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The diversity of flood‐generating mechanisms superimposed on catchment physiographic features with non‐stationary meteorological drivers makes future flood hazard assessment a grand challenge. To date, many studies have examined patterns in rainfall and streamflow, but far fewer have investigated trends in the other drivers of flooding. The complex transfer function between precipitation and flooding makes it potentially misleading to simply look at the change in rainfall to express the hazard. Furthermore, there are very few studies that have directly used output from km‐scale climate models in flood modeling. Coarse resolution climate data sets may not credibly resolve local climate and weather extremes. Changes in rainfall distribution and antecedent moisture over extended time periods due to climate change have so far been ignored when assessing urban pluvial flood risk. In this paper, an urban flood hazard assessment framework using the latest 2.2 km resolution UK Climate Projections Local is proposed. Global warming induced changes in pluvial flood risks under RCP8.5 are projected, focusing on the impact of changing precipitation patterns and soil moisture dynamics on flood generation. Results indicate a strong increase in the frequency of occurrence of extreme floods, and the resultant future (2060–2080) annual flood volume is expected to increase up to 52.6% relative to 1980–2000 over a major UK urban region, and these patterns are likely to hold more generally elsewhere in the UK. Shifts to a later occurrence of extreme flooding is identified under global warming. Previous studies that have neglected soil moisture dynamics are unlikely to give accurate flood estimates. Plain Language Summary: The future flood hazard status over the major UK urban region of Bristol (domain size ∼746 km2) is evaluated using the latest 12‐member UK Climate Projections Local ensemble rainfall data set at the hourly and kilometer scale. A total of 30,098 rainfall events from an equivalent 720 years of climate data are identified and used for flood modeling. Impact of changing precipitation pattern and soil moisture dynamics on surface water floods are evaluated, and the interaction between precipitation, inundation, infiltration, and soil wetness are handled simultaneously at a spatial resolution of ∼30 m or less using an improved hydrodynamic model (LISFLOOD‐FP). Our findings highlight a shift toward a later seasonal occurrence of extreme flooding under global warming. Specifically, a large proportion of future extreme flood hazards is projected to manifest in December, contrasting with historical trends where most extreme events occurred in November. Extreme precipitation can be magnified in rainy seasons due to amplified moisture convergence, while in dry periods limited moisture availability may offset precipitation increases. Despite an overall increase in the total annual rainfall volume, the future summer is anticipated to be much drier due to limited rainfall availability, leading to a further reduction in soil moisture availability. Key Points: Shifts to a later seasonal occurrence of extreme flooding is identified under global warming in the UKIncrease in annual total rainfall leads to a disproportionate rise in the resultant flood volumeImpact of the antecedent soil moisture on flood generation shows seasonality [ABSTRACT FROM AUTHOR]

For those involved in planning for regional and local scale changes in future climate, there is a requirement for climate information to be available in a context more usually associated with meteorological timescales. Here we combine a tool used in numerical weather prediction, the 30 weather patterns produced by the Met Office, which are already applied operationally to numerical weather prediction models, to assess changes in the UK Climate Projections (UKCP) Global ensemble. Through assessing projected changes in the frequency of the weather patterns at the end of the 21st Century, we determine that future changes in large-scale circulation tend towards an increase in winter of weather patterns associated with cyclonic and westerly wind conditions at the expense of more anticyclonic, settled/blocked weather patterns. In summer, the results indicate a shift towards an increase in dry settled weather types with a corresponding reduction in the wet and windy weather types. Climatologically this suggests a shift towards warmer, wetter winters and warmer, drier summers; which is consistent with the headline findings from the UK Climate Projections 2018. This paper represents the first evaluation of weather patterns analysis within UKCP Global. It provides a detailed assessment of the changes in these weather patterns through the 21st Century and how uncertainty in emissions, structural and perturbed parameters affects these results. We show that the use of these weather patterns in tandem with the UKCP projections is useful for future work investigating changes in a range of weather-related climate features such as extreme precipitation. [ABSTRACT FROM AUTHOR]

Bibliometric analysis is a quantitative evaluation method for scientific research aiming at measuring knowledge expressed as scientific publications in a given field. This paper proposes to analyze the worldwide scientific production on social vulnerability of coastal populations through six bibliometric indicators: typology, historical evolution, geographic distribution, main sources, relevant authors and publications and recurring keywords. The research theme was chosen given the continuous increase of studies related to climatic changes and their consequences to populations in coastal zones. In total, 191 indexed documents covering the period from 1991 to 2019 were selected from the Scopus database, after the examination of more than 900 entries, and analyzed through VOSViewer software and the Bibliometrix R package. The results obtained confirmed the exponential growth of scientific production on this subject. Most frequently impacts considered were coastal flooding and erosion triggered by extreme events and the majority of studies have been presented as academic articles published in scientific journals. Moreover, most documents identified were site-specific, based on secondary data and associated with authors from the USA and the UK, with an emerging production related to authors from developing economies in recent years. Among the 658 authors found, only nine have published three or more articles on the theme, with citations highly concentrated in only four publications. The analysis also revealed the evolution of preferred keywords over time and the lack of consensus in the use of terminology. Studies about coastal social vulnerability were initially mostly focused on the evaluation of risks and exposure to hazards, evolving over time such that the focus shifted to adaptation measures seeking to minimize impacts from climate change to coastal zones. [ABSTRACT FROM AUTHOR]

The Cardigan Bay Basin (UK) may have functioned as a deep and narrow strait, and thereby influenced Early Jurassic oceanic circulation through the northern and southern Laurasian Seaway, and between Boreal and Peri-Tethys domains. Toarcian hemipelagic deposits of the basin in the Mochras borehole show strongly bioturbated contourite facies. Trace fossils are strongly dominated by Phycosiphon incertum (represented by four morphotypes), which was produced by opportunistic colonizers. Thalassinoides, Schaubcylindrichnus and Trichichnus are common (the latter is a deep-tier trace fossil produced by filamentous sulfide-oxidizing bacteria with a high tolerance for dysoxia), accompanied by less common Zoophycos, Planolites, Palaeophycus, Teichichnus, Rhizocorallium, Chondrites, and dwelling and resting structures, such as cf. Polykladichnus, Siphonichnus, Skolithos, Arenicolites, Monocraterion and Lockeia. Ichnological and lithological signals suggest repetitive fluctuations in benthic conditions attributed to a hierarchy of orbital cycles (precession and obliquity [4th order], short eccentricity [3rd order], long eccentricity [2nd order] and Earth–Mars secular resonance [1st order]). The Pliensbachian–Toarcian transition appears to be a significant palaeoceanographic turning point in the Cardigan Bay Basin, starting a CaCO3 decline, and with the most severe oxygen crisis of the Tenuicostatum Zone (here dysoxic but not anoxic) ending at the onset, in the early Serpentinum Zone (Exaratum Subzone), of the Toarcian negative carbon isotope excursion (To-CIE—linked with the Toarcian Oceanic Anoxic Event occurring in the lower part in the Serpentinum Zone). This trend contrasts with the prevalence of anoxia synchronous with the To-CIE in many other settings. Minor dysoxia returned to the Mochras setting in the latest Thouarsense to Dispansum zone interval. Extreme climate warming during the To-CIE may have enhanced and caused a reversal in the direction of deep marine circulation, improving oxygenation of the sea floor. Spectral analysis of binary data on ichnotaxa appearances gives high confidence in orbital signals and allows refined estimation of ammonite zones and the duration of the Toarcian (minimum ~ 9.4 Myr). [ABSTRACT FROM AUTHOR]

• Impact and uncertainty framework for the identification of compound hydro-hazards. • UK example application using EDgE RCP8.5 projections. • NE Scotland and SW UK identified as spatio-temporally compound hotspot regions. • Hydrological models identified as the largest source of variability. • Raises questions regarding spatial variability of hydroclimatological modelling uncertainty. There exists an increasing need to understand the impact of climate change on the hydrological extremes of flood and drought, collectively referred to as 'hydro-hazards'. At present, current methodology are limited in their scope, particularly with respect to inadequate representation of the uncertainty in the hydroclimatological modelling chain. This paper proposes spatially consistent comprehensive impact and uncertainty methodological framework for the identification of compound hydro-hazard hotspots – hotspots of change where concurrent increase in mean annual flood and drought events is projected. We apply a quasi-ergodic analysis of variance (QE-ANOVA) framework, to detail both the magnitude and the sources of uncertainty in the modelling chain for the mean projected mean change signal whilst accounting for non-stationarity. The framework is designed for application across a wide geographical range and is thus readily transferable. We illustrate the ability of the framework through application to 239 UK catchments based on hydroclimatological projections from the EDgE project (5 CMI5-GCMs and 3 HMs, forced under RCP8.5). The results indicate that half of the projected hotspots are temporally concurrent or temporally successive within the year, exacerbating potential impacts on society. The north-east of Scotland and south-west of the UK were identified as spatio-temporally compound hotspot regions and are of particular concern. This intensification of the hydrologic dynamic (timing and seasonality of hydro-hazards) over a limited time frame represents a major challenge for future water management. Hydrological models were identified as the largest source of variability, in some instances exceeding 80% of the total variance. Critically, clear spatial variability in the sources of modelling uncertainty was also observed; highlighting the need to apply a spatially consistent methodology, such as that presented. This application raises important questions regarding the spatial variability of hydroclimatological modelling uncertainty. In terms of water management planning, such findings allow for more focussed studies with a view to improving the projections which inform the adaptation process. [ABSTRACT FROM AUTHOR]

Extreme sea level estimates are fundamental for mitigating coastal flooding as they provide insight for defence engineering. As the global climate changes, rising sea levels combined with increases in storm intensity and frequency pose an increasing risk to coastline communities. We present a new method for estimating extreme sea levels that accounts for the effects of climate change on extreme events that are not accounted for by mean sea level trends. We follow a joint probabilities methodology, considering skew surge and peak tides as the only components of sea levels. We model extreme skew surges using a non-stationary generalised Pareto distribution (GPD) with covariates accounting for climate change, seasonality and skew surge–peak tide interaction. We develop methods to efficiently test for extreme skew surge trends across different coastlines and seasons. We illustrate our methods using data from four UK tide gauges and estimate sea level return levels when accounting for these long-term trends. [ABSTRACT FROM AUTHOR]

INTRODUCTION: This report provides a summary of the UK weather and climate through the calendar year 2019, alongside the historical context for a number of essential climate variables. This is the sixth in a series of annual 'State of the UK Climate' publications and an update to the 2018 report (Kendon et al., 2019). It provides an accessible, authoritative and up‐to‐date assessment of UK climate trends, variations and extremes based on the most up to date observational datasets of climate quality. The majority of this report is based on observations of temperature, precipitation, sunshine and wind speed from the UK land weather station network as managed by the Met Office and a number of key partners and co‐operating volunteers. The observations are carefully managed such that they conform to current best practice observational standards as defined by the World Meteorological Organization (WMO). The observations also pass through a range of quality assurance procedures at the Met Office before application for climate monitoring. Time series of near‐coast sea‐surface temperature (SST) and sea‐level are also presented and in addition a short section on phenology which provides dates of first leaf and bare tree indicators for four common shrub or tree species. National and regional statistics in this report are from the HadUK‐Grid dataset (Hollis et al., 2019). Temperature and rainfall series from this dataset extend back to 1884 and 1862, respectively. Details are provided in the relevant sections and appendices. The report presents summary statistics for the year 2019 and the most recent decade (2010–2019) relative to 1961–1990 and 1981–2010 averages. The period 2010–2019 is a non‐standard reference period, but it provides a 10‐year 'snapshot' of the most recent experience of the UK's climate and how that compares to historical records. This means differences between 2010 and 2019 and the baseline reference averages may reflect shorter‐term decadal variations as well as long‐term trends. These data are presented to show what has happened in recent years, not necessarily what is expected to happen in a changing climate. The majority of maps in this report show the year 2019 relative to the 1981–2010 baseline reference averaging period—that is, they are anomaly maps which show the spatial variation in this difference from average. Maps of actual values are in most cases not displayed because these are dominated by the underlying climatology, which for this report is of a lesser interest than the year‐to‐year variability. Throughout the report's text the terms 'above normal' and 'above average', and so on refer to the 1981–2010 baseline reference averaging period unless otherwise stated. Values quoted in tables throughout this report are rounded, but where the difference between two such values is quoted in the text (e.g., comparing the most recent decade with 1981–2010), this difference is calculated from the original unrounded values. Updates compared to State of UK Climate 2018 A section on phenology has been addedThe method used to calculate rainfall percentiles (fig. 31) has been revisedUpdated climate data to HadUK‐Grid version 1.0.2.0, including data rescue projects that have improved or extended early monthly sunshine and rainfall series. Feedback We would welcome suggestions or recommendations for future publications of this report. Please send any feedback to the Met Office at ncic@metoffice.gov.uk This State of the UK Climate report was supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra. [ABSTRACT FROM AUTHOR]

Observed trends, theory and modelling results all suggest increases in future extreme precipitation due to climate warming. The largest increases are expected in short‐duration events with less than a day. Relatively few previous studies have focused specifically on the projection of sub‐daily precipitation extremes. In this study, a statistical downscaling method based on circulation patterns (CPs) is developed to project site‐specific extreme hourly precipitation over the United Kingdom. First, a CP‐classification categorizes extreme hourly precipitation events based on the underlying atmospheric pressure conditions on each day. An analogue day method is then used to find for each future day the most similar day in the past by comparing the predictor values of daily precipitation and temperature simulated by regional climate models (RCMs) with observations conditioned on different CPs and seasons. Finally, the maximum hourly precipitation records on the most similar days are extracted and perturbed using precipitation duration‐temperature relationships. The applied statistical downscaling method is a combination of the analogue and the regression‐based method. It is found that the statistical downscaling method is able to reproduce observed extreme hourly precipitation. In terms of future changes under a warmer climate, it is shown that increases in extreme hourly precipitation can be as high as 112% but are highly variable depending on the rainfall stations, the future time periods, the emission scenarios, and the different RCM runs. [ABSTRACT FROM AUTHOR]

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 [ABSTRACT FROM AUTHOR]

When assessing the impact of extreme events, it is often not just a single component, but the combined behavior of several components which is important. Statistical modeling using multivariate generalized Pareto (GP) distributions constitutes the multivariate analogue of univariate peaks over thresholds modeling, which is widely used in finance and engineering. We develop general methods for construction of multivariate GP distributions and use them to create a variety of new statistical models. A censored likelihood procedure is proposed to make inference on these models, together with a threshold selection procedure, goodness-of-fit diagnostics, and a computationally tractable strategy for model selection. The models are fitted to returns of stock prices of four UK-based banks and to rainfall data in the context of landslide risk estimation. Supplementary materials and codes are available online. [ABSTRACT FROM AUTHOR]