In recent decades, extreme event attribution (EEA) has become more widespread, and extreme weather events are rapidly attributed to climate change through different methods. More recently, EEA has expanded to also attribute impacts, in terms of fatalities, damages, displacements, etc. EEA and impact attribution studies are useful for a variety of different purposes, including raising awareness, litigation, the Loss and Damage Mechanism, decision-making, and adaptation.
In this session we welcome research exploring different methods to attribute weather extremes and their impacts to different drivers, including climate change, land use changes, adaptation, etc. We also welcome contributions investigating the utilization of attribution for societal scopes. This includes but it is not limited to:
• Comparison of different attribution methods;
• Developing a new method for attribution;
• Attribution of extreme events;
• Attribution of impact of extreme events;
• Applications of attribution studies.
Over the past two decades, the pan-Arctic region has experienced rapid climatic change, accompanied by an unprecedented rise in extreme wildfire activity. Yet, a systematic and regionally comprehensive attribution of these events, and their broader ecosystem impacts, remains limited. Here, we apply a probabilistic extreme event attribution (EEA) framework to quantify the role of anthropogenic forcings in enabling the extreme pan-Arctic wildfire seasons of 2019–2021, and assess their compound implications for Arctic carbon-cycle dynamics.
Using large ensemble simulations with the Community Earth System Model version 2 (CESM2), alongside remote sensing burned area products and ERA5 reanalysis, we evaluate both event magnitude (burned area) and extreme fire risk (Canadian Forest Fire Weather Index, FWI). Anthropogenic forcings emerge as a necessary condition for these extremes, with the fraction of attributable risk (FAR) exceeding 0.75 for burned area and reaching FAR>0.99 for FWI in 2020 and 2021. However, low probabilities of sufficient causation indicate that anthropogenic forcing alone is insufficient, highlighting the importance of interacting drivers. Risk ratios (RRs) show that such events have become over 200 times more likely compared to a pre-industrial climate (RR = 235 [5–95% CI: 98–489] in 2021). By decomposing FWI into its individual meteorological components, we are able to attribute this increase primarily to anthropogenically driven temperature and humidity changes, linked to enhanced vapour pressure deficit in the pan-Arctic.
Furthermore, we place these wildfire extremes within the context of compound climate extreme events and their impacts on land–atmosphere carbon exchange. Using a multivariate framework, we assess how fires co-occurring with other extreme events modulate extremes in gross primary productivity, ecosystem respiration, and Arctic net carbon balance.
How to cite: Fiedler, L., Barkhordarian, A., Brovkin, V., and Baehr, J.: Attribution of Observed Pan-Arctic Extreme Wildfire Events to Anthropogenic Forcings and Their Implications for Future Compound Carbon Extremes, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-499, https://doi.org/10.5194/ems2026-499, 2026.
This study identifies a significant increasing trend in the frequency of cyclonic storms (CS; maximum sustained winds exceeding 34 kts) over the northern Indian Ocean (NIO), primarily contributed by a pronounced rise in the number of very severe cyclonic storms (VSCS; maximum sustained wind speed exceeding 64 kts) since 1979. The observed increase in the VSCS frequency is closely associated with the enhanced lower-middle tropospheric relative humidity due to the vertical moisture advection processes. The strengthened upward motion is primarily caused by anomalous positive vorticity advection by mean westerly flows. Through analysis of Detection and Attribution Model Intercomparison Project (DAMIP) experiments, it is demonstrated that the mid-level cyclonic circulation trend is predominantly forced by greenhouse gas emissions, while anthropogenic aerosols exert a dampening effect. These findings underscore an escalating risk of stronger cyclones for the densely populated coastal nations around the NIO under continued climate change. The increasing frequency of VSCS over the NIO poses escalating threats, including more destructive storm surges, extreme winds, and heavy rainfall that exacerbate coastal flooding and infrastructure damage. These intensified storms also endanger critical ecosystems, like mangroves and fisheries, impacting vulnerable coastal communities. Addressing these risks requires improved early warning systems, climate-resilient infrastructure, and accelerated emission reductions to mitigate long-term intensification of VSCSs.
Key points
- The frequency of very severe cyclonic storms over the northern Indian Ocean has an increasing trend.
- The increase in very severe cyclonic storms is primarily driven by the lower-middle tropospheric
- The observed moistening trend in the lower-middle troposphere is largely attributable to the anthropogenic greenhouse gas forcing.
How to cite: Cao, X.: Increasing frequency of very severe cyclonic storms over the northern Indian Ocean driven by anthropogenic greenhouse gas forcing, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-9, https://doi.org/10.5194/ems2026-9, 2026.
Extreme event attribution aims to understand the role of climate change in impactful weather events. One method to achieve this consists in comparing two sets of weather instances selected as ‘circulation analogues’ of a given event, one representing the past and the other the present climate (or present and future). Differences between climate periods show how climate change affects the hazards associated with a specific circulation.
In this work, we focus on a selection of high-impact, cyclone-driven precipitation extremes that have affected Italy during the recent climatological period. These events are selected to span a range of distinct synoptic conditions known to produce extreme precipitation [1]. Using regional large-ensemble climate projections from the CRCM5 model under the RCP8.5 scenario, we identify, for each observed event, its best analogue in the model (BAM). The BAMs are then used to conduct attribution analyses within a perfect model approach, that is, by searching for model analogues of simulated rather than observed events. In this framework, individual ensemble members are treated as pseudo-observations, allowing us to assess the robustness of analogue-based attribution studies based on single realization datasets, such as reanalyses or observational records. Furthermore, the use of a large ensemble enables a comprehensive assessment of present and future changes in cyclone-driven precipitation over the central Mediterranean region, capturing variations in the mean and tails of the precipitation distribution.
Our results provide new insights into the influence of anthropogenic climate change on cyclone-driven precipitation in Italy, and into the methodological robustness of attribution studies in complex regional settings such as the Mediterranean. We find that attribution outcomes vary substantially depending on the specific event considered. In particular, intense cyclones in the northern Mediterranean show an increase in associated precipitation under climate change, whereas weaker cyclones at lower latitudes become shallower in the future climate and are, on average, associated with reduced precipitation. The most extreme events linked to these lower-latitude cyclones show no change in intensity. Finally, by examining the sensitivity of our results to ensemble size, we find that robust precipitation signals typically emerge when each climate period is represented by approximately 100 years of data.
[1] Iacomino, C., S. Pascale, G. Zappa, et al. 2025. “ A Classification of High-Risk Atmospheric Circulation Patterns for Italian Precipitation Extremes.” International Journal of Climatology e70118. https://doi.org/10.1002/joc.70118.
How to cite: Portal, A., Zappa, G., Pascale, S., Grazzini, F., Iacomino, C., Ghinassi, P., Iotti, M., Simolo, C., and Burderi, M.: Past, Present and Future precipitation extremes driven by Mediterranean cyclones in a regional large ensemble, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-467, https://doi.org/10.5194/ems2026-467, 2026.
The sequence of compounding winter storms of 2013/14 in the United Kingdom (UK) caused a range of significant impacts across the country, totalling an economic cost of approximately £1.3 billion. Heavy rain, totalling 545mm over the season, caused widespread flooding, and coastal impacts were exacerbated by high spring tides and strong winds. The Somerset Levels particularly felt the impact of the flooding, accounting for 30% of the total UK area of flooded agricultural land. This event is a case study for the Horizon-Europe COMPASS project (Compound events attribution to climate change: towards an operational service), where the main goal is to produce a flexible and harmonised methodological framework for such compound extremes, with a focus on impact attribution.
Using the flood model SFINCS (Super-Fast Inundation of Coasts), developed by Deltares, we model the total flood extent for a small region of the Somerset levels for the season. We drive this model with both factual and counterfactual (“natural”, with anthropogenic warming removed) simulations of the winter precipitation, using the HadGEM3-A large-ensemble attribution runs. Initial results demonstrate the magnitude of the observed flood extent to be 1.21 times more likely due to climate change, based on return periods. We also found that a flood event under “natural” forcing but with the same return period as the factual event would be slightly less severe in its extent, 113.40km² compared to 114.02km².
We aim to extend this initial work further both by improving the representation of flood defences, and including the sea level rise component. Attribution of the flood extent to sea level rise can be investigated by removing post-industrial sea level rise from the model boundary conditions to create a counterfactual; this opens another avenue for exploring the compound nature of the event. The impact of the proportion of sea level rise specifically attributable to anthropogenic influence will also be explored.
How to cite: Matthews, E., Munday, G., Perks, R., Cotterill, D., Bernie, D., Couasnon, A., Vertegaal, D., and Palmer, D.: Climate change attribution of the compound 2013/14 winter storms flooding in Somerset, UK, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-226, https://doi.org/10.5194/ems2026-226, 2026.
Analog-based methods identify historical climate events that closely resemble a recent target event. They are widely used in climate science to investigate the role of anthropogenic climate change in the severity of current extreme weather events, as well as for impact and risk assessment and adaptation strategies.
Despite their intuitive appeal, the definition of "similarity" between extreme events remains an open and often implicit methodological choice: which variables to consider, how to preprocess them, and how to aggregate them into a distance or similarity measure, can substantially affect which analogs are retrieved and, consequently, the conclusions drawn.
Here, we frame the analog search problem within the framework of Information Retrieval (IR), a well-established field in computer science focused on identifying relevant items from large collections in response to a query. This framing enables a rigorous, pipeline-oriented evaluation of different methodological choices, including variable selection, normalization strategies, dimensionality reduction, and similarity metrics, treating each configuration as a retrieval system whose performance can be systematically assessed. We apply this framework to the Emergency Events Database (EM-DAT), which provides a structured record of historical extreme events. We use EM-DAT both to define the query events and to provide a ground-truth signal for evaluating retrieval quality, i.e., whether retrieved analogs correspond to a disaster of the same type as the query event.
Our results suggest that pipeline configuration has a non-trivial effect on analog quality, with preprocessing choices and variable selection emerging as particularly critical. This work aims to provide a reproducible, quantitative framework for comparing analog-search strategies in the context of extreme event analysis, with potential applications in impact attribution, climate risk assessment and adaptation strategies.
Acknowledgements
This research has been carried out with funding from Ministero dell'Università e della Ricerca under the call Fondo Italiano per la Scienza 2022-2023 (FIS-2) for the project "Mediterranean Extreme Events and Tipping elements in a changing climate on multiple spatiotemporal scales", grant number FIS-2023-00159, CUP: D53C24005450001.
How to cite: Siciliano, F., Zanchi, M., Zazulie, N., de Leeuw, J., Scardino, G., Coppola, E., Faranda, D., and Alberti, T.: Finding Extreme Event Analogs Through Information Retrieval: A Methodological Assessment Using the Emergency Events Database, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-127, https://doi.org/10.5194/ems2026-127, 2026.
Over the past 20 years, extreme event attribution has developed rapidly, providing a wide range of methods to attribute weather events – from unconditioned probabilistic to strongly conditioned storyline approaches. Advancing the field now requires combining results from multiple methods, allowing more robust conclusions drawn from various lines of evidence. Yet, doing so remains challenging. I will outline various methods currently used highlighting the benefits and disadvantages of each.
I will then present the ‘new kid on the block’: ReBASE. ReBASE (Reanalysis Based Attribution and Storylines of Extremes) is a collaborative project led jointly by the University of Edinburgh and the University of Reading.
We use a novel data driven reanalysis based approach to examine real-world weather translated into different climates. We produce a reanalysis product of the current decade. Then, by altering the sea surface temperature, sea-ice concentrations, and forcings, we create storylines of how the weather could play out in both warmer and colder climates. These storylines can be used to attribute impacts and assess amplification of extreme weather events in a warmer climate. We can also provide counterfactuals of past events, translated to the present day climate.
This approach allows a global perspective on extreme events and their impacts - the same experiments produce global factual and counterfactual reconstructions of every day in the chosen periods. The data will be made openly available to allow anyone to explore their own choice of extreme event anywhere in the globe. Counterfactuals will also be developed for future warmer climate conditions to understand how extreme events and their impacts will change, and help inform adaptation decisions.
How to cite: Thompson, V., Thomas, R., Schurer, A., Hegerl, G., Shepherd, T., and Hawkins, E.: Why do we need multiple methods for extreme event attribution? , EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-130, https://doi.org/10.5194/ems2026-130, 2026.
There are ever increasing demands by society for timely climate attribution information following extreme events, and for inclusion of extreme event attribution within operational climate services. The science supporting routine climate attribution assessments has also progressed substantially in recent years, and there is a landscape of a growing number of providers of such climate intelligence. The Copernicus Climate Change Service (C3S) aims to establish an operational framework for extreme event attribution with a global scope and a European focus. In this presentation the key outcomes from the development phase of this activity will be presented and discussed. The service is building on established methodologies and previous European collaborations, combining scientific, operational and communication expertise from across a number of institutions, to produce a flexible and portable operational extreme event service based on multiple attribution methods and mature science. In this presentation we will present and discuss key outputs and lessons learned during the development phase of this as an operational climate attribution service.
The key outputs include:
- Interactive Web Application – A tool for exploring trends in extreme events and their links to climate change through maps, time series, and statistical analyses.
- Extreme Event Attribution Office – A distributed office across four European meteorological services, in collaboration with ECMWF, delivering rapid climate attribution assessments.
- Rapid Attribution Studies – Production of factsheets within five business days of an event, with extended analyses for longer-term events.
- Counter-Factual Weather Data – Development of alternative climate scenarios using advanced dynamical models.
- Communication Products – User documentation, visualisation guidance, training materials, and peer-reviewed scientific reports.
How to cite: McCarthy, M., Philip, S., Kew, S., Vamborg, F., Beck, T., and Jones, Z.: Copernicus Operational Extreme Event Monitoring and Attribution Service, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-602, https://doi.org/10.5194/ems2026-602, 2026.
The need and interest in operational detection and attribution services is growing. To increase the operational efficiency of relevant and rapid attribution studies, an efficient method for the first step in the process - triggering and selection of extreme events for potential study, is required. It can also be beneficial to ensure that the triggering process is as objective as possible in order to reduce risks of selection bias and ensure any operational service is fully traceable regarding decisions made when initiating a study.
The “Heat wave magnitude index daily (HWMId)” of Russo et al. 2015 is adapted for the purpose of triggering heat, cold and wet extremes on a daily basis. Using a clustering algorithm, events are automatically ranked per type across a 2-week period, covering recent and upcoming days, according to an index accounting for their intensity, duration and area. This index, together with related metrics such as DEI, EFI and RX3day, is displayed regionally and globally in the “Hazard Monitoring Tool” - a user interface for operational use.
The outcome of the method’s application to heat extremes will be demonstrated and compared to HWMId for well known extreme events and other events of interest. The adaptation of the method for cold and wet extremes will also be presented, along with several other diagnostic tools that can aid the selection of the most suitable extreme events for a rapid attribution study. As this is work in progress, we look forward to discussions on the challenges as well as the promising results of this method.
How to cite: Kew, S., Pinto, I., and Philip, S.: Automated trigger procedure for operational attribution, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-715, https://doi.org/10.5194/ems2026-715, 2026.
In early 2026, an exceptional extreme weather events struck Southern Africa. Following heavy and persistent rains, rivers within the region exceeded their alert levels, causing large-scale flooding in South Africa, Mozambique, Zimbabwe and Eswatini. In January 2026, Mozambique’s National Institute of Meteorology (INAM) reported that several regions received record-breaking 24-hour rainfall, surpassing their annual averages. Notably, Gaza (Massangena station) recorded 271.9 mm on January 11, Maputo (Maputo Observatory) saw 213 mm on January 19, and Inhambane (Massinga station) reached 253 mm on January 10. The combination of very intense rainfall over a short period, together with high vulnerability and exposure, led to the worst flooding in Mozambique in 25 years. This led to severe socioeconomic losses, characterized by loss of life, casualties, and extensive damage to critical infrastructure in the region. At seasonal timescales, large parts of the study regions experienced record-breaking surface weather associated with the influence of La Nina setting up favourable circulation patterns for heavy rainfall. This study analyses the atmospheric and oceanic patterns linked to the event, as well as the influence of climate change, using reanalysis and gridded observational datasets. Using a probabilistic attribution approach, we found that the heavy rainfall was an exceptionally rare event in today’s climate, characterized by a high local return period. Furthermore, human-induced climate change and the weak La Niña increased the intensity and frequency of events of this magnitude. This study contributes to an improved process-understanding of extreme weather events in the region with implications for adaptation and disaster risk management.
How to cite: Pinto, I., Kimutai, J., Zachariah, M., Philip, S., Meque, A., and Otto, F.: Extreme rainfall and floods in southern Africa in January 2026 -associated circulation patterns and role of climate change, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-178, https://doi.org/10.5194/ems2026-178, 2026.
Western disturbances (WD) and Indian Summer Monsoon (ISM) are two key atmospheric phenomena driving the complex hydroclimate over India, subsequently influencing the winter and monsoon season of the subcontinent. In recent decades, the WDs have been increasingly observed in the monsoon season, potentially enhancing their interaction with the Indian Summer Monsoon. This interaction is prone to high-impact precipitation extremes (such as the Uttarakhand flood 2013, Himachal Flood 2023) over Northern India and the Himalayan region, potentially impacting the water security and disaster preparedness of the region. Despite their importance, the role of climate change in modulating these WD–ISM precipitation extremes remain underexplored. To address this crucial gap, the study investigates the shift in WD occurrences during the monsoon season and their co-occurrence with extreme precipitation events for the period 1950-2024 over the Hindu Kush Himalayan region using multiple precipitation datasets, including ERA5, CPC, MSWEP and the WD track dataset (developed by Hunt et al. 2018). Additionally, a probabilistic climate attribution framework has been applied in this research using CMIP6 model simulations to compare the occurrence of such extremes in factual (recent) and counterfactual (pre-industrial) climate conditions. Preliminary findings indicate a significant increasing observed trend of ~0.054 events per year (p=0.002) in the occurrence of WD-associated monsoon extreme systems during 1950–2024, with a more pronounced rise in recent decades. Subsequently, a significant upward tendency (p<0.001) has been observed in total annual precipitation from WD-associated extreme grids for the same. The findings emphasise the growing importance of the interaction between Western Disturbances and the Indian Summer Monsoon in shaping regional water security and highlight the need for enhanced disaster preparedness in a warming climate.
Keywords: Western Disturbances (WD), Indian Summer Monsoon (ISM), Hindu Kush Himalayan Region (HKH), Climate Attribution, Climate Change.
How to cite: Mitra, S., Clarke, B., Otto, F., and Agarwal, A.: Observed and Attributed Increase in Western Disturbance Induced Monsoon Extremes in a Warming Climate , EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-566, https://doi.org/10.5194/ems2026-566, 2026.
The objective of this project of the ECMWF is to create an “Operational Extreme Event Monitoring and Attribution Service”, building on established methodologies and previous collaborations, including C3S, EUCLEIA, EUPHEME, and XAIDA. The service is enabled by a flexible, globally applicable framework, based on scientific, operational, and communication expertise. In this study, we apply the different methodologies available in the operational framework and beyond to different climate extremes, to compare attribution across different types of extreme weather events.
The main methodologies in the framework are probabilistic attribution and analogue-based dynamical attribution. We also include storyline-based methods in our comparison, to provide a more comprehensive picture of all key methodologies used by the research community. Each methodology has their unique strengths and may therefore be useful in specific user cases. Furthermore, the advantages and drawbacks of the methods are dependent on the type of extreme weather event considered. For example, extreme rainfall events are relatively short-lived, whereas droughts generally occur for several months. It is therefore crucial to have a comparison of the framework across different types of climate extremes - both univariate and compound. We therefore aim to include a wide range of extreme events, including a heatwave, drought, and extreme rainfall event. Similarly, we apply a range of methods including probabilistic attribution, dynamical attribution using analogues, and storyline attribution using nudged climate model simulations from DestinE, and the 20th century reanalysis project. By doing so, we provide a coherent case study comparison using the Operational Extreme Event Monitoring and Attribution Service, as part of the C3S project.
How to cite: Happé, T., Thompson, V., Coumou, D., and Scussolini, P.: Operational Extreme Event Monitoring and Attribution Service: a multi-method comparison, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-631, https://doi.org/10.5194/ems2026-631, 2026.
Climate attribution is a rapidly evolving field quantifying the effect of climate change on extreme weather events. Findings from attribution studies often fuel news headlines to inform on the consequences of climate change. Moreover, the field of climate attribution has become an important knowledge base to build our understanding of how the likelihood and intensity of extreme events is affected by climate change. However, the applicability of climate attribution for allocating Loss & Damage funds, climate litigation cases, and informing adaptation decisions remains a matter of debate. For example for adaptation planning, Osaka & Bellamy (2020) showcase diverging views on the usefulness of climate attribution between scientists, stakeholders, and citizens. Other studies argue that by purely focusing on meteorological drivers, climate attribution ignores other, perhaps more impactful, drivers of disasters, such as unplanned urban expansion into flood-prone areas.
A newer field, rising from climate attribution, is the field of impact attribution that aims to quantify the effect of climate change on impact, thereby including exposure and vulnerability. It can be argued that propagating extreme weather events to impact aligns closer with the lived experience of society, thereby providing a more holistic analysis. By including other components of risk, one could argue that impact attribution becomes useful for adaptation, while climate attribution might be more useful for incentivizing climate mitigation.
During this session, we invite you to reflect on the purpose, usefulness, and future directions of impact attribution. Key questions include: Does impact attribution complement or replace climate attribution? Should it incorporate non-climate drivers, and is it feasible for all hazard types, including compound events? What is needed for the field to reach its full potential? In a rapidly developing field where much remains open, structured reflection on these foundations is not a distraction from progress, but essential for guiding it.
How to cite: Vertegaal, D., van den Hurk, B., Couasnon, A., and Muis, S.: Moving beyond climate attribution: A shared reflection on the purpose, usefulness, and future of impact attribution, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-705, https://doi.org/10.5194/ems2026-705, 2026.
This study investigated the impacts of cold waves on winter mortality in the Korean Peninsula using long-term meteorological observations and mortality records from 2000 to 2023. Cold-wave days were first examined in terms of their temporal and regional characteristics, revealing substantial interannual variability and a tendency for increased cold-wave occurrence during winters characterized by the negative phase of the Arctic Oscillation. Spatially, cold-wave days were more frequent in inland and high-altitude regions such as Gyeonggi, Gangwon, and Chungbuk, whereas southern coastal regions and Jeju Island experienced few or no cold-wave events.
Mortality analyses showed distinct differences between direct cold-related deaths (T68–T69) and indirect causes, including cardiovascular and respiratory diseases (CVD+Resp). While T68–T69 deaths were concentrated under extremely low temperatures, CVD+Resp deaths occurred under relatively milder conditions, indicating the influence of multiple physiological and environmental factors. Time-lagged analyses demonstrated that excess mortality was most pronounced one day after cold-wave onset (lag 1), and that prolonged cold-wave duration (≥4 days) substantially amplified excess mortality, particularly for CVD+Resp deaths.
To further explore the relative importance and nonlinear effects of meteorological factors, a Gradient Boosting Machine (GBM) model was applied. Partial dependence analyses indicated that solar radiation and wind direction exerted the strongest influence on winter mortality, followed by minimum temperature, dew-point temperature, and diurnal temperature range. Two-way interaction analyses revealed that extreme cold combined with low solar radiation, specific wind regimes (northwesterly and easterly flows), dry atmospheric conditions, or large temperature variability significantly increased mortality levels. Overall, the results demonstrate that winter mortality associated with cold waves is governed by the combined effects of multiple meteorological factors rather than temperature alone. These findings highlight the importance of incorporating compound meteorological conditions into cold-wave risk assessment and public health adaptation strategies.
How to cite: Kim, Y.-J. and Lim, B.: Impacts of cold waves on winter mortality in the Korean Peninsula, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-249, https://doi.org/10.5194/ems2026-249, 2026.
Supporters & sponsors
