC) and Department for Environment Food and Rural Affairs (Defra) Met Office Hadley Centre Climate Programme (GA01101). S. Khodayar research is supported by the Bundesministerium für Bildung und Forschung (BMBF; German Federal Ministry of Education and Research). Support of Ministry of Education, Youth and Sports of the Czech Republic for funding the participation in Euro-CORDEX activities via the scheme INTER-TRANSFER under the Grant no. LTT17007. Funding from the Research Council of Norway through the SUPER (Grant no. 250573) and HYPRE (Grant no. 243942) projects.

Surface water flooding (SWF) is a recurrent hazard that affects lives and livelihoods. Climate change is projected to change the frequency of extreme rainfall events that can lead to SWF. Increasingly, data from Regional Climate Models (RCMs) are being used to investigate the potential water‐related impacts of climate change; such assessments often focus on broad‐scale fluvial flooding and the use of coarse resolution (>12 km) RCMs. However, high‐resolution (

Climatological features of observed annual maximum hourly precipitation have not been documented systematically compared to those on daily timescales due to observational limitations. Drawing from a quality-controlled database of hourly records sampling different climatic regions including the United States, Australia, the British Isles, Japan, India and peninsular Malaysia over the 1950–2016 period, we examined climatological features of annual maximum precipitation (AMP) across timescales ranging from 1-hr (AMP1−hr) to 24-hr (AMP24−hr). Our analysis reveals strong relations between the magnitude of AMP and the climatological average annual precipitation (AAP), with geographic variations in the magnitude of AMP24−hr across topographic gradients not evident in AMP1−hr. Most AMP1−hr are found to be embedded within short-duration storms (>70% of AMP1−hr are embedded within 1–5 h storms), especially in regions with low AAP and in the tropical zone. Likewise, most AMP24−hr are found to be the accumulation of a very limited number of wet hours in the 24-h period (>80% of AMP24−hr are due to storms lasting

The precipitation and diabatic heating resulting from moist convection make it a key component of the atmospheric water budget in the tropics. With convective parameterization being a known source of uncertainty in global models, convection-permitting (CP) models are increasingly being used to improve understanding of regional climate. Here, a new 10-yr CP simulation is used to study the characteristics of rainfall and atmospheric water budget for East Africa and the Lake Victoria basin. The explicit representation of convection leads to a widespread improvement in the intensities and diurnal cycle of rainfall when compared with a parameterized simulation. Differences in large-scale moisture fluxes lead to a shift in the mean rainfall pattern from the Congo to Lake Victoria basin in the CP simulation—highlighting the important connection between local changes in the representation of convection and larger-scale dynamics and rainfall. Stronger lake–land contrasts in buoyancy in the CP model lead to a stronger nocturnal land breeze over Lake Victoria, increasing evaporation and moisture flux convergence (MFC), and likely unrealistically high rainfall. However, for the mountains east of the lake, the CP model produces a diurnal rainfall cycle much more similar to satellite estimates, which is related to differences in the timing of MFC. Results here demonstrate that, while care is needed regarding lake forcings, a CP approach offers a more realistic representation of several rainfall characteristics through a more physically based realization of the atmospheric dynamics around the complex topography of East Africa.

The West African climate is unique and challenging to reproduce using standard resolution climate models as a large proportion of precipitation comes from organised deep convection. For the first time, a regional 4.5 km convection permitting simulation was performed on a pan-African domain for a period of 10 years (1997–2006). The 4.5 km simulation (CP4A) is compared with a 25 × 40 km convection-parameterised model (R25) over West Africa. CP4A shows increased mean precipitation, which results in improvements in the mature phase of the West African monsoon but deterioration in the early and late phases. The distribution of precipitation rates is improved due to more short lasting intense rainfall events linked with mesoscale convective systems. Consequently, the CP4A model shows a better representation of wet and dry spells both at the daily and sub-daily time-scales. The diurnal cycle of rainfall is improved, which impacts the diurnal cycle of monsoon winds and increases moisture convergence in the Sahel. Although shortcomings were identified, with implications for model development, this convection-permitting model provides a much more reliable precipitation distribution than its convection-parameterised counterpart at both daily and sub-daily time-scales. Convection-permitting scales will therefore be useful to address the crucial question of how the precipitation distribution will change in the future.

The impact of climate change on vegetation including agricultural production has been the focus of many studies. Climate change is expected to have heterogeneous effects across locations globally, and the diversity of land uses characterising Great Britain (GB) presents a unique opportunity to test methods for assessing climate change effects and impacts. GB is a relatively cool and damp country, hence, the warmer and generally drier growing season conditions projected for the future are expected to increase arable production. Here we use state-of-the-art, kilometre-scale climate change scenarios to drive a land surface model (JULES; Joint UK Land Environment Simulator) and an ECOnometric AGricultural land use model (ECO-AG). Under unmitigated climate change, by the end of the century, the growing season in GB is projected to get >5 °C warmer and 140 mm drier on average. Rising levels of atmospheric CO2 are predicted to counteract the generally negative impacts of climate change on vegetation productivity in JULES. Given sufficient precipitation, warming favours higher value arable production over grassland agriculture, causing a predicted westward expansion of arable farming in ECO-AG. However, drying in the East and Southeast, without any CO2 fertilisation effect, is severe enough to cause a predicted reversion from arable to grassland farming. Irrigation, if implemented, could maintain this land in arable production. However, the predicted irrigation demand of ∼200 mm (per growing season) in many locations is comparable to annual predicted runoff, potentially demanding large-scale redistribution of water between seasons and/or across the country. The strength of the CO2 fertilisation effect emerges as a crucial uncertainty in projecting the impact of climate change on GB vegetation, especially farming land-use decisions.

During the winter of 2013/14, much of the UK experienced repeated intense rainfall events and flooding. This had a considerable impact on property and transport infrastructure. A key question is whether the burning of fossil fuels is changing the frequency of extremes, and if so to what extent. We assess the scale of the winter flooding before reviewing a broad range of Earth system drivers affecting UK rainfall. Some drivers can be potentially disregarded for these specific storms whereas others are likely to have increased their risk of occurrence. We discuss the requirements of hydrological models to transform rainfall into river flows and flooding. To determine any general changing flood risk, we argue that accurate modelling needs to capture evolving understanding of UK rainfall interactions with a broad set of factors. This includes changes to multiscale atmospheric, oceanic, solar and sea-ice features, and land-use and demographics. Ensembles of such model simulations may be needed to build probability distributions of extremes for both pre-industrial and contemporary concentration levels of atmospheric greenhouse gases.© 2014 Macmillan Publishers Limited. All rights reserved.

Many climate studies assess trends and projections in heavy precipitation events using precipitation percentile (or quantile) indices. Here we investigate three different percentile indices that are commonly used. We demonstrate that these may produce very different results and thus require great care with interpretation. More specifically, consideration is given to two intensity-based indices and one frequency-based index, namely (a) all-day percentiles, (b) wet-day percentiles, and (c) frequency indices based on the exceedance of a percentile threshold. Wet-day percentiles are conditionally computed for the subset of wet events (with precipitation exceeding some threshold, e.g. 1 mm/d for daily precipitation). We present evidence that this commonly used methodology can lead to artifacts and misleading results if significant changes in the wet-day frequency are not accounted for. Percentile threshold indices measure the frequency of exceedance with respect to a percentile-based threshold. We show that these indices yield an assessment of changes in heavy precipitation events that is qualitatively consistent with all-day percentiles, but there are substantial differences in quantitative terms. We discuss the reasons for these effects, present a theoretical assessment, and provide a series of examples using global and regional climate models to quantify the effects in typical applications. Application to climate model output shows that these considerations are relevant to a wide range of typical climate-change applications. In particular, wet-day percentiles generally yield different results, and in most instances should not be used for the impact-oriented assessment of changes in heavy precipitation events., Climatic Change, 137 (1), ISSN:0165-0009, ISSN:1573-1480

The realistic representation of rainfall on the local scale in climate models remains a key challenge. Realism encompasses the full spatial and temporal structure of rainfall, and is a key indicator of model skill in representing the underlying processes. In particular, if rainfall is more realistic in a climate model, there is greater confidence in its projections of future change. In this study, the realism of rainfall in a very high-resolution (1.5 km) regional climate model (RCM) is compared to a coarser-resolution 12-km RCM. This is the first time a convection-permitting model has been run for an extended period (1989–2008) over a region of the United Kingdom, allowing the characteristics of rainfall to be evaluated in a climatological sense. In particular, the duration and spatial extent of hourly rainfall across the southern United Kingdom is examined, with a key focus on heavy rainfall. Rainfall in the 1.5-km RCM is found to be much more realistic than in the 12-km RCM. In the 12-km RCM, heavy rain events are not heavy enough, and tend to be too persistent and widespread. While the 1.5-km model does have a tendency for heavy rain to be too intense, it still gives a much better representation of its duration and spatial extent. Long-standing problems in climate models, such as the tendency for too much persistent light rain and errors in the diurnal cycle, are also considerably reduced in the 1.5-km RCM. Biases in the 12-km RCM appear to be linked to deficiencies in the representation of convection.

Precipitation downscaling improves the coarse resolution and poor representation of precipitation in global climate models and helps end users to assess the likely hydrological impacts of climate change. This paper integrates perspectives from meteorologists, climatologists, statisticians, and hydrologists to identify generic end user (in particular, impact modeler) needs and to discuss downscaling capabilities and gaps. End users need a reliable representation of precipitation intensities and temporal and spatial variability, as well as physical consistency, independent of region and season. In addition to presenting dynamical downscaling, we review perfect prognosis statistical downscaling, model output statistics, and weather generators, focusing on recent developments to improve the representation of space-time variability. Furthermore, evaluation techniques to assess downscaling skill are presented. Downscaling adds considerable value to projections from global climate models. Remaining gaps are uncertainties arising from sparse data; representation of extreme summer precipitation, subdaily precipitation, and full precipitation fields on fine scales; capturing changes in small-scale processes and their feedback on large scales; and errors inherited from the driving global climate model. © 2010 by the American Geophysical Union.

This paper presents the first multi-model ensemble of 10-year, “convection-permitting” kilometer- scale regional climate model (RCM) scenario simulations downscaled from selected CMIP5 GCM projections for historical and end of century time slices. The technique is to first downscale the CMIP5 GCM projections to an intermediate 12–15 km resolution grid using RCMs, and then use these fields to downscale further to the kilometer scale. The aim of the paper is to provide an overview of the representation of the precipitation characteristics and their projected changes over the greater Alpine domain within a Coordinated Regional Climate Downscaling Experiment Flagship Pilot Study and the European Climate Prediction system project, tasked with investigating convective processes at the kilometer scale. An ensemble of 12 simulations performed by different research groups around Europe is analyzed. The simulations are evaluated through comparison with high resolution observations while the complementary ensemble of 12 km resolution driving models is used as a benchmark to evaluate the added value of the convection-permitting ensemble. The results show that the kilometer-scale ensemble is able to improve the representation of fine scale details of mean daily, wet-day/hour frequency, wet- day/hour intensity and heavy precipitation on a seasonal scale, reducing uncertainty over some regions. It also improves the representation of the summer diurnal cycle, showing more realistic onset and peak of convection. The kilometer-scale ensemble refines and enhances the projected patterns of change from the coarser resolution simulations and even modifies the sign of the precipitation intensity change and heavy precipitation over some regions. The convection permitting simulations also show larger changes for all indices over the diurnal cycle, also suggesting a change in the duration of convection over some regions. A larger positive change of frequency of heavy to severe precipitation is found. The results are encouraging towards the use of convection-permitting model ensembles to produce robust assessments of the local impacts of future climate change.