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This paper demonstrates the potential for crowdsourced rainfall data to infill gaps in the official rain gauge network and to provide new datasets for use in research. We use data from the Met Office Weather Observation Website (WOW) over 10 years (2011–2020) to generate two open-source datasets for Britain; multi-parameter raw data in an easy-to-use format; and an hourly rainfall dataset. We have compiled and prepared the data and detail here station selection, rain depth calculation, and data resampling to hourly intervals to create a consistent dataset for further processing (including statistical quality control) and application. Mapping the new rainfall dataset establishes that WOW observations fill spatial gaps in the official ground-based rain gauge network over Britain, particularly in urban areas. This could be particularly useful for post-event analysis of rainfall that results in pluvial flash flooding. Here, we focus on Britain but due to agreements with meteorological services in Belgium, the Netherlands, Australia, New Zealand, Sweden, and the Republic of Ireland, plus many citizen scientists globally opting to share data via WOW, there is potential for the development of similar datasets using these methods around the world.

Natural hazards often occur in combination with other natural hazards rather than as isolated events. While some combinations of hazards are well studied, and their physical connection is increasingly understood, other combinations have received considerably less attention. High temperatures are known to be an important component for conditions that lead to heavy rainfall; however, sequences of heatwaves followed by heavy rainfall are not well understood, especially in a compound event context. Here, we analyse heatwave-heavy rainfall events across Australia using rainfall observations at hourly resolution. Our results show that heavy rainfall is more likely to occur if preceded by a heatwave, demonstrating that heatwave-heavy rainfall sequences should be seen as temporally compounding events. In particular, many regions in Australia experience both more frequent and more extreme wet days immediately following a heatwave. This behaviour is strongest in coastal regions, especially on the Australian east coast. These findings highlight the need for heatwave-heavy rainfall sequences to be studied as compounding events, as future changes in either hazard is likely to have impacts on related risks such as flash flooding.

Atmospheric circulations bring moisture from above the ocean to the high mountains of the western Tibet Plateau (TP), thus wind variability is of great importance to the water cycle centered on the western TP. This study therefore examines the leading modes of the wind fields over the western TP. We use the multivariate empirical orthogonal function (MV-EOF) analysis method to detect the dominant wind patterns above the western TP. This method extracts the leading modes of combined meridional and zonal wind variability at 200-hPa in the region of 22° N–50° N, 50° E–92° E. We find the first leading mode of the combined zonal and meridional wind field in the annual mean and in most seasons (spring, summer and autumn) over the western TP shows high similarity to the Western Tibetan Vortex (WTV), a large-scale atmospheric vortex-like pattern recently recognized over the western TP. In winter, the WTV, however, is closer to the second leading mode. We estimate the sensitivity of our results by changing the domain of the MV-EOF analysis region surrounding the western. We find the influence of the WTV is less sensitive to analysis location around the western TP. In short, the WTV generally represents the first leading mode of the wind field in most seasons over the western TP. This study augments our knowledge on wind variability over the western TP.

Extratropical cyclones produce extreme surface wind speeds and heavy rainfall which can individually and jointly influence impacts and potentially produce large aggregate impacts. Within this study, we assess the UKCP 12-member ensemble of local convection-permitting 2.2 km climate projections. We quantify the likelihood of cyclones producing large footprints of both extreme winds and rainfall over the UK in a control (1981-2000) and future (2061-2080, RCP8.5) climate simulation. Following this, we characterise the convective and frontal drivers of wet and windy conditions within cyclones, and identify the characteristics of cyclones, their tracks and interactions with the jet stream that contribute to the occurrence of large, combined footprints in the control and future simulations. The future simulations project an increased probability of extratropical cyclones producing extremely wet and windy conditions in the same storm, as well as an increase in the land area covered by such conditions. In both the control and future simulations, combined wet and windy extremes largely occur close to cold and warm fronts, likely due to the warm conveyor belt which produces heavy rainfall (due its ascent over the frontal boundaries) and high winds (when occurring within a region of tight pressure gradients). Cyclone composites reveal that the largest changes in joint extremes are closely located within the sector of cyclones where we expect to see the warm conveyor belt, suggesting their change arises partly through the response of this shared driver rather than being a simple consequence of increased rainfall due to thermodynamics. In further analysis, we identify favourable conditions and cyclone characteristics that lead to cyclones producing large rainfall and wind footprints over the UK.

The uncertainties around the hydrological and socio-economic implications of climate change pose a challenge for Nile River system management, especially with rapidly rising demands for river-system-related services and political tensions between the riparian countries. Cooperative adaptive management of the Nile can help alleviate some of these stressors and tensions. Here we present a planning framework for adaptive management of the Nile infrastructure system, combining climate projections; hydrological, river system and economy-wide simulators; and artificial intelligence multi-objective design and machine learning algorithms. We demonstrate the utility of the framework by designing a cooperative adaptive management policy for the Grand Ethiopian Renaissance Dam that balances the transboundary economic and biophysical interests of Ethiopia, Sudan and Egypt. This shows that if the three countries compromise cooperatively and adaptively in managing the dam, the national-level economic and resilience benefits are substantial, especially under climate projections with the most extreme streamflow changes.

High uncertainty exists in the projected climate change impacts on the Nile’s economies and water-dependent sectors. Under these uncertainties, managing the Grand Ethiopian Renaissance Dam cooperatively and adaptively can produce economic and water management benefits for Ethiopia, Sudan and Egypt.

Larger organised convective storms (mesoscale-convective systems) can lead to major flood events in Europe. Here we assess end-of-century changes to their characteristics in two convection-permitting climate simulations from the UK Met Office and ETH-Zürich that both use the high Representative Concentration Pathway 8.5 scenario but different approaches to represent atmospheric changes with global warming and different models. The UK Met Office projections indicate more frequent, smaller, and slower-moving storms, while ETH-Zürich projections show fewer, larger, and faster-moving storms. However, both simulations show increases to peak precipitation intensity, total precipitation volume, and temporal clustering, suggesting increasing risks from mesoscale-convective systems in the future. Importantly, the largest storms that pose increased flood risks are projected to increase in frequency and intensity. These results highlight that understanding large-scale dynamical drivers as well as the thermodynamical response of storms is essential for accurate projections of changes to storm hazards, needed for future climate adaptation., Communications Earth & Environment, 4 (1), ISSN:2662-4435

A ‘roadmap’ for the future of UK flood hydrology over the next 25 years has been published, based on a wide-ranging and inclusive co-creation process involving more than 270 individuals and 50 organisations from different sectors and disciplines. This paper highlights key features of the roadmap and its development as a community-owned initiative. The roadmap's relationship with hydrological research and practice is discussed, as is its context within the wider flood risk management innovation landscape, including funding. While the paper has a focus on UK flood hydrology, reflecting the scope of the roadmap, it is also considered in the context of advances in hydrology internationally.

The potential compounding behaviour of heatwaves and extreme rainfall have important implications for a range of hazards, including wildfires and flooding, yet remain poorly understood. In this global study, we analyse the likelihood of extreme 1-hr rainfall immediately following a heatwave, and identify climate zones where this phenomenon is most pronounced. We find the strongest compounding heatwave-extreme rainfall relationships in central Europe and Japan, where the likelihood of extreme rainfall after a heatwave is increased by approximately four times compared to climatology. Significant compounding is found mainly in temperate or colder climates, provided these areas receive ample moisture. As both heatwaves and extreme rainfall are expected to become more frequent in the future, our results indicate that the potential impacts from compounding heatwave-extreme rainfall events might significantly increase as well.

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.

Globally, thermodynamics explains an increase in atmospheric water vapor with warming of around 7%/°C near to the surface. In contrast, global precipitation and evaporation are constrained by the Earth's energy balance to increase at ∼2-3%/°C. However, this rate of increase is suppressed by rapid atmospheric adjustments in response to greenhouse gases and absorbing aerosols that directly alter the atmospheric energy budget. Rapid adjustments to forcings, cooling effects from scattering aerosol, and observational uncertainty can explain why observed global precipitation responses are currently difficult to detect but are expected to emerge and accelerate as warming increases and aerosol forcing diminishes. Precipitation increases with warming are expected to be smaller over land than ocean due to limitations on moisture convergence, exacerbated by feedbacks and affected by rapid adjustments. Thermodynamic increases in atmospheric moisture fluxes amplify wet and dry events, driving an intensification of precipitation extremes. The rate of intensification can deviate from a simple thermodynamic response due to in-storm and larger-scale feedback processes, while changes in large-scale dynamics and catchment characteristics further modulate the frequency of flooding in response to precipitation increases. Changes in atmospheric circulation in response to radiative forcing and evolving surface temperature patterns are capable of dominating water cycle changes in some regions. Moreover, the direct impact of human activities on the water cycle through water abstraction, irrigation, and land use change is already a significant component of regional water cycle change and is expected to further increase in importance as water demand grows with global population.

This study was partially supported by core funds of ICIMOD contributed by the governments of Afghanistan, Australia, Austria, Bangladesh, Bhutan, China, India, Myanmar, Nepal, Norway, Pakistan, Sweden, and Switzerland. AO was supported by funding from the National Environmental Research Council (NERC) National Capability Overseas Development Assistance under the grant ‘Polar expertise –Supporting development’ (NE/R000107/1). River systems originating from the Upper Indus Basin (UIB) are dominated by runoff from snow and glacier melt and summer monsoonal rainfall. These water resources are highly stressed as huge populations of people living in this region depend on them, including for agriculture, domestic use, and energy production. Projections suggest that the UIB region will be affected by considerable (yet poorly quantified) changes to the seasonality and composition of runoff in the future, which are likely to have considerable impacts on these supplies. Given how directly and indirectly communities and ecosystems are dependent on these resources and the growing pressure on them due to ever-increasing demands, the impacts of climate change pose considerable adaptation challenges. The strong linkages between hydroclimate, cryosphere, water resources, and human activities within the UIB suggest that a multi- and inter-disciplinary research approach integrating the social and natural/environmental sciences is critical for successful adaptation to ongoing and future hydrological and climate change. Here we use a horizon scanning technique to identify the Top 100 questions related to the most pressing knowledge gaps and research priorities in social and natural sciences on climate change and water in the UIB. These questions are on the margins of current thinking and investigation and are clustered into 14 themes, covering three overarching topics of 'governance, policy, and sustainable solutions', 'socioeconomic processes and livelihoods', and 'integrated Earth System processes'. Raising awareness of these cutting-edge knowledge gaps and opportunities will hopefully encourage researchers, funding bodies, practitioners, and policy makers to address them. Publisher PDF

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

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 (

Climate change is the biggest challenge facing humanity today. The associated global warming and humidification, increases in the severity and frequency of extreme climate events, extension of the ranges of vector‐borne diseases, and the consequent social and economic stresses and disruption will have major negative consequences on many aspects of health care. People whose resilience to change is already impaired may suffer disproportionately from these environmental changes, which are of unprecedented reach and magnitude. There has been little connection made so far between climate change and epilepsy. We briefly review the history of climate change science and the subsequent response of the global scientific community. We consider how climate change effects might in general affect health and disease. We consider some of the underlying complex interactions that, for example, favor the spread of vector‐borne diseases and how climate models operate and may help plan for global and local changes. We then speculate specifically on how these generic ideas may apply specifically to epilepsy. We consider these impacts at levels from molecular to the epidemiological. Data are sparse, and there is undoubtedly a need for more information to enable better estimation of possible effects of climate change on care in epilepsy. We also consider how the professional activities of those involved in epilepsy health care might contribute to global carbon emissions, for example, through flying for conference attendance. Healthcare organizations across the world are already considering, and responding to, many of these issues. We argue for more research in this area, but also for action today. Actions today are likely to generate cobenefits for health care, including care in epilepsy, resulting from efforts to decarbonize, mitigate effects of climate change that has already happened, and plan for adaptation to climate change.

Using data from 520 gauging stations in Britain and gridded rainfall datasets, the seasonality of storm rainfall and flood runoff is compared and mapped. Annual maximum (AMAX) daily rainfall occurs predominantly in summer, but AMAX floods occur most frequently in winter. Seasonal occurrences of annual daily rainfall and flood maxima differ by more than 50% in dry lowland catchments. The differences diminish with increasing catchment wetness, increase with rainfalls shorter than daily duration and are shown to depend primarily on catchment wetness, as illustrated by variations in mean annual rainfall. Over the whole dataset, only 34% of AMAX daily flood events are matched to daily rainfall annual maxima (and only 20% for 6-hour rainfall maxima). The discontinuity between rainfall maxima and flooding is explained by the consideration of coincident soil moisture storage. The results have serious implications for rainfall-runoff methods of flood risk estimation in the UK where estimation is based on a depth–duration–frequency model of rainfall highly biased to summer. It is concluded that inadequate treatment of the seasonality of rainfall and soil moisture seriously reduces the reliability of event-based flood estimation in Britain.