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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.

Objective: Health systems make a sizeable contribution to national emissions of greenhouse gases that contribute to global climate change. The UK National Health Service is committed to being a net zero emitter by 2040, and a potential contribution to this target could come from reductions in patient travel. Achieving this will require actions at many levels. We sought to determine potential savings and risks over the short term from telemedicine through virtual clinics.\ud Methods: During the severe acute respiratory syndrome coronavirus 2 (SARS-2-CoV) pandemic, scheduled face-to-face epilepsy clinics at a specialist site were replaced by remote teleclinics. We used a standard methodology applying conversion factors to calculate emissions based on the total saved travel distance. A further conversion factor was used to derive emissions associated with electricity consumption to deliver remote clinics from which net savings could be calculated. Patients’ records and clinicians were interrogated to identify any adverse clinical outcomes.\ud Results: We found that enforced telemedicine delivery for over 1200 patients resulted in the saving of ~224 000 km of travel with likely avoided emissions in the range of 35 000–40 000 kg carbon dioxide equivalent (CO2e) over a six and half month period. Emissions arising directly from remote delivery were calculated to be

The chronology provides a record of flash flood events in Britain based on data collated mainly between 1700 and 2020. The primary purpose of the chronology is to improve the risk assessment of flash floods of given magnitude. It is divided into 18 regions of the country and contains descriptions of nearly 8000 events. It extends a previous chronology covering northern and southwest England which is provided as an online resource in (http://ceg-fepsys.ncl.ac.uk/outputs/). Flash floods have had a variety of previous definitions but are here defined in terms of the speed of onset which can apply to both river floods and surface water floods. The chronology for the first time provides a comprehensive list of surface water floods and their recorded impact on cities, towns and villages. It also draws attention to the prevalence of very rapid rates of rise in river level either as ‘walls of water’, or at a rate likely to endanger life as a result of intense rainfall. Nearly 300 such events have been identified mainly in upland areas of northern England, Wales and Scotland. Practical and theoretical issues with respect to flood risk assessment and warning are discussed. The chronology is available to download and is hosted on https://www.jbatrust.org/how-we-help/publications-resources/rivers-and-coasts/uk-chronology-of-flash-floods-1/

It is widely recognized that future rainfall extremes will intensify. This expectation is tied to the Clausius-Clapeyron (CC) relation, stating that the maximum water vapour content in the atmosphere increases by 6–7% per degree warming. Scaling rates for the dependency of hourly precipitation extremes on near-surface (dew point) temperature derived from day-to-day variability have been found to exceed this relation (super-CC). However, both the applicability of this approach in a long-term climate change context, and the physical realism of super-CC rates have been questioned. Here, we analyse three different climate change experiments with a convection-permitting model over Western Europe: simple uniform-warming, 11-year pseudo-global warming and 11-year global climate model driven. The uniform-warming experiment results in consistent increases to the intensity of hourly rainfall extremes of approximately 11% per degree for moderate to high extremes. The other two, more realistic, experiments show smaller increases—usually at or below the CC rate—for moderate extremes, mostly resulting from significant decreases to rainfall occurrence. However, changes to the most extreme events are broadly consistent with 1.5–2 times the CC rate (10–14% per degree), as predicted from the present-day scaling rate for the highest percentiles. This result has important implications for climate adaptation. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.

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.

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.

Numerous applications, including generating future predictions via numerical modelling, establishing appropriate policy instruments, and effectively tracking progress against them, require the multitude of complex processes and interactions operating in rapidly changing mountainous environmental systems to be well monitored and understood. At present, however, not only are environmental available data pertaining to mountains often severely limited, but interdisciplinary consensus regarding which variables should be considered absolute observation priorities remains lacking. In this context, the concept of so-called Essential Mountain Climate Variables (EMCVs) is introduced as a potential means to identify critical observation priorities and thereby ameliorate the situation. Following a brief overview of the most critical aspects of ongoing and expected future climate-driven change in various key mountain system components (i.e. the atmosphere, cryosphere, biosphere and hydrosphere), a preliminary list of corresponding potential EMCVs – ranked according to perceived importance – is proposed. Interestingly, several of these variables do not currently feature amongst the globally relevant Essential Climate Variables (ECVs) curated by GCOS, suggesting this mountain-specific approach is indeed well justified. Thereafter, both established and emerging possibilities to measure, generate, and apply EMCVs are summarised. Finally, future activities that must be undertaken if the concept is eventually to be formalized and widely applied are recommended.

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.

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.

Did you know there are millions of rain observations from thousands of privately owned automated weather stations located throughout Britain (and beyond) held in a freely accessible online archive? Citizen Scientists are sharing detailed sub-daily weather observations, including from locations where other gauge data is not available, often in close to real-time. There is distinct clustering of rain gauges in British urban areas, and with an anticipated increase in convective storms resulting in localised pluvial flooding, such high-resolution data should not be ignored. The aims of this research are to assess data quality, investigate how access to the data can be made easier, and to explore how the data can be used to support improved flood risk assessment.British rain observations are presented, spanning 10 years from more than 3000 unique citizen science weather stations via the Met Office WOW archive. These citizen science observations have the potential to fill gaps in the official monitoring network run by the Met Office and agencies responsible for flooding in Britain. Analysis indicates that if the official ground based rain gauge network was interpolated on a 5km grid there would be coverage for 36% of Britain, but if citizen science weather stations were included that figure increases to over 50%. A methodology to identify poor quality observations has been developed; the preliminary findings show that even where absolute values may be inaccurate, citizen science gauges can capture the pattern of extreme rainfall. Examples are shown from work in progress showing how combining citizen science observations with official rain data (radar and ground based gauges) can improve delineation of specific events that resulted in pluvial flooding.

Hydrological extreme events such as droughts and floods have a wide range of impacts on society and sectors such as agriculture and energy production. The impact of these extremes are projected to increase with future climate change and there is an urgent need to develop adaptation measures to reduce and manage the impacts. Long-term analysis of hydrological extremes, using a combination of models and climate data, helps better plan and manage water resources under global change. In this study, we modelled and analyzed hydrological extremes of the Volta river basin at very high-resolution (>10000 river reaches) using the Variable Infiltration Capacity (VIC) hydrological model, the vector-based river network routing model (RAPID), and high-resolution meteorological forcing datasets. The output from the VIC model is evaluated at multiple time scales (daily to annual) and for extreme events (droughts and floods) using observed streamflow data during the period 1979-2013. The model performed very well in areas less affected by dams, with performance increasing from daily to annual time scale. The modelled streamflow data is used to assess changes and variability in droughts (duration days and severity) and floods (annual daily maximum). The results show a decreasing and increasing trend in moderate and severe droughts in northern-eastern and southern parts of the basin, respectively. An increasing trend in floods is observed in the upper part of the basin (Black and White Volta) and the main river of the Lower Volta and we found a strong correlation with changes in precipitation and soil moisture.

Hourly precipitation extremes can intensify with higher temperatures at higher rates than theoretically expected from thermodynamic increases explained by the Clausius-Clapeyron (CC) relationship (~6.5%/K), but local scaling with surface air temperature is highly variable. Here, we use daily dewpoint temperature, a direct proxy of absolute humidity, as the scaling variable instead of surface air temperature. Using a global dataset of over 7000 hourly precipitation gauges, we estimate the at-gauge local scaling across six macro-regions; this ranges from CC to 2xCC for more than 60% of gauges. We find positive scaling in subtropical and tropical regions in contrast to previous work. Moreover, regional scaling rates show surprisingly universal behaviour at around CC, with higher scaling rates in Europe. Our results show a much greater consistency of scaling across the globe than previous work, usually at or above the CC rate, suggesting the relevance of dewpoint temperature scaling to understand future changes.

Research into potential implications of climate change on flood hazard has made significant progress over the past decade, yet efforts to translate this research into practical guidance for flood estimation remain in their infancy. In this commentary, we address the question: how best can practical flood guidance be modified to incorporate the additional uncertainty due to climate change? We begin by summarizing the physical causes of changes in flooding and then discuss common methods of design flood estimation in the context of uncertainty. We find that although climate science operates across aleatory, epistemic and deep uncertainty, engineering practitioners generally only address aleatory uncertainty associated with natural variability through standards-based approaches. A review of existing literature and flood guidance reveals that although research efforts in hydrology do not always reflect the methods used in flood estimation, significant progress has been made with many jurisdictions around the world now incorporating climate change in their flood guidance. We conclude that the deep uncertainty that climate change brings signals a need to shift towards more flexible design and planning approaches, and future research effort should focus on providing information that supports the range of flood estimation methods used in practice. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks'.

Study region: Volta River Basin, West Africa Study focus: Hydrological droughts have a wide range of impacts on societies and economic sectors such as agriculture and energy production. Analysis of hydrological droughts helps better plan and manage water resources under global change. This study analyses the spatial and temporal variability of hydrological drought occurrence (duration and severity) in the Volta River basin during 1979–2013. We used the Variable Infiltration Capacity and vector-based routing (RAPID) models and high-resolution forcing data to simulate streamflow for 10300 river reaches. New hydrological insights for the region: Drought duration and severity show high spatial variability and large differences between the three decades (1980 s, 1990 s and 2000 s). Droughts are more severe in larger catchments as the flows are generally higher. The trend analysis shows a general decreasing trend (up to 5% per event) in drought duration in the north-eastern and an increasing trend in southern parts of the basin. Drought severity shows an increasing and decreasing trend (up to ± 20%) in south and north part of the basin, respectively. Daily streamflow has a maximum correlation (up to 0.78) with upstream precipitation for the previous 30-days with a clear signal of propagation from meteorological to hydrological drought with an average lag-time of two weeks. The results indicate the need to consider site-specific and adaptive drought management measures to minimize the impacts.

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.

Summary The numerous processes implicated in the rapid and profound climate-driven changes that are underway across the world's mountains must be well monitored, understood, and—as far as possible—accurately projected. However, not only are the available environmental data upon which such activities hinge often severely limited, but interdisciplinary consensus regarding which variables should be considered observation priorities also remains elusive. Here, the concept of Essential Mountain Climate Variables (EMCVs) is introduced as a potential means of ameliorating the situation. After a review of climate-driven environmental change in mountains, a preliminary set of corresponding EMCVs is proposed. Variables pertaining to several disciplines naturally feature prominently. In addition, several are not currently considered to hold broader global relevance, which justifies our mountain-specific approach. Established and emerging possibilities to measure, generate, and apply EMCVs are then summarized. Finally, future activities toward the concept’s formalization are recommended. Ultimately, the approach hopes to increase the utility of mountainous environmental data to both fundamental science and decision making related to environmental management, risk mitigation, and adaptation.

Collected rainfall records by gauges lead to key forcings in most hydrological studies. Depending on sensor type and recording systems, such data are characterized by different time-resolutions (or temporal aggregations), ta. We present an historical analysis of the time-evolution of ta based on a large database of rain gauge networks operative in many study areas. Globally, ta data were collected for 25,423 rain gauge stations across 32 geographic areas, with larger contributions from Australia, USA, Italy and Spain. For very old networks early recordings were manual with coarse time-resolution, typically daily or sometimes monthly. With a few exceptions, mechanical recordings on paper rolls began in the first half of the 20th century, typically with ta of 1 h or 30 min. Digital registrations started only during the last three decades of the 20th century. This short period limits investigations that require long time-series of sub-daily rainfall data, e.g, analyses of the effects of climate change on short-duration (sub-hourly) heavy rainfall. In addition, in the areas with rainfall data characterized for many years by coarse time-resolutions, annual maximum rainfall depths of short duration can be potentially underestimated and their use would produce errors in the results of successive applications. Currently, only 50% of the stations provide useful data at any time-resolution, that practically means ta = 1 min. However, a significant reduction of these issues can be obtained through the information content of the present database. Finally, we suggest an integration of the database by including additional rain gauge networks to enhance its usefulness particularly in a comparative analysis of the effects of climate change on extreme rainfalls of short duration available in different locations.

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.

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.

The intensity and frequency of extreme precipitation events have increased globally and are likely to rise further under the warming climate. The Clausius-Clapeyron (CC) relationship (scaling) provides a physical basis to understand the relationship of precipitation extremes with temperature. Recent studies have used global sub-daily precipitation data from satellite, reanalysis and climate model outputs (due to the limited availability of long term observed sub-daily data at global scales) and have reported a higher sensitivity of sub-daily precipitation extremes to surface air temperature than for daily extremes. Moreover, at higher temperatures, moisture availability becomes the dominant driver of extreme precipitation, therefore, dewpoint temperature can be a better scaling variable to overcome humidity limitations as compared to air temperature. Here, we used hourly precipitation data from the Global Sub-daily Rainfall (GSDR) dataset and daily dewpoint temperature data (DPT) from the Met Office Hadley Centre observations dataset (HadISD) at 6695 locations across the United States of America, Australia, Europe, Japan, India and Malaysia. We found that more than 60% of locations (scaling estimated for individual location) show scaling greater than 7%/K (CC rate). Moreover, more than 55% of locations across Europe, Japan, Australia and Malaysia show scaling greater than 1.5CC. Furthermore, when locations across selected regions are pooled within similar climatic zones (based on Koppen Geiger classification), scaling curves show around 7%/K scaling. The scaling curves for locations at greater altitude (>400m MSL) are flat compared to locations at relatively lower altitude. The difference in scaling rates at-station and for pooled regions highlight the importance of understanding the thermodynamic and dynamic processes governing precipitation extremes at different spatial scales and indicate that local processes are driving the super-CC sensitivities in most regions.

While summer rain storms are very intermittent, chaotic and influenced by multiple atmospheric drivers, some statistics of observed short duration precipitation actually display surprisingly simple, regular behaviour. As an example, 10-min rainfall extremes derived from Dutch climate data show a dependency of 13% per degree over an almost 20-degree dew point temperature range. Similar behaviour has also been found in hourly precipitation observations. Each degree of warming reflects 6-7% more moisture in the air, following from the well-known Clausius-Clapeyron (CC) relation which is the cornerstone to understand and quantify the influence of climate change on precipitation extremes. According to the above finding, however, precipitation intensities may be increasing with temperature at a rate twice the commonly expected CC rate. In this presentation we will use output from a number of 10-year simulations for present-day and future climate with the convection permitting model HCLIM-AROME to investigate how hourly extremes respond to warming in both a pseudo global warming (PGW) and a GCM driven setup. In particular, we use the scaling diagram -- different percentiles of the rainfall distribution, usually the 90, and 99th conditioned on the occurrence of rain, as a function of dew point temperature -- as a analysis environment. Focus will be on how the scaling diagram is affected by climate change, and what information can be derived from these changes in scaling. While changes in the scaling diagram between present-day and future climate are in general consistent with a CC prediction, evidence of super CC behaviour, between 10 and 14 % per degree dew point, is also present. The same applies to changes in the most extreme events from the simulations, which show super CC behaviour in both PGW and GCM driven setups when scaled with the appropriate dew point temperature change.

Heat escape-motivated travel, called “sunbird” tourism, has become increasingly important with global warming and associated urban heat island effects. This study proposes a new method based on defining “comfortable” calendar days, to identify regions thermally suitable for “sunbird” tourism (namely northern Northeast China, eastern Inner Mongolia Plateau, northern Xinjiang Province, eastern Qinghai-Tibet Plateau, and Yungui Plateau) and their comfortable periods in China. From 1961–1990 to 1987–2016, comfortable periods have extended by 5 to over 20 days in eastern Qinghai-Tibet Plateau and parts of Yungui Plateau, but shortened by 5 to over 20 days in northern Northeast China and eastern Inner Mongolia Plateau, corresponding to 9 and 21 locations respectively becoming suitable and no longer suitable for “sunbird” tourism. Moreover, comfortable periods are now much earlier in the eastern Inner Mongolia Plateau and have dramatically altered in terms of their temporal distribution over the eastern Qinghai-Tibet Plateau. Finally, we discuss the implications for tourism.

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.

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.

Some weather circulation patterns (WPs) derived by the UK Met Office and defining a certain type of atmospheric circulation over Europe have been recently used to analyze the relationship of the regional UK precipitation and drought with respect to the atmospheric circulation over Europe (Richardson et al. 2018). In this study, we attempt to find out one or more relationships between precipitation depth and weather patterns over a non UK-centred domain, such as Sicily (Italy), which is characterized by a totally different climate as compared to the climate of UK. Since the island has been affected by many floods in the last years, occurred as a consequence of extreme rainfall events, it would be very important to understand if there exist some European WPs that are responsible for causing extreme rainfall events on the island. This aspect could be very helpful in reducing the flood risk, since it would make it possible to prevent extreme rainfall events, almost likely leading to floods, by simply preventing the atmospheric circulation with a meteorological model.

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.

Sewer flooding, urban surface water flooding and wet weather pollution are recognised as significant problems in the UK and elsewhere in the world, and changes in extreme rainfall arising as a consequence of climate change are likely to exacerbate these problems. This paper reports on new approaches to estimate potential future rainfall intensity changes over the UK at temporal and spatial scales that impact on urban drainage systems. The research (part of UK Water Industry Research’s programme of climate change related projects) has produced estimates of rainfall intensity change over different parts of the UK using a climate analogue approach and a very high-resolution (1·5 km) climate model developed by the UK Met Office. The new estimates produced are, in general, higher than existing UK climate change allowances for rainfall intensity. Sewer flooding volumes, flooding frequency and frequency of pollution events are also investigated for one location; indicating that these incidents and flood volumes are also likely to increase in the future.

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.