Extreme storms are a major natural hazard in the extratropics. These storms can cause substantial economic damage due to strong winds and flooding, interrupt transportation networks and electricity supply and lead to casualties. Future climate projections predict an extension of the storm track further into Europe posing a potential for increased risk with climate change, especially in winter. However, despite its importance, the connection between extreme, high-impact extratropical storms in midlatitudes and changes in the jet stream remains uncertain. 

Using reanalysis data and multi-model ensemble of climate models under future socio-economic scenarios, we examine the variability of extreme and high-impact storms in the northern hemisphere midlatitude and investigate the connection between jet stream intensity and extreme storm impacts. For this purpose, extreme storm events are diagnosed using the wind field (defined as spatially organized clusters exceeding the 98th percentiles of wind speeds over a specific area for a specific duration). High-impact storms, on the other hand, are identified according to the Emergency Events Database, a global database on natural and technological disasters, for the period 1998 to 2023. This comparison provides insights on extreme storm damage variability in midlatitudes and allows us to explore regional differences in storm damage and future changes. Understanding and connecting the dynamical processes controlling the variability of the jet stream and extreme, high-impact storms in midlatitudes is essential for skillful prediction of these extreme hazards under climate change and for assessing their potentially devastating impacts.

How to cite: Afargan Gerstman, H. and Domeisen, D. I. V.: On the connection between the jet stream and high-impact, extreme storms in midlatitudes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13248, https://doi.org/10.5194/egusphere-egu24-13248, 2024.

Understanding the evolution of tropical cyclones (TC) over the 21st century under a changing climate is essential to improve the resilience of the North American electricity system. In this regard, several studies have projected future changes in TC behavior by detecting and tracking their evolution using climate simulations. One of the key limitations of climate models, specifically attributed to their limited spatial resolution, is that they are unable to simulate all the non-linear interactions between various components of the Earth system. Hence, in this study, instead of tracking TCs in the coarse spatial-resolution climate models, we investigate the evolution of the large-scale drivers influencing the North Atlantic TCs over the mid-future (2041-2060) and far-future (2081-2100). We use five bias-corrected simulations under two shared socio-economic pathway scenarios from the 6th generation Coupled Model Intercomparison Project. In particular, we examine the changes in the large-scale thermodynamic and atmospheric dynamic indicators favorable for TCs, namely sea surface temperature, wind shear, and lapse rate. 

Our results show an increase in the seasonal mean North Atlantic sea surface temperature (between +1 and +3°C), the length of the TC season (between +2 and +5 months), and the ocean heat content (3-6 times) relative to the historical period (1995-2014), while a decrease in the temperature lapse rate (between -0.8% and -1.45%) over both the mid-future and far-future. We find no significant changes in the vertical wind shear under a changing climate. These results suggest an increase in both the frequency and intensity of TCs over the North Atlantic, the latter by 2.6%-5.2% on average. Additionally, our results show a plausible reduction in the conditions favorable for TCs by mitigating from high-emission to moderate-emission scenarios.

How to cite: Goutham, N., Omrani, H., Collet, L., and Legorgeu, C.: Projections of the large-scale drivers influencing the North Atlantic tropical cyclones, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11146, https://doi.org/10.5194/egusphere-egu24-11146, 2024.

Future projections of European windstorms and the resultant socioeconomic losses are subject to large uncertainties associated with model differences, internal variability, and emissions scenarios. Here we have used a dataset of objectively identified extratropical cyclones from reanalysis and a multi-model ensemble of climate models under different future warming scenarios. We have applied two storm severity indices; one that is only a measure of the severity of the windstorms; and one that takes into account the population (and its projected future changes) to better understand projections of losses from windstorms. Over northern and central Europe the storm severity itself more than doubles, but the losses estimated from the population-weighted index more than triple due to projected population increases. We also consider an idealised adaptation scenario, where future damage thresholds are used that take into account the increasing future wind speeds. This indicates that adaptation can only partially offset the increased losses. Considering different emissions scenarios, future increase in risk is reduced when following a lower emissions scenario. We show that to understand the future changing risk associated with European windstorms, there is a need to go beyond physical hazard modelling to consider risk and adaptation from a socio-economic perspective.

How to cite: Catto, J., Priestley, M., and Little, A.: Changing risk from extratropical windstorms in Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17837, https://doi.org/10.5194/egusphere-egu24-17837, 2024.

The widespread destruction incurred by midlatitude storms every year makes it an imperative to study how storms change with climate. The impact of climate change on midlatitude windstorms, however, is hard to evaluate due to the small signals in variables such as wind speed, as well as the high interannual variability in Atlantic storms.

Here, we compare multiple severe midlatitude cyclones with both wind and precipitation impacts using forecast-based event attribution. We use a recent version of the ECMWF IFS ensemble prediction system which is demonstrably able to predict the storms, significantly increasing our confidence in its ability to model the key physical processes and their response to climate change.

The comparably high resolution of our simulations, and the focus on individual case studies are particularly useful for dynamically driven events like storms. Our approach is able to combine a dynamical analysis of the storm in question with an analysis of past and future changes.

Our results confirm trends of increased severity in storm impacts found in climate projections but add reliability to the forecasted structure and impacts of the storm. This indicates that forecast-based attribution is viable for reliable and fast attribution systems.

How to cite: Ermis, S., Leach, N., Sparrow, S., Lott, F., and Weisheimer, A.: Forecast-based attribution for midlatitude cyclones, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1978, https://doi.org/10.5194/egusphere-egu24-1978, 2024.

The World Climate Research Programme (WCRP) has created a new core project: Regional Information for Society (RIfS), which has begun to plan its inaugural activities. Recognizing a gap between core disciplinary projects of WCRP and societal impact, RIfS seeks to foster community exchange around the practices of creating and utilizing climate information. The members of the Scientific Steering Group and International Project Office see this as a collaborative process with stakeholders from various sectors of society. Rather than reproducing more climate services, we are focused on identifying best-practices, building worldwide capacity and equity, and contributing to existing projects at the regional scale, particularly in regions where there are limited resources for such services. This RIfS presentation will focus on the identification of best-practices, particularly in the assessment of climate information. Currently there is no systematic, consistent, or accepted approach to assessing which climate information is robust and actionable, at regional or global scales. This recognizes the multiplicity of non-congruent data and information sources that may be used, the choice of which depends often on subjective selections that can lead to different decision outcomes and the commensurate consequences. At the same time, the volumes of data and demand for information are only growing, and new organizations are emerging offering products to decision-makers with varying levels of transparency about methods. Decisions are being made that affect the global distribution of resources, for example in finance and the insurance sectors. No professional organization has so far managed to establish widely accepted standards and guidelines for what constitutes robust information appropriate for various types of decision-making. This is the central challenge of the moment for the community of climate researchers interested in societal applications. RIfS will begin a process of consensus-building with an expert meeting on robustness of climate information just after the EGU meeting this year, to be followed by additional opportunities to come together around these questions.

How to cite: Goldenson, N., Hewitson, B., Pryor, S., Solman, S., Alves, L., Block, P., Bojovic, D., Caron, L.-P., Dosio, A., Harrington, L., Horsburgh, K., Larsen, M., and Maina, J.: Regional Information for Society within the World Climate Research Programme, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21161, https://doi.org/10.5194/egusphere-egu24-21161, 2024.

Extreme weather events of unprecedented intensity in historical records can have major impacts on society and ecosystems. While adaptation plans often consider past trends in extreme weather events, few consider the possibility of exceptional extremes. This oversight leaves society underprepared and ill-equipped to handle ‘surprising’ events. There is a long history of science inquiry into the question of what low likelihood weather events are possible. Here, we present an overview of the methods used to identify exceptional weather events. We discuss tools for scientists, practitioners and policy-makers to ‘see the unseen’ and evaluate unexpected yet plausible disruptive events. We first discuss existing approaches for estimating rare extremes; then give an example for exceptional heat in The Netherlands; and finally outline how this knowledge can be leveraged to strengthen resilience and adaptation efforts.

How to cite: Kelder, T., Klok, L., Slater, L., Thompson, V., Goulart, H. M. D., Suarez-Gutierrez, L., Wilby, R., Heinrich, D., Coughlan de Perez, E., Stephens, L., Hawkins, E., Burt, S., van den Hurk, B., de Vries, H., van der Wiel, K., and Fischer, E.: Anticipating the unseen: a community review on how to better prepare for exceptional weather events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7944, https://doi.org/10.5194/egusphere-egu24-7944, 2024.

The human impacts of weather and climate hazards are usually felt at ground level. Aviation is perhaps unique, however, in the sense that the impacts often occur in the upper atmosphere at cruising altitudes of around 40,000 feet. Anthropogenic climate change is occuring at those altitudes in the upper troposphere and lower stratosphere, too. Weather-related hazards such as turbulence already cause a large fraction of commercial aircraft accidents. This presentation will review how these hazards are changing over time because of the changing climate.

Turbulence currently causes 71% of weather-related aircraft accidents, injuring hundreds of passengers and flight attendants annually and costing hundreds of millions of dollars. Recent evidence shows that clear-air turbulence that is strong enough to lift passengers from their seats has increased by 55% since 1979 over the North Atlantic, with similar increases over the USA and elsewhere. Climate model projections indicate a doubling or trebling in turbulence this strong around the midlatitudes in the coming decades, as the jet streams become more sheared in response to anthropogenic temperature changes at cruising altitudes.

Other weather and climate hazards to aviation that will be reviewed in this presentation include the propsect of more lightning strikes; rising sea levels and storm surges flooding coastal airports with increasing frequency; and warmer air on the runway reducing lift generation and making it more difficult for aircraft to take-off.

How to cite: Williams, P., Prosser, M., and Smith, I.: Future changes in weather and climate hazards to aviation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18675, https://doi.org/10.5194/egusphere-egu24-18675, 2024.

Rising global temperatures have been linked to changes in rainfall patterns and an increase in extreme rainfall-related weather events worldwide. Because of its fluctuating precipitation, Bangladesh, a nation susceptible to natural catastrophes, has experienced and will continue to confront more catastrophic calamities. Among these hazards, drought is a more concerning issue for an agriculture-dependent country like Bangladesh. This study has addressed this issue and analyzed the drought condition for the historical period (1985–2014) and near future (2025–2054) by estimating the SPI index in the north-west region of Bangladesh. In this study, an investigation has been done for future projections under various scenarios, such as SSP-245 and SSP-370, using seven suitable Coupled Model Intercomparisons Project 6 (CMIP6). Also, the SPI index has been predicted using a feed-forward backpropagation algorithm in an artificial neural network (ANN). This study has compared the results from two analyses (7 CMIP6 models) and machine-learning-based predictive output. For this study, the drought index was determined to be the Standard Precipitation Index (SPI) on three timescales: three months, six months, and twelve months. For the analysis, a three-layer artificial neural network model was used. In order to determine the most accurate predictive model for the SPI, this model was trained utilizing the SPI timescales with varying lag durations. The correlation coefficient indicated a high accuracy range (75%–85%) in predictive values, demonstrating the model's effectiveness. Additionally, the comparison of observed versus predicted curves for the SPI index across the three timescales also revealed similar trends. The SPI index, derived from 7 CMIP6 models, shows that in the near future, drought events for SSP-370 scenarios are more frequent than SSP-245 scenarios. For the historical period, Chirps precipitation data has been used along with CMIP6 model data, and it has also shown an increasing trend in drought frequencies with time. This study has analyzed the historical and future drought conditions, which can benefit policymakers by improving infrastructure for giving early warning to farmers and taking necessary precautions to protect the losses due to drought.

How to cite: Sarkar, I. and Islam, T.: Comparative Analysis of SPI Index for Drought Conditions in North-West Bangladesh: A Study of CMIP6 Model Data and Machine Learning-Based Predictions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18895, https://doi.org/10.5194/egusphere-egu24-18895, 2024.

Climate change is a pressing concern impacting contemporary society, with anticipated global warming trends poised to exacerbate environmental challenges. This study explores the implications for the Iberian Peninsula (IP) at the close of the 21st century, exploring the effects of warming and drying trends on population exposure to hot and dry extreme weather events (HDEs). Despite a potential decline in overall population across the IP, warming and drying trends are expected, as highlighted by various studies. Projections indicate increased temperatures and aridity, and a surge in the frequency and intensity of droughts and heatwaves.

For this research, two EURO-CORDEX experiments (13 simulations RCM-GCM (Regional Climate Models – Global Climate Models)) were considered, encompassing different time periods, namely the historical period from 1971 to 2000 and the projected end of the century period spanning 2066 to 2095, aligned with two distinct emission scenarios: RCP4.5 and RCP8.5. The Standardized Precipitation-Evapotranspiration Index (SPEI) is used to quantify the duration of droughts, and the number of hot days is used to quantify warm months. Two representative concentration pathways (RCPs), specifically RCP4.5 and RCP8.5, are employed to delineate distinct greenhouse gas emission trajectories. A weighted multi-variable multi-model ensemble was used with the aim of improving climate simulations and providing reliable projections over the IP.

The findings of this study reveal a notable projected surge in population exposure to both droughts and warm months throughout the entire IP by the close of the century, with climate change identified as the predominant factor for this escalation. Specific regions may undergo a particularly pronounced increase in drought exposure, while instances of exposure to warm months may surpass the 500% mark. Assessment of exposure to future droughts and warm months indicates that climate change plays a predominant role, accounting for a significant percentage of exposure in both Portugal and Spain.

In conclusion, population exposure to droughts and warm months is projected to escalate significantly in the IP by the end of the century, primarily driven by climate change. The study also emphasizes the critical need for mitigation and adaptation strategies to address the potential consequences, particularly in sectors such as water resources, agriculture, human health, and wildfire management. The findings underscore the urgency for regional authorities, policymakers, and society to prioritize adaptation planning and develop a comprehensive understanding of the vulnerabilities and potential strategies to cope with the challenges posed by hot and dry extreme events.

This work was funded by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020 (https://doi.org/10.54499/UIDB/50019/2020), UIDP/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020). This work was performed under the scope of project https://doi.org/10.54499/2022.09185.PTDC (DHEFEUS) and supported by national funds through FCT. DL and AR acknowledge FCT I.P./MCTES (Fundação para a Ciência e a Tecnologia) for the FCT https://doi.org/10.54499/2022.03183.CEECIND/CP1715/CT0004 and https://doi.org/10.54499/2022.01167.CEECIND/CP1722/CT0006, respectively.

How to cite: Bento, V. A., Lima, D. C. A., and Russo, A.: An outlook into Iberia’s population exposure to hot and dry extreme weather events at the end of the century, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6217, https://doi.org/10.5194/egusphere-egu24-6217, 2024.

Extreme heat events often result in considerable harm to both ecosystems and human populations. Heat extremes arise from diverse processes, resulting in heatwaves with distinct characteristics and therefore potentially strongly varying impacts and trends. Relying on the surface energy balance decomposition of temperature, we categorize terrestrial summer heat extremes from 1979 to 2020 into four types: Sunny-humid (36.5%), Sunny–dry (24.5%), Advective (25.0%), and Adiabatic (14.0%). Sunny-humid and Sunny-dry heat extremes are characterized by high-pressure systems and diminished cloud cover, resulting in heightened solar radiation. However, they diverge concerning soil moisture and latent heat fluxes. Conversely, the latter two types emerge from advective heating due to anomalies in the horizontal wind and adiabatic heating from air subsidence, respectively. Both are correlated with an upsurge in downward longwave radiation. Sunny-dry and Advective heat extremes lead to more detrimental effects on terrestrial ecosystem production (reducing net ecosystem uptake by 0.09 gC/m²/d and decreasing maize yield by 7.6%) and human health (raising the thermal stress index by 8.6 K and increasing human mortality by 3.3%), respectively.

State-of-the-art climate models (CMIP6) generally replicate the relative proportions and the geographical distributions of the four types of heatwaves but tend to underestimate the Advective heatwave days. Under a high emission scenario (SSP585), the proportion of Sunny-dry and Advective heat extremes increases by 3.4% and 1.5%, respectively, while Sunny-humid and Adiabatic heatwave days decrease by 3.2% and 1.7%, respectively. This suggests, on top of the already expected increase in heatwaves, additional heat stress on both terrestrial carbon uptake potential and human populations. Our findings underscore the importance of distinction among different types of heat extremes and their impacts, paving the way to develop tailored adaptive.

How to cite: Tian, Y., Kleidon, A., Lesk, C., Zhou, S., Luo, X., Alam Ghausi, S., Wang, G., Zhong, D., and Zscheischler, J.: Global warming increases the proportion of more damaging heat extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6242, https://doi.org/10.5194/egusphere-egu24-6242, 2024.

While high impact weather events pose considerable challenges to society, we have limited understanding of their risks and potential impacts due to their rare nature. Climate change, in combination with internal climate variability, increases the uncertainty around these events and their impacts in the future. Storylines offer a non-probabilistic approach into estimating and understanding such events and their impacts conditioned on specific assumptions and scenarios, such as climate change and internal climate variability. Our study presents storylines of Hurricane Sandy (2012) to assess compound coastal flooding's impact on New York City's critical infrastructure under different scenarios. These include the effects of climate change, such as changes in storm dynamics and sea-level rise, as well as internal climate variability, accounting for variations in storm intensity and location. We use a comprehensive modelling framework, spanning from the driving climatological conditions to compound flooding and societal impacts. Our findings indicate that a 1m sea level rise could increase flood volumes by an average of 4.2 times, while internal climate variability could lead to a 2.5-fold increase in flood volumes. We find that impacts on critical infrastructure depend not only on flood volume, but also on the predominant flood hazard in each storyline, like storm surge or local precipitation. This study highlights the importance of developing societal-relevant scenarios that consider both climate change and internal variability. Such scenarios, coupled with a comprehensive modelling framework, provide useful information for decision making when preparing for high impact events in the future.

How to cite: Moreno Dumont Goulart, H., Benito Lazaro, I., van der Wiel, K., gavras-van Garderen, L., Le Bars, D., Koks, E., and van den Hurk, B.: Storylines of Hurricane Sandy under climate change to assess compound coastal flooding impacts in New York City, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3643, https://doi.org/10.5194/egusphere-egu24-3643, 2024.

The Northeast US has faced the most rapidly increasing occurrences of extreme rainfall within the US in the past few decades. The latest fully-coupled 25-km GFDL SPEAR simulation, possessing 10 ensemble members, presents a good opportunity to study changes in regional extreme rainfall and relevant physical processes in both current and future climates. The surge in extreme rainfall over the Northeast US since the 1990s is primarily linked to events associated with tropical cyclones (TCs). In a future warming climate, the 25-km GFDL SPEAR SSP5-8.5 simulations project unprecedented rainfall events over the Northeast US, driven by increasing anthropogenic radiative forcing and distinguishable from natural variability, by the mid-21^st century. Also, the occurrences of extreme rainfall related to both atmospheric rivers and TCs are projected to increase, even though the number of TC in the North Atlantic is projected to decrease in the 25-km GFDL SPEAR SSP5-8.5 simulations. Factors such as enhancing TC intensity, strengthening TC-related rainfall, or/and westward shift in TC tracks may offset the influence of declining TC numbers in the model projections, leading to more frequent TC-related extreme rainfall over the Northeast US in the future. On the other hand, the increase in extreme rainfall linked to atmospheric rivers is projected to outpace that associated with TCs. Given the distinct spatial patterns of rainfall resulting from atmospheric rivers and TCs, shifts in their relative contributions carry profound implications for risk prevention and mitigation strategies.

How to cite: Jong, B.-T., Murakami, H., and Delworth, T.: TC-induced Increases in Extreme Rainfall over the Northeast United States , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2476, https://doi.org/10.5194/egusphere-egu24-2476, 2024.

The impacts of the western North Pacific (WNP) tropical cyclone (TC) on East and Southeast Asian inland regions are analyzed. Here, based on a stringent TC selecting criterion, robust increase of TC-related inland impacts between 1979 and 2016 over East and Southeast Asian regions have been detected. The storms sustained for 2–9 h longer and penetrated 30–190 km further inland, as revealed from different best track datasets. The most significant increase of the TC inland impacts occurred over Hanoi and South China. The physical mechanism that affects TC-related inland impacts is shortly discussed. First, the increasing TC inland impacts just occur in the WNP region, but it is not a global effect. Second, besides the significant WNP warming effects on the enhanced TC landfall intensity and TC inland impacts, it is suggested that the weakening of the upper-level Asian Pacific teleconnection pattern since 1970s may also play an important role, which may reduce the climatic 200 hPa anti-cyclonic wind flows over the Asian region, weakening the wind shear near the Philippine Sea, and may eventually intensify the TC intensity when the TCs across the basin. Moreover, the TC inland impacts in the warming future are projected based on a high-resolution (20 km) global model according to the Representative Concentration Pathway 8.5 scenario. By the end of the 21st century, TC mean landfall intensity will increase by 2 m/s (6%). The stronger storms will sustain 4.9 h (56%) longer and penetrate 92.4 km (50%) farther inland, thereby almost doubling the destructive power delivered to Asian inland regions. More inland locations will therefore be exposed to severe storm–related hazards in the future due to warmer climate. Long-term planning to enhance disaster preparedness and resilience in these regions is called for.

How to cite: Chen, J., Tam, C.-Y., Chueng, K., and Wang, Z.: Changing impacts of tropical cyclones on East and Southeast Asian inland regions in the past and a globally warmed future climate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3003, https://doi.org/10.5194/egusphere-egu24-3003, 2024.

Climate change will impact the probabilities of different weather conditions and make new weather conditions possible, with implications for societal exposure to extreme weather hazards. While there is agreement that the frequency and intensity of many hazards will increase at the global scale, there is uncertainty in the spatial distribution of the changes, which needs to be considered in assessments of future extreme weather risk. Typically, this uncertainty is quantified by exploring the range of hazard intensities across a climate model ensemble for a given climate forcing. An alternative approach is to consider the range of atmospheric circulation changes across an ensemble – the driver of much of the relevant uncertainty – and extract a limited set of “physical storylines”. Rather than viewing an ensemble as a continuum of possibilities from which percentiles can be drawn, this physical storyline approach identifies “scenarios within scenarios”, thereby enabling risk modelers to work with more tractable amounts of climate data, end users to explore a “plausible worst case”, and scientists to focus their efforts on which circulation changes might be most likely.

Here, we demonstrate a prototype storyline approach for future flood risk in Central America. We consider how the frequency and intensity of flooding might change by using a pattern-scaling approach to extract the climate signal from climate model output. As a first step towards quantifying the uncertainty in our future flood risk data, we use output from three CMIP6 models that span the range of climate sensitivities and provide different flood storylines for Central America because of their distinct precipitation and temperature trends. We show how return periods for precipitation and streamflow may change under a range of policy-relevant global warming levels, providing useful insights about future surface water and river flooding for the financial, insurance, and development sectors.

How to cite: Dentith, J., Young, P., Filipova, V., Butler, J., Hawkins, A., Leedal, D., Pascoe, M., Styles, K., and Walkden, A.: Towards a storyline approach for examining future flood risk: A Central American case study, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15708, https://doi.org/10.5194/egusphere-egu24-15708, 2024.

As global climate patterns shift, Europe faces increasing challenges from key risks such as floods. However, translating this knowledge into locally usable risk information presents a significant challenge. A primary reason is the large variability associated with climate projection outcomes, particularly in precipitation patterns. This paper introduces a seasonal decision-scaling approach to identify decision-relevant climate storylines for regional discharge patterns, which are crucial in assessing flood risks. We sample scenarios within the uncertainty space of future projections and employ a statistical weather generator to determine probabilistic flow changes. Through the analysis of flow changes across various climate scenarios, we identify the most impactful seasonal climate parameters. These parameters are then used to cluster Global Climate Models, from which we create a set of decision-relevant climatological storylines for floods. A case study in Latvia demonstrates that river flows depend on only a few key seasonal parameters, indicating that the uncertainty can be effectively captured with a select number of distinct climatological storylines. This study not only simplifies the complexity of analysing future climate risks but also enhances the practicality of climate information at the regional level. Our novel seasonal approach to decision-scaling and the selection of decision-relevant climate storylines can be applied globally in areas where GCMs indicate varying climate trends and can also be used for drought analyses. This methodology leads to simpler climate risk information, thereby fostering improved and more robust adaptation strategies.

How to cite: Buskop, T., Sperna Weiland, F., and van den Hurk, B.: Decision-Relevant Climate Storylines: Using Seasonal Decision-Scaling to Identify Flood Changes in Uncertain GCM Trends, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1647, https://doi.org/10.5194/egusphere-egu24-1647, 2024.

Extreme events such as storms, heatwaves and flooding are increasing in severity worldwide owing to climate change. This study evaluates impacts of future projected climate events that could pose a threat to public health in the UK. An aging population means more people will be susceptible to trips and falls during and following extreme climatic events, such as being blown over during high winds. Data from the UK Climate Projections 2018 (UKCP18) were used to analyse daily extreme events for the current climate and assess projected changes in these events during the remainder of the 21st century. The hazards studied are heat and cold waves, heat stress related events, extreme precipitation and extreme wind speeds and gusts. The use of the latest convection-permitting climate model simulations (2.2 km resolution) from UKCP18 allows better simulation of localised events which could lead to differing levels of impact on public health across the UK. Under a high emission scenario (RCP8.5), extreme heat and precipitation events are projected to increase in frequency (and in some cases duration) throughout the 21st century. Alternately, extreme cold and cold wave events could reduce in frequency, although extreme cold events could still occur and thus monitoring annually would be advised. Little change is projected in extreme wind speeds and gusts. Many of the existing hazards that the UK is already vulnerable to are therefore likely to increase in severity in most cases, which therefore escalates the threat to public health. Although this study focuses on public health in the UK, a similar approach could be used for hazards in other countries.

How to cite: Sanderson, M., Eastaugh, K., Barciela, R., and Bernie, D.: Extreme climatic events and public health in the UK, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15240, https://doi.org/10.5194/egusphere-egu24-15240, 2024.