Search

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.

Combining multiple data sources with multi-physics simulation frameworks offers new potential to extend snow model inter-comparison efforts to the Himalaya. As such, this study evaluates the sensitivity of simulated regional snow cover and runoff dynamics to different snowpack process representations. The evaluation is based on a spatially distributed version of the Factorial Snowpack Model (FSM) set up for the Astore catchment in the upper Indus basin. The FSM multi-physics model was driven by climate fields from the High Asia Refined Analysis (HAR) dynamical downscaling product. Ensemble performance was evaluated primarily using MODIS remote sensing of snow-covered area, albedo and land surface temperature. In line with previous snow model inter-comparisons, no single FSM configuration performs best in all of the years simulated. However, the results demonstrate that performance variation in this case is at least partly related to inaccuracies in the sequencing of inter-annual variation in HAR climate inputs, not just FSM model limitations. Ensemble spread is dominated by interactions between parameterisations of albedo, snowpack hydrology and atmospheric stability effects on turbulent heat fluxes. The resulting ensemble structure is similar in different years, which leads to systematic divergence in ablation and mass balance at high elevations. While ensemble spread and errors are notably lower when viewed as anomalies, FSM configurations show important differences in their absolute sensitivity to climate variation. Comparison with observations suggests that a subset of the ensemble should be retained for climate change projections, namely those members including prognostic albedo and liquid water retention, refreezing and drainage processes.

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.

There is an urgent need for high-quality and high-spatial-resolution hourly precipitation products around the globe, including the UK. Although hourly precipitation products exist for the UK, these either contain large errors, or are insufficient in spatial resolution. An efficient way to solve this is to develop a merged precipitation product that combines the information and benefits from multiple data sources, improving both the spatial resolution and accuracy of hourly precipitation estimates over the UK. In this study, we develop a UK high-resolution gauge–radar–satellite merged hourly precipitation analysis: the UKGrsHP. It covers the UK from 12.5° W to 3.5° E, 49° N–60° N, with a spatial resolution of 0.01° × 0.01° in latitude/longitude (equivalent to 1 km resolution in the mid-latitudes). An optimal interpolation (OI)–based multi-source merging scheme with compound strategy is developed and tested for producing the UKGrsHP. Three input data sources are used: gauge analysis data interpolated from 1903 quality-controlled hourly observations, the UK Nimrod radar precipitation analysis and the GSMaP global satellite precipitation analysis. Using independent tests against ~ 220 independent gauge observations on 1 year’s experimental UKGrsHP, covering the period from January to December 2014, we find that the final merged data performs better than three individual precipitation analyses used as inputs. A full version of the UKGrsHP starting in April 2004 is now under production, which will have wide applications in climate services and scientific research across multiple disciplines. Electronic supplementary material The online version of this article (10.1007/s00382-020-05144-2) contains supplementary material, which is available to authorized users.

Intense sub‐daily summer rainfall is linked to flooding impacts in the UK. Characterizing the atmospheric conditions prior to the rainfall event can improve understanding of the large‐scale mechanisms involved. The most intense sub‐daily rainfall intensity data generated from rain gauge records across the UK over the period 1979‐2014 are combined with fields from the ERA Interim reanalysis to characterize atmospheric conditions prior to heavy rainfall events. The 200 most intense 3‐hourly events for six UK regions are associated with negative anomalies in sea level pressure (< –2 hPa) and 200hPa geopotential height (

Downscaling is usually necessary for robust hydrological impact assessments. This may be undertaken using a wide range of methods, including a combination of dynamical and statistical-stochastic downscaling. This study uses the Spatial–Temporal Neyman-Scott Rectangular Pulses model—RainSimV3, the precipitation-conditioned daily weather generator—ICAAM-WG, and the change factor approach for downscaling synthetic climate scenarios for robust hydrological impact assessment at middle-sized basins. The ICAAM-WG was developed based on the concept of the Climate Research Unit daily weather generator (CRU-WG), motivated by the need for improved representation of heat waves by downscaling methods given the positive feedback between low soil moisture and high air temperature. We demonstrated the validity of the proposed methodology in the 705-km2 Mediterranean climate basin in southern Portugal. The results show that, for the control period 1980–2010, both RainSimV3 and ICAAM-WG reproduced not only the mean climatology, but also extreme wet and low precipitation events, as well as the extremes of temperature and heat waves. We found that downscaling with ICAAM-WG (SIM6), which uses second-order autoregressive processes for the simulation of temperature during consecutive dry and wet days, outperformed ICAAM-WG (SIM4), which used only first-order autoregressive processes, leading to improved simulation of heat waves. ICAAM-WG (SIM6) well reproduced observed heatwave extremes with return periods of up to 30 years; however, ICAAM-WG (SIM4) overestimated these extremes substantially. This indicates the importance of incorporating second-order autoregressive processes in the simulation of heatwave length. In the context of climate warming, the proposed methodology provides a tool to improve downscaled projections of future extremes with confidence intervals for not only wet events but also dry spells and heat waves.

The synoptic‐scale meteorological conditions leading up to the 30 most extreme subdaily summer rain events for two regions of the United Kingdom (northwest and southeast) were examined for the period 1979–2013. Using a recently available, quality controlled, national hourly rain gauge data set, we were able to identify extreme 3‐hr rainfall accumulations that may be indicative of flash flooding. Composites of the state of the atmosphere leading up to these dates were produced to investigate synoptic‐scale processes, thus potentially allowing for them to be identified in coarse resolution reanalyses and in climate models. The results show that the two regions have different dominant synoptic‐scale conditions leading to extreme 3‐hr rainfall, which is thought to be related to the type of rainfall typically experienced in each region. In particular, positive anomalies in mean sea level pressure and the geopotential height at 200 hPa over the United Kingdom are associated with extreme rainfall in the northwest, where the position of the westerly jet is also important. For the southeast, no clear anomalous synoptic‐scale conditions could be identified; however, localized moisture sources and unstable air masses were observed in association with extremes. These results indicate the importance of better understanding of both synoptic‐scale and thermodynamic drivers of short‐duration extreme rainfall, with potential implications in forecasting and flood warning, as well as for understanding the representation of key processes by regional climate models., Key Points Different synoptic‐scale meteorological processes dominate on days with JJA subdaily extreme rainfall depending on the region of interestA positive anomaly in the geopotential height is associated with extreme rain events in the northwest of the United KingdomLocalized moisture sources and unstable air masses observed with extreme rain events in the southeast of the United Kingdom

Data paucity is a severe barrier to the characterization of Himalayan near-surface climates. Regional climate modeling can help to fill this gap, but the resulting data products need critical evaluation before use. This study aims to extend the appraisal of one such dataset, the High Asia Refined Analysis (HAR). Focusing on the upper Indus basin (UIB), the climatologies of variables needed for process-based hydrological and cryospheric modeling are evaluated, leading to three main conclusions. First, precipitation in the 10-km HAR product shows reasonable correspondence with most in situ measurements. It is also generally consistent with observed runoff, while additionally reproducing the UIB’s strong vertical precipitation gradients. Second, the HAR shows seasonally varying bias patterns. A cold bias in temperature peaks in spring but reduces in summer, at which time the high bias in relative humidity diminishes. These patterns are concurrent with summer overestimation (underestimation) of incoming shortwave (longwave) radiation. Finally, these seasonally varying biases are partly related to deficiencies in cloud, snow, and albedo representations. In particular, insufficient cloud cover in summer leads to the overestimation of incoming shortwave radiation. This contributes to the reduced cold bias in summer by enhancing surface warming. A persistent high bias in albedo also plays a critical role, particularly by suppressing surface heating in spring. Improving representations of cloud, snow cover, and albedo, and thus their coupling with seasonal climate transitions, would therefore help build upon the considerable potential shown by the HAR to fill a vital data gap in this immensely important basin.

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’.

Heatwaves and extreme rainfall events are natural hazards that can have severe impacts on society. The relationship between temperature and extreme rainfall has received scientific attention with studies focussing on how single daily or sub-daily rainfall extremes are related to day-to-day temperature variability. However, the impact multi-day heatwaves have on sub-daily extreme rainfall events and how extreme rainfall properties change during different stages of a heatwave remains mostly unexplored.In this study, we analyse sub-daily rainfall records across Australia, a country that experiences severe natural hazards on a frequent basis, and determine their extreme rainfall properties, such as rainfall intensity, duration and frequency during SH-summer heatwaves. These properties are then compared to extreme rainfall properties found outside heatwaves, but during the same time of year, to examine to what extent they differ from normal conditions. We also conduct a spatial analysis to investigate any spatial patterns that arise.We find that rainfall breaking heatwaves is often more extreme than average rainfall during the same time of year. This is especially prominent on the eastern and south-eastern Australian coast, where frequency and intensity of sub-daily rainfall extremes show an increase during the last day or the day immediately after a heatwave. We also find that although during heatwaves the average rainfall amount and duration decreases, there is an increase in sub-daily rainfall intensity when compared to conditions outside heatwaves. This implies that even though Australian heatwaves are generally characterised by dry conditions, rainfall occurrences within heatwaves are more intense.Both heatwaves and extreme rainfall events pose great challenges for many sectors such as agriculture, and especially if they occur together. Understanding how and to what degree these events co-occur could help mitigate the impacts caused by them.

Short duration precipitation extremes can lead to severe flash flooding and destructive landslides. Yet many gaps remain in our understanding of these acute precipitation events, partly due to the lack of accessible and high quality sub-daily observational datasets available to researchers. To address this problem, the INTENSE project (leading the GEWEX Hydroclimatology Panel Cross-Cutting Project on Sub-Daily Extremes) has coordinated a major international effort to collate sub-daily precipitation observations from around the world. The resulting Global Sub-Daily Rainfall (GSDR) dataset contains hourly precipitation records from over 20,000 gauges globally. The quality of the raw data underpinning the GSDR dataset is variable, so an automated and wide-ranging quality control procedure has been developed and applied to the records. To facilitate research and other applications of the dataset, we have defined and calculated a novel set of sub-daily precipitation indices. These indices complement and extend the ETCCDI daily precipitation indices by characterising key aspects of shorter duration precipitation variability, including intensity, duration and frequency properties. Project partners and other collaborators continue to augment the resulting indices database by performing the calculations on their own observations and sharing these with the INTENSE project, with new contributors always welcome. This combined effort has led to an extensive observation-based climatology of various sub-daily precipitation characteristics (including extremes) across large parts of the world. These indices will be publicly available for as many gauges as possible, alongside a gridded dataset that also incorporates indices calculated for additional restricted-access gauge records.

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.

Climate extremes, as recurring events, are the result of natural climate variability (including phenomena such as El Nino), which can have significant local and regional impacts on the society and the environment. These events are typically related to unusually high or low temperature, prolonged dry or wet conditions, heavy precipitation, or extreme winds. Recently, there has been considerable debate about the possible consequences of warming of the atmosphere for terrestrial ecosystems and societies, particularly related to changes in frequency, intensity, spatial extent, and duration of climate extremes over most land areas. This chapter provides an overview of the state of knowledge concerning the science of climate variability and climate extremes, emphasizing both present and past climate conditions and the projected changes over the 21st century. Science-based information based on robust findings and relevant uncertainties on changing extremes can provide useful information for sectorial planning, disaster risk prevention, and overall reduction of societal vulnerability related to climate and weather extremes.

Extremes of precipitation can cause flooding and droughts which can lead to substantial damages to infrastructure and ecosystems and can result in loss of life. It is still uncertain how hydrological extremes will change with global warming as we do not fully understand the processes that cause extreme precipitation under current climate variability. Progress has been limited so far in this area due to the lack of data available to researchers. The INTENSE project, part of the with the World Climate Research Programme (WCRP)'s Grand Challenge on 'Understanding and Predicting Weather and Climate Extremes', has used a novel and fully-integrated data-modelling approach to provide a step-change in our understanding of the nature and drivers of global sub-daily precipitation extremes and change on societally relevant timescales.The first step towards achieving this was to construct a new global sub-daily precipitation dataset. The dataset contains hourly rainfall data from ~25,000 gauges across >200 territories from a wide range of sources. A rigorous, flexible quality-control algorithm has been developed to ensure that the data collected is as accurate as possible. The QC methodology combines a number of checks against neighbouring gauges, known biases and errors, and thresholds based on the Expert Team on Climate Change Detection and Indices (ETCCDI) Climate Change Indices. An open source version of the QC software will set a new standard for verifying sub-daily precipitation data.A set of global sub-daily precipitation indices have also been produced (and will be made freely available later this year) based upon stakeholder recommendations including indices that describe maximum rainfall totals and timing, the intensity, duration and frequency of storms, frequency of storms above specific thresholds and information about the diurnal cycle. The talk will discuss the major findings from the production of these new global sub-daily precipitation indices.

The question of when the influence of climate change on U.K. rainfall extremes may be detected is important from a planning perspective, providing a time scale for necessary climate change adaptation measures. Short-duration intense rainfall is responsible for flash flooding, and several studies have suggested an amplified response to warming for rainfall extremes on hourly and subhourly time scales. However, there are very few studies examining the detection of changes in subdaily rainfall. This is due to the high cost of very high-resolution (kilometer scale) climate models needed to capture hourly rainfall extremes and to a lack of sufficiently long, high-quality, subdaily observational records. Results using output from a 1.5-km climate model over the southern United Kingdom indicate that changes in 10-min and hourly precipitation emerge before changes in daily precipitation. In particular, model results suggest detection times for short-duration rainfall intensity in the 2040s in winter and the 2080s in summer, which are, respectively, 5–10 years and decades earlier than for daily extremes. Results from a new quality-controlled observational dataset of hourly rainfall over the United Kingdom do not show a similar difference between daily and hourly trends. Natural variability appears to dominate current observed trends (including an increase in the intensity of heavy summer rainfall over the last 30 years), with some suggestion of larger daily than hourly trends for recent decades. The expectation of the reverse, namely, larger trends for short-duration rainfall, as the signature of underlying climate change has potentially important implications for detection and attribution studies.

Midlatitude extreme precipitation events are caused by well-understood meteorological drivers, such as vertical instability and low pressure systems. In principle, dynamical weather and climate models behave in the same way, although perhaps with the sensitivities to the drivers varying between models. Unlike parameterized convection models (PCMs), convection-permitting models (CPMs) are able to realistically capture subdaily extreme precipitation. CPMs are computationally expensive; being able to diagnose the occurrence of subdaily extreme precipitation from large-scale drivers, with sufficient skill, would allow effective targeting of CPM downscaling simulations. Here the regression relationships are quantified between the occurrence of extreme hourly precipitation events and vertical stability and circulation predictors in southern United Kingdom 1.5-km CPM and 12-km PCM present- and future-climate simulations. Overall, the large-scale predictors demonstrate skill in predicting the occurrence of extreme hourly events in both the 1.5- and 12-km simulations. For the present-climate simulations, extreme occurrences in the 12-km model are less sensitive to vertical stability than in the 1.5-km model, consistent with understanding the limitations of cumulus parameterization. In the future-climate simulations, the regression relationship is more similar between the two models, which may be understood from changes to the large-scale circulation patterns and land surface climate. Overall, regression analysis offers a promising avenue for targeting CPM simulations. The authors also outline which events would be missed by adopting such a targeted approach.

The UK Met Office has previously conducted convection-permitting climate simulations over the southern UK (Kendon et al. in Nat Clim Change 4:570–576, 2014). The southern UK simulations have been followed up by a new set of northern UK simulations using the same model configuration. Here we present the mean and extreme precipitation projections from these new simulations. Relative to the southern UK, the northern UK projections show a greater summertime increase of return levels and extreme precipitation intensity in both $$1.5\,\hbox {km}$$ convection-permitting and $$12\,\hbox {km}$$ convection-parameterised simulations, but this increase is against a backdrop of large decreases in summertime mean precipitation and precipitation frequency. Similar to the southern UK, projected change is model resolution dependent and the convection-permitting simulation projects a larger intensification. For winter, return level increases are somewhat lower than for the southern UK. Analysis of model biases highlight challenges in simulating the diurnal cycle over high terrain, sensitivity to domain size and driving-GCM biases, and quality issues of radar precipitation observations, which are relevant to the wider regional climate modelling community.

The “Karakoram Vortex” (KV), hereafter also referred to as the “Western Tibetan Vortex” (WTV), has recently been recognized as a large-scale atmospheric circulation system related to warmer (cooler) near-surface and mid-lower troposphere temperatures above the Karakoram in the western Tibetan Plateau (TP). It is characterized by a deep, anti-cyclonic (cyclonic) wind anomaly associated with higher (lower) geopotential height in the troposphere, during winter and summer seasons. In this study, we further investigate the seasonality and basic features of the WTV in all four seasons, and explore its year-to-year variability and influence on regional climate. We find the WTV accounts for the majority of year-to-year circulation variability over the WTP as it can explain over 50% ( $${R^2} \geqslant 0.5$$ ) variance of the WTP circulation on multiple levels throughout the troposphere, which declines towards the eastern side of the TP in most seasons. The WTV is not only more (less) active but also has a bigger (smaller) domain area, with a deeper (shallower) structure, in winter and spring (summer and autumn). We find that the WTV is sensitive to both the location and intensity of the Subtropical Westerly Jet (SWJ), but the relationship is highly dependent on the climatological mean location of SWJ axes relative to the TP in different seasons. We also show that the WTV significantly modulates surface and stratospheric air temperatures, north–south precipitation patterns and total column ozone surrounding the western TP. As such, the WTV has important implications for the understanding of atmospheric, hydrological and glaciological variability over the TP.

Increasing precipitation extremes are one of the possible consequences of a warmer climate. These may exceed the capacity of urban drainage systems, and thus impact the urban environment. Because short-duration precipitation events are primarily responsible for flooding in urban systems, it is important to assess the response of extreme precipitation at hourly (or sub-hourly) scales to a warming climate. This study aims to evaluate the projected changes in extreme rainfall events across the region of Sicily (Italy) and, for two urban areas, to assess possible changes in Depth-Duration-Frequency (DDF) curves. We used Regional Climate Model outputs from Coordinated Regional Climate Downscaling Experiment for Europe area ensemble simulations at a ~12 km spatial resolution, for the current period and 2 future horizons under the Representative Concentration Pathways 8.5 scenario. Extreme events at the daily scale were first investigated by comparing the quantiles estimated from rain gauge observations and Regional Climate Model outputs. Second, we implemented a temporal downscaling approach to estimate rainfall for sub-daily durations from the modelled daily precipitation, and, lastly, we analysed future projections at daily and sub-daily scales. A frequency distribution was fitted to annual maxima time series for the sub-daily durations to derive the DDF curves for 2 future time horizons and the 2 urban areas. The overall results showed a raising of the growth curves for the future horizons, indicating an increase in the intensity of extreme precipitation, especially for the shortest durations. The DDF curves highlight a general increase of extreme quantiles for the 2 urban areas, thus underlining the risk of failure of the existing urban drainage systems under more severe events.

Identifying mechanisms driving spatially heterogeneous glacial mass-balance patterns in the Himalaya, including the ‘Karakoram anomaly’, is crucial for understanding regional water resource trajectories. Streamflows dependent on glacial meltwater are strongly positively correlated with Karakoram summer air temperatures, which show recent anomalous cooling. We explain these temperature and streamflow anomalies through a circulation system—the Karakoram vortex—identified using a regional circulation metric that quantifies the relative position and intensity of the westerly jet. Winter temperature responses to this metric are homogeneous across South Asia, but the Karakoram summer response diverges from the rest of the Himalaya. We show that this is due to seasonal contraction of the Karakoram vortex through its interaction with the South Asian monsoon. We conclude that interannual variability in the Karakoram vortex, quantified by our circulation metric, explains the variability in energy-constrained ablation manifested in river flows across the Himalaya, with important implications for Himalayan glaciers’ futures. The mass balance of glaciers will influence regional water resources in the Himalayas. Changes in atmospheric dynamics, the Karakoram vortex contraction, and interaction with the monsoon influence the glacial melt of the region.

Present-day precipitation–temperature scaling relations indicate that hourly precipitation extremes may have a response to warming exceeding the Clausius–Clapeyron (CC) relation; for the Netherlands the dependency on surface dewpoint temperature follows 2 times the CC relation (2CC). The authors’ hypothesis—as supported by a simple physical argument presented here—is that this 2CC behavior arises from the physics of convective clouds. To further investigate this, the large-scale atmospheric conditions accompanying summertime afternoon precipitation events are analyzed using surface observations combined with a regional reanalysis. Events are precipitation measurements clustered in time and space. The hourly peak intensities of these events again reveal a 2CC scaling with the surface dewpoint temperature. The temperature excess of moist updrafts initialized at the surface and the maximum cloud depth are clear functions of surface dewpoint, confirming the key role of surface humidity on convective activity. Almost no differences in relative humidity and the dry temperature lapse rate were found across the dewpoint temperature range, supporting the theory that 2CC scaling is mainly due to the response of convection to increases in near-surface humidity, while other atmospheric conditions remain similar. Additionally, hourly precipitation extremes are on average accompanied by substantial large-scale upward motions and therefore large-scale moisture convergence, which appears to accelerate with surface dewpoint. Consequently, most hourly extremes occur in precipitation events with considerable spatial extent. Importantly, this event size appears to increase rapidly at the highest dewpoint temperature range, suggesting potentially strong impacts of climatic warming.

Weather-pattern, or weather-type, classifications are a valuable tool in many applications as they characterize the broad-scale atmospheric circulation over a given region. This study analyses the aspects of regional UK precipitation and meteorological drought climatology with respect to a new set of objectively defined weather patterns. These new patterns are currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. Weather pattern definitions and daily occurrences are mapped to Lamb weather types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Standardized precipitation index (SPI) and drought severity index (DSI) series are calculated for a range of aggregation periods and seasons. Monthly weather-pattern frequency anomalies are calculated for SPI wet and dry periods and for the 5% most intense DSI-based drought months. The new weather-pattern definitions and daily occurrences largely agree with their respective LWTs, allowing comparison between the two classifications. There is also broad agreement between weather pattern and LWT changes in frequencies. The new data set is shown to be adequate for precipitation-based analyses in the UK, although a smaller set of clustered weather patterns is not. Furthermore, intra-pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in this context. Six of the new weather patterns are associated with drought over the entire UK, with several other patterns linked to regional drought. It is demonstrated that the new data set of weather patterns offers a new opportunity for classification-based analyses in the UK.

Water scarcity is a critical issue in Iberia but few studies have investigated future drought over the region. The few that do are continental or global studies and do not report the range of possible future projections. In this paper, historical drought and future projections of drought were examined, using observed and downscaled rainfall data from climate models, for the main Iberian international basins (Douro, Tagus and Guadiana). Two drought indices were used, the standardized precipitation index (SPI) and the drought severity index (DSI). However, problems were found in the distribution fitting required for the calculation of SPI which render this index inadequate for assessing droughts in Iberia. The skill of CMIP5 climate models in representing historical drought for the Douro, Tagus and Guadiana is very variable with some not showing enough persistence of dry conditions, and others simulating droughts that are too long and too severe. Nevertheless, the observed range of drought conditions for these basins was encompassed by the ensemble members. Furthermore, we found no relationship between performance in simulating mean large-scale circulation and model ability to reproduce the historical drought characteristics for the region. All models project an intensification of drought conditions for the three basins. However, some only project small increases, while most project extreme multi-year droughts by the end of the century. We found that climate model future projections are neither related to their performance in simulating historical drought nor to their large-scale circulation patterns. This result emphasises the need for climate change impact studies to take into account the whole range of climate model projections in order to provide the best information for robust adaptation. Choosing one or a subset of climate models based on historical performance would not lead to a credible and justified reduction in uncertainty.

The changing characteristics of precipitation extremes under global warming have recently received tremendous attention, yet the mechanisms are still insufficiently understood. The present study attempts to understand these processes over India by separating the ‘dynamic’ and ‘thermodynamic’ components of precipitation extremes using a suite of observed and reanalysis datasets. The former is mainly due to changes in atmospheric motion, while the latter is driven mainly by the changes associated with atmospheric moisture content. Limited studies have attributed dynamic and thermodynamic contributions to precipitation extremes, and their primary focus has been on the horizontal atmospheric motion component of the water budget. Our study, on the other hand, implements the decomposition of vertical atmospheric motion, based on the framework proposed by Oueslati et al. (Sci Rep 9: 2859, 2019), which has often been overlooked, especially for India. With the focus on two major and recent extreme events in the Kerala and Uttarakhand regions of India, we show that the vertical atmospheric motion has a more significant contribution to the events than the horizontal atmospheric motion. Further, decomposition of the vertical atmospheric motion shows that the dynamic component overwhelms the thermodynamic component’s contribution to these extreme events, which is found to be negligible. Using a threshold method to define extreme rainfall, we further extended our work to all India, and the results were consistent with those of the two considered events. Finally, we evaluate the contributions from the recently made available CMIP6 climate models, and the results are interestingly in alignment with the observations. The outcomes of this study will play a critical role in the proper prediction of rainfall extremes, whose value to climate adaptation can hardly be overemphasised. Electronic supplementary material The online version of this article (10.1007/s00382-020-05410-3) contains supplementary material, which is available to authorized users.

Dynamical model skill in forecasting extratropical precipitation is limited beyond the medium-range (around 15 d), but such models are often more skilful at predicting atmospheric variables. We explore the potential benefits of using weather pattern (WP) predictions as an intermediary step in forecasting UK precipitation and meteorological drought on sub-seasonal timescales. Mean sea-level pressure forecasts from the European Centre for Medium-Range Weather Forecasts ensemble prediction system (ECMWF-EPS) are post-processed into probabilistic WP predictions. Then we derive precipitation estimates and dichotomous drought event probabilities by sampling from the conditional distributions of precipitation given the WPs. We compare this model to the direct precipitation and drought forecasts from the ECMWF-EPS and to a baseline Markov chain WP method. A perfect-prognosis model is also tested to illustrate the potential of WPs in forecasting. Using a range of skill diagnostics, we find that the Markov model is the least skilful, while the dynamical WP model and direct precipitation forecasts have similar accuracy independent of lead time and season. However, drought forecasts are more reliable for the dynamical WP model. Forecast skill scores are generally modest (rarely above 0.4), although those for the perfect-prognosis model highlight the potential predictability of precipitation and drought using WPs, with certain situations yielding skill scores of almost 0.8 and drought event hit and false alarm rates of 70 % and 30 %, respectively.

We introduce the Precipitation Probability DISTribution (PPDIST) dataset, a collection of global high-resolution (0.1°) observation-based climatologies (1979–2018) of the occurrence and peak intensity of precipitation (P) at daily and 3-hourly time-scales. The climatologies were produced using neural networks trained with daily P observations from 93,138 gauges and hourly P observations (resampled to 3-hourly) from 11,881 gauges worldwide. Mean validation coefficient of determination (R2) values ranged from 0.76 to 0.80 for the daily P occurrence indices, and from 0.44 to 0.84 for the daily peak P intensity indices. The neural networks performed significantly better than current state-of-the-art reanalysis (ERA5) and satellite (IMERG) products for all P indices. Using a 0.1 mm 3 h−1 threshold, P was estimated to occur 12.2%, 7.4%, and 14.3% of the time, on average, over the global, land, and ocean domains, respectively. The highest P intensities were found over parts of Central America, India, and Southeast Asia, along the western equatorial coast of Africa, and in the intertropical convergence zone. The PPDIST dataset is available via www.gloh2o.org/ppdist., Measurement(s) hydrological precipitation process • precipitation occurrence • precipitation intensity Technology Type(s) Neural networks models • Gauge or Meter Device • satellite imaging of a planet • reanalyses Factor Type(s) daily and 3-hourly time-scales • year of data collection Sample Characteristic - Environment climate system Sample Characteristic - Location Earth (planet) Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12815585

[Departement_IRSTEA]Territoires [ADD1_IRSTEA]Adaptation des territoires au changement global; International audience; In recent years, numerous studies have investigated the relationship of extreme precipitation intensities with temperature derived from a binning method using present-day weather data. The aim of this approach is that these dependencies, or so-called apparent scaling rates, provide insights on how precipitation extremes could evolve in the future climate. In a recent paper, Bao et al. showed that there is a large discrepancy between the present-day apparent scaling rates

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

We examine wet events (WEs) defined from an hourly rainfall dataset based on 64 gauged observations across India (1969–2016). More than 90% of the WEs (accounting for nearly 60% of total rainfall) are found to last less than or equal to 5 h. WEs are then clustered into six canonical local-scale storm profiles (CanWE). The most frequent canonical type (CanWE#1 and #2) are associated with very short and nominal rainfall. The remaining canonical WEs can be grouped into two broad families: (i) CanWE#3 and #5 with short (usually less than or equal to 3–4 h), but very intense rainfall strongly phase-locked onto the diurnal cycle (initiation peaks in mid-afternoon) and probably related to isolated thunderstorms or small mesoscale convective clusters (MCS), and (ii) CanWE#4 and #6 with longer and lighter rainfall in mean (but not necessarily for their maximum) and more independent of the diurnal cycle, thus probably related to larger MCSs or tropical lows. The spatial extent of the total rainfall received during each CanWE, as shown by IMERG gridded rainfall, is indeed smaller for CanWE#3 and #5 than for CanWE#4 and especially #6. Most of the annual maximum 1 hour rainfalls occur during CanWE#5. Long-term trend analysis of the June–September canonical WEs across boreal monsoonal India reveals an increase in the relative frequency of the convective storm types CanWE#3 and #5 in recent years, as expected from global warming and thermodynamic considerations.This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.

Although it has been documented that daily precipitation extremes are increasing worldwide, faster increases may be expected for subdaily extremes. Here after a careful quality control procedure, we compared trends in hourly and daily precipitation extremes using a large network of stations across the United States (U.S.) within the 1950–2011 period. A greater number of significant increasing trends in annual and seasonal maximum precipitation were detected from daily extremes, with the primary exception of wintertime. Our results also show that the mean percentage change in annual maximum daily precipitation across the U.S. per global warming degree is ~6.9% °C−1 (in agreement with the Clausius-Clapeyron rate) while lower sensitivities were observed for hourly extremes, suggesting that changes in the magnitude of subdaily extremes in response to global warming emerge more slowly than those for daily extremes in the climate record.

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 midlatitude 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.

Summary Floods pose multi-dimensional hazards to critical infrastructure and society and these hazards may increase under climate change. While flood conditions are dependent on catchment type and soil conditions, seasonal precipitation extremes also play an important role. The extreme precipitation events driving flood occurrence may arrive non-uniformly in time. In addition, their seasonal and inter-annual patterns may also cause sequences of several events and enhance likely flood responses. Spatial and temporal patterns of extreme daily precipitation occurrence are characterized across the UK. Extreme and very heavy daily precipitation is not uniformly distributed throughout the year, but exhibits spatial differences, arising from the relative proximity to the North Atlantic Ocean or North Sea. Periods of weeks or months are identified during which extreme daily precipitation occurrences are most likely to occur, with some regions of the UK displaying multimodal seasonality. A Generalized Additive Model is employed to simulate extreme daily precipitation occurrences over the UK from 1901 to 2010 and to allow robust statistical testing of temporal changes in the seasonal distribution. Simulations show that seasonality has the strongest correlation with intra-annual variations in extreme event occurrence, while Sea Surface Temperature (SST) and Mean Sea Level Pressure (MSLP) have the strongest correlation with inter-annual variations. The north and west of the UK are dominated by MSLP in the mid-North Atlantic and the south and east are dominated by local SST. All regions now have a higher likelihood of autumnal extreme daily precipitation than earlier in the twentieth century. This equates to extreme daily precipitation occurring earlier in the autumn in the north and west, and later in the autumn in the south and east. The change in timing is accompanied by increases in the probability of extreme daily precipitation occurrences during the autumn, and in the number of days with a very high probability of an extreme event. These results indicate a higher probability of several extreme occurrences in succession and a potential increase in flooding.

Warming induced by greenhouse gases will increase the amount of moisture in the atmosphere, causing heavier rainfall events. Changing atmospheric circulation dynamics are now shown to either amplify or weaken regional increases, contributing to uncertainty in future precipitation extremes.

Extreme precipitation is one of the most devastating forms of atmospheric phenomenon, causing severe damage worldwide, and is likely to intensify in strength and occurrence in a warming climate. This contribution gives an overview of the potential and challenges associated with using weather radar data to investigate extreme precipitation. We illustrate this by presenting radar data sets for Germany, the U.S. and the UK that resolve small-scale heavy rainfall events of just a few km2 with return periods of 5 years or more. Current challenges such as relatively short radar records and radar-based QPE uncertainty are discussed. An example from a precipitation climatology derived from the German weather radar network with spatial resolution of 1 km reveals the necessity of radars for observing short-term (1–6 h) extreme precipitation. Only 17.3% of hourly heavy precipitation events that occurred in Germany from 2001 to 2018 were captured by the rain gauge station network, while 81.8% of daily events were observed. This is underlined by a similar study using data from the UK radar network for 2014. Only 36.6% (52%) of heavy hourly (daily) rain events detected by the radar network were also captured by precipitation gauging stations. Implications for the monitoring of hydrologic extremes are demonstrated over the U.S. with a continental-scale radar-based reanalysis. Hydrologic extremes are documented over ∼1000 times more locations than stream gauges, including in the majority of ungauged basins. This underlines the importance of high-resolution weather radar observations for resolving small-scale rainfall events, and the necessity of radar-based climatological data sets for understanding the small-scale and high-temporal resolution characteristics of extreme precipitation.

Droughts and heatwaves can have profound impacts on society and the environment, which can be exacerbated by their co-occurrence. However, in China, co-occurrence of droughts and heatwaves has not been explored. Here we assess concurrent drought and heatwave events (CONDH) in summer across eastern China (EC) for 1962–2015. We found that these events are more frequent in the North and South of EC (>20 events during 1962–2015) and less frequent in the central region. In the North and South regions, intensity of heatwaves is ~2–4 times higher during drought conditions than in average conditions. Also, in these two regions the number of CONDH events is more than double what would be expected if droughts and heatwaves were independent. When analyzing changes between 1962–1988 and 1989–2015, the dependence between drought and heatwave was shown to be stable, but the number of CONDH more than doubled in parts of the North and small areas in the South, and decreased by over 50% in the southern central region. We have shown that the North and South of EC are hotspots of compound droughts and heatwaves and therefore it is crucial to considering both events together when assessing how to adapt to present and future weather extremes.

A robust hydrological impact assessment is indispensable for mitigation and adaptation planning. This study presents an integrated modelling methodology for evaluating climate change impacts on water availability, sediment yield and extreme events at the catchment scale. We propose the use of the spatial–temporal Neyman–Scott Rectangular Pulses (STNSRP) model—RainSim V3 and the rainfall conditioned daily weather generator—ICAAM-WG, as well as the physically based spatially distributed hydrological model—SHETRAN. The change factor approach was applied for obtaining unbiased rainfall and temperature statistics. The ICAAM-WG was developed based on the modified Climate Research Unit daily Weather Generator (CRU-WG). The methodology is proposed to generate synthetic series of hourly precipitation, daily temperature and potential evapotranspiration, hourly runoff and hourly sediment discharge. We demonstrated a possible application in a 705-km2 Mediterranean climate basin in southern Portugal. The case study showed the evaluation of future climate change impacts on annual and monthly water balance components and sediment yield, annual and seasonal flow duration curves, empirical extreme value distributions and the theoretical fits. It did not consider the possible uncertainty due to the limit of computational resources. The methodology can be well justified as follows: (a) the use of synthetic hourly instead of daily precipitation enables SHETRAN to be more capable of reproducing reliable storm runoff processes and the consequent sediment transport processes; (b) the use of SHETRAN makes possible the impact assessment to be accessible for any model grid square within the study basin; (c) the use of a statistical–stochastic downscaling method facilitates the generation of the synthetic series with unlimited length. It makes possible robust hydrological impact assessments if uncertainties related to the global climate model, regional climate model, greenhouse gas emission scenario, downscaling method, hydrological model and observational data are considered.

Changes in sub-daily precipitation extremes potentially lead to large impacts of climate change due to their influence on soil erosion, landslides, and flooding. However, these changes are still rather uncertain, with only limited high-resolution results available and a lack of fundamental knowledge on the processes leading to sub-daily extremes. Here, we study the response of hourly extremes in a convection-permitting regional climate model (CPRCM) for an idealized warming experiment—repeating present-day observed weather under warmer and moister conditions. Ten months of simulation covering summer and early autumn for two domains over western Central Europe and western Mediterranean are performed. In general, we obtain higher sensitivities to warming for local-scale extreme precipitation at the original grid-scale of 2.5–3 km than for aggregated analyses at a scale of 12–15 km, representative for currently conventional regional climate models. The grid-scale sensitivity over sea, and in particular over the Mediterranean Sea, approaches 12%–16% increase per degree, close to two times the Clausius–Clapeyron (CC) relation. In contrast, over the dry parts of Spain the sensitivity is close to the CC rate of 6%–7% per degree. For other land areas, sensitivities are in between these two values, with a tendency for the cooler and more humid areas to show lower scaling rates for the most intense hourly precipitation, whereas the land area surrounding the Mediterranean Sea shows the opposite behaviour with the largest increases projected for the most extreme hourly precipitation intensities. While our experimental setup only estimates the thermodynamic response of extremes due to moisture increases, and neglects a number of large-scale feedbacks that may temper future increases in precipitation extremes, some of the sensitivities reported here reflect findings from observational trends. Therefore, our results can provide guidance within which to understand recent observed trends and for future climate projections with CPRCMs.

[Departement_IRSTEA]Territoires [ADD1_IRSTEA]Dynamique et fonctionnement des écosystèmes [Departement_IRSTEA]Territoires [ADD1_IRSTEA]Dynamique et fonctionnement des écosystèmes; International audience; Six weather types (WTs) are computed for tropical Australia during the wet season (November-March 1979-2015) using cluster analysis of 6-hourly low-level winds at 850 hPa. The WTs may be interpreted as a varying combination of at least five distinct phenomena operating at different time scales: the diurnal cycle, fast and recurrent atmospheric phenomena such as transient low pressure, the intraseasonal Madden-Julian oscillation, the annual cycle, and interannual variations mostly associated with El Niño-Southern Oscillation. The WTs are also strongly phase-locked onto the break/active phases of the monsoon; two WTs characterize mostly the trade-wind regime prevalent either at the start and the end of the monsoon or during its breaks, while three monsoonal WTs occur mostly during its core and active phases. The WT influence is strongest for the frequency of wet spells, while the influence on intensity varies according to the temporal aggregation of the rainfall. At hourly time scale, the climatological mean wet intensity tends to be near-constant in space and not systematically larger for the monsoonal WTs compared to other WTs. Nevertheless, one transitional WT, most prevalent around late November and characterized by weak synoptic forcings and overall drier conditions than the monsoonal WTs, is associated with an increased number of high hourly rainfall intensities for some stations, including for the interior of the Cape York Peninsula. When the temporal aggregation exceeds 6-12 h, the mean intensity tends to be larger for some of the monsoonal WTs, in association with more frequent and also slightly longer wet spells.

The “Western Tibetan Vortex” (WTV)—also termed the Karakoram Vortex—dominates the middle-to-lower troposphere and the near-surface air temperature variability above the western Tibetan Plateau (TP). Here, we explore the thermodynamic mechanisms through which the WTV modulates air temperature over the western TP by diagnosing the three major terms of the thermodynamic energy equation—adiabatic heating, horizontal temperature advection, and diabatic heating—that maintain the atmospheric thermal balance. We composite these major terms to examine the differences between anti-cyclonic and cyclonic WTV events. Our theoretical approach demonstrates that adiabatic sinking-compression (rising-expansion) provides the overwhelming control on both the middle-to-lower tropospheric and lower stratospheric temperature increases (decreases) under anti-cyclonic (cyclonic) WTV conditions over the western TP high mountain area in all four seasons. This also explains the mechanisms behind the anomalous temperature “dipole” found between the mid-lower troposphere and lower stratosphere when the WTV was initially identified. Spatially, adiabatic heating effects are centred on the central western TP in summer and the south slope centring at 70°–80°E of the TP in other seasons. The other two terms, horizontal temperature advection and diabatic heating, have localized importance over the edges of the western TP. In a case study over the Karakoram area, we further demonstrate that adiabatic heating (rising-expanding-cooling/sinking-compressing-warming) is the dominant thermodynamic process controlling Karakoram air temperatures under WTV variability, except for at the very near surface in autumn and winter. Our analysis methods can be applied to investigate the thermodynamic processes of other atmospheric circulation systems or climate variability modes. Electronic supplementary material The online version of this article (10.1007/s00382-019-04785-2) contains supplementary material, which is available to authorized users.

Extreme daily precipitation is thought to increase with warming at a rate of 6.5% per K. High-resolution simulations for the southern UK show this scaling for present conditions, but above 22 °C this scaling fails owing to changes in dynamics. Extreme daily precipitation is thought to increase with temperature at a rate of 6.5% per K according to the Clausius–Clapeyron relationship between temperature and saturation vapour pressure1. A wide range of scaling relationships has been observed globally for extreme daily and hourly precipitation, with evidence of scaling above 6.5% per K for sub-daily extreme precipitation in some regions2,3,4. Only high-resolution climate models can simulate this scaling relationship5. Here we examine the scaling of hourly extreme precipitation intensities in a future climate using experiments with a model for the southern UK with kilometre-scale resolution6. Our model simulates the present-day scaling relationship at 6.5% per K, in agreement with observations. The simulated overall future increase in extreme precipitation follows the same relationship. However, UK extreme precipitation intensities decline at temperatures above about 22 °C—a temperature range that is not well sampled in the present-day integration—as a result of a more frequent occurrence of anticyclonic weather systems. Anticyclones produce more days with strong daytime heating, but are not favourable to the development of deep intense convective storms. We conclude that future extreme hourly precipitation intensities cannot simply be extrapolated from present-day temperature scaling, and demonstrate the pitfalls of using regional surface temperature as a scaling variable.

Clouds play a key role in hydroclimatological variability by modulating the surface energy balance and air temperature. This study utilizes MODIS cloud cover data, with corroboration from global meteorological reanalysis (ERA-Interim) cloud estimates, to describe a cloud climatology for the upper Indus River basin. It has specific focus on tributary catchments in the northwest of the region, which contribute a large fraction of basin annual runoff, including 65% of flow originating above Besham, Pakistan or 50 km3 yr−1 in absolute terms. In this region there is substantial cloud cover throughout the year, with spatial means of 50%–80% depending on the season. The annual cycles of catchment spatial mean daytime and nighttime cloud cover fraction are very similar. This regional diurnal homogeneity belies substantial spatial variability, particularly along seasonally varying vertical profiles (based on surface elevation). Correlations between local near-surface air temperature observations and MODIS cloud cover fraction confirm the strong linkages between local atmospheric conditions and near-surface climate variability. These correlations are interpreted in terms of seasonal and diurnal variations in apparent cloud radiative effect and its influence on near-surface air temperature in the region. The potential role of cloud radiative effect in recognized seasonally and diurnally asymmetrical temperature trends over recent decades is also assessed by relating these locally observed trends to ERA-Interim-derived trends in cloud cover fraction. Specifically, reduction in nighttime cloud cover fraction relative to daytime conditions over recent decades appears to provide a plausible physical mechanism for the observed nighttime cooling of surface air temperature in summer months.

[Departement_IRSTEA]Territoires [ADD1_IRSTEA]Adaptation des territoires au changement global; International audience; Midlatitude synoptic weather regimes account for a substantial portion of annual precipitation accumulation as well as multi-day precipitation extremes across parts of the United States (US). However, little attention has been devoted to understanding how synoptic-scale patterns contribute to hourly precipitation extremes. A majority of 1-h annual maximum precipitation (AMP) across the western US were found to be linked to two coherent midlatitude synoptic patterns: disturbances propagating along the jet stream, and cutoff upper-level lows. The influence of these two patterns on 1-h AMP varies geographically. Over 95% of 1-h AMP along the western coastal US were coincident with progressive midlatitude waves embedded within the jet stream, while over 30% of 1-h AMP across the interior western US were coincident with cutoff lows. Between 30-60% of 1-h AMP were coincident with the jet stream across the Ohio River Valley and southeastern US, whereas a a majority of 1-h AMP over the rest of central and eastern US were not found to be associated with either midlatitude synoptic features. Composite analyses for 1-h AMP days coincident to cutoff lows and jet stream show that an anomalous moisture flux and upper-level dynamics are responsible for initiating instability and setting up an environment conducive to 1-h AMP events. While hourly precipitation extremes are generally thought to be purely convective in nature, this study shows that large-scale dynamics and baroclinic disturbances may also contribute to precipitation extremes on sub-daily timescales.

[Departement_IRSTEA]Territoires [ADD1_IRSTEA]Adaptation des territoires au changement global; National audience; Historical in situ sub-daily rainfall observations are essential for the understanding of short-duration rainfall extremes but records are typically not readily accessible and data are often subject to errors and inhomogeneities. Furthermore, these events are poorly quantified in projections of future climate change making adaptation to the risk of flash flooding problematic. Consequently, knowledge of the processes contributing to intense, short-duration rainfall is less complete compared with those on daily timescales. The INTENSE project is addressing this global challenge by undertaking a data collection initiative that is coupled with advances in high-resolution climate modelling to better understand key processes and likely future change. The project has so far acquired data from over 23 000 rain gauges for its global sub-daily rainfall dataset (GSDR) and has provided evidence of an intensification of hourly extremes over the US. Studies of these observations, combined with model simulations, will continue to advance our understanding of the role of local-scale thermodynamics and large-scale atmospheric circulation in the generation of these events and how these might change in the future.