Past Extreme Events Research Articles

“They just won't listen”—The role of blame in narratives of past extreme weather events for anticipating future crisis

AbstractThe phase before an extreme weather event is crucial for the actual reaction to the impacts of such an event. In this phase, professionals in the field of civil protection and emergency management anticipate the intensity and impact of the event and use these expectations for action. We argue that anticipation is—beyond others—shaped by the organizations’ shared narratives of past crisis that resulted from extreme weather events. The findings focus on the frame of ‘blame’ in the narration and are based on two fields of study, road maintenance services and forest fire control. Qualitative group discussions and semistructured interviews show two very different views on blame depending on the organization: human factors and fate. This contrast can be traced back to the character of the weather events itself, but also with the self‐image of the organization and perceived external expectations. Depending on the narrative plot and threshold of the event, narratives can affect and alter practices of anticipation through narrations of renewal. Findings contribute to the understanding of organizational sensemaking through narratives of blame and consequences.

Interannual Variability of Winter Rainfall in Upper Myanmar

Upper Myanmar region, roughly located between 21° 00' N and 28° 30' N latitude and 92° 10' E and 101° 11' E longitude, is the place where the winter cold season contributes ~2% of the annual total rainfall. The rainfall associated with Western disturbances is small in quantum but veritably important for the cold season crops, maintaining the glaciers over the Putao region, hydropower generation for the whole country and hazard of Jade mining of the Upper Myanmar area. This study aims to find interannual variability and related ocean-atmospheric pattern link with Upper Myanmar cold season rainfall by using great-resolution reanalysis data (ERA5) during 1990-2020. Correlation analysis to test the validation of ERA5 gridded data with the observed data from 25 stations across Myanmar, showed a strong correlation value in the same period that enough reliable for best analysis results. An anomalous anticyclonic (cyclonic) circulation persists over the southern part of the Bay of Bengal and South China sea during wet (dry) years. Also, the warming over the Indian Ocean and the cooling over the Tibetan plateau region correspond to south-north transport of moisture, ensuing in positive rainfall anomalies over the study region during winter. The wide patches of strong negative (positive) correlation are found over the Pacific Ocean, the Atlantic Ocean, Mediterranean Sea (MED), Arabian Sea (ARS), and Red Sea (RED) during wet (dry) years. The link implies that NPO, SPO, and MED have an impact on the winter rainfall inter-annual variability. In addition, the cooling (warming) over the Indochina and western Pacific regions influences the Hadley and Walker circulation bringing above (below) normal rainfall, respectively, over Upper Myanmar. The reply of indices (PO, MED, NINO3.4, IOD, and WDs) on winter rainfall, necessary to further investigation. The complete analysis of winter rainfall aids in the understanding of past extreme events as well as the forecasting and monitoring of drought and floods in Upper Myanmar.

Blasts from the Past: Reimagining Historical Storms with Model Simulations to Modernize Dam Safety and Flood Risk Assessment

Abstract Accurate estimation of the potential “upper limit” for extreme precipitation is critical for dam safety and water resources management, as dam failures pose significant risks to life and property. Methods used to estimate the theoretical upper limit of precipitation are often outdated and in need of updating. The rarity of extreme events means that old storms with limited observational data are often used to define the upper bound of precipitation. Observations of many important old storms are limited in spatial and temporal coverage, and sometimes of dubious quality. This reduces confidence in flood hazard assessments used in dam safety evaluations and leads to unknown or uncertain societal risk. This paper describes a method for generating and applying ensembles of high-resolution, state-of-the-art numerical model simulations of historical past extreme precipitation events to meet contemporary stakeholder needs. The method was designed as part of a research-to-application-focused partnership project to update state dam safety rules in Colorado and New Mexico. The results demonstrated multiple stakeholder and user benefits that were applied directly into storm analyses utilized for extreme rainfall estimation, and diagnostics were developed and ultimately used to update Colorado state dam safety rules, officially passed in January 2020. We discuss how what started as a prototype research foray to meet a specific user need may ultimately inform wider adoption of numerical simulations for water resources risk assessment, and how the historical event downscaling method performed offers near-term, implementable improvements to current dam safety flood risk estimates that can better serve society today.

Which consequences matter in risk analysis and disaster assessment?

Extreme events (like earthquakes, hurricanes, wildfires) can create significant physical damage to structures and infrastructure, downtime and business interruptions, economic losses, and casualties. The assessment of the consequences of past extreme events and the prediction of the consequences of future extreme events has typically focused on these types of consequences. However, the consequences of extreme events typically exceed these more immediately evident consequences. The societal consequences are complex and multi-faceted, affecting financial, economic, and physical aspects of individual well-being such as psychological trauma, missed work and school opportunities. Yet due to restrictions on time and resources, not every possible consequence of an extreme event can be included in risk analysis or impact analysis. To assess the societal impact of extreme events, it is critical to first determine which consequences should be considered (measured for disasters and predicted for hazards.) This paper develops a comprehensive list of which consequences need to be considered. We provide a theoretical justification for the list by adopting a capability approach for extreme event consequences. The list of consequences is meant to go beyond the traditional metrics of infrastructure damage and downtime. We show how the developed list incorporates the diverse insights of recent work expanding the consequences of extreme events. The proposed list is general and can be used within different assessment approaches.

Localized health monitoring for seismic resilience quantification and safety evaluation of smart structures

Natural hazards such as earthquakes, hurricanes, and floods cause billions of dollars of economic loss and claim thousands of lives every year. Researchers have proposed various tools and techniques to evaluate, manage, and mitigate seismic risk and improve resilience. Nonetheless, given the uncertainties involved, accurate system assessment requires real-time data on structural health and performance which can be attained through structural health monitoring (SHM) systems. This paper integrates component-based resilience quantification methods and SHM techniques to present a new probabilistic framework for seismic structural system evaluation and decision analysis. A trilateral framework is introduced which (1) uses the data obtained from a localized wireless sensor network to detect and locate damage, (2) develops component-based functionality curves to quantify the seismic resilience of the structure, and (3) makes post-quake rapid decisions based on a multi-criteria safety evaluation method. A nonlinear autoregressive exogenous (ARX) model is used to identify structural response and a statistical damage-sensitive coefficient is used to detect, locate, and measure damage in the system. Minor damages due to corrosion and major damages due to past extreme events are studied in the functionality analysis. Two groups of archetype building structures located in a high seismic region are studied, namely steel diagrid and special reinforced concrete structures. The results show that maximum absolute floor acceleration is the most accurate demand parameter for locating damage whereas maximum floor displacement and interstory drift ratio can effectively detect and measure damages.

Human activities disturb lake-sediment records of past flood frequencies

30th AnniversAry Flood frequencies as a proxy of past extreme precipitation events In the current context of global climate change, predicting the evolution of precipitation is particularly challenging: an increase of extreme events is expected globally due to the capacity of a warmer atmosphere to hold more water, although regional trends may differ (IPCC 2012). Assessing this requires the acquisition of long-term hydrological datasets (Wilhelm et al. 2019). As flood occurrence and magnitude are linked to precipitation-regime fluctuation through time, the establishment of regional flood chronicles from natural archives could be a key to evaluate the evolution of precipitation regimes on emerged land (PAGES Floods Working Group 2017).

Study of the Impact of Past Extreme Solar Events on the Modern Air Traffic

AbstractThe ancient solar energetic particle (SEP) events of 774/775 CE and 993/994 CE were characterized thanks to radionuclide productions stored in environmental archives as ice cores or tree rings. Primary cosmic ray spectra deduced from these cosmogenic isotope data indicate that the impact of these extreme SEP events would have been much more significant than any of the ones observed during the modern era. However, the impact of these should be studied more accurately in the framework of the ambient dose equivalent impacting aircrew and passengers in the air traffic context by considering physical parameters such as time profile or anisotropy properties. In this study, the impact that 774/775 CE and 993/994 CE past extreme SEP events could have had on modern air traffic is discussed. Possible event spectra for these ancient events are derived from the spectra ground‐level enhancement (GLE) 5 and GLE 69, which have been observed during the modern era and have been widely studied/characterized using measurements. The investigations include the impact of the SEP activity on ambient dose equivalent, including detailed analyses considering route, airplane characteristics (departure, arrival, continent, airplane type), and the time occurrence of the SEP event. Statistical analyses show that additional dose levels can reach values on the order of 70 mSv, which is absolutely significant considering the current air traffic recommendations. The orders of magnitude of the ambient dose equivalent induced during past extreme SEP events raises a number of issues, both for aircrews and for avionics hardware. This study demonstrates that simulations can be useful for the evaluation of risks in case of extreme SEP events.

Tracking precipitation patterns across a western U.S. metropolitan area using volunteer observers: RainLog.Org

AbstractThe southwestern United States experiences extreme hydroclimatic variability, including intense but localized monsoon thunderstorms, tropical storms, and winter storms, resulting in complex and variable patterns of precipitation over space and time. Official gauges associated with long‐term monitoring networks are sparsely distributed throughout the region and are unable to capture the spatial complexity and variability of these precipitation patterns. The RainLog program, a volunteer precipitation monitoring program, was started in southern Arizona in 2005 to leverage enthusiasm among non‐scientists around weather, water, and climate to address the gaps in official monitoring networks. An examination of the portion of the dataset that spans the Tucson metropolitan area illustrates the opportunities and challenges in using volunteer data to track precipitation. We compare near‐complete records to an official observation to highlight how the broader RainLog network supports characterizing hydroclimatic variability over the period of record. We also examine several case study events drawn from metrics of network variability that represent different forms of hydroclimatic extremes. We find that in most cases the RainLog network captures a range of precipitation values that were notably different than the single value recorded at the official observing site, adding substantial value in recording and reconstructing past extreme precipitation events. This work highlights how volunteer citizen science precipitation monitoring networks can provide critical data for tracking precipitation variability and changes, although are only one complementary piece of coherent, long‐term hydroclimatic monitoring.

Tail Granger causalities and where to find them: Extreme risk spillovers vs spurious linkages

Identifying risk spillovers in financial markets is of great importance for assessing systemic risk and portfolio management. Granger causality in tail (or in risk) tests whether past extreme events of a time series help predicting future extreme events of another time series. The topology and connectedness of networks built with Granger causality in tail can be used to measure systemic risk and to identify risk transmitters. Here we introduce a novel test of Granger causality in tail which adopts the likelihood ratio statistic and is based on the multivariate generalization of a discrete autoregressive process for binary time series describing the sequence of extreme events of the underlying price dynamics. The proposed test has very good size and power in finite samples, especially for large sample size, allows inferring the correct time scale at which the causal interaction takes place, and it is flexible enough for multivariate extension when more than two time series are considered in order to decrease false detections as spurious effect of neglected variables. An extensive simulation study shows the performances of the proposed method with a large variety of data generating processes and it introduces also the comparison with the test of Granger causality in tail by Hong et al. (2009). We report both advantages and drawbacks of the different approaches, pointing out some crucial aspects related to the false detections of Granger causality for tail events. An empirical application to high frequency data of a portfolio of US stocks highlights the merits of our novel approach.

K-Gaps: a novel technique for clustering incomplete climatological time series

In this paper, we show a new clustering technique (k-gaps) aiming to generate a robust regionalization using sparse climate datasets with incomplete information in space and time. Hence, this method provides a new approach to cluster time series of different temporal lengths, using most of the information contained in heterogeneous sets of climate records that, otherwise, would be eliminated during data homogenization procedures. The robustness of the method has been validated with different synthetic datasets, demonstrating that k-gaps performs well with sample-starved datasets and missing climate information for at least 55% of the study period. We show that the algorithm is able to generate a climatically consistent regionalization based on temperature observations similar to those obtained with complete time series, outperforming other clustering methodologies developed to work with fragmentary information. k-Gaps clusters can therefore provide a useful framework for the study of long-term climate trends and the detection of past extreme events at regional scales.

Microbial Abundance and Enzyme Activity Patterns: Response to Changing Environmental Characteristics along a Transect in Kongsfjorden (Svalbard Islands)

Svalbard archipelago is experiencing the effects of climate changes (i.e., glaciers’ thickness reduction and glacier front retreat), but how ice melting affects water biogeochemistry is still unknown. Microbial communities often act as environmental sentinels, modulating their distribution and activity in response to environmental variability. To assess microbial response to climate warming, within the ARctic: present Climatic change and pAst extreme events (ARCA) project, a survey was carried out along a transect in Konsfjorden from off-shore stations towards the Kronebreen glacier. Total bacterial abundance and the fraction of actively respiring cells (labelled by cyanotetrazolium chloride, CTC), cultivable heterotrophic bacterial abundance, and extracellular enzymatic activities (leucine aminopeptidase (LAP), beta-glucosidase (GLU), and alkaline phosphatase (AP)) were measured. In addition, water temperature, salinity, dissolved oxygen, turbidity, total suspended matter (TSM), particulate and chromophoric dissolved organic matter (CDOM), chlorophyll-a (Chl-a), and inorganic compounds were determined, in order to evaluate whether variations in microbial abundance and metabolism were related with changes in environmental variables. Colder waters at surface (3.5–5 m) depths and increased turbidity, TSM, and inorganic compounds found at some hydrological stations close to the glacier were signals of ice melting. CDOM absorption slope values (275–295 nm) varied from 0.0077 to 0.0109 nm−1, and total bacterial cell count and cultivable heterotrophic bacterial abundance were in the order of 106 cells/mL and 103 colony forming units/mL, respectively. Enzymatic rates <1.78, 1.25, and 0.25 nmol/L/h were recorded for AP, LAP, and GLU, respectively. Inorganic compounds, TSM, and turbidity correlated inversely with temperature; AP was significantly related with CDOM absorption spectra and heterotrophic bacteria (r = 0.59, 0.71, p < 0.05); and LAP with Chl-a, Particulate Organic Carbon (POC) and Particulate Organic Nitrogen (PON) (0.97, 0.780, 0.734, p < 0.01), suggesting that fresh material from ice melting stimulated the metabolism of the cultivable fraction.

Quantifying processes contributing to marine hazards to inform coastal climate resilience assessments, demonstrated for the Caribbean Sea

Abstract. Scientific evidence is critical to underpin the decisions associated with shoreline management, to build climate-resilient communities and infrastructure. We explore the role of waves, storm surges and sea level rise for the Caribbean region with a focus on coastal impacts in the eastern Caribbean islands. We simulate past extreme events and a worst-case scenario, modelling the storm surges and waves, suggesting a storm surge might reach 1.5 m, depending on the underwater topography. Coastal wave heights of up to 12 m offshore and up to 5 m near the coast of St Vincent are simulated with a regional wave model. We deliver probabilistic sea level projections for 2100, with a low-probability–high-impact estimate of possible sea level rise up to 2.2 m, exceeding the 1.8 m global estimate for the same scenario. We introduce a combined vulnerability index, which allows for a quantitative assessment of relative risk across the region, showing that sea level rise is the most important risk factor everywhere but wave impacts are important on windward coasts, increasing to the north, towards the main hurricane track. Our work provides quantitative evidence for policy-makers, scientists and local communities to actively prepare for and protect against climate change.

Numerical investigation on hydrodynamic load of coastal bridge deck under joint action of solitary wave and wind

Coastal bridges are vulnerable to extreme surges and waves during tsunamis and hurricanes. Many of them have been significantly damaged or destroyed during past extreme weather events, such as Hurricane Katrina in 2005. Although extensive experimental work and numerical simulations have been carried out focusing on identifying the damage mechanisms of coastal bridges impacted by extreme waves, the coastal bridge deck needs to withstand the combined actions of waves and wind. Strong winds can easily deform the water surface and influence how waves impact the coastal bridge deck and the final resultant hydrodynamic load. Hence, there is a strong need for investigating the hydrodynamic characteristics of coastal bridges under the joint action of wind and surge waves. The direct effects of wind on the hydrodynamic load of a bridge deck under the impact of extreme surge waves had not been taken into account in past studies. To fill this knowledge gap, in this paper, a high-resolution numerical wave-wind tank is established by solving the governing equations of two-phase incompressible flow using the finite volume method. The hydrodynamic load of coastal bridge deck under joint action of solitary wave and wind are numerically investigated by considering the effects of several prominent factors, i.e. wind speed, wave height, submersion depth, and water depth. The results show that strong wind can greatly enhance the impacting intensity of solitary waves on bridge deck, resulting in greater horizontal and vertical hydrodynamic loads. It is believed that findings of this study can further enhance our understanding on damage mechanism of coastal bridge decks during hurricanes.

Adaptive Infrastructure To Mitigate Future Climate Risk: Building Upon Our Geotechnical Engineering Heritage

It’s time to recognize that past extreme events may no longer serve as reliable proxies for the future. Current infrastructure design concepts rely on historical events, assuming temporal stationarity (i.e., statistics of past extremes do not change significantly over time). However, global warming and land use change have increased the risk of extreme events, including floods, ocean water levels, drought, extreme precipitation, and the associated damage to critical infrastructure, such as dams, highways, and storm water and sewer systems. Experts have observed an increasing trend in severity and frequency of extreme events, which introduces a new level of uncertainty that should be included when planning, designing, and operating infrastructure systems.

Tail Granger Causalities and Where to Find Them: Extreme Risk Spillovers vs Spurious Linkages

Identifying risk spillovers in financial markets is of great importance for assessing systemic risk and portfolio management. Granger causality in tail (or in risk) tests whether past extreme events of a time series help predicting future extreme events of another time series. The topology and connectedness of networks built with Granger causality in tail can be used to measure systemic risk and to identify risk transmitters. Here we introduce a novel test of Granger causality in tail which adopts the likelihood ratio statistic and is based on the multivariate generalization of a discrete autoregressive process for binary time series describing the sequence of extreme events of the underlying price dynamics. The proposed test has very good size and power in finite samples, especially for large sample size, allows inferring the correct time scale at which the causal interaction takes place, and it is flexible enough for multivariate extension when more than two time series are considered in order to decrease false detections as spurious effect of neglected variables. An extensive simulation study shows the performances of the proposed method with a large variety of data generating processes and it introduces also the comparison with the test of Granger causality in tail by [Hong et al., 2009]. We report both advantages and drawbacks of the different approaches, pointing out some crucial aspects related to the false detections of Granger causality for tail events. An empirical application to high frequency data of a portfolio of US stocks highlights the merits of our novel approach.

Temporal approaches of historical extreme storm events based on sedimentological archives

This paper presents the benefits of multiplying environmental indicators to better understand the impacts of past storm events on the environment. It aims to describe the methodological approaches used to reconstruct past extreme events from washover deposits, at the three main temporal scales used in scientific bibliography: i) the long timescale (Holocene, since 12 000 years BP), ii) the meso timescale (for the last millenary) and iii) the short timescale (Anthropocene, for the last centuries). This methodology is based on a “multiproxy” analysis using sedimentology, geochemistry and various methods of isotope dating. Linking these methods with other disciplines such as history, archaeology and meteorology leads us to confirm with great certainty the existence of these extreme events, and to expose their impacts on the environment and on past coastal societies. These different approaches enable us to enhance and refine our knowledge of coastal hazards, but also to apprehend possible storm influences in the context of climate change.

Meteorological conditions leading to the 2015 Salgar flash flood: lessons for vulnerable regions in tropical complex terrain

Abstract. Flash floods are a recurrent hazard for many developing Latin American regions due to their complex mountainous terrain and the rainfall characteristics in the tropics. These regions often lack the timely and high-quality information needed to assess, in real time, the threats to the vulnerable communities due to extreme hydrometeorological events. The systematic assessment of past extreme events allows us to improve our prediction capabilities of flash floods. In May 2015, a flash flood in the La Liboriana basin, municipality of Salgar, Colombia, caused more than 100 casualties and significant infrastructure damage. Despite the data scarcity, the climatological aspects, meteorological conditions, and first-order hydrometeorological mechanisms associated with the La Liboriana flash flood, including orographic intensification and the spatial distribution of the rainfall intensity relative to the basin's geomorphological features, are studied using precipitation information obtained using a weather radar quantitative precipitation estimation (QPE) technique, as well as from satellite products, in situ rain gauges from neighboring basins, quantitative precipitation forecasts (QPFs) from an operational Weather Research and Forecasting Model (WRF) application, and data from reanalysis products. The La Liboriana flash flood took place during a period with negative precipitation anomalies over most of the country as a result of an El Niño event. However, during May 2015, moist easterly flow towards the upper part of La Liboriana caused significant orographic rainfall enhancement. The overall evidence shows an important role of successive precipitation events in a relatively short period and of orography in the spatial distribution of rainfall and its intensification as convective cores approached the steepest topography. There were three consecutive events generating significant rainfall within the La Liboriana basin, and no single precipitation event was exceptionally large enough to generate the flash flood, but rather the combined role of precedent rainfall and the extreme hourly precipitation triggered the event. The results point to key lessons for improving local risk reduction strategies in vulnerable regions with complex terrain.

Unraveling extreme events from deep water cores of the south Caspian Sea

South Caspian Sea sub-basin, as the deepest part of the Caspian Sea (CS) remained as land-locked basin even during extreme sea level fall that most part of the CS desiccated. Therefore, bottom sediments of the south CS continuously recorded many past intra-basinal and extra-basinal events. In the current research we have used four short cores (<2 m) from deep waters of the south CS (300–800 m) to unravel past extreme events based on the sedimentological and geochemical analysis. Presence of coarse grained sediment laminae in the deep basin represents frequent slope failure that transported materials from lower shelf. XRF core scanning along with Magnetic Susceptibility measurements showed multiple changes along the cores. Elements incorporating in biological activities (Ca, Sr) have sharp contrast with lithogenic elements (Zr, Ti) mainly during rapid environmental changes. The deepest core has significant changes in the basal part that covers certainly Younger Dryas or even older sediments. Material influx into the deep basin of the south CS demonstrate both basinal extreme events as turbidite and mass wasting as well as catchment basin events e.g. river avulsion that caused changes in sediment properties.

Pluridisciplinary analysis and multi-archive reconstruction of paleofloods: Societal demand, challenges and progress

Abstract Floods are one of the gravest natural hazards for societies, worsened by population growth, unchecked development, and climate change. From a Global Change perspective, past extreme events merit particular interest because they can be linked to wider climate and environmental changes, introduce perturbations. During the last decade, knowledge of long-term flood frequency and magnitude has been improved by extracting data from different types of archive. But, despite advances in dating methods, proxies and statistical techniques and efforts to identify atmospheric drivers, some fundamental questions remain unresolved. The Special Issue entitled “Pluridisciplinary analysis and multi-archive reconstruction of paleofloods” in the journal Global and Planetary Change addresses these uncertainties and complexities by assembling a selection of studies, which were first presented at the Past Climate Changes (PAGES) Open Scientific Meeting held at Zaragoza in 2017. In this introductory paper, the guest editors outline the 17 research contributions and meta-data from the 17 paleoflood studies were systematically analyzed in terms of i) geographical distribution; ii) methodologies applied; iii) types of archives; iii) numbers of flood series compiled and iv) spatial and temporal resolution of paleoflood data. The data indicate that paleoflood studies focused on fluvial depositional environments show a higher rate of integration with other types of paleoflood archive (mean of 4.5 types of archive) than studies focused on documentary sources (mean of 3.5) and lake sediments (mean of 2.4). We suggest that this strategy of archive integration has been adapted to effectively compensate for the higher uncertainties of fluvial deposition in floodplains. Statistical processing of the meta-data shows quantitative associations between specific types of flood archive and offers a solid platform for designing the optimal approach for multi-archive paleoflood research. A qualitative review and visual comparison of the 17 paleoflood series shows some consistent trends and breaks but also notable differences within and between regions. While a trend of increased flooding since 4-5 ka BP is evident, the lack of synchronicity between breaks and the coeval increases and decreases in fluvial activity is manifest. The majority of studies in the Special Issue do denote the 19th century – including the youngest cool climate pulses during the Little Ice Age – as a particularly flood-rich period. It is more difficult to assess the 20th century because of social changes, population growth and extensive river modification. Despite the mentioned uncertainties, 10 of 14 papers do not record the 20th century as an exceptional flood period. Assessing the effects of human impact on paleoflood calendars and disentangling anthropogenic from natural drivers are major challenges in integrated paleoflood analysis. It is concluded that the interpretation of flood series is complex as landscapes and flood drivers are heterogeneous and systems show different sensitivities to flood control and drivers. Thus, the study of past floods, from historical and natural archives, is challenging but also offers unparalleled opportunities to document low-frequency, large-magnitude flood events, which occurred under a broad range of climate and/or environmental scenarios, and, probably, the only way to reconstruct robust paleoflood series.

Anticipating cascading effects of extreme precipitation with pathway schemes - Three case studies from Europe

Extreme precipitation events with high local precipitation intensities, heavy snowfall or extensive freezing rain can have devastating impacts on society and economy. Not only is the quantitative forecast of such events sometimes difficult and associated with large uncertainties, also are the potential consequences highly complex and challenging to predict. It is thus a demanding task to anticipate or nowcast the impacts of extreme precipitation, even more so in situations where human lives or critical infrastructure might be at risk.In recent years, the term “cascading effects” has been increasingly used to describe events in which an initial trigger leads to a sequence of consequences with significant magnitude. We here analyze three examples for different precipitation types where the initial triggering event generated a cascade of events and impacts, namely a convective precipitation event in the Swiss Prealps, a freezing rain in Slovenia, and a heavy snowfall episode in Catalonia. With the aim to improve process understanding of complex precipitation-triggered events, we assess the prediction of the selected events and analyze the cascading effects that caused diverse impacts. To this end, we use a framework of cascading effects which should ultimately allow the development of a better design risk assessment and management strategies.Our findings confirm that damage of extreme precipitation events is clearly related to the knowledge of potential cascading effects. Major challenges of predicting cascading effects are the high complexity, the interdependencies and the increasing uncertainty along the cascade. We propose a framework for cascading effects including two approaches: (i) one to analyze cascading effects during past extreme precipitation events, which then serves as a basis for a (ii) more generalized approach to increase the preparedness level of operational services before and during future extreme precipitation events and to anticipate potential cascading effects of extreme precipitation. Both approaches are based on pathway schemes that can be used in addition to numerical models or hazard maps to analyze and predict potential cascading effects, but also as training tools.