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Reliable projections of extreme future precipitation are fundamental for risk management and adaptation strategies. Convection‐permitting models (CPMs) explicitly resolve large convective systems and represent sub‐daily extremes more realistically than coarser resolution models, but present short records due to the high computational costs. Here, we evaluate the potential of a non‐asymptotic approach, the Simplified Metastatistical Extreme Value (SMEV) to provide information on the future change of extreme sub‐daily return levels based on CPM simulations. We focus on a complex‐orography area in the North Eastern Italy and use three 10‐year time periods COSMO‐crCLIM simulations (2.2 km resolution) under RCP8.5 scenario. When compared to a block r‐maxima approach currently used in similar applications, the proposed approach shows reduced uncertainty in rare return level estimates (about 5%–10% smaller confidence interval) and can improve the quantification of future changes from CPM simulations. We evaluate these changes and their statistical significance in return levels for 1–24 hr durations. The changes show an interesting spatial organization associated with orography, with significant positive changes located at high elevations. These positive changes tend to increase with increasing return period and decreasing duration. Because SMEV can separate the roles of event intensity and occurrence, it allows for physical interpretations of these changes. We suggest that non‐asymptotic approaches permit the quantification of change in rare extremes within available CPM runs. Plain Language Summary: Short duration heavy rainfall may lead to various natural hazards like floods and landslides. Expected change in extreme precipitation due to global warming is a major concern. However, we still cannot quantify these changes because typical climate models cannot reproduce extreme precipitation accurately. The few models that can are very computationally expensive so that we have too few simulations for properly quantifying changes in extremes using traditional statistical methods. Here, we show how to use a new statistical method to quantify extremes from short model simulations. This method is more accurate than currently used methods and may help provide additional insights on the reasons underlying the observed changes. This method could represent a new tool in the hands of the climate research community. Examining the simulations of one model over North‐Eastern Italy, we report an increase in extreme precipitation in mountainous areas and a non‐significant decrease in the low elevation areas. Key Points: Future changes in extreme precipitation are estimated from a convection‐permitting climate model using a non‐asymptotic statistical approachThe method allows to evaluate the significance of the future changes in return levels and to link them to the changing processesSignificant increase in return levels is generally found in the mountains, higher at the short durations (1–3 hr) and for rarer return levels [ABSTRACT FROM AUTHOR]

Viticulture is tied to climate, it influences the suitability of an area, yield and quality of wine grapes. Therefore, traditional wine-growing regions could be threatened by a changing climate. Italy is at-risk being part of the Mediterranean climatic hotspot and judged in 2022 the second-largest exporter of wine worldwide. The article explores the potential of climate models to predict wine grape productivity at local scale. To this end, both single and multi-regression approaches are used to link productivity data provided by two Italian wine consortia with bioclimatic indices. Temperature and precipitation-based bioclimatic indices are computed by using the observational dataset E-OBS, the high-resolution climate reanalysis product SPHERA, and both the Regional and the Convection-permitting Climate Model (RCM and CPM). The potential of CPMs to represent the impact of climate variability on wine grape productivity at local scale in Italy is evaluated. The results indicate high correlations between some bioclimatic indices and productivity. Climate models appear to be a useful tool to explain productivity variance, however, the added value of CPM, became evident only when precipitation-based indices are considered. This assessment opens the path for using climate models, especially at convection-permitting scale, to investigate future climate change impact on wine production. [ABSTRACT FROM AUTHOR]

Extreme precipitation events lead to dramatic impacts on society and the situation will worsen under climate change. Decision-makers need reliable estimates of future changes as a basis for effective adaptation strategies, but projections at local scale from regional climate models (RCMs) are highly uncertain. Here we exploit the km-scale convection-permitting multi-model (CPM) ensemble, generated within the FPS Convection project, to provide new understanding of the changes in local precipitation extremes and related uncertainties over the greater Alpine region. The CPM ensemble shows a stronger increase in the fractional contribution from extreme events than the driving RCM ensemble during the summer, when convection dominates. We find that the CPM ensemble substantially reduces the model uncertainties and their contribution to the total uncertainties by more than 50%. We conclude that the more realistic representation of local dynamical processes in the CPMs provides more reliable local estimates of change, which are essential for policymakers to plan adaptation measures. [ABSTRACT FROM AUTHOR]

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'. [ABSTRACT FROM AUTHOR]

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. Alarge 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. [ABSTRACT FROM AUTHOR]

The future increase in extreme precipitation is likely to have a severe impact on society due to flooding. Previous research has shown the improved representation of precipitation in convection‐permitting models (CPMs), but until now it has not been possible to quantify uncertainties in future changes at convective (<5 km) scales. Here we analyze the first‐ever ensemble of convection‐permitting climate projections run within the UK Climate Projections project. We find that the CPM ensemble shows a significantly stronger intensification of summer hourly precipitation compared to the driving 12 km ensemble, with increases above the Clausius‐Clapeyron relation and natural variability dominating the ensemble spread for extremes. Results suggest that the climate change signal across different CPMs may converge thanks to the more realistic representation of the local storm dynamics. We conclude that CPMs offer the promise of reducing uncertainties for extreme summer precipitation projections due to the better and explicit representation of convection. Plain Language Summary: Accurate predictions of future changes in precipitation extremes are crucial for developing effective adaptation measures to avoid severe impacts on society due to flooding. State‐of‐the‐art kilometer‐scale models, called convection‐permitting models, give a much better simulation of how rainfall varies hour by hour and thus provide credible projections of future changes in hourly rainfall extremes. Up to now it was not possible to evaluate uncertainties in the future changes in extremes at convective (<5 km) scales since only single simulations were available due to the high computational costs. Thus, the ensemble of 12 local (2.2 km) projections, run within the UK Climate Projections project, represents a key step forward for climate prediction. We find that the 2.2 km ensemble shows a significantly stronger future increase of summer hourly precipitation compared to the coarser resolution (12 km) ensemble. The climate change signals are found to be consistent across the 2.2 km ensemble simulations, with differences largely explained just by natural variations in the climate from year to year. This means that convection‐permitting models could reduce the uncertainties in future changes in extreme summer precipitation and thus allow more robust and effective adaptation policy. Key Points: Convection‐permitting model (CPM) ensemble projects an intensification above the Clausius‐Clapeyron relation for extreme precipitationClimate change signal for extreme precipitation appears to converge in the CPM ensemble, with uncertainty dominated by natural variabilityThe correct representation of convection may lead to reduced model uncertainties in future changes in extreme precipitation [ABSTRACT FROM AUTHOR]

Convection‐permitting models (CPMs) provide a better representation of sub‐daily precipitation statistics and convective processes on both climate and weather forecasting timescales. This study aims to establish what horizontal resolution and physical process settings are suitable for the first ensemble of convection‐permitting climate projections for the United Kingdom. For this purpose, 12‐year‐long simulations were run using three different convection‐permitting resolutions (grid spacing of 4 km, 2.2 km and 1.5 km) each with several configurations. The focus is on the ability to represent sub‐daily precipitation due to its potential for high impacts on society through flooding. The analysis shows that the use of a finer grid spacing within the convection‐permitting regime improves the representation of sub‐daily precipitation but the added value decreases as the grid becomes increasingly finer, while the computational costs substantially increase. Changes in the representation of physical processes can have as much impact as the grid spacing and can lead to similar differences in the diurnal cycle as between convection‐parametrized models and CPMs. Although the 4km model shows some key deficiencies that make it unreliable for climate projection, the 2.2km model performs as well as the 1.5km model for most of the metrics examined with considerable benefits in terms of computer cost. The optimal configuration and resolution identified here is being used for an ensemble of simulations run within the UK Climate Projections 2018 (UKCP18) project, which allows, for the first time, an estimate of uncertainty in future changes at convection‐permitting scale and providing more reliable climate change projections at local and hourly scales. [ABSTRACT FROM AUTHOR]

In this study we investigate the scaling of precipitation extremes with temperature in the Mediterranean region by assessing against observations the present day and future regional climate simulations performed in the frame of the HyMeX and MED-CORDEX programs. Over the 1979-2008 period, despite differences in quantitative precipitation simulation across the various models, the change in precipitation extremes with respect to temperature is robust and consistent. The spatial variability of the temperature-precipitation extremes relationship displays a hook shape across the Mediterranean, with negative slope at high temperatures and a slope following Clausius-Clapeyron (CC)-scaling at low temperatures. The temperature at which the slope of the temperature-precipitation extreme relation sharply changes (or temperature break), ranges from about 20 °C in the western Mediterranean to <10 °C in Greece. In addition, this slope is always negative in the arid regions of the Mediterranean. The scaling of the simulated precipitation extremes is insensitive to ocean-atmosphere coupling, while it depends very weakly on the resolution at high temperatures for short precipitation accumulation times. In future climate scenario simulations covering the 2070-2100 period, the temperature break shifts to higher temperatures by a value which is on average the mean regional temperature change due to global warming. The slope of the simulated future temperature-precipitation extremes relationship is close to CC-scaling at temperatures below the temperature break, while at high temperatures, the negative slope is close, but somewhat flatter or steeper, than in the current climate depending on the model. Overall, models predict more intense precipitation extremes in the future. Adjusting the temperature-precipitation extremes relationship in the present climate using the CC law and the temperature shift in the future allows the recovery of the temperature-precipitation extremes relationship in the future climate. This implies negligible regional changes of relative humidity in the future despite the large warming and drying over the Mediterranean. This suggests that the Mediterranean Sea is the primary source of moisture which counteracts the drying and warming impacts on relative humidity in parts of the Mediterranean region. [ABSTRACT FROM AUTHOR]

Regional climate projections are used in a wide range of impact studies, from assessing future flood risk to climate change impacts on food and energy production. These model projections are typically at 12-50-km resolution, providing valuable regional detail but with inherent limitations, in part because of the need to parameterize convection. The first climate change experiments at convection-permitting resolution (kilometer-scale grid spacing) are now available for the United Kingdom; the Alps; Germany; Sydney, Australia; and the western United States. These models give a more realistic representation of convection and are better able to simulate hourly precipitation characteristics that are poorly represented in coarser-resolution climate models. Here we examine these new experiments to determine whether future mid-latitude precipitation projections are robust from coarse to higher resolutions, with implications also for the tropics. We find that the explicit representation of the convective storms themselves, only possible in convection-permitting models, is necessary for capturing changes in the intensity and duration of summertime rain on daily and shorter time scales. Other aspects of rainfall change, including changes in seasonal mean precipitation and event occurrence, appear robust across resolutions, and therefore coarse-resolution regional climate models are likely to provide reliable future projections, provided that large-scale changes from the global climate model are reliable. The improved representation of convective storms also has implications for projections of wind, hail, fog, and lightning. We identify a number of impact areas, especially flooding, but also transport and wind energy, for which very high-resolution models may be needed for reliable future assessments. [ABSTRACT FROM AUTHOR]