NP2.2

Record-breaking natural hazards occur regularly throughout the world, leading to a variety of impacts [1]. According to the WMO, since 1970 there were more than 11000 reported disasters attributed to these hazards globally, with just over 2 million deaths and US$ 3.64 trillion in losses [2]. From 1970 to 2019, weather, climate and water hazards accounted for 50% of all disasters, 45% of all reported deaths and 74% of all reported economic losses [2]. Droughts and heatwaves are both included in the top 4 disasters in terms of human losses [2], with uneven impacts throughout the world and a high likelihood that anthropogenic climate forcing will increase economic inequality between countries [3].

Nowadays there is strong evidence that droughts and heatwaves are at times synergetic and that their combined occurrence is largely caused by land-atmosphere feedbacks [4]. In fact, increasing trends of Compound Dry and Hot (CDH) events have been observed in both South America [5,6] and Europe [7,8], some of them with aggravated impacts. Specifically, the severe 2020 Pantanal extreme fire season (Brazil) resulted from the interplay between extreme and persistent temperatures (maximum temperatures 6 ºC above-average) and long-term soil dryness conditions [6]. Similarly, in the Iberian Peninsula, CDH events were shown to have an influence on the dramatic 2017 fire season [9] and also on crop losses [8]. Moreover, future climate projections suggest that CDH conditions are expected to become more common in a warming climate [4]. Therefore, it is very important to address weather events in a compound manner, identifying synergies, driving mechanisms and dominant atmospheric modes controlling single and combined hazards.

[1] IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of WGI to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte  V. et al., (eds.)]. Cambridge University Press. 

[2] WHO, 2021. Weather-related disasters increase over past 50 years, causing more damage but fewer deaths, https://public.wmo.int/en/media/press-release/weather-related-disasters-increase-over-past-50-years-causing-more-damage-fewer

[3] Diffenbaugh N.S., Burke M. (2019) Global warming has increased global economic inequality, PNAS, 116, 20, 9808-9813

[4] Zscheischler J. et al. (2018). Future climate risk from compound events. Nat. Clim. Change, 8, 469–477.

[5] Geirinhas J.L. et al. (2021). Recent increasing frequency of compound summer drought and heatwaves in Southeast Brazil. Environ. Res.  Lett., 16(3).

[6] Libonati R. et al (2022) Assessing the role of compound drought and heatwave events on unprecedented 2020 wildfires in the Pantanal, Environ. Res. Lett. 17 015005.

[7] Geirinhas J.L. et al. (2020) Heat-related mortality at the beginning of the twenty-first century in Rio de Janeiro, Brazil. Int. J. Biometeorol., 64, 1319–1332

[8] Russo A. et al. (2019) The synergy between drought and extremely hot summers in the Mediterranean. Environ. Res. Lett., 14, 014011

[9] Ribeiro A.F.S. et al. (2020) Risk of crop failure due to compound dry and hot extremes estimated with nested copulas. Biogeosciences, 17, 4815–4830

[10] Turco M. et al. (2019) Climate drivers of the 2017 devastating fires in Portugal. Sci. Rep., 9, 1

This work was supported by Fundação para a Ciência e a Tecnologia (Portugal) under projects PTDC/CTA-CLI/28902/2017, JPIOCEANS/0001/2019 and FCT- UIDB/50019/2020 –IDL.

How to cite: Russo, A., Libonati, R., Geirinhas, J. L., Ramos, A. M., Silva, P. S., Sousa, P. M., DaCamara, C. C., Miralles, D. G., and Trigo, R. M.: Complex interactions of extreme events in Southern Europe and Brazil: a compound event perspective, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12508, https://doi.org/10.5194/egusphere-egu22-12508, 2022.

• The occurrence of extreme weather events has increased during the two last decades.  European heat waves are responsible for social, economic and environmental damage and are projected to increase in magnitude, frequency and duration under global warming, heightening the  interest about the contribution of different drivers. 
• By using the ERA5 Re-analysis product, we performed a two-sided composite analysis to investigate a potential relation between North Atlantic sea surface temperatures (SSTs) and the near-surface air temperature (T2m) over the European continent. Here, we show that in the presence of cold North Atlantic SSTs during summer, the distribution of European T2m shifts towards positive anomalies a few days later, increasing the likelihood for heat waves. During these events a predominant wave number three pattern in addition to regionally confined Rossby wave activity  contribute to a trough-ridge pattern in the North Atlantic-European sector. Specifically, five of 17 European heat waves within the period of 1979 to 2019 could be related to a cold North Atlantic SST event a few days in advance. In the upstream analysis we identify eleven of 17 European heat waves co-existent with cold North Atlantic SSTs. 
• In order to confirm the crucial role of North Atlantic SSTs for European heat waves, we analysed output from a coupled climate model, HadGEM3, with three different horizontal resolutions. The high-resolution run revealed the closest resemblance to the ERA5 data, suggesting that mechanisms on the mesoscales (<50 km) play a role in the relationship between North Atlantic SSTs and European T2m. Results also highlight the importance of using a climate model with a high horizontal resolution for the purpose of studying the variability of European heat waves.
• Based upon our results, conducted with ERA5 Re-analysis and HadGEM3 data, North Atlantic SSTs provide potential predictive skill of European heat waves.

How to cite: Krüger, J., Kjellsson, J., Pilch Kedzierski, R., and Claus, M.: The relation between European heat waves and North Atlantic SSTs: a two-sided composite study, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5420, https://doi.org/10.5194/egusphere-egu22-5420, 2022.

The extratropical meridional energy transport in the atmosphere is fundamentally intermittent in nature, having extremes large enough to affect the net seasonal transport. Here, we investigate how these extreme transports are associated with the dynamics of the atmosphere at multiple scales, from planetary to synoptic. We use ERA5 reanalysis data to perform a wavenumber decomposition of meridional energy transport in the Northern Hemisphere mid-latitudes during winter and summer. We then relate extreme transport events to atmospheric circulation anomalies and dominant weather regimes, identified by clustering 500 hPa geopotential height fields. In general, planetary-scale waves determine the strength and meridional position of the synoptic-scale baroclinic activity with their phase and amplitude, but important differences emerge between seasons. During winter, large wavenumbers (k = 2 − 3) are key drivers of the meridional energy transport extremes, and planetary and synoptic-scale transport extremes virtually never co-occur. In summer, extremes are associated with higher wavenumbers (k = 4 − 6), identified as synoptic-scale motions. We link these waves and the transport extremes to recent results on exceptionally strong and persistent co-occurring summertime heat waves across the Northern Hemisphere mid-latitudes. We show that these events are typical, in terms of dominant regime patterns associated with extremely strong meridional energy transports.

Link to pre-print: https://wcd.copernicus.org/preprints/wcd-2021-85/

How to cite: Lembo, V., Fabiano, F., Galfi, V. M., Graversen, R., Lucarini, V., and Messori, G.: Meridional energy transport extremes and the general circulation of NH mid-latitudes: dominant weather regimes and preferred zonal wavenumbers, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1884, https://doi.org/10.5194/egusphere-egu22-1884, 2022.

Detecting trends in regional large-scale circulation (LSC) is an important challenge as LSC is a key driver of local weather conditions. In this work, we investigate the past evolution of Western Europe LSC based on the 500 hPa geopotential height fields from 20CRv2c (1851-2010), ERA20C (1900-2010) and ERA5 (1950-2010) reanalyses. We focus on the evolution of large-scale circulation characteristics using three atmospheric descriptors that are based on analogy, by comparing daily geopotential height fields to each other. They characterize the stationarity of geopotential shape and how well a geopotential shape is reproduced in the climatology. A non-analogy descriptor is also employed to account for the intensity of the centers of action. We then combine the four atmospheric descriptors with an existing weather pattern classification over the period 1950-2019 to study the recent changes in the main atmospheric influences driving precipitation in the Northern French Alps. Even though LSC characteristics and trends are consistent among the three reanalyses after 1950, we find major differences between 20CRv2c and ERA20C from 1900 to 1950 in accordance with previous studies. Notably, ERA20C produces flatter geopotential shapes in the beginning of the 20th century and shows a reinforcement of the meridional pressure gradient that is not observed in 20CRv2c. Over the period 1950-2019, we show that winter Atlantic circulations (zonal flows) tend to be shifted northward and they become more similar to known Atlantic circulations. Mediterranean circulations tend to become more stationary, more similar to known Mediterranean circulations and associated with stronger centers of action in autumn, while an opposite behaviour is observed in winter. Finally, we discuss the responsibility of these LSC changes for extreme precipitation in the Northern French Alps. We show these changes in LSC characteristics are linked to more circulations that are likely to generate extreme precipitation in autumn.

How to cite: Blanc, A., Blanchet, J., and Creutin, J.-D.: Past Evolution of Western Europe Large-scale Circulation and Link to Extreme Precipitation Trend in the Northern French Alps, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1594, https://doi.org/10.5194/egusphere-egu22-1594, 2022.

The Extreme Event Attribution field aims at evaluating the impact of global warming linked to anthropogenic emissions on extreme events. This work performs an attribution to climate change of the storm Alex, an explosive extratropical cyclone [1] that hit especially Southern France and Northern Italy at the beginning of October 2020. We apply the analogues method on sea-level pressure maps [2] to identify 30 cyclones that match the dynamical structure of Alex for two periods, the counterfactual and the factual world, namely 1950-1985 and 1985-2021, using 6-hourly ERA5 data. Results show that in the factual period the anticyclonic circulation over the North Atlantic and the cyclonic circulation over Northern Africa are deeper than in the counterfactual. Precipitation differences depict a significant increase over North Italy and the Alps. 2-meter air temperature differences consist of a positive non-uniform pattern, with a significant increase over the Alps and east of Newfoundland. We also have computed two indices in the frame of dynamical systems theory for each period: the persistence, which characterizes the average time that the sea-level pressure pattern remains stationary, and the local dimension, which gives a measure of the predictability of the storm [3]. We found that in the factual world there is a significant increase in the persistence and a modest decrease in the local dimension with respect to the counterfactual. Hence, storms like Alex are more persistent and more predictable in present-like conditions. Cyclone tracking shows that the backward trajectories of the analogues in the factual world are more meridional than in the counterfactual one, while the response for the forward trajectories is less clear. This suggests that under current conditions patterns like Alex are more wavy than in the past. Finally, using the metrics to identify explosive cyclones in [1] , we found the same number of analogues that are explosive cyclones in both periods, although in the counterfactual world they come from lower latitudes and the deepening rates are significantly larger.

References

[1]  Reale, M., M. L. Liberato, P. Lionello, J. G. Pinto, S. Salon, and S. Ulbrich, A global climatology of explosive cyclones using a multi-tracking approach, Tellus A: Dynamic Meteorology and Oceanography, 71 (1), 1611,340, 2019.

[2] Yiou, P., AnaWEGE: a weather generator based on analogues of atmospheric circulation, Geosci. Model Dev., 7, 531–543, 2014.

[3] Faranda, D., G. Messori, and P. Yiou, Dynamical proxies of North Atlantic predictability and extremes, Sci Rep, 7, 41,278, 2017.

Acknowledgments

This work is part of the EU International Training Network (ITN) European weather extremes: drivers, predictability and impacts (EDIPI). This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement N° 956396. 

How to cite: Ginesta, M., Yiou, P., Messori, G., and Faranda, D.: A framework for attributing explosive cyclones to climate change: the case study of Alex storm 2020, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3133, https://doi.org/10.5194/egusphere-egu22-3133, 2022.

Marine heatwaves (MHWs) are periods of extreme warm ocean temperatures that can have devastating impacts on marine
organisms and socio-economic systems. Despite recent advances in understanding the underlying processes of individual events, a
global view of the local oceanic and atmospheric drivers of MHWs is currently missing. Here, we use daily-mean output of
temperature tendency terms from a comprehensive fully coupled Earth system model to quantify the main local processes leading
to the buildup and decay of MHWs in the surface ocean. Our analysis reveals that net ocean heat uptake associated with more
shortwave heat absorption and less latent heat loss is the primary driver of the buildup of MHWs in the subtropics and mid-to-high
latitudes. Reduced vertical mixing from the nonlocal portion of the KPP boundary layer scheme partially dampens the temperature
increase. In contrast, ocean heat uptake is reduced during the MHW build-up in the tropics, where reduced vertical local mixing
and diffusion cause the warming. In the subsequent decay phase, ocean heat loss to the atmosphere dominates the temperature
decrease globally. The processes leading to the buildup and decay of MHWs are similar for short and long MHWs. Different types of
MHWs with distinct driver combinations are identified within the large variability among events. Our analysis contributes to a
better understanding of MHW drivers and processes and may therefore help to improve the prediction of high-impact marine
heatwaves.

How to cite: Vogt, L., Burger, F., Griffies, S., and Frölicher, T.: Local drivers of marine heatwaves: A global analysis with an Earth system model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1832, https://doi.org/10.5194/egusphere-egu22-1832, 2022.

Cold and snowy spells are compound extreme events with the potential of causing high socioeconomic impacts. Gaining insight on their dynamics in climate change scenarios could help anticipating the need for adaptation efforts. We focus on winter cold and snowy spells over Italy, reconstructing 32 major events in the past 60 years from documentary sources. Despite warmer winter temperatures,  very recent cold spells have been associated to abundant, and sometimes exceptional snowfall.
Our goal is to analyse the dynamical weather patterns associated to these events, and understand whether those patterns would be more or less recurrent in different emission scenarios using an intermediate complexity model (PlaSim). Our results, obtained by considering RCP2.6, RCP4.5 and RCP8.5 end-of-century CO2 concentrations, suggest that the likelihood of analogous synoptic configurations of these extreme cold spells would grow substantially under increased emissions.

This work was supported by the ANR-TERC grant BOREAS and by the Horizon 2020 research and innovation programme XAIDA (grant agreement No 101003469)

How to cite: Pons, F., D’Errico, M., Yiou, P., Tao, S., Nardini, C., Lunkeit, F., and Faranda, D.: Present and future synoptic circulation patterns associated with cold and snowy spells over Italy, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5511, https://doi.org/10.5194/egusphere-egu22-5511, 2022.

The Pacific Northwest is characterized by a temperate climate with mild to warm summers, yet in late June 2021, the region was ravaged by extreme heat and ensuing wildfires. With local daily maximum temperatures 20 °C above the long term mean, the occurrence of such a brute heatwave makes it imperative to understand the underlying physical processes. Using the Community Earth System Model, we simulate this exceptional event and disentangle its thermodynamic and dynamic drivers. A factorial experimental design based on the ExtremeX framework is employed, in which the mid and upper-tropospheric circulation and soil moisture are either prescribed using reanalysis (ERA5) data, or calculated interactively. With this setup, the lower troposphere can always respond to land and ocean surface fluxes. Our results indicate that, despite widespread drought conditions in the analysis region (including the metropolitan areas of Portland, Seattle and Vancouver) and surroundings, the dynamic contribution far exceeded the effect of anomalous soil moisture. We further disentangle the soil moisture contribution into initial and event-driven, and find that precipitation in the first half of June 2021 prevented even higher near-surface temperatures by weakening the initial effect. Overall, the analysis highlights the role of the anticyclone that governed the large-scale circulation, and whose intensity during summertime and within 45°N–60 °N surpasses any other event in recent decades. As such, this heatwave presents an opportunity to investigate whether our Earth System Model of choice is capable of generating similarly extreme heat at large spatial scales on its own, i.e. with fully interactive winds. While the mean intensity of hot anticyclonic summer events over land (45°N–60 °N) is underestimated with respect to our reference simulation with prescribed circulation, the model portrays stronger variability with an interactive atmosphere and hence generates heatwaves that rival and even surpass the large-scale temperature anomalies of the Pacific Northwest 2021 event. Our investigation also points to strong temperature anomalies aloft, which we track back in time with a Lagrangian trajectory model driven by ERA5 data. By doing so, we find evidence for intense latent heating of the air that would later be part of the anticyclone, and mixed into the unusually deep atmospheric boundary layer. We further demonstrate that in the absence of anthropogenic climate change, an otherwise identical heatwave would not have reached such extreme temperatures. Altogether, this study shows that for the right atmospheric configuration and fuelled by our changing climate, unprecedented heat may be unleashed even in regions traditionally considered devoid of excessive heatwaves.

How to cite: Schumacher, D. L., Hauser, M., and Seneviratne, S. I.: Mechanisms and drivers of the 2021 Pacific Northwest heatwave, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9156, https://doi.org/10.5194/egusphere-egu22-9156, 2022.

Climate change has an influence on daily weather. It translates into a heightened public perception of any type of « weird » weather. For example, it has been shown that extreme weather events are seen as pointing towards the reality of climate change. These perceived attributions are not only related to heatwaves, but also to cold spells (Capstick and Pigeon (2014)), and floods (Taylor et al (2014)).

Extreme events however represent only a subset of the weather distribution experienced by the public. Another manifestation of « weird » weather is the succession of very different types of weather in a short period of time, e.g. two following days with a 10°C difference. While this is widely regarded as another manifestation of climate change by the general public, there are only a few studies exploring short timescale weather variability. For example, Cattiaux et al (2015) have found a projected increase in diurnal and interdiurnal variations of European summer temperatures in CMIP5 simulations.

Here, we use the ERA5 reanalyses (1950-2020) over Europe to study observed diurnal and interdiurnal (2, 3, 5 and 7 days) variations of temperature. We focus on extremes (below the 5th percentile and above the 95th percentile of the distribution of temperature differences) for all seasons and independently for each season and calculate trends. While the general result is that, contrarily to popular beliefs, the diurnal and interdiurnal variations have not increased in the observational periods, we show regional differences over Europe and discuss potential explanations for these differences. 

References:
Capstick, S.B., Pidgeon, N.F. Public perception of cold weather events as evidence for and against climate change. Climatic Change 122, 695–708 (2014). https://doi.org/10.1007/s10584-013-1003-1
Cattiaux, J., Douville, H., Schoetter, R., Parey, S. and Yiou, P. (2015), Projected increase in diurnal and interdiurnal variations of European summer temperatures. Geophys. Res. Lett., 42: 899– 907. doi: 10.1002/2014GL062531.
Taylor, A., de Bruin, W.B. and Dessai, S. (2014), Climate Change Beliefs and Perceptions of Weather-Related Changes in the United Kingdom. Risk Analysis, 34: 1995-2004. https://doi.org/10.1111/risa.12234

How to cite: Jezequel, A. and Fararanda, D.: Is the weather getting "weirder"?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7381, https://doi.org/10.5194/egusphere-egu22-7381, 2022.

How to cite: Minjares, M., Yiou, P., Serra, I., Barreiro, M., and Corral, Á.: Extreme Value Analysis of Madden-Julian Oscillation Events, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12484, https://doi.org/10.5194/egusphere-egu22-12484, 2022.

The intensity and frequency of persistent heat waves and droughts have increased over the last few decades. While some of the changes may be attributed to natural variability, it is a known reality that climate change contributes to these tendencies. According to the Fifth Assessment Report of the IPCC, these anomalies are projected to be accelerated and impact humans, ecology, agricultural events, and natural systems.

Understanding the spatiotemporal structure of heat waves is crucial to deciding what environmental change will affect the above-mentioned impacts. In this study, the temporal autocorrelation of near-surface temperature and 850 hPa geopotential height from daily ERA-5 reanalysis data is examined. The focus is on the period from 1979 to 2019. To explore this 41-year long dataset, spatio-temporal trend analysis is also conducted along with autocorrelation. The trends are inspected under 3, 5, and 7-day lag autocorrelations.

In this context, the summer of 2003 shows a very high autocorrelation of geopotential height over central Europe in this analysis, which is consistent with a persistent heat wave that resulted in a death toll. Along with the yearly analyzed data, the trends are calculated both as a whole and divided into intervals. The trend analysis yields high results that cluster around Northern Africa, the Middle East, Middle China, and Middle Russia in the summer season. Furthermore, in the winter season, Siberia, Middle Africa, and the northern part of South America reflect high trends.

How to cite: Gözlet, M. S., Kjellsson, J., Savita, A., and Latif, M.: Recent changes in persistence over Europe and the World in reanalysis dataset, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10586, https://doi.org/10.5194/egusphere-egu22-10586, 2022.

There are many regions where the duration of reliable scientific observations of key weather hazard variables, such as rainfall and wind speed, is of the order of just a few decades.  This length of dataset is often inadequate for the application of extreme value theory to rare events. Theoretical analysis of chaotic dynamical systems shows that extremes should be distributed according to the classical Pareto distribution, with explicit expressions for the scaling and shape parameter[1]. Discrepant results may be interpreted as indicating the need for a longer data time series.

Physicists acknowledge that history is just one realisation of what could have happened. One way of supplementing a brief duration observational dataset is to generate an ensemble of alternative realisations of history. Of special practical interest within this counterfactual ensemble are downward counterfactuals - where the outcome turned for the worse.  Extreme hazard events often cause surprise, which reflects an underlying degree of outcome cognitive bias. Downward counterfactual is a term originating in the cognitive psychological literature, which has been applied by Woo[2] to the search for extreme hazard events.  Most human counterfactual thoughts are upward, focusing on risk mitigation or prevention, rather than downward, focusing on potential rare Black Swan events. 

The insight gained from downward counterfactual analysis is illustrated with the example of rainfall and flooding in Cumbria, Northwest England.  Daily rainfall records at Honister Pass, Cumbria, from 1970 to 2004, were statistically analysed to estimate the return period for the rainfall of 301.4mm oberved on 20 November 2009.  This return period was estimated to be 396 years[3].  But six years later, on 5 December 2015, this was substantially exceeded by 341.4mm rainfall.

In 2009, there was only a moderate El Niňo.  Counterfactually, there might have been a strong El Niňo.  Indeed, in 2015 there was a very strong El Niňo. A downward counterfactual analysis of the heavy rainfall on 20 November 2009 would have included the possibility of a very strong El Niňo.  This is one of a number of exacerbating dynamical meteorological factors that might have elevated the rainfall.

Where the data duration is much shorter than the return period of extreme events, a downward counterfactual stochastic simulation of factors raising the hazard will provide important additional insight for geophysical hazard assessment.

How to cite: Woo, G.: Downward counterfactual insights into weather extremes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-30, https://doi.org/10.5194/egusphere-egu22-30, 2022.

Natural hazards cause a plethora of impacts on society, ranging from direct impacts such as loss of lives to cascading ones such as power outages and supply shortages. Despite the severe social and economic losses of extreme events, a comprehensive assessment of their impacts remains largely missing. Existing studies tend to focus on impacts that are relatively easy to measure (e.g. financial loss, number of deaths) and commonly break down impact assessments into specific sectors (e.g. forestry, agriculture). Thus, in the absence of multi-sector impact datasets, decision-makers have no baseline information for evaluating whether adaptation measures effectively reduce impacts. This can result in blind spots in adaptation.

In recent years, text data (e.g. newspapers, social media, and Wikipedia entries) have been used to elaborate impact datasets. However, the manual extraction of impact information by human experts is a time-consuming task. To develop comprehensive impact datasets, we propose using text-mining on text documents. We developed a tool termed TM-Impacts (text-mining of natural hazard impacts), which allows us to automatically extract information on impacts by applying natural language processing (NLP) and machine learning (ML) tools to text-corpora. TM-Impacts is built upon a previous prototype application (de Brito et al., 2020).

TM-Impacts consists of three complementary modules. The first focuses on using unsupervised topic modelling to identify the main topics covered in the text. These can include not only the disaster impacts but also information on response and recovery. The second module is based on the use of hand-crafted rules and pattern matching to extract information on specific impact types (e.g. traffic disruption, power outages). The final module builds upon the second one, and it uses the resulting labelled data to train supervised ML algorithms aiming to classify unlabeled text data into impact types.

We illustrate the application of TM-Impacts using the example of the 2021 flood in Germany. This event led to more than 180 fatalities and the disruption of critical infrastructure that continued for months after the event. We built a text corpus with more than 26,000 newspaper articles published in 200 different news outlets between July and November 2021. By using TM-Impacts, we were able to detect 20 different impact types, which were mapped at the NUTS 3 scale. We also identified temporal patterns. As expected, during the onset of the event, reporting on impacts tended to focus on deaths and missing people, whereas texts published in November focused on long term impacts such as the disruption of water supply.

In conclusion, we demonstrate that TM-Impacts allows scanning large amounts of text data to build multi-sector impact datasets with a great spatial and temporal stratification. We expect the use of text-mining to become widespread in assessing the impacts of natural hazards.

de Brito, M.M., Kuhlicke, C., Marx, A. (2020) Near-real-time drought impact assessment: A text mining approach on the 2018/19 drought in Germany. Environmental Research Letters. doi:org/10.1088/1748-9326/aba4ca

How to cite: Madruga de Brito, M., Sodoge, J., Kreibich, H., and Kuhlicke, C.: Text-mining of natural hazard impacts (TM-Impacts): an application to the 2021 flood in Germany, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2001, https://doi.org/10.5194/egusphere-egu22-2001, 2022.

Under continued global warming, extreme events such as heatwaves will continue to rise in frequency, intensity, duration, and spatial extent over the next decades. Younger generations are therefore expected to face more such events across their lifetimes compared to older generations. This raises important questions about solidarity and fairness across generations that have fueled a surge of climate protests led by young people in recent years, and that underpin questions of intergenerational equity raised in recent climate litigation. However, the standard scientific paradigm is to assess climate change in discrete time windows or at discrete levels of warming, a “period” approach that inhibits quantification of how much more extreme events a particular generation will experience over its lifetime compared to another. By developing a “cohort” perspective to quantify changes in lifetime exposure to climate extremes and compare across generations, we estimate that children born in 2020 will experience a two to sevenfold increase in extreme events, particularly heatwaves, under current climate policy pledges. Our results highlight a severe threat to the safety of young generations and call for drastic emission reductions to safeguard their future.

Thiery, W., Lange, S., Rogelj, J., Schleussner, C.-F., Gudmundsson, L., Seneviratne, S.I., Frieler, K., Emanuel, K., Geiger, T., Bresch, D.N., Zhao, F., Willner, S.N., Büchner, M., Volkholz, J., Andrijevic, M., Bauer, N., Chang, J., Ciais, P., Dury, M., François, L., Grillakis, M., Gosling, S.N., Hanasaki, N., Hickler, T., Huber, V., Ito, A., Jägermeyr, J., Khabarov, N., Koutroulis, A., Liu, W., Lutz, W., Mengel, M., Müller, C., Ostberg, S., Reyer, C.P.O., Stacke, T., Wada, Y., 2021, Intergenerational inequities in exposure to climate extremes, Science, 374(6564), 158-160.

How to cite: Thiery, W. and the The kids aren't alright team: Intergenerational inequities in exposure to climate extremes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2050, https://doi.org/10.5194/egusphere-egu22-2050, 2022.

A more accurate characterization of S2S extremes may result in great positive societal impact. Featurized S2S forecasts in the form of risk or extreme indices will aid in disaster response (especially for drought and flood events), inform disease outbreaks and heatwave onset, persistence, and decay. In this study, we identify a set of ECMWF-derived extreme weather indices that have spatio-temporal windows of opportunity for better-than-climatology skill. We report on the correlation between ECMWF-derived indices and ground-truth values.  The selected indices can be calculated directly form probabilistic daily forecasts, or alternatively, by training specialized ML-models to process ensembles in a multi-task learning setup. Our goal is to find better approaches to communicate S2S climate risk by deploying a set of ECMWF-derived climate forecast products.

How to cite: Patel, Z., Baloyi, G., Watson, C., Zaytar, A., Zadrozny, B., Civitarese, D., Makhanya, S., and Vos, E.: S2S Extreme Weather Featurization: A Global Skill Assessment Study, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12461, https://doi.org/10.5194/egusphere-egu22-12461, 2022.

Rare events, such as heat waves, floods, or hurricanes, play a crucial role in climate dynamics mainly due to the large impact they have. Predicting the occurrence of such events is thus a major challenge. 

In this talk, we introduce the relevant mathematical object for predicting a future event: the committor function is the probability that an event will occur, conditioned on the current state of the system. Computing this quantity from observations is an extremely difficult task since rare events have a very low probability of occurring and may not even have been observed in measurements made to date. Similarly, direct simulation of such events with comprehensive climate models comes at a prohibitive computational cost. Hence, rare event algorithms have been devised to simulate rare events efficiently, avoiding the computation of long periods of typical fluctuations.

The effectiveness of these algorithms strongly relies on the knowledge of a measure of how close the event of interest is to occur, called the “score function”. The main difficulty is that the optimal score function is the committor function which is exactly the quantity to be computed. Therefore, it is very natural to consider an iterative procedure where the data produced by the algorithm is used to improve the score function, which in turn improves the algorithm, and so on.

In this presentation, we propose a data-driven approach for computing the committor function, based on a Markov chain approximation of the dynamics of the system (the analogue method). We first illustrate this approach for a paradigmatic toy model of multistability for atmospheric dynamics with six variables (the Charney-Devore model). Secondly, we apply this methodology to data generated from a climate model, in order to study and predict the occurrence of extreme heat waves. In both cases, we show that it is possible to obtain fairly precise estimates of the committor function, even when few observations are available.

In the second part of the talk, we show the advantage of coupling the analogue Markov chain with a rare event algorithm. Indeed, the committor learned with the analogue Markov chain can be used as a score function performing better than user-defined score functions, as we show for the Charney-Devore model. 

This new approach is promising for studying rare events in complex dynamics: the rare events can be simulated with a minimal prior knowledge and the results are much more precise than those obtained with a user-designed score function.

How to cite: Lucente, D., Rolland, J., Herbert, C., and Bouchet, F.: Advances in rare event simulations using data-based estimation of committor functions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4021, https://doi.org/10.5194/egusphere-egu22-4021, 2022.

The Indian Summer Monsoon (ISM) and the East Asian Summer monsoon (EASM) are two integral components of the Asian Summer Monsoon system, largely influencing the agro-based economy of the densely populated southern and eastern parts of Asia. In our study, we use a complex network based approach to investigate the spatial coherence of extreme precipitation in the Asian Summer Monsoon region and gain a deep insight into the complex nature of the interaction between the ISM and the EASM. We identify two dominant modes of ISM-EASM interaction – (a) a southern mode connecting onset of the ISM over the Arabian Sea and southern India in June to the onset of Meiyu over south-eastern China, i.e., lower and middle reaches of the Yangtze river valley, and (b) a northern mode relating the occurrence and intensity of rainfall over the northern and central parts of India to that in northern China during July. Through determination of specific times of high synchronization of extreme precipitation, we distinctly identify the particular large-scale atmospheric circulation and moisture transport patterns associated with each mode. Thereafter, we investigate the role of the different components of the tropical intraseasonal oscillations, such as the Madden-Julian Oscillation and the boreal summer intraseasonal oscillation, in the intraseasonal variability of the relationship between the ISM and the EASM.

This work is funded by the CAFE project which has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813844.

How to cite: Gupta, S., Su, Z., Boers, N., Kurths, J., Marwan, N., and Pappenberger, F.: Interrelation between the Indian and East Asian Summer Monsoon: A complex network-based approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8626, https://doi.org/10.5194/egusphere-egu22-8626, 2022.

Under the ongoing climate change, extreme weather events are becoming more prolonged, intense, and frequent; and this trend is expected to continue in a future warmer climate. Several studies have found that the synoptic atmospheric circulation at the time of the event is the main contributing factor in most cases. Moreover, they are shaped by slower processes, including sea-surface temperature and soil moisture, in turn influenced by the history of preceding weather patterns, and by the background climate. The separation of influencing components is exploited by the storyline approach, where an atmosphere model is nudged toward the observed dynamics using different climate boundary conditions. Thus, the storyline approach focuses on the less uncertain thermodynamic influence of climate on extreme events, disregarding the somewhat controversial dynamical changes. This approach provides a very efficient way of making the impacts of climate change more tangible to experts and non-experts alike as events fresh in the people's memory are reproduced in different plausible climates with just moderate computational resources.

Spectral nudging experiments have been run with two coupled climate models, AWI-CM-1 and AWI-CM-3. In these simulations, the large-scale free-troposphere dynamics are constrained toward ERA5 data and the model is run for different boundary conditions. Here, the ocean and sea-ice state are consistently simulated, unlike previous studies which employed atmosphere-only models. Our setups reasonably reproduce daily to seasonal observed anomalies of relevant unconstrained parameters, including near-surface temperature, soil moisture or cloud cover. In particular, our configurations showed satisfactory skills in reproducing two different extreme events: the July 2019 European heat wave, and the July 2021 European extreme rainfall. Therefore, this methodology has been applied to study several extreme events in different climates. To do so, nudged simulations are branched off CMIP6 historical and scenario simulations of the same model. For the particular July 2021 extreme rainfall event, we have run five ensemble members for AWI-CM-1-1-MR for dynamical conditions from 1st January 2017 to 31st July 2021 in pre-industrial, present-day, +2K, and +4K climates. These simulations are complemented with similar experiments for AWI-CM-3. 

The most outstanding finding of these studies is a global warming amplification associated with some events, which exacerbates their exceptionality, especially in a high emission scenario.

How to cite: Sánchez Benítez, A., Jung, T., Athanase, M., Pithan, F., and Goessling, H.: Storylines of past and plausible future climates for recent extreme weather events with coupled climate models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11389, https://doi.org/10.5194/egusphere-egu22-11389, 2022.