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With climate change, rainfall is expected to get more intense, leading to cities being increasingly at risk of urban flooding. Understanding local climate change over cities has therefore become a priority for the scientific community and city planners on building resilient cities and mitigating hydrometeorological disasters. Very high resolution (km-scale, ‘convection-permitting’) climate models are required to adequately represent cities and local rainfall extremes. Here we assess the Weather Research and Forecasting (WRF) model for simulating urban rainfall. Despite the wide application of WRF in rainfall simulations (including urban areas), there are limited investigations on the impact of the domain size and how to search for a suitable domain size over a particular city region.To fill this knowledge gap, Newcastle upon Tyne is selected as the study area to simulate a summer heavy rainfall event with ERA5 (a fifth-generation dataset of global reanalysis developed by the European Centre for Medium-Range Weather Forecasts) as the input data and a radar product from the UK Met Office for validation. Accordingly, different domain sizes with the convection-permitting resolutions from 1 km to 4.5 km (increment: 0.5 km) are explored, and the hourly model outputs are compared with the radar observation data.This study has proposed and tested a method to decide the most suitable domain size. By using eight assessment indexes (including pattern, cumulative time series, hourly time series, particular values (max/min/mean) as well as the seven statistical indicators of each data and overall data), there are two preliminary conclusions: 1) 200 km × 200 km is the best domain size for the single domain simulation; 2) For 200 km × 200 km or smaller domain sizes, higher resolution produces better results, but for 250 km × 250 km or large domain sizes, resolution sensitivity is opposite. Regarding next steps, the above procedure will be further investigated by applying it to more extreme rainfall case studies and to other cities in order to assess whether results here are generally applicable, and therefore the optimal domain configuration can be usefully applied to produce reliable urban rainfall simulations.

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.

Increasing summer temperatures in a warming climate will increase the exposure of the UK population to heat-stress and associated heat-related mortality. Urban inhabitants are particularly at risk, as urban areas are often significantly warmer than rural areas as a result of the urban heat island phenomenon. The latest UK Climate Projections include an ensemble of convection-permitting model (CPM) simulations which provide credible climate information at the city-scale, the first of their kind for national climate scenarios. Using a newly developed urban signal extraction technique, we quantify the urban influence on present-day (1981–2000) and future (2061–2080) temperature extremes in the CPM compared to the coarser resolution regional climate model (RCM) simulations over UK cities. We find that the urban influence in these models is markedly different, with the magnitude of night-time urban heat islands overestimated in the RCM, significantly for the warmest nights (up to $$4~^{\circ }$$ 4 ∘ C), while the CPM agrees much better with observations. This improvement is driven by the improved land-surface representation and more sophisticated urban scheme MORUSES employed by the CPM, which distinguishes street canyons and roofs. In future, there is a strong amplification of the urban influence in the RCM, whilst there is little change in the CPM. We find that future changes in soil moisture play an important role in the magnitude of the urban influence, highlighting the importance of the accurate representation of land-surface and hydrological processes for urban heat island studies. The results indicate that the CPM provides more reliable urban temperature projections, due at least in part to the improved urban scheme.

The Hadley circulation and tropical rain belt are dominant features of African climate. Moist convection provides ascent within the rain belt, but must be parameterized in climate models, limiting predictions. Here, we use a pan-African convection-permitting model (CPM), alongside a parameterized convection model (PCM), to analyze how explicit convection affects the rain belt under climate change. Regarding changes in mean climate, both models project an increase in total column water (TCW), a widespread increase in rainfall, and slowdown of subtropical descent. Regional climate changes are similar for annual mean rainfall but regional changes of ascent typically strengthen less or weaken more in the CPM. Over a land-only meridional transect of the rain belt, the CPM mean rainfall increases less than in the PCM (5% vs 14%) but mean vertical velocity at 500 hPa weakens more (17% vs 10%). These changes mask more fundamental changes in underlying distributions. The decrease in 3-hourly rain frequency and shift from lighter to heavier rainfall are more pronounced in the CPM and accompanied by a shift from weak to strong updrafts with the enhancement of heavy rainfall largely due to these dynamic changes. The CPM has stronger coupling between intense rainfall and higher TCW. This yields a greater increase in rainfall contribution from events with greater TCW, with more rainfall for a given large-scale ascent, and so favors slowing of that ascent. These findings highlight connections between the convective-scale and larger-scale flows and emphasize that limitations of parameterized convection have major implications for planning adaptation to climate change.

For the first time, a model at a resolution on par with operational weather forecast models has been used for national climate scenarios. An ensemble of 12 climate change projections at convection-permitting (2.2 km) scale has been run for the United Kingdom, as part of the UK Climate Projections (UKCP) project. Contrary to previous studies, these show greater future increases in winter mean precipitation in the convection-permitting model compared with the coarser (12 km) driving model. A large part (60%) of the future increase in winter precipitation occurrence over land comes from an increase in convective showers in the 2.2 km model, which are most likely triggered over the sea and advected inland with potentially further development. In the 12 km model, increases in precipitation occurrence over the sea, largely due to an increase in convective showers, do not extend over the land. This is partly due to known limitations of the convection parameterization scheme, used in conventional coarse-resolution climate models, which acts locally without direct memory and so has no ability to advect diagnosed convection over the land or trigger new showers along convective outflow boundaries. This study shows that the importance of accurately representing convection extends beyond short-duration precipitation extremes and the summer season to projecting future changes in mean precipitation in winter.

For the first time, we analyze 2.2 km UK Met Office Unified Model convection-permitting model (CPM) projections for a pan-European domain. These new simulations represent a major increase in domain size, allowing us to examine the benefits of CPMs across a range of European climates. We find a change to the seasonality of extreme precipitation with warming. In particular, there is a relatively muted response for summer, which contrasts with much larger increases in autumn and winter. This flattens the hourly extreme precipitation seasonal cycle across Northern Europe which has a summer peak in the present climate. Over the Western Mediterranean, where autumn is the main extreme precipitation season, there is a regional increase in hourly extreme precipitation frequency, but local changes for lower precipitation thresholds are often insignificant. For mean precipitation, decreases are projected across Europe in summer, smaller decreases in autumn, and increases in winter; comparable changes are seen in the driving general circulation model (GCM) simulations. The winter mean increase is accompanied by a large decrease of winter mean snowfall. Comparing the driving GCM projections with the CPM ones, the CPMs show a robust enhanced intensification of precipitation extremes at the convection-permitting scale compared to coarser resolution climate model projections across various European regions for summer and autumn. Electronic supplementary material The online version of this article (10.1007/s00382-020-05192-8) contains supplementary material, which is available to authorized users.

We investigate the global distribution of hourly precipitation and its connections with the El Niño–Southern Oscillation (ENSO) using both satellite precipitation estimates and the global sub-daily rainfall gauge dataset. Despite limited moisture availability over continental surfaces, we find that the highest mean and extreme hourly precipitation intensity (HPI) values are mainly located over continents rather than over oceans, a feature that is not evident in daily or coarser resolution data. After decomposing the total precipitation into the product of the number of wet hours (NWH) and HPI, we find that ENSO modulates total precipitation mainly through the NWH, while its effects on HPI are more limited. The contrasting responses to ENSO in NWH and HPI is particularly apparent at the rising branches of the Pacific and Atlantic Walker Circulations, and is also notable over land-based gauges in Australia, Malaysia, the USA, Japan and Europe across the whole distribution of hourly precipitation (i.e. extreme, moderate and light precipitation). These results provide new insights into the global precipitation distribution and its response to ENSO forcing.

Eastern Africa’s fast-growing population is vulnerable to changing rainfall and extremes. Using the first pan-African climate change simulations that explicitly model the rainfall-generating convection, we investigate both the climate change response of key mesoscale drivers of eastern African rainfall, such as sea and lake breezes, and the spatial heterogeneity of rainfall responses. The explicit model shows widespread increases at the end of the century in mean (~40%) and extreme (~50%) rain rates, whereas the sign of changes in rainfall frequency has large spatial heterogeneity (from −50% to over +90%). In comparison, an equivalent parameterized simulation has greater moisture convergence and total rainfall increase over the eastern Congo and less over eastern Africa. The parameterized model also does not capture 1) the large heterogeneity of changes in rain frequency; 2) the widespread and large increases in extreme rainfall, which result from increased rainfall per humidity change; and 3) the response of rainfall to the changing sea breeze, even though the sea-breeze change is captured. Consequently, previous rainfall projections are likely inadequate for informing many climate-sensitive decisions—for example, for infrastructure in coastal cities. We consider the physics revealed here and its implications to be relevant for many other vulnerable tropical regions, especially those with coastal convection.

Compared to standard regional climate models (RCMs), convection-permitting models (CPMs) provide an improved representation of sub-daily precipitation statistics and extremes thanks mainly to the possibility to switch off the deep convection parameterisation, a known source of model error and uncertainties. The more realistic representation of local processes in CPMs leads to a greater confidence in their projections of future changes in short-duration precipitation extremes.The quantification of uncertainties on future changes at this resolution has been barely touched. Using the first-ever ensemble of CPMs run within the UK Climate Projections project, Fosser et al. (2020) found that the climate change signal for extreme summer precipitation may converge in CPMs in contrast to RCMs, thanks to a more realistic representation of the local storm dynamics.Here we use the first multi-model CPMs ensemble over the greater Alpine region, run under the auspices of the World Climate Research Programme’s (WCRP) Coordinated Regional Downscaling Experiment Flagship Pilot Study on Convective phenomena at high resolution over Europe and the Mediterranean (Coppola et al. 2020). Several statistics are used to determine the uncertainties in the climate change signal trying to disentangle model uncertainties from natural variability. We found that the contribution of model to the total uncertainties is substantially reduced in CPMs compared to the driving models in summer. This is likely linked to the removal of the uncertainties associated with the convective parameterisation and to a more realistic representation of convective and local dynamical processes in the CPMs. Fosser G, Kendon EJ, Stephenson D, Tucker S (2020) Convection‐Permitting Models Offer Promise of More Certain Extreme Rainfall Projections. Geophys Res Lett 47:0–2. doi: 10.1029/2020GL088151Coppola, E., Sobolowski, S., Pichelli, E. et al.A first-of-its-kind multi-model convection permitting ensemble for investigating convective phenomena over Europe and the Mediterranean. Clim Dyn55, 3–34 (2020). https://doi.org/10.1007/s00382-018-4521-8

Extratropical windstorms can lead to considerable impacts in the UK. Anthropogenic climate change is likely to influence the frequency of extreme windstorms, although there is considerable uncertainty in the simulated response by climate models due to internal variability and differences in climate model formulations. A further source of uncertainty arises from model inadequacies in their representation of key processes that drive extreme winds and their future changes due to their spatial resolution. To assess this uncertainty, we study the UKCP18 climate projections, generated by the UK Met Office, which comprises a 12-member perturbed parameter ensemble from a 60km global climate model (GCM), downscaled by a 12km regional climate model (RCM) over Europe and a 2.2km convection-permitting model (CPM) over the UK. We study a control (1981-2000) and future (2061-2080, RCP8.5) period over a domain covering the UK and Ireland. Storm intensity is quantified using the storm severity index (SSI) which incorporates surface wind gusts, while we also assess wind speeds at 850hPa. The CPM and RCM project a future increase in the frequency of extreme windstorms and both are very similar in their representation of the SSI as well as extreme winds at 850hPa. In contrast, the GCM underestimates the severity of windstorms due to poorer representation of cold sector winds driven by cold conveyor belts and sting jets. Furthermore, the GCM projects little change in extreme windstorms in the future period resulting in a large underestimation in the future change compared to the CPM and RCM. Overall, little difference is seen between the CPM and RCM, with CPM added value largely restricted to fine-scale detail in the spatial structure of storms. This may in part be due to the small domain size of the CPM, and the relatively high resolution of the RCM. Results for the GCM may bring into question the usefulness of coarser resolution models, such as those used in CMIP5 and CMIP6, for studying future changes in windstorm severity.

In the twenty-first century, extreme weather events leading to flooding and heat waves, have become one of the most severe challenges in urban areas, especially under the circumstances of local climate change and rapid urbanisation. In the future, cities are going to encounter more severe natural disaster risks and understanding how these could combine with modification of the urban environment (for example through adoption of green infrastructure) is critical for decisions relating to mitigation and adaptation to climate change. Green infrastructure is a subset of resilient infrastructure, which may mitigate the adverse effects caused by extreme weather and contribute to regulating urban climate. In addition, high-performing green spaces bring additional benefits for society in terms of health and wellbeing. The Weather Research and Forecasting (WRF) model is a numerical weather prediction system supporting both atmospheric research and operational forecasting. Within this modelling system, there is the possibility to modify parameters according to various urban areas within the WRF-Urban configuration. In this study, Newcastle upon Tyne (a UK city with the benefit of a lot of observational sensor data) is selected as an initial target city for identifying the optimal WRF configuration by varying the model resolution, domain size and nesting strategy. Future work will explore the influence of implementing green infrastructure in the context of climate change and urbanisation, then extending this analysis to London.

Extra-tropical windstorms are one of the costliest natural hazards affecting Europe, and windstorms that develop a sting jet are extremely damaging. A sting jet is a mesoscale core of very high wind speeds that occurs in Shapiro–Keyser type cyclones, and high-resolution models are required to adequately model sting jets. Here, we develop a low-cost methodology to automatically detect sting jets, using the characteristic warm seclusion of Shapiro–Keyser cyclones and the slantwise descent of high wind speeds, within pan-European 2.2 km convection-permitting climate model (CPM) simulations. The representation of wind gusts is improved with respect to ERA-Interim reanalysis data compared to observations; this is linked to better representation of cold conveyor belts and sting jets in the CPM. Our analysis indicates that Shapiro–Keyser cyclones, and those that develop sting jets, are the most damaging windstorms in present and future climates. The frequency of extreme windstorms is projected to increase by 2100 and a large contribution comes from sting jet storms. Furthermore, extreme wind speeds and their future changes are underestimated in the global climate model (GCM) compared to the CPM. We conclude that the CPM adds value in the representation of extreme winds and surface wind gusts and can provide improved input for impact models compared to coarser resolution models.

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.

Precipitation within extratropical cyclones is very likely to increase towards the end of the century in a business-as-usual scenario. We investigate hourly precipitation changes in end-of-century winter storms with the first km-scale model ensemble covering northwest Europe and the Baltic region. This is an ensemble that explicitly represents convection (convection permitting models (CPMs)). Models agree that future winter storms will bring 10%-50% more precipitation, with the same level of light precipitation but more moderate and heavy precipitation, together with less frequent frozen precipitation. The warm sector precipitation rates will get closer (up to similar) to those in present-day autumn storms, along with higher convective available potential energy and convective inhibition, suggesting more convection embedded in storms. To the first order, mean hourly precipitation changes in winter storms are driven by temperature increase (with little relative humidity changes) and storm dynamical intensity (more uncertain), both captured by regional climate models (RCMs). The CPMs agree with this, and in addition, most CPMs show more increase in intense precipitation in the warm sector of storms compared to their parent RCM., Environmental Research Letters, 17 (11), ISSN:1748-9326, ISSN:1748-9318

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’.

Extra-tropical windstorms are one of the costliest natural hazards affecting Europe, and windstorms that develop a sting-jet are extremely damaging. A sting-jet is a mesoscale core of very high wind speeds that occurs in Shapiro-Keyser type cyclones, and high-resolution models are required to adequately model sting-jets. Here, we develop a low-cost methodology to automatically detect sting jets, using the characteristic warm seclusion of Shapiro-Keyser cyclones and the slantwise descent of high wind speeds, within pan-European 2.2km convection-permitting climate model (CPM) simulations over Europe. The representation of wind gusts is improved with respect to ERA-Interim reanalysis data compared to observations; this is linked to better representation of cold conveyor belts and sting-jets in the CPM. Our analysis indicates that Shapiro-Keyser cyclones, and those that develop sting-jets, are the most damaging windstorms in present and future climates. The frequency of extreme windstorms is projected to increase by 2100 and a large contribution comes from sting-jet storms. Furthermore, extreme wind speeds and their future changes are underestimated in the GCM compared to the CPM. We conclude that the CPM adds value in the representation of extreme winds and surface wind gusts and can provide improved input for impact models compared to coarser resolution models.

Increasingly, we are using high-resolution convection-permitting models for climate projections but these models are less well understood in terms of the interaction between soil moisture, precipitation and evapotranspiration. The work was motivated by the discovery of warm, dry biases in summer in the 2.2 km convection-permitting model over France and eastern Europe compared to the 12 km convection-parametrised model that were associated with drier soils. We analyse several 12 km and 2.2 km versions of the Met Office Unified Model including sensitivity tests relating to soil hydraulics, land cover type and runoff model. We conduct similar tests using the land surface only to compare results between online and offline versions as the absence of some feedbacks can also produce differences.

Met Office convection-permitting 2.2km simulations over a European domain show 10-20% larger increases in winter mean precipitation at the end of the century compared to their 25km convection-parameterised driving model. We identify individual storms with a maximum vorticity tracking algorithm and look at storm characteristics at their time of deepest minimum sea level pressure. We show that the thermodynamical characteristics of future winter storms are getting closer to present-day autumn storms, with future winter storms showing larger values of convective available potential energy and convective inhibition and more intense rainfall in their warm sector. This suggests that embedded convection in the warm conveyor belt is a good candidate to explain the larger future intensification of rainfall per storm in the 2.2km model compared to the convection-parameterised model. Multi-model analysis is underway to identify whether these conclusions hold in other convection-permitting models.

Extra-tropical windstorms are one of the costliest natural hazards affecting Europe, and windstorms that develop a phenomenon known as a sting-jet account for some of the most damaging storms. A sting-jet (SJ) is a mesoscale core of high wind speeds that occurs in particular types of cyclones, specifically Shapiro-Keyser (SK) cyclones, and can produce extremely damaging surface wind gusts. High-resolution climate models are required to adequately model SJs and so it is difficult to gauge their contribution to current and future wind risk. In this study, we develop a low-cost methodology to automate the detection of sting jets, using the characteristic warm seclusion of SK cyclones and the slantwise descent of high wind speeds, within pan-European 2.2km convection-permitting climate model (CPM) simulations. Following this, we quantify the contribution of such storms to wind risk in Northern Europe in current and future climate simulations, and secondly assess the added value offered by the CPM compared to a traditional coarse-resolution climate model. This presentation will give an overview of the developed methods and the results of our analysis.Comparing with observations, we find that the representation of wind gusts is improved in the CPM compared to ERA-Interim reanalysis data. Storm severity metrics indicate that SK cyclones account for the majority of the most damaging windstorms. The future simulation produces a large increase (>100%) in the number of storms exceeding high thresholds of the storm metric, with a large contribution to this change (40%) coming from windstorms in which a sting-jet is detected. Finally, we see a systematic underestimation in the GCM compared to the CPM in the frequency of extreme wind speeds at 850hPa in the cold sector of cyclones, likely related to better representation of sting-jets and the cold conveyor belt in the CPM. This underestimation is between 20-40% and increases with increasing wind speed above 35m/s. We conclude that the CPM adds value in the representation of severe surface wind gusts, providing more reliable future projections and improved input for impact models.

Compared to standard regional climate models (RCMs), convection-permitting models (CPMs) provide an improved representation of sub-daily precipitation statistics and extremes thanks mainly to the possibility to switch off the deep convection parameterisation, a known source of model error and uncertainties. The more realistic representation of local processes in CPMs leads to a greater confidence in their projections of future changes in short-duration precipitation extremes. Recent literature on CPMs seems to agree on a future increase of extreme precipitation, above Clausius‐Clapeyron scaling in some cases, which is likely to have severe socio-economic impacts.The quantification of uncertainties on future changes at this resolution has been barely touched. Using the first‐ever ensemble of CPMs run within the UK Climate Projections project, Fosser et al. (2020) found that the climate change signal for extreme summer precipitation may converge in CPMs in contrast to RCMs, thanks to a more realistic representation of the local storm dynamics.Here we use the first multi-model CPMs ensemble over the greater Alpine region, run under the auspices of the World Climate Research Programme’s (WCRP) Coordinated Regional Downscaling Experiment Flagship Pilot Study on Convective phenomena at high resolution over Europe and the Mediterranean (Coppola et al. 2020). In our analysis we compared the uncertainties in the CPMs ensemble to the driving models following a similar method to Fosser et al. (2020). In this presentation we will show if multi-model CPMs can really provide more certain extreme rainfall projections then their parent coarser resolution models. Fosser G, Kendon EJ, Stephenson D, Tucker S (2020) Convection‐Permitting Models Offer Promise of More Certain Extreme Rainfall Projections. Geophys Res Lett 47:0–2. doi: 10.1029/2020GL088151Coppola, E., Sobolowski, S., Pichelli, E. et al. A first-of-its-kind multi-model convection permitting ensemble for investigating convective phenomena over Europe and the Mediterranean. Clim Dyn 55, 3–34 (2020). https://doi.org/10.1007/s00382-018-4521-8

The UNSEEN (UNprecedented Simulated Extremes using ENsembles) method involves using a large ensemble of initialised climate model simulations to increase the sample size of rare events. In this work we extended UNSEEN to focus on intense summertime daily rainfall events. Specifically, plausible extreme rainfall scenarios were developed to help understand potential surface water flooding impacts, and ultimately better inform flood management and resilience across the UK. To help address modelling limitations a large ensemble of simulations from two climate models were used; an initialised 25km global model that uses parametrized convection, and a dynamically downscaled 2.2km model that uses explicit convection. Climate model fidelity was assessed using a regional pooling technique based on extreme value theory. Across much of the UK both models are indistinguishable from the observations in terms of the statistical characteristics which govern the magnitude of very rare return periods. The UNSEEN analysis provides new estimates of plausible extreme return levels (i.e. 1-in-1000 year) across the UK and can reduce uncertainty in the expected frequency of very rare events by 50-70% compared to estimates using observations alone. These results enable suitable observed rainfall profiles to be uplifted to plausible extreme return levels, which can then be used within regional hydrological models to stress test surface flooding scenarios. The annual chance of unprecedented daily rainfall events in the current climate is also quantified, and found to be up to 5% (1-in-20 year return level) for many grid cells across southern parts of the UK. Finally, a significant benefit of the UNSEEN approach over purely statistical emulators is the use of dynamical climate models which allow the large-scale dynamical drivers of extreme daily summertime rainfall to be assessed.

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).

Global climate models struggle to simulate both the convection and cloud ice fundamental to lightning formation. We use the first convection‐permitting, future climate simulations for the lightning hot spot of Africa, at the same time utilizing an ice‐based lightning parametrization. Both the model and observations show that lightning over Africa's drier areas, as well as the moist Congo, have more lightning per rainfall than other regions. Contrary to results in the literature, the future projection shows little increase in total lightning (~107 flashes (or 2%) per degree warming). This is a consequence of increased stability reducing the number of lightning days, largely offsetting the increased graupel and updraft velocity driving an increase in lightning per lightning day. The next step is to establish if these results are robust across other models and, if combined with parametrized‐convection models, whether ensemble‐based information on the possible responses of lightning to climate change can be investigated. Plain Language Summary Lightning depends on ascending air in thunderstorms and the collision of cloud ice particles, which charge the thundercloud. Many climate models have too coarse a resolution to reliably capture these processes. We focus on Africa, which has some of the most frequent lightning in the world. We use a model that is much higher resolution than usual, and this allows us to explicitly simulate the deep convection associated with thunderstorms as well as provide more detailed representation of the distribution of cloud ice particles. Our results show that in drier regions, as well as the much wetter Congo, there is relatively more lightning per kilogram of surface rainfall than there is in other parts of the continent. Lightning does increase across the continent under climate change, but by a relatively small amount. This is despite the number of days with lightning decreasing as the lower atmosphere becomes more stable. On days with lightning, there are more lightning flashes because there is an increase in cloud ice and intensity of convection. This study gives much more detailed information about African lightning than previous work. However, it is a single simulation. Future research should look at these results across other climate models.

Subdaily rainfall extremes have been found to intensify, both from observations and climate model simulations, but much uncertainty remains regarding future changes in the spatial structure of rainfall events. Here, future changes in the characteristics of heavy summer rainfall are analyzed by using two sets (1980–2000, 2060–2080) of 12‐member 20‐year‐long convection‐permitting ensemble simulations (2.2 km, hourly) over the UK. We investigated how the peak intensity, spatial coverage and the speed of rainfall events will change and how those changes jointly affect hourly extremes at different spatial scales. We found that in addition to the intensification of heavy rainfall events, the spatial extent tends to increase in all three subregions, and by up to 49.3% in the North‐West. These changes act to exacerbate intensity increases in extremes for most of spatial scales (North: 30.2%–34.0%, South: 25.8%). The increase in areal extremes is particularly pronounced for catchments with sizes 20–500 km2.

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 study assesses the added-value offered by a regional convection-permitting climate model (CPM) in its representation of sting-jets (SJs); a mesoscale slanted core of strong winds within a Shapiro-Keyser type of cyclone that can lead to extremely damaging surface wind speeds close to southern side of a cyclone’s centre. Low-resolution climate models cannot resolve SJs, and so estimates of risk posed by extreme winds due to SJs are difficult to determine and will likely be underestimated in coarse-resolution climate simulations.We analyse three 10-year simulations from the UK Met Office, run at a 2.2km resolution over a European domain. The simulations include a hindcast driven by the ERA-Interim reanalysis dataset (ERAI) for the period 2001-2010, as well as a present day (2001-2010) and future simulation (2100-2109) that follows the RCP8.5 scenario. Both climate simulations are driven by a 25km GCM. To diagnose potential SJ storms in each simulation, we firstly identify cyclone tracks with a cyclone tracking algorithm and apply an objective indicator that identifies the warm seclusion of a Shapiro-Keyser cyclone and the slanted core of strong winds of the sting-jet.Within this presentation, we will present the objective indicator as well as results of the added value seen in the CPM. In order to identify any added value of the CPM, we analyse differences between the CPM and its respective driving data, in terms of storm severity metrics and their future projections. An example metric used is the Storm Severity Index that quantifies the overall severity of a storm. In all simulations, the conditional PDF of SSI for sting-jet storms is shifted towards higher values compared to PDF of the SSI from all storms within the studied domain. However, we see little difference in the SSI derived from the CPM and its respective driving model/reanalysis when CPM wind speeds are upscaled to the respective driving reanalysis/GCM grid. In further analysis, we will look to explore the added value at a local scale on the native CPM grid.

UK Climate Projections 2018 (UKCP18) included land and marine projections and were published in 2018 to replace UKCP09. The land projections had three components, and all were designed to provide more information on future weather compared to UKCP09. The first component updated the UKCP09 probabilistic projections by including newer CMIP5 data and focussing on seasonal means from individual years rather than 30-year averages. The probabilistic projections represent the wider uncertainty. The second two components (global and regional projections) both had the aim of providing plausible examples of future climate, but at different resolutions.The global projections were a combination of 13 CMIP5 models and a 15-member perturbed parameter ensemble (PPE) of coupled simulations for 1900-2100 using CMIP5 RCP8.5 from 2005 onwards. The PPE was provided at 60km atmosphere, quarter degree ocean and the large-scale conditions from twelve of the members were used to drive the regional model at both 12km and 2.2km resolution. These plausible examples are more useful for providing information about weather in a future climate to support a storyline approach for decision making.The talk will present examples of new ways to use UKCP18 compared to UKCP09. We will show how the global projections can be used to understand that the recent record winter daily maximum temperature in the UK in 2019 had a large contribution from internal variability and what this means for breaking the record in a warming climate. We also use an example from China to demonstrate one way to exploit information at different time scales, looking at how a circulation index, which is predictable and related to tropical cyclone landfall, changes in a future climate.Finally, we show that while the enhanced resolution of the global and regional projections has improved our capability to provide climate information linked to the better representation of circulation, they lack diversity in some of the key drivers of future climate. Therefore, a key way forward will be to find an appropriate balance between the need for better diversity (e.g. multiple ensembles such as CMIP or PPEs) and the need for an appropriate resolution to retain this new capability.

Convection-permitting models (CPMs) provide a better representation of sub-daily precipitation statistics and convective processes, both on climate and NWP time scales, mainly thanks to the possibility to switch off the parameterisation of convection. The improved realism of these models gives us greater confidence in their ability to project future changes in short-duration precipitation extremes.The first 12-member ensemble of convection-permitting climate simulations over the UK was completed within the latest updates to the UK Climate Projections (UKCP). The 20-year long CPM simulations for present-day and end of century periods are nested in an ensemble of regional climate model (RCM) simulations over Europe driven by a global climate model ensemble. In the driving ensembles, uncertain parameters in the model physics are varied within plausible bounds to sample uncertainty. Although no perturbations are applied directly to the CPMs, this project allow us to provide a first-ever estimate of uncertainty at convection-permitting scale and thus provide UK risk assessment studies with more reliable climate change projections at local and hourly scales.Here we will present results looking at the uncertainty in future changes in hourly precipitation extremes across the CPM ensemble, and how this differs from the driving RCM ensemble.

For the first time internationally a model at a resolution on par with operational weather forecast models has been used for national climate scenarios. As part of the UK Climate Projections (UKCP) project, an ensemble of 12 projections at 2.2km resolution have been carried out over the UK. These were launched in September 2019, with the aim of providing an improved simulation of extreme precipitation and also other high-impact events at local scales for the coming decades. At such high (2.2km) resolution, convection can be represented explicitly (‘permitted’) without the need for a parameterisation scheme, leading to a much more realistic representation of hourly precipitation characteristics, including extremes. In this talk initial results from the UKCP local (2.2km) projections will be presented. This includes new understanding of changes in winter mean precipitation, as well as projected changes in hourly precipitation extremes and the frequency of hot spells. I will also discuss remaining outstanding issues and the future outlook for convective-scale climate modelling.

We present a multi-model ensemble of regional climate model scenario simulations run at scales allowing for explicit treatment of convective processes (2-3km) over historical and end of century time slices, providing an overview of future precipitation changes over the Alpine domain within the convection-permitting CORDEX-FPS initiative. The 12 simulations of the ensemble have been performed by different research groups around Europe. The simulations are compared with high resolution observations to assess the performance over the historical period and the ensemble of 12 to 25 km resolution driving models is used as a benchmark.An improvement of the representation of fine scale details of the analyzed fields on a seasonal scale is found, as well as of the onset and peak of the summer diurnal convection. An enhancement of the projected patterns of change and modifications of its sign for the daily precipitation intensity and heavy precipitation over some regions are found with respect to coarse resolution ensemble. A change of the amplitude of the diurnal cycle for precipitation intensity and frequency is also shown, as well also a larger positive change for high to extreme events for daily and hourly precipitation distributions. The results are challenging and promising for further assessment of the local impacts of climate change.

We investigate the attribution of the flooding in Northern England that saw at least 500 homes flooded and over 1000 properties evacuated in flooded areas in 2019. This occurred during the wettest Autumn on record in some areas and also contained some very high daily rainfall totals. In the light of climate change, it is expected that intense rainfall events are to become more intense as a result of increased global average temperatures and the Clausius-Clapeyron relationship, but here we investigate quantitatively how much climate change has increased the risk of such an event to date.We use results from the 2.2km convective permitting high resolution local UK Climate Projections (UKCP) and observations to show that more intense rainfall events may already be occurring in Autumn in the UK. This work shows using this high resolution UKCP data that a heavy rainfall event exceeding 50mm in one day in Autumn was 33-40% more likely to occur in 2019 than 1985. Further work that looks at the HadGEM3-A simulations shows that these heavy rainfall days are more likely to occur in a climate impacted by human activity than one with just natural climate forcings.

Urban flooding and wet weather pollution are recognised as significant problems across the world, and changes in rainfall patterns arising as a consequence of climate change are likely to exacerbate these problems. This paper shares learning from a ground-breaking project led by CH2M for UK Water Industry Research and approaches used in other CH2M projects around the world. The UK project has explored the use of very high resolution (1.5 km) climate model output and climate analogues; other projects have used other methods to derive new design rainfall statistics commonly used in modelling wet weather collection systems for flooding and pollution investigations. Estimates of rainfall change have been used within collection system models to estimate the flooding and pollution impact of these changes. The methods applied in these projects can be replicated globally.