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High electric fields that occur in thunderstorm clouds in the Earth’s atmosphere might accelerate energetic charged particles produced by cosmic rays. Such energetic particles, especially electrons, can cause additional ionization as they are multiplied and thus form avalanche of relativistic electrons. These relativistic electrons emit Bremsstrahlung in the X- or gamma-ray spectral ranges as they lose their kinetic energy via collisions. Thunderstorm ground enhancements (TGEs) of secondary cosmic ray fluxes recorded at the top of a sharp rocky mountain of Lomnický Štít in High Tatras (2634 m, Slovak Republic) are compared with simultaneous measurements of electric field at the mountain top and on its slope at the observatory of Skalnaté Pleso (1780 m). Results of measurements performed from May to September in 2017 and from May to October in 2018 are presented. The cosmic ray flux is measured by Space Environment Viewing and Analysis Network (SEVAN) and by neutron monitor with 1-s resolution. The TGEs that persisted usually several minutes were mainly detected in the SEVAN channel 1 which has the lowest energy threshold, about 7–8 MeV. A statistical analysis shows that these enhancements usually occurred (not only) during large values of vertical, upward-pointing electric fields measured just above the detector. It is shown that the measurement of electric field at Skalnaté Pleso, distant about 1.86 km from the mountain top is also partly correlated with the enhancements and can provide additional useful information about the distance or dimension of charge structure and dynamics of electric field, especially on short time scales. The enhancements usually did not exceed several tens of percent of background values. However, events that exceeded the background values several times were also recorded. The most extreme event exceeded the background values about 215 times. This event was also detected by other SEVAN channels and by the neutron monitor (~ 130% enhancement), which indicates a possibility of photonuclear reactions. The enhancements were often terminated by a nearby lightning.

Sun-induced fluorescence in the far-red region (SIF) is increasingly used as a remote and proximal-sensing tool capable of tracking vegetation gross primary production (GPP). However, the use of SIF to probe changes in GPP is challenged during extreme climatic events, such as heatwaves. Here, we examined how the 2018 European heatwave (HW) affected the GPP-SIF relationship in evergreen broadleaved trees with a relatively invariant canopy structure. To do so, we combined canopy-scale SIF measurements, GPP estimated from an eddy covariance tower, and active pulse amplitude modulation fluorescence. The HW caused an inversion of the photosynthesis-fluorescence relationship at both the canopy and leaf scales. The highly nonlinear relationship was strongly shaped by nonphotochemical quenching (NPQ), that is, a dissipation mechanism to protect from the adverse effects of high light intensity. During the extreme heat stress, plants experienced a saturation of NPQ, causing a change in the allocation of energy dissipation pathways towards SIF. Our results show the complex modulation of the NPQ-SIF-GPP relationship at an extreme level of heat stress, which is not completely represented in state-of-the-art coupled radiative transfer and photosynthesis models.

International audience; Nonparametric resampling methods such as Direct Sampling are powerful tools to simulate new datasets preserving important data features such as spatial patterns from observed datasets while using only minimal assumptions. However, such methods cannot generate extreme events beyond the observed range of data values. We here propose using tools from extreme value theory for stochastic processes to extrapolate observed data towards yet unobserved high quantiles. Original data are first enriched with new values in the tail region, and then classical resampling algorithms are applied to enriched data. In a first approach to enrichment that we label "naive resampling'', we generate an independent sample of the marginal distribution while keeping the rank order of the observed data. We point out inaccuracies of this approach around the most extreme values, and therefore develop a second approach that works for datasets with many replicates. It is based on the asymptotic representation of extreme events through two stochastically independent components: a magnitude variable, and a profile field describing spatial variation. To generate enriched data, we fix a target range of return levels of the magnitude variable, and we resample magnitudes constrained to this range. We then use the second approach to generate heatwave scenarios of yet unobserved magnitude over France, based on daily temperature reanalysis training data for the years 2010 to 2016.

The increasing science and society requests for ocean monitoring from global to regional and local scales, the need for integration and convergence into a globally consistent ocean observing system as well as the need for improvement of access to information are now internationally recognized goals to progress toward the sustainable management of a healthy ocean. To respond to these challenges at regional level, the Balearic Islands Coastal Observing and Forecasting System (SOCIB) is developing a comprehensive set of ocean indicators in the Mediterranean Sea and around the Balearic Islands, key environments that are strongly affected by climate change and human pressure. This new SOCIB value-added product addresses the sub-regional ocean variability from daily (events) to interannual/decadal (climate) scales. A user-friendly interface has been implemented to monitor, visualize and communicate ocean information that is relevant for a wide range of sectors, applications and regional end-users. These sub-regional indicators allowed us to detect specific events in real time. Remarkable events and features identified include marine heat waves, atmospheric storm, extreme river discharge, mesoscale eddy, deep convection among others, all of them being oceanic phenomena that directly impact the ocean circulation and marine ecosystems. The long-term variations, in response to climate change, are also addressed highlighting and quantifying trends in physical and biogeochemical components of the ocean as well as sub-regional differences. At both (sub-) regional, national and international levels, a society-aligned science will have stronger impact on policy decision-makings and will support society to implement specific actions to address worldwide environmental challenges., Part of this work was supported by the JERICO-S3 and EuroSea projects. These projects have received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement Nos. 871153 and 862626, respectively.

International audience; For many environmental processes, recent studies have shown that the dependence strength is decreasing when quantile levels increase. This implies that the popular max-stable models are inadequate to capture the rate of joint tail decay, and to estimate joint extremal probabilities beyond observed levels. We here develop a more flexible modeling framework based on the class of max-infinitely divisible processes, which extend max-stable processes while retaining dependence properties that are natural for maxima. We propose two parametric constructions for max-infinitely divisible models, which relax the max-stability property but remain close to some popular max-stable models obtained as special cases. The first model considers maxima over a finite, random number of independent observations, while the second model generalizes the spectral representation of max-stable processes. Inference is performed using a pairwise likelihood. We illustrate the benefits of our new modeling framework on Dutch wind gust maxima calculated over different time units. Results strongly suggest that our proposed models outperform other natural models, such as the Student-t copula process and its max-stable limit, even for large block sizes.

Disastrous bushfires during the last months of 2019 and January 2020 affected Australia, raising the question to what extent the risk of these fires was exacerbated by anthropogenic climate change. To answer the question for southeastern Australia, where fires were particularly severe, affecting people and ecosystems, we use a physically based index of fire weather, the Fire Weather Index; long-Term observations of heat and drought; and 11 large ensembles of state-of-The-Art climate models. We find large trends in the Fire Weather Index in the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis (ERA5) since 1979 and a smaller but significant increase by at least 30 % in the models. Therefore, we find that climate change has induced a higher weather-induced risk of such an extreme fire season. This trend is mainly driven by the increase of temperature extremes. In agreement with previous analyses we find that heat extremes have become more likely by at least a factor of 2 due to the long-Term warming trend. However, current climate models overestimate variability and tend to underestimate the long-Term trend in these extremes, so the true change in the likelihood of extreme heat could be larger, suggesting that the attribution of the increased fire weather risk is a conservative estimate. We do not find an attributable trend in either extreme annual drought or the driest month of the fire season, September-February. The observations, however, show a weak drying trend in the annual mean. For the 2019/20 season more than half of the July-December drought was driven by record excursions of the Indian Ocean Dipole and Southern Annular Mode, factors which are included in the analysis here. The study reveals the complexity of the 2019/20 bushfire event, with some but not all drivers showing an imprint of anthropogenic climate change. Finally, the study concludes with a qualitative review of various vulnerability and exposure factors that each play a role, along with the hazard in increasing or decreasing the overall impact of the bushfires.

The Songhua River Basin is one of the main grain-producing areas in China, and local climate change has had a direct impact on grain production during the past several decades. This study focused on changes in mean and extreme climate conditions in the Songhua River Basin during the period 1961–2014. We founded that the precipitation decreased slightly over most of the basin; however, an increasing occurrence of extreme events was detected in the northern and eastern parts of the basin, especially for the number of very wet days and, correspondingly, how much those days contributed to total precipitation. By contrast, the mean, maximum and minimum temperature values between 1961 and 2014 showed statistically significant positive trends in almost all regions of the basin. The rate of change was greater for minimum temperature than maximum temperature, which resulted in a significant increasing trend for the number of warm nights and an overall decreasing trend in the annual mean diurnal temperature range. Generally, the magnitudes of changes in temperature were more remarkable than the magnitudes of changes in precipitation over the Songhua River Basin. If we take both precipitation and temperature changes into account, the areas sensitive to climate change during the last five decades were in the southern and central parts of the Songhua River Basin.

Sub-Saharan Africa is among the regions that contribute least to global climate change, yet it is among the most vulnerable to its impacts due to low levels of economic and technological development. The frequency and magnitude of extreme events in the region are rising at a faster rate than the population capacity to deal with the attendant disasters. This paper interrogates some emerging and existing evidence of the potential for extreme weather events to obviate countries’ attainment of the Sustainable Development Goals (SDGs). Whilst previous studies have assessed the vulnerabilities of sub-Saharan African (SSA) countries to extreme weather events on specific sectors, a comprehensive assessment of the implications of these extreme events for attaining the SDGs remains largely untouched. The direct impacts of flooding, extreme heat and drought on five key SDGs – Zero hunger (Goal 2), Good health and well-being (Goal 3), Quality education (Goal 4), Clean water and sanitation (Goal 6) and Sustainable cities and communities (Goal 11) - are assessed in this paper. The remote implications for attaining No poverty (Goal 1) and Gender equality (Goal 5) are further explored. Based on empirical cases from different SSA country contexts, and guided by the SDG targets and indicators, we discuss the main interactions with between extreme weather events and different SDGs, emerging with a framework for the climate change – sustainable development nexus. Such an assessment, with regard to specific national and local case studies, would guide policy formulation and implementation, research and investment towards sustainable development in the region. Integrating disaster risk reduction strategies into national development policies will offer sub-Saharan African countries the opportunity to reduce the impacts of extreme weather events on attaining their targets for sustainable development in fulfilment of Agenda 2030.

Global climate change is expected to further raise the frequency and severity of extreme events, such as droughts. The effects of extreme droughts on trees are difficult to disentangle given the inherent complexity of drought events (frequency, severity, duration, and timing during the growing season). Besides, drought effects might be modulated by trees’ phenotypic variability, which is, in turn, affected by long‐term local selective pressures and management legacies. Here we investigated the magnitude and the temporal changes of tree‐level resilience (i.e., resistance, recovery, and resilience) to extreme droughts. Moreover, we assessed the tree‐, site‐, and drought‐related factors and their interactions driving the tree‐level resilience to extreme droughts. We used a tree‐ring network of the widely distributed Scots pine (Pinus sylvestris) along a 2,800 km latitudinal gradient from southern Spain to northern Germany. We found that the resilience to extreme drought decreased in mid‐elevation and low productivity sites from 1980–1999 to 2000–2011 likely due to more frequent and severe droughts in the later period. Our study showed that the impact of drought on tree‐level resilience was not dependent on its latitudinal location, but rather on the type of sites trees were growing at and on their growth performances (i.e., magnitude and variability of growth) during the predrought period. We found significant interactive effects between drought duration and tree growth prior to drought, suggesting that Scots pine trees with higher magnitude and variability of growth in the long term are more vulnerable to long and severe droughts. Moreover, our results indicate that Scots pine trees that experienced more frequent droughts over the long‐term were less resistant to extreme droughts. We, therefore, conclude that the physiological resilience to extreme droughts might be constrained by their growth prior to drought, and that more frequent and longer drought periods may overstrain their potential for acclimation., We examined tree growth resilience of Scots pine along a 2,800 km latitudinal gradient from southern Spain to north‐eastern Germany using 615 adult trees from 30 different sites. We found that the resilience of Scots pine to extreme drought decreased in mid‐elevation and low productivity sites from 1980–1999 to 2000–2011 due to more frequent and severe droughts in the later period. We showed that the impact of drought on tree‐level resilience was not dependent on its latitudinal location, but rather on the type of sites trees were growing at and on their growth performances during the pre‐drought period.

The susceptibility of coastal environments to shifts in the biogeochemical cycles of carbon and nutrients driven by anthropogenic pressure and climate change is a real challenge for the scientific community. This paper evaluated the effects of an extreme rainfall event over the nutrients and carbonate parameters in two polluted tropical estuaries. Surface water samples were taken seasonally along a salinity gradient in the Capibaribe and Barra de Jangadas estuaries in order to investigate the spatial and seasonal variability of dissolved nutrients, chlorophyll-a, dissolved oxygen, total alkalinity, inorganic carbon, partial pressure of CO2 (pCO2) and CO2 fluxes. The increased riverine influence caused by the fluvial flooding during the extremely rainy season augmented the nitrogen concentrations in the plumes, which also presented reduced salinity, alkalinity and dissolved oxygen values. In the Capibaribe plume it has also shifted the mean CO2 flux value of - 4.01 mmolC m-2 d-1 during the dry season, to a positive mean flux of + 5.7 mmolC m-2 d-1 during the rainy season. Within the estuaries the BOD5,20 and dissolved phosphorus values were higher during the dry season (p

Dans la nuit du 6 au 7 octobre 2014, des cellules orageuses peu mobiles se sont organisées sur le nord montpelliérain et ont déversé jusqu'à 260 mm de pluie en 4 heures. Survenant sur un sol relativement saturé, ces pluies ont provoqué de fortes crues de la Mosson et du Lez. Les inondations ont été particulièrement dommageables dans le village de Grabels, où un lotissement a été submergé par le Rieu Massel (affluent de la Mosson) avec des hauteurs d'eau dans les maisons atteignant 1,5 m, malgré la présence d'un barrage écrêteur de crue en amont du bassin. Dans cet article, nous présentons les résultats du retour d'expérience conduit sur cet événement avec des débits estimés sur 15 sections de petits bassins non jaugés. Ces débits sont ensuite comparés à ceux obtenus lors d'autres retours d'expérience récents, et à ceux estimés par diverses formules régionales. L'inventaire des pluies intenses survenues autour de Montpellier au cours de la période 1970-2014 incite à réviser les normes d'aménagement actuellement en vigueur dans la région, qui paraissent sous-estimer les pluies et les débits de fréquence rare. In the night of 6-7th October 2014, static storm cells stood over the North of Montpellier, and poured up to 260 mm of rain in 4 hours. Due to previous saturation of the soils, this rain caused major floods on the Mosson and Lez watersheds. The biggest damages occurred in Grabels where a part of the city was submerged by the Rieu Massel (a Mosson river tributary). The water level reached up to 1.5 m in some houses despite a flood retention dam upstream. In this paper we present the results of the post flood survey of this event, dealing with 15 peak discharge estimations on ungauged streams. Then we compare these peak discharge to those obtained from other recent post-flood surveys in South of France for the one hand, to those derived from regional formulas on the other hand. The relative frequency of such events during the period 1970-2014 suggests that the estimations of intense rainfalls and critical peak flows are underestimated in Montpellier area, and should be updated.

This is an Accepted Manuscript of an article published by Taylor & Francis in Norsk Geografisk Tidsskrift on 27 Oct 2017, available online: http://www.tandfonline.com/10.1080/00291951.2017.1391876. . Icy surfaces impose challenges for northern societies, wildlife and agriculture. However, there have been relatively few studies of the impacts of anoxic ground ice on non-agricultural plants. During the winter of 2009–2010, an extreme winter warming event led to thick ground-ice layer development in the world’s northernmost botanical garden in Tromsø, in subarctic Norway, due to much rain on warm days interspersed with cold dry days. After ice melt in late spring, the authors assessed plant mortality and tested whether certain growth forms, geographical origins, or terrain features were more vulnerable to stress. They found that mortality was negatively correlated with terrain slope, that cryptophytes were most vulnerable, and that good soil drainage improved all plants’ survival. Vegetation greenness (measured by the Normalized Difference Vegetation Index, NDVI) reached an unprecedented minimum in the summer of 2010 and remained low for two more years. The results suggest that more investigations of the impacts of ground ice are needed to understand better how alpine ecosystems might change with increasing climate change. In conclusion, the study revealed that botanical garden studies may be a valuable supplement to field studies, as plants of different origins could be studied under similar climatic conditions. anoxia, extreme event, NDVI, plant mortality, winter warming

International audience; Globally, trees are increasingly dying from extreme drought, a trend that is expected to increase with climate change. Loss of trees has significant ecological, biophysical, and biogeochemical consequences. In 2011, a record drought caused widespread tree mortality in Texas. Using remotely sensed imagery, we quantified canopy loss during and after the drought across the state at 30-m spatial resolution, from the eastern pine/hardwood forests to the western shrublands, a region that includes the boundaries of many species ranges. Canopy loss observations in ~200 multitemporal fine-scale orthophotos (1-m) were used to train coarser Landsat imagery (30-m) to create 30-m binary statewide canopy loss maps. We found that canopy loss occurred across all major ecoregions of Texas, with an average loss of 9.5%. The drought had the highest impact in post oak woodlands, pinyon-juniper shrublands and Ashe juniper woodlands. Focusing on a 100-km by ~1,000-km transect spanning the State's fivefold east-west precipitation gradient (~1,500 to ~300 mm), we compared spatially explicit 2011 climatic anomalies to our canopy loss maps. Much of the canopy loss occurred in areas that passed specific climatic thresholds: warm season anomalies in mean temperature (+1.6°C) and vapor pressure deficit (VPD, +0.66 kPa), annual percent deviation in precipitation (-38%), and 2011 difference between precipitation and potential evapotranspiration (-1,206 mm). Although similarly low precipitation occurred during the landmark 1950s drought, the VPD and temperature anomalies observed in 2011 were even greater. Furthermore, future climate data under the representative concentration pathway 8.5 trajectory project that average values will surpass the 2011 VPD anomaly during the 2070-2099 period and the temperature anomaly during the 2040-2099 period. Identifying vulnerable ecological systems to drought stress and climate thresholds associated with canopy loss will aid in predicting how forests will respond to a changing climate and how ecological landscapes will change in the near term.

Coastal flood impact assessments are important tools for risk management and are performed by combining the hazard component with the vulnerability of exposed assets, to quantify consequences (or impacts) in terms of relative or absolute (e.g. financial) damage. The process generates uncertainties that should be taken into account for the correct representation of the consequences of floods. This study presents a coastal flood impact application at the spatial level of the Stavanger municipality (Norway), based on a multi-damage model approach able to represent impacts, and their overall uncertainty. Hazard modelling was performed using the LISFLOOD-FP code, taking into account historical extreme water level events (1988–2017) and relative sea level rise scenarios. Direct impacts were calculated in the form of relative and financial damage for different building categories, using flood damage curves. The results showed that the expected impacts are fewer than 50 flooded receptors and less than €1 million in damage in the current sea level scenario. The impacts could double by the end of the century, considering the most optimistic relative sea level scenario. The results were discussed considering the limitations of the approach for both hazard and impact modelling, that will be improved in future implementations. The outcome of this study may be useful for cost–benefit analyses of mitigation actions and local-scale plans for adaptation. © 2020 The Authors

Identifying patterns in data relating to extreme rainfall is important for classifying and estimating rainfall and flood frequency distributions routinely used in civil engineering design and flood management. This study demonstrates the novel use of several self-organising map (SOM) models to extract the key moisture pathways for extreme rainfall events applied to example data in northern Spain. These models are trained using various subsets of a backwards trajectory data set generated for extreme rainfall events between 1967 and 2016. The results of our analysis show 69.2% of summer rainfall extremes rely on recirculatory moisture pathways concentrated on the Iberian Peninsula, whereas 57% of winter extremes rely on deep-Atlantic pathways to bring moisture from the ocean. These moisture pathways have also shown differences in rainfall magnitude, such as in the summer where peninsular pathways are 8% more likely to deliver the higher magnitude extremes than their Atlantic counterparts.

International audience; We develop new flexible univariate models for light-tailed and heavy-tailed data, which extend a hierarchical representation of the generalized Pareto (GP) limit for threshold exceedances. These models can accommodate departure from asymptotic threshold stability in finite samples while keeping the asymptotic GP distribution as a special (or boundary) case and can capture the tails and the bulk jointly without losing much flexibility. Spatial dependence is modeled through a latent process, while the data are assumed to be conditionally independent. Focusing on a gamma-gamma model construction, we design penalized complexity priors for crucial model parameters, shrinking our proposed spatial Bayesian hierarchical model toward a simpler reference whose marginal distributions are GP with moderately heavy tails. Our model can be fitted in fairly high dimensions using Markov chain Monte Carlo by exploiting the Metropolis-adjusted Langevin algorithm (MALA), which guarantees fast convergence of Markov chains with efficient block proposals for the latent variables. We also develop an adaptive scheme to calibrate the MALA tuning parameters. Moreover, our model avoids the expensive numerical evaluations of multifold integrals in censored likelihood expressions. We demonstrate our new methodology by simulation and application to a dataset of extreme rainfall events that occurred in Germany. Our fitted gamma-gamma model provides a satisfactory performance and can be successfully used to predict rainfall extremes at unobserved locations.

An event catalog is a foundation of the risk analysis for any natural hazard. Especially if the catalog is comparatively brief relative to the return periods of possible events, it may well be deficient in extreme events that are of special importance to risk stakeholders. It is common practice for quantitative risk analysts to construct ensembles of future scenarios that include extreme events that are not in the event catalog. But past poor experience for many hazards shows that these ensembles are still liable to be missing crucial unknown events. An explicit systematic procedure is proposed here for searching for these key missing events. This procedure starts with the historical catalog events, and explores alternative realizations of them where things turned for the worse. These are termed downward counterfactuals. By repeatedly exploring ways in which the event loss might have been incrementally worse, missing events can be discovered that may take risk analysts, and risk stakeholders, by surprise. The downward counterfactual search for extreme events is illustrated with examples drawn from a variety of natural hazards. Attention is drawn to the problem of overfitting to the historical record, and the value of stochastic modeling of the past.

Extreme climatic events, such as late frosts in spring during leaf flush, have considerable impacts on the radial growth of temperate broadleaf trees. Albeit, all broadleaved species are potentially vulnerable, damage depends on the particularities of the local climate, the species, and its phenology. The impact of late spring frosts has been widely investigated in the Northern Hemisphere, but the potential incidence in Southern Hemisphere tree species is still poorly known. Here, we reconstruct spring frost occurrence at 30 stands of the deciduous tree Nothofagus pumilio in its northern range of distribution in the Patagonian Andes. We identified tree ring-width reductions at stand level not associated with regional or local drought events, matching unusual minimum spring temperatures during leaf unfolding. Several spring frosts were identified along the northern distribution of N. pumilio, being more frequent in the more continental Argentinean forests. Spring frost in 1980 had the largest spatial extent. The spring frosts in 1980 and 1992 also induced damages in regional orchards. Spring frost damage was associated with (i) a period of unusually warm temperatures at the beginning of leaf unfolding, followed by (ii) freezing temperatures. This study helps expand our understanding of the climatic constraints that could determine the future growth and dynamics of Andean deciduous forests and the potential use of tree-rings as archives of extreme events of spring frosts in northern Patagonia. Fil: Sangüesa Barreda, Gabriel. Universidad de Valladolid; España Fil: Villalba, Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentina Fil: Rozas, Vicente. Universidad de Valladolid; España. Universidad Austral de Chile; Chile Fil: Christie, Duncan A.. Centro de Investigaciones sobre Clima y Resiliencia; Chile. Universidad Austral de Chile; Chile Fil: Olano, José Miguel. Universidad de Valladolid; España

This study provides a literature‐based comparative assessment of uncertainties and biases in global to world‐regional scale assessments of current and future coastal flood risks, considering mean and extreme sea‐level hazards, the propagation of these into the floodplain, people and coastal assets exposed, and their vulnerability. Globally, by far the largest bias is introduced by not considering human adaptation, which can lead to an overestimation of coastal flood risk in 2100 by up to factor 1300. But even when considering adaptation, uncertainties in how coastal societies will adapt to sea‐level rise dominate with a factor of up to 27 all other uncertainties. Other large uncertainties that have been quantified globally are associated with socio‐economic development (factors 2.3–5.8), digital elevation data (factors 1.2–3.8), ice sheet models (factor 1.6–3.8) and greenhouse gas emissions (factors 1.6–2.1). Local uncertainties that stand out but have not been quantified globally, relate to depth‐damage functions, defense failure mechanisms, surge and wave heights in areas affected by tropical cyclones (in particular for large return periods), as well as nearshore interactions between mean sea‐levels, storm surges, tides and waves. Advancing the state‐of‐the‐art requires analyzing and reporting more comprehensively on underlying uncertainties, including those in data, methods and adaptation scenarios. Epistemic uncertainties in digital elevation, coastal protection levels and depth‐damage functions would be best reduced through open community‐based efforts, in which many scholars work together in collecting and validating these data., Key Points We present the first comparison of uncertainties in global to world‐regional scale assessments of current and future coastal flood riskThe largest uncertainty relates to future coastal adaptation, which can influence future coastal flood risk by factors of 20–27Uncertainties in socioeconomic development, elevation data, defense levels, emissions and ice sheets can affect risks by factors of 2–6

Here we report from a experiment imposing different warming scenarios [control with ambient temperature, constant level of moderate warming for 3�years, stepwise increase in warming for 3�years, and one season of high level warming (pulse) simulating an extreme summer event] on an alpine ecosystem to study the impact on species diversity?biomass relationship, and community resistance in terms of biomass production. Multiple linear mixed models indicate that experimental years had stronger influence on biomass than warming scenarios and species diversity. Species diversity and biomass had almost humpback relationships under different warming scenarios over different experimental years. There was generally a negative diversity?biomass relationship, implying that a positive diversity?biomass relationship was not the case. The application of different warming scenarios did not change this tendency. The change in community resistance to all warming scenarios was generally negatively correlated with increasing species diversity, the strength of the correlation varying both between treatments and between years within treatments. The strong effect of experimental years was consistent with the notion that niche complementarity effects increase over time, and hence, higher biomass productivity over experimental years. The strongest negative relationship was found in the first year of the pulse treatment, indicating that the community had weak resistance to an extreme event of one season of abnormally warm climate. Biomass production started recovering during the two subsequent years. Contrasting biomass-related resistance emerged in the different treatments, indicating that micro sites within the same plant community may differ in their resistance to different warming scenarios. Scopus

Assessments of local-scale windstorm hazard require highly resolved spatial information on wind speeds and gusts. In this study, maximum (peak) sustained wind speeds on a 3-km horizontal grid over Switzerland are obtained by dynamical downscaling from the Twentieth Century Reanalysis (20CR) employing the Weather Research and Forecasting (WRF) model. Subsequently, simulated peak gusts are derived using four wind gust parameterizations (WGPs). Evaluations against observations at 63 locations in complex terrain include four high-impact windstorms (occurring in 1919, 1935, 1990, and 1999) and 14 recent windstorms (occurring between 1993 and 2011). Peak sustained wind speeds and directions are generally well simulated, although wind speeds are mostly overestimated. In general, performance and skill measures are best for locations on the Swiss Plateau and inferior for Alpine mountain and valley locations. An independent ERA-Interim WRF downscaling configuration produces overall comparable results, implying that the 20CR ensemble mean is a reliable data set in dynamical downscaling exercises. The four evaluated WGPs largely reproduce the observed gustiness, although the timing and magnitude of the peak gusts are not regularly captured. None of the WGPs stands out as single best for the complex topography of Switzerland. Differences among the WGPs are small compared to the biases inherited from the sustained-wind part in the WGP formulations. All WGPs transform overestimated peak sustained winds into underestimated peak gusts, which points to an underrepresentation of the turbulent part in the WGP formulations. The range of simulated peak gusts from downscaling all 20CR ensemble members does not reliably include the observed peak gust, indicating limited benefit in applying an ensemble approach. Despite the limitations, we infer that with spatial optimisations of the simulation (e.g. by bias correction or adaptation of the WGP schemes), downscaling of 20CR input is an efficient option for high-resolution assessments of windstorm hazard and risk in Switzerland. Keywords: dynamical downscaling, 20CR, ERA-Interim, wind speed, wind gust estimation, extreme event, hazard map, Alps, gust factor, risk, WRF wind evaluation (Published: 19 August 2016) Citation: Tellus A 2016, 68, 31820, http://dx.doi.org/10.3402/tellusa.v68.31820

The objective of this study was to examine the interaction of extreme growth years in teak (Tectona grandis) with climatic conditions of current, antecedent and subsequent years, in order to explain the nature and the effects of climatic variability on teak growth in northeastern Thailand. A 33-year tree-ring index was constructed and extreme growth years during the period 1976-2008 were identified. A superposed epoch analysis (SEA) was used to study the interaction of climatic data and extreme growth years. Extreme growth years were derived from eight wider and seven narrower annual rings identified using the Cropper’s method. Seventeen false rings were detected using the threshold value ≥ 80% of false ring occurrence for all samples in each growth year. False ring occurrence was associated with narrow ring width formation and triggered by increasing maximum and mean temperatures at the beginning of the rainy season (May to August). In the third year after false ring formation, we observed a pattern of wet year occurrence when annual rainfall and relative humidity in September to December were higher than in adjacent years. Moreover, in the sixth year before false ring formation, a wet year was observed when relative humidity in September to December was higher than in adjacent years. Wider ring width index occurring in a particular year was found to be triggered by a decrease in maximum and mean temperatures in May to August of the current year, suggesting that wet years promote teak growth. The third year after the formation of wider rings was characterized by a low annual rainfall. Our results showed that drought years trigger false ring and narrow ring formation, while wet years trigger wide ring formation in teak. A cycle of wet years between the sixth year prior to, and the third year after, the formation of false rings was also observed, as well as the occurrence of drought in the third year since the formation of wide rings. False ring, narrow ring and wide ring occurrences appear to be good indicators of a 3-6 year climate fluctuation pattern, similar to that of the El Nino-Southern Oscillation (ENSO) cycle in this region.

Study region: The Present work shows trend analysis results for temperature and precipitation around the world and for river discharges in the Americas, Australia and some European countries for a common time period with free access hydrometeorological information. Study focus: Hydrometeorological data sets for discharge, precipitation and temperature around the world were analysed for statistically significant trends both in average and extreme value data sets between 1970 and 2010. The data was analysed with the Mann–Kenndall trend test at annual, monthly and daily resolutions, to compare the results on a global scale and between the different time resolutions. New hydrological insights for the region: Results indicate that trends can be found for all variables and on all latitudes, with an increase of global temperature in the analysed time period. Fewer trends were observed in extreme value data. Trends in discharge data were predominantly negative, and precipitation trends were not very common. In some cases, an opposing pattern was observed in the northern and southern hemisphere. The highest number of trends was found at the annual and least on the daily resolution, nevertheless, trend patterns for discharges remained similar at different time scales. Some of the factors that might influence these results are discussed. Keywords: Trend analysis, Hydrometeorological data sets, Extreme event, Mann–Kendall trend test, Time resolution, Global analysis

Under a declining trend of fog days in China, the duration of fog events since the 1990s reached a significant peak in the late autumn of 2018 over Eastern China. The average anomalous fog days were 4.74 d in November 2018 over Jiangsu Province in Eastern China, with a 1.73 standard deviation departure from climatology. Those fogs can thus be identified as a significantly abnormal climatic event with long duration, strong intensity, and extensive coverage. Based on the daily evolutions and correlations of atmospheric parameters, the dense fogs are revealed to be well configured by favorable metrological conditions such as weak dynamic progress, strong inversion in the lower troposphere and saturated air near the surface. If not disturbed, the intensification or duration of these conditions will further promote and maintain the development of fogs. The anomalous atmospheric background associated with those favorable meteorological conditions is revealed by composing the standardized anomalies of circulation fields during the fog days. Over the fog areas, vortex activities or cold air invasion is effectively hampered and the atmosphere inclines to be stable, due to the anomalous circulation pattern composed of the broadened jet stream, weakened jet core over Eastern China, undermined East Asian trough, declined East Asian winter monsoon, and enhanced anomalous southerly flows that transport abnormal warm and wet air to Eastern China. The vapor supplement is intensified by both sustained anomalous northward wind at the lower troposphere and anomalous westward wind in the near-surface. Overall, the numbers of standardized anomalies of 1000&ndash, 200-hPa height, temperature, wind, and moisture fields during these fog days all significantly depart from climatology for that locale and time of the season, further demonstrating that the persistent dense fogs over Eastern China in the late autumn of 2018 is an unusual weather event with extreme synoptic-scale departures from normal.

Tropical mountain regions are prone to high erosion rates, due to the occurrence of heavy rainfall events and intensely weathered steep terrain. Landslides are a recurrent phenomenon, and often considered as the dominant erosion process on the hillslopes and the main source of sediment. Quantifying the contribution of landslide-derived sediment to the overall sediment load remains a challenge. In this study, we derived catchment-average erosion rates from sediment gauging data and cosmogenic radionuclides (CRN), and examined their reliability and validity for constraining sediment yields in tectonically active regions. Then, we analysed the relationship between catchment-average erosion rates and landslide-derived sediment fluxes. The Pangor catchment, located in the western Andean mountain front, was selected for this study given its exceptionally long time series of hydrometeorological data (1974-2009). When including magnitude-frequency analyses of the sediment yields at the measurement site, the corrected gauging-based sediment yields remain one order of magnitude lower than the CRN-derived erosion rates. The underestimation of catchment-average erosion rates from gauging data points to the difficulty of extrapolating flow frequency and sediment rating data in non-stationary hydrological regimes, and severe undersampling of extreme events. In such conditions, erosion rates derived from cosmogenic radionuclides are a reliable alternative method for the quantification of catchment-average sediment yield. Landslide inventories from remote sensing data (1963-2010) and field measurements of landslide geometries are the input data for the derivation of landslide-derived sediment fluxes. The landslide-related erosion rates of 1688+901−326 and 630+300−108 t.km2.y-1 are similar to the CRN-derived erosion rates, likely indicating that landslides are the main source of sediment in this mountainous catchment., Las cadenas montañosas en las regiones tropicales se caracterizan por las altas tasas de erosión debido a los eventos de lluvia intensa, terrenos escarpados y al alto grado de meteorización del material parental. Los deslizamientos son fenómenos recurrentes, y son considerados como los procesos más importantes de erosión en las zonas montañosas y las principales fuentes de sedimentos en el sistema fluvial. Con el objetivo de cuantificar la contribución de sedimentos provenientes de los deslizamientos al sistema fluvial, se realizó un estudio de caso en la Cuenca del Río Pangór, Ecuador. En este estudio, se cuantificó las tasas de erosión a escala de cuenca por medio de información derivada de estaciones de aforo de caudales e inventarios de isótopos cosmogénicos en sedimentos fluviales. Después, se evaluó la fiabilidad y validez de la información obtenida con el objetivo de cuantificar la carga de sedimento transportado por el río en regiones montañosas. Finalmente, se analizó la fracción de la carga total de sedimento proveniente de deslizamientos en las laderas. La cuenca del Río Pangór fue seleccionada por su extensa serie de tiempo de datos hidrometeorológicos (1974-2009). La carga de sedimento en el Río Pangór fue estimada por medio de un análisis de magnitudfrecuencia de la información recolectada en una estación hidrométrica y datos de concentración de sedimentos en suspensión. Los resultados muestran un valor de un orden de magnitud menor que la tasa de erosión calculada en función de los inventarios de isótopos cosmogénicos. Esta diferencia se explica por (i) la dificultad de extrapolar la información sobre la frecuencia temporal de los caudales y la carga de sedimento en regímenes hidrológicos no estacionarios, y (ii) el submuestreo de eventos extremos. Bajo estas condiciones, la cuantificación de las tasas de erosión derivadas de los isótopos cosmogénicos proporcionan una metodología alternativa para la cuantificación de la carga total de sedimentos en el sistema fluvial. Un inventario multitemporal (1963-2010) de deslizamientos fue desarrollado a partir de imágenes de satélite y fotografías aéreas. Mediante trabajo de campo se generó información sobre la geometría de los deslizamientos para la cuantificación de volúmenes de sedimento producido por los deslizamientos. En la cuenca del Río Pangór las altas tasas de erosión producida por los deslizamientos varían entre 1688+901−326 y 630+300−108 t.km2.y-1, valores que son similares a las tasas de erosión derivadas de isotopos cosmogénicos. Los resultados indican que los deslizamientos son las principales fuentes de sedimento en esta cuenca montañosa.

The Soil and Water Assessment Tool (SWAT) is a physical model designed to predict the hydrological processes that could characterize natural and anthropized watersheds. The model can be forced using input data of climate prediction models, soil characteristics and land use scenarios to forecast their effect on hydrological processes. In this study, the SWAT model has been applied in the Aspio basin, a small watershed, highly anthropized and characterized by a short runoff generation. Three simulations setup, named SL1, SL2 and SL3, were investigated using different soil resolution to identify the best model performance. An increase of space requirement and calibration time has been registered in conjunction with the increasing soil resolution. Among all simulations, SL1 has been chosen as the best one in describing watershed streamflow, despite it was characterized by the lower soil resolution. A map of susceptibility to runoff for the entire basin was so created reclassifying the runoff amount of four years in five classes of susceptibility, from very low to very high. Eleven sub-basins, coinciding with the main urban settlements, were identified as highly susceptible to runoff generation. Considering future climate predictions, a slight increase of runoff has been forecasted during summer and autumn. The map of susceptibility successfully identified as highly prone to runoff those sub-basins where extreme flood events were yet recorded in the past, remarking the reliability of the proposed assessment and suggesting that this methodology could represent a useful tool in flood managing plan.

International audience; We study experimentally, in a large-scale basin, the propagation of unidirectional deep water gravity waves stochastically modulated in phase. We observe the emergence of nonlinear localized structures that evolve on a stochastic wave background. Such a coexistence is expected by the integrable turbulence theory for the nonlinear Schrödinger equation (NLSE), and we report the first experimental observation in the context of hydrodynamic waves. We characterize the formation, the properties and the dynamics of these nonlinear coherent structures (solitons and extreme events) within the incoherent wave background. The extreme events result from the strong steepening of wave train fronts, and their emergence occurs after roughly one nonlinear length scale of propagation (estimated from NLSE). Solitons arise when nonlinearity and dispersion are weak, and of the same order of magnitude as expected from NLSE. We characterize the statistical properties of this state. The number of solitons and extreme events is found to increase all along the propagation, the wave-field distribution has a heavy tail, and the surface elevation spectrum is found to scale as a frequency power-law with an exponent −4.5 ± 0.5. Most of these observations are compatible with the integrable turbulence theory for NLSE although some deviations (e.g. power-law spectrum, asymmetrical extreme events) result from effects proper to hydrodynamic waves.

Coastal ecosystems throughout the world are increasingly vulnerable to degradation as a result of accelerating sea-level rise and saltwater intrusion, more frequent and powerful extreme weather events, and anthropogenic impacts. Hardwood swamp forests in the Big Bend region of Florida&rsquo, s Gulf of Mexico coast (USA) are largely devoid of the latter, but have degraded rapidly since the turn of the 21st Century. Photographs of the forest, collected on the ground since 2009, were used to guide an analysis of a 60 km2 study area using satellite images. The images confirm that the coastal forest area declined 0.60% from 1982 to 2003, but degraded rapidly, by 7.44%, from 2010 to 2017. The forest declined most rapidly along waterways and at the coastal marsh&ndash, forest boundary. Additional time series of aerial-photographs corroborated the onset of degradation in 2010. Degradation continued through 2017 with no apparent recovery. Previous research from the area has concluded that increased tidal flooding and saltwater intrusion, of the coastal plain, represent a chronic stress driving coastal forest decline in this region, but these drivers do not explain the abrupt acceleration in forest die-off. Local tide gage data indicate that sea-level rise is 2 mm yr&minus, 1 and accelerating, while meteorological data reveal at least two short-term cold snap events, with extreme temperatures exceeding the reported temperature threshold of local vegetation (&minus, 10 &deg, C) between January 2010 and January 2011, followed by more extremes in 2016. The Big Bend hardwood forest experienced acute cold snap stress during the 2010&ndash, 2017 period, of a magnitude not experienced in the previous 20 years, that compounded the chronic stress associated with sea-level rise and saltwater intrusion. This and other coastal forests can be expected to suffer further widespread and lasting degradation as these stresses are likely to be sustained.

Information on extreme precipitation for future climate is needed to assess the changes in the frequency and intensity of flooding. The primary source of information in climate change impact studies is climate model projections. However, due to the coarse resolution and biases of these models, they cannot be directly used in hydrological models. Hence, statistical downscaling is necessary to address climate change impacts at the catchment scale. This study compares eight statistical downscaling methods (SDMs) often used in climate change impact studies. Four methods are based on change factors (CFs), three are bias correction (BC) methods, and one is a perfect prognosis method. The eight methods are used to downscale precipitation output from 15 regional climate models (RCMs) from the ENSEMBLES project for 11 catchments in Europe. The overall results point to an increase in extreme precipitation in most catchments in both winter and summer. For individual catchments, the downscaled time series tend to agree on the direction of the change but differ in the magnitude. Differences between the SDMs vary between the catchments and depend on the season analysed. Similarly, general conclusions cannot be drawn regarding the differences between CFs and BC methods. The performance of the BC methods during the control period also depends on the catchment, but in most cases they represent an improvement compared to RCM outputs. Analysis of the variance in the ensemble of RCMs and SDMs indicates that at least 30% and up to approximately half of the total variance is derived from the SDMs. This study illustrates the large variability in the expected changes in extreme precipitation and highlights the need for considering an ensemble of both SDMs and climate models. Recommendations are provided for the selection of the most suitable SDMs to include in the analysis. ispartof: Hydrology and Earth System Sciences vol:19 issue:4 pages:1827-1847 status: published

Space weather is driven by the solar wind and many geospace storms and substorms are natural hazards with considerable societal impact. The dynamical and statistical features of these events are complicated because of the turbulent nature of their driver, the solar wind. Large-scale data sets of geospace storms and substorms are analysed for this study of the inherent statistical characteristics of extreme events in geospace. The detrended fluctuation analysis, based on the autocorrelation functions, is used and yields scaling behavior representing long-term correlations. The scaling function is represented by two exponents, arising due mainly to the presence of the largely coherent internal dynamics of the magnetosphere and the turbulent nature of the solar wind driver.

Highlights • Global magnitude–frequency relationship for large explosive volcanic eruptions • Conservative treatment of rounding and under-recording • Return period for super-eruptions (1000 Gt) estimated as 17ka (95% CI: 5.2ka, 48ka) • Much shorter than the previous estimate, wider implications for risk management For volcanoes, as for other natural hazards, the frequency of large events diminishes with their magnitude, as captured by the magnitude–frequency relationship. Assessing this relationship is valuable both for the insights it provides about volcanism, and for the practical challenge of risk management. We derive a global magnitude–frequency relationship for explosive volcanic eruptions of at least of erupted mass (or M4.5). Our approach is essentially empirical, based on the eruptions recorded in the LaMEVE database. It differs from previous approaches mainly in our conservative treatment of magnitude-rounding and under-recording. Our estimate for the return period of ‘super-eruptions’ (, or M8) is (95% CI: , ), which is substantially shorter than previous estimates, indicating that volcanoes pose a larger risk to human civilisation than previously thought.

International audience; Extreme weather events may be just as important as gradual trends for the long‐term trajectories of ecosystems. For alpine lakes, which are exposed to both exacerbated atmospheric warming and intense episodic weather events, future conditions might not be appropriately forecast by only climate change trends, i.e., warming, if extreme events have the potential to deflect their thermal and metabolic states from their seasonal ranges. We used high‐frequency monitoring data over three open‐water seasons with a one‐dimensional hydrodynamic model of the high‐altitude Lake Muzelle (France) to show that rainstorms or windstorms, notwithstanding their intensity, did not trigger long‐lasting consequences to the lake characteristics when light penetration into the lake was not modified. In contrast, storms associated with high turbidity input from the watershed (“turbid storms”) strongly modified the lacustrine hydrodynamics and metabolism for the rest of the open‐water season through reduced light penetration. The long‐lasting effects of turbid storms were related to the inputs and in‐lake persistence of very‐light glacial suspensoids from the watershed. The occurrence of the observed turbid storms was not related to the wind or rain intensities during the events. Instead, the turbid storms occurred after dry and atypically warm spells, i.e., meteorological conditions expected to be more frequent in this alpine region in the upcoming decades. Consequently, storm events, notwithstanding their intensity, are expected to strongly imprint the future ecological status of alpine lakes under climate warming.

A long-standing hypothesis in evolutionary biology is that polyploid plants have a fitness advantage over diploids in climatically variable or extreme habitats. Here we provide the first empirical evidence that polyploid advantage in these environments is caused by two distinct processes: homeostatic maintenance of reproductive output under elevated abiotic stress, and fixed differences in seed development. In an outdoor climate manipulation experiment using coastal to inland Australian populations of the perennial grass Themeda triandra Forssk., we found that total output of viable seed in drought- and heat-stressed tetraploid plants was over four times higher than in diploids, despite being equal under more favourable growing conditions. Tetraploids also consistently produced heavier seeds with longer hygroscopic awns, traits which increase propagule fitness in extreme environments. These differences add to fitness benefits associated with broader-scale local adaptation of inland T. triandra populations to drought stress. Our study provides evidence that nucleotypic effects of genome size and increased reproductive flexibility can jointly underlie polyploid advantage in plants in stressful environments, and argue that ploidy can be an important criterion for selecting plant populations for use in genetic rescue, restoration and revegetation projects, including in habitats affected by climate change.

Using the wave model SWAN (simulating waves nearshore), high waves on the southwestern Atlantic generated by extra-tropical cyclones are simulated from 2000 to 2010, and their impact on the Rio Grande do Sul (RS) coast is studied. The modeled waves are compared with buoy data and good agreement is found. The six extreme events in the period that presented significant wave heights above 5 m, on a particular point of interest, are investigated in detail. It is found that the cyclogenetic pattern between the latitudes 31.5 and 34° S is the most favorable for developing high waves. Hovmöller diagrams for deep water show that the region between the south of Rio Grande do Sul up to a latitude of 31.5° S is the most energetic during a cyclone's passage, although the event of May 2008 indicates that the location of this region can vary, depending on the cyclone's displacement. On the other hand, the Hovmöller diagrams for shallow water show that the different shoreface morphologies were responsible for focusing or dissipating the waves' energy; the regions found are in agreement with the observations of erosion and progradation regions. It can be concluded that some of the urban areas of the beaches of Hermenegildo, Cidreira, Pinhal, Tramandaí, Imbé and Torres have been more exposed during the extreme wave events on the Rio Grande do Sul coast, and are more vulnerable to this natural hazard.

At daybreak and late morning of 18th of February 2008 Lisbon and Setubal have been under the influence of a heavy rain event. This period was simulated by two operational WRF model set ups running for Portugal at the University of Aveiro in two different horizontal and vertical resolution and physical parameterisations. These two model configurations were tested for the described precipitation event in terms of microphysics and cumulus parameterisation and also in their domain configuration setup. Results suggest that the combination of cumulus and microphysics schemes is very important in the prediction of the amounts of precipitation. A small change in domain resolution has more impact in the spatial patterns of precipitation rather than in the amounts predicted.

Possible changes in the intensity of heavy precipitation events at the end of the twenty-first century over the Euro-Mediterranean region are investigated, using a subset of numerical climate simulations taking part to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). As a measure of the intensity associated with heavy precipitation events, we use the difference between the 99th and the 90th percentiles. Despite a slight tendency to underestimate the observed heavy precipitation intensity during summer and to overestimate it during winter, the considered CMIP5 models well represent the observed patterns of the defined 99th–90th percentile metric during both seasons for the 1997–2005 period over the Euro-Mediterranean region. Over the investigated domain, an increase of the width of the right tail of the precipitation distribution is projected in a warmer climate, even over regions where nearly the entire precipitation distribution becomes dryer. This is the case of the European domain within the 45N–55N belt.

Climate change is modifying disturbance regimes, affecting the severity and occurrence of extreme events. Current experiments investigating extreme events have a large diversity of experimental approaches and key aspects such as the interaction with other disturbances, the timing, and long-term effects are not usually incorporated in a standardized way. This lack of comparability among studies limits advances in this field of research. This study presents a framework that is comprised of two experimental approaches designed to test expected changes on disturbance regime due to climate change. These approaches test the effects of disturbances becoming more clustered and more extreme. They use common descriptor variables regardless of the type of disturbance and ecosystem. This framework is completed with a compilation of procedures that increase the realism of experiments in the aforementioned key aspects. The proposed framework favours comparability among studies and increases our understanding of extreme events. Examples to implement this framework are given using rocky shores as a case study. Far from being perfect, the purpose of this framework is to act as a starting point that triggers the comparability and refinement of these types of experiments needed to advance our understanding of the ecological effects of extreme events. Funded by the University of Alicante (Ref. UATALENTO 17-11).

Adequate design of pipelines used for oil, gas, water, and wastewater transmission is essential not only for their proper operation but particularly to avoid failure and the possible extreme consequences. This is even more drastic in nearshore environments, where pipelines are potentially exposed to extreme hydrodynamic events, such as tsunami- or storm-surge-induced inundation. The American Society of Civil Engineers (ASCE), in its ASCE7 Chapter 6 on Tsunami Loads and Effects which is the new standard for tsunami impacts and loading, specifically stresses the need to study loads on pipelines located in tsunami-prone areas. To address this issue, this study is the first of its kind to investigate loading on pipelines due to tsunami-like bores. A comprehensive program of physical model experiments was conducted in the Dam-Break Hydraulic Flume at the University of Ottawa, Canada. The tests simulated on-land tsunami flow inundation propagating over a coastal plain. This allowed to record and investigate the hydrodynamic forces exerted on the pipe due to the tsunami-like, dam-break waves. Different pipe configurations, as well as various flow conditions, were tested to investigate their influence on exerted forces and moments. The goal of this study was to propose, based on the results of this study, resistance and lift coefficients which could be used for the design of pipelines located in tsunami-prone areas. The values of the resistance and lift coefficients investigated were found to be in the range of 1 &lt, CR&lt, 3.5 and 0.5 &le, CL&lt, 3, respectively. To that end, the study provides an upper envelope of resistance and lift coefficients over a wide range of Froude numbers for design purposes.

The ongoing global climate change involves not only increased temperatures but may also produce more frequent extreme events, such as severe rainfall that could trigger a pulse of nutrients to lakes. In shallow lakes, this may affect primary producers through a number of direct and indirect mechanisms. We conducted a six-month mesocosm experiment to elucidate how periphyton (on inert substrata), epiphyton and epipelon biomass responded to a nitrogen (N) pulse, an approximately tenfold enrichment of the NO3-pool, under three contrasting warming scenarios: ambient temperature and ca. +3°C and ca. +4.5°C elevated temperatures (hereafter T1, T2 and T3). After the N pulse, we found a higher periphyton biomass at elevated than at ambient temperatures but no change in epiphyton biomass. Epipelon biomass was lower in T3 than in T1. Both periphyton and epiphyton biomasses correlated negatively with snail biomass, while epiphyton biomass correlated positively with light. Different responses to higher temperatures under short-term extreme nutrient loading conditions may be attributed to differences in the access to nutrient sources and light. Our data suggest that the biomass of periphyton in oligotrophic clear-water lakes will increase significantly under conditions exhibiting short-term extreme nutrient loading in a warmer climate. Fil: Cao, Yu. University Aarhus; Dinamarca. Chinese Academy of Sciences; República de China Fil: Olsen, Saara. Sino-danish Centre For Education And Research (sdc); China. University Aarhus; Dinamarca Fil: Gutierrez, Marìa Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto Nacional de Limnología. Universidad Nacional del Litoral. Instituto Nacional de Limnología; Argentina Fil: Brucet, Sandra. Institucio Catalana de Recerca I Estudis Avancats; . University Aarhus; Dinamarca. Universitat de Vic; Fil: Davidson, Thomas A.. University Aarhus; Dinamarca Fil: Li, Wei. Chinese Academy of Sciences; República de China. Sino-danish Centre For Education And Research (sdc); China Fil: Lauridsen, Torben L.. University Aarhus; Dinamarca. Sino-danish Centre For Education And Research (sdc); China Fil: Søndergaard, Martin. University Aarhus; Dinamarca Fil: Jeppesen, Erik. University Aarhus; Dinamarca. Sino-danish Centre For Education And Research (sdc); China

“The 2–days precipitation event over Jakarta in February 2015 was very unusual, the highest in the 135–year long historical records with a return period more than 60 years in the current climate. An intensified monsoon with an unusual northerly winds leading to this event is described. The 2015 event has become about 2.2 times more likely due to the trend towards more extreme precipitation.”

International audience; This research presents a study of extreme low flow events that occurred from 1871 onwards in a large number of near-natural catchments in France. It aims at assessing and comparing their characteristics to improve our knowledge on historical events and to provide a selection of benchmark events for climate change adaptation purposes. The historical length of streamflow observations is generally limited to the last 50 years and therefore covers too small a sample of extreme low flow events to properly explore the long-term evolution of their characteristics and associated impacts. In order to overcome this limit, this study takes advantage of a 140-year ensemble hydrometeorological dataset over France based on: (1) probabilistic precipitation and temperature downscaling of the global Twentieth Century Reanalysis over France (Caillouet et al., 2016a), and (2) continuous hydrological modelling based on high-resolution meteorological reconstructions as forcings over the whole period. The resulting SCOPE Hydro dataset provides an ensemble of 25 equally plausible daily streamflow time series for a reference network of more than 600 stations in France over the 1871-2012 period. Extreme low-flow events are identified using a combination of a fixed threshold and a daily variable threshold. The procedure is applied to the 25 simulated time series as well as to the observed time series in order to compare observed and reconstructed events over the recent period, and to characterize in a probabilistic way unrecorded historical events. A spatial matching procedure at the scale of France is then developed in order to spatially assemble local extreme events into the same spatio-temporal event. After these steps, an event can be studied at the local or national scale through its spatial extent, duration or severity characteristics in a probabilistic setting (Caillouet et al., 2016b). This work identifies past and little known exceptional extreme events (1878, 1893, 1942-1949) or recent but poorly documented events (1972, 1978, 1985) besides well-known events (1921, 1976, 1989-1990, 2011). The evolution of these events since 1871 shows that an increasing part of the French territory is affected by extreme low-flow events since the 1940s. Finally, a good coherence is found between reconstructed events and narrative sources on historical droughts. For the first time, extreme low-flow events are described in a homogeneous manner over 140 years for a large set of near-natural French catchments, enabling detailed analyses of the effect of climate variability and anthropogenic climate change on low-flow hydrology.

Describing the complex dependence structure of extreme phenomena is particularly challenging. To tackle this issue we develop a novel statistical method that describes extremal dependence taking advantage of the inherent tree-based dependence structure of the max-stable nested logistic distribution, and that identifies possible clusters of extreme variables using reversible jump Markov chain Monte Carlo techniques. Parsimonious representations are achieved when clusters of extreme variables are found to be completely independent. Moreover, we significantly decrease the computational complexity of full likelihood inference by deriving a recursive formula for the likelihood function of the nested logistic model. The method’s performance is verified through extensive simulation experiments which also compare different likelihood procedures. The new methodology is used to investigate the dependence relationships between extreme concentrations of multiple pollutants in California and how these concentrations are related to extreme weather conditions. Overall, we show that our approach allows for the representation of complex extremal dependence structures and has valid applications in multivariate data analysis, such as air pollution monitoring, where it can guide policymaking

[object ObjectThis study was the first to investigate the direct effects of anomalous concentrations of ozone mediated by summer heat waves on seed germination in alpine plants. During germination, the seeds were exposed to three peaks of O3 concentration (125 ppb for 5 and 10 days; 185 ppb for 5 days), derived from measurements taken close to the species growing site. High O3 concentration delayed the first germination time, increased the mean germination time, and reduced the germination percentage during and immediately after the treatment, but, in most cases, effects were weak and had almost vanished three weeks after the treatments. In few cases, chronic exposure to O3 (125 for 10 days' treatment) enhanced seed germination compared to the control, suggesting that ozone may induce antioxidant and DNA-repair mechanisms or dormancy-breaking effects in hydrated seeds. Although seed mortality increased during O3 treatments in four species, the effect of O3 on seed germination is mostly limited to the period of exposure, indicating that it is unlikely to produce permanent negative effects on seeds, during the germination phase. Our results show that the direct effect of O3 on seeds of alpine plants may have minor impacts on plant reproductive performance during seed germination.

A good knowledge of extreme storm surges is necessary to ensure protection against flood. In this paper we introduce a methodology to determine time series of skew surges in France as well as a statistical approach for estimating extreme storm surges. With the aim to cope with the outlier issue in surge series, a regional frequency analysis has been carried out for the surges along the Atlantic coast and the Channel coast. This methodology is not the current approach used to estimate extreme surges in France. First results showed that the extreme events identified as outliers in at-site analyses do not appear to be outliers any more in the regional empirical distribution. Indeed the regional distribution presents a curve to the top with these extreme events that a mixed exponential distribution seems to recreate. Thus, the regional approach appears to be more reliable for some sites than at-site analyses. A fast comparison at a given site showed surge estimates with the regional approach and a mixed exponential distribution are higher than surge estimates with an at-site fitting. In the case of Brest, the 1000-yr return surge is 167 cm in height with the regional approach instead of 126 cm with an at-site analysis.

Hurricane Harvey made landfall in August 2017 as the first land-falling category 4 hurricane to hit the state of Texas since Hurricane Carla in September 1961. While its intensity at landfall was notable, most of the vast devastation in the Houston metropolitan area was due to Harvey stalling near the southeast Texas coast over the next several days. Harvey's long-duration rainfall event was reminiscent of extreme flooding that occurred in the neighboring state of Louisiana: both of which were caused by a stalled tropical low-pressure system producing four days of intense precipitation. A quantitative attribution analysis of Harvey's rainfall was conducted using a mesoscale atmospheric model forced by constrained boundary and initial conditions that had their long-term climate trends removed. The removal of the various trends of the boundary and initial conditions minimizes the effects of warming in the air and the ocean surface on Harvey. The 60 member ensemble simulations suggest that post-1980 climate warming could have contributed to the extreme precipitation that fell on southeast Texas during 26–29 August 2017 by approximately 20%, with an interquartile range of 13%–37%. While the attribution outcome could be model dependent, this downscaling approach affords the closest means possible of a case-to-case comparison for event attribution, complementing other statistics-based attribution studies on Harvey. Further analysis of a global climate model tracking Harvey-like stalling systems indicates an increase in storm frequency and intensity over southeast Texas through the mid-21st century.

On 28th September 2012, more than 150 mm rain fell in just two hours in some points of southeastern Spain, triggering intense flash floods that resulted in the death of ten people and widespread material damage. In the gypsum karst of Sorbas, rainfall intensity reached 33 mm/h. Air temperature monitoring in different levels of Covadura Cave, down to 85 m depth, enabled the effect of this extreme episode on the cave microclimate to be evaluated in real time. The cave air temperature increased by between 0.9 and 4.1 °C as a result of water flow into the cavity and intense mixing of air masses, in addition to the displacement of deeper air masses toward shallower levels produced by fast recharge of the surrounding karst aquifer. The lag between peak rainfall intensity and the highest cave air temperature was 5–6 h, indicating the response time of the karst to this rainfall event. No trends with depth were observed, suggesting that water not only flowed in through the main cave entrance but also through secondary accesses and fractures. Furthermore, the size of the cave passages and the intensity of air turbulence generated by waterfalls in the cave played an important role in producing these temperature differences. Even though the rainfall event lasted 10 h, cave air temperature did not return to pre-flash flood values until more than 20 days later. This indicates that, while waterflow through the cave might stop a few hours after the rainfall event, cave air temperature can be affected over a longer period. This can be explained by slow groundwater level decreasing of the surrounding karst aquifer and latent heat liberation produced by moisture condensation on the cave walls. Our results show how continuous monitoring of air temperature in caves can be a useful tool for evaluating the short-term effects of flash floods in subterranean karst systems., Financial support was made available through funds from the Water Resources and Environmental Geology Research Group (University of Almería) and the ‘‘GLOCHARID’’ Project (852/2009/M/00) of the Junta de Andalucía Regional Government. Funding was also provided by the People Programme (Marie Curie Actions – Intra-European Fellowships, call 2013) of the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA grant agreement no. 624204 to Dr. Fernández-Cortés.

Current methods for monitoring deforestation from satellite data at sub-annual scales require pixel time series to have many historical observations in the reference period to model normal forest dynamics before detecting deforestation. However, in some areas, pixel time series often do not have many historical observations. Detecting deforestation at a pixel with scarce historical observations can be improved by complementing the pixel time series with spatial context information. In this work, we propose a data-driven space-time change detection method that detects deforestation events at sub-annual scales in data cubes of satellite image time series. First we spatially normalised observations in the local space-time data cube to reduce seasonality. Subsequently, we detected deforestation by assessing whether a newly acquired observation in the monitoring period is an extreme when compared against spatially normalised values in a local space-time data cube defined over reference period. We demonstrated our method at two sites, a dry tropical Bolivian forest and a humid tropical Brazilian forest, by varying the spatial and temporal extent of data cube. We emulated a “near real-time” monitoring scenario, implying that observations in the monitoring period were sequentially rather than simultaneously assessed for deforestation. Using Landsat normalised difference vegetation index (NDVI) time series, we achieved a median temporal detection delay of less than three observations, a producer’s accuracy above 70%, a user’s accuracy above 65%, and an overall accuracy above 80% at both sites, even when the reference period of the data cube only contained one year of data. Our results also show that large percentile thresholds (e.g., 5th percentile) achieve higher producer’s accuracy and shorter temporal detection delay, whereas smaller percentiles (e.g., 0.1 percentile) achieve higher user’s accuracy, but longer temporal detection delay. The method is data-driven, not based on statistical assumption on the data distribution, and can be applied on different forest types. However, it may face challenges in mixed forests where, for example, deciduous and evergreen forests coexist within short distances. A pixel to be assessed for deforestation should have a minimum of three temporal observations, the first of which must be known to represent forest. Such short time series allow rapid deployment of newly launched sensors (e.g., Sentinel-2) for detecting deforestation events at sub-annual scales.

Nuclear power plants in France are designed for low probabilities of failure. Nevertheless, some exceptional surges, considered as outliers, are not properly addressed by statistical models. Regional information may be used to mitigate the paucity of data and the influence of outliers. A regional frequency analysis (RFA) model assumes a homogenous behavior of the variable of interest at a regional scale. The first stage in an RFA is the delineation of homogeneous regions. We propose herein a new approach to form a homogenous region centered on a target site and using the spatial extremal dependence between observations (the spatial extremogram) to measure the neighborhood between sites. Skew surge data set collated at a total of 19 sites located on the French coast (Atlantic and English Channel) were used as the case study for this contribution (with La Rochelle as a target site). Once a physically plausible region of interest is defined, a related issue regards the statistical homogeneity of the region of interest. The L-moment-based homogeneity tests of Hosking and Wallis, widely used in hydrology, are used in this paper. The principle of the extremogram allows us to form a physically and statistically homogenous group of sites centered on a target site. It also allows to overcome the problem of the so-called "border effect" and these are two key original points of the developed concept. © 2016 WIT Press.

Among the outcomes of the drastic changes aff ecting the Earth ’ s ecosystems, nothing is more telling than a complete failure in the reproductive success of a sentinel species: a ‘ zero ’ year. Here, we found that unusual environmental conditions in the Terre Ad e lie sector of Antarctica disrupted the breeding activity of Ad e lie penguins Pygoscelis adeliae on land – but also their foraging activity at sea – to such a degree that no chicks survived in the 2013/2014 breeding season. Uncommonly heavy precipitation for this normally dry desert killed chicks en masse, while weak katabatic winds maintained a persistent sea ice around the colony, thereby impacting chick provisioning by adults. Extreme events such as this have direct repercussions for the species in question, and may also aff ect the wider sea-ice dependent food web. Understanding the nature, frequency, and consequences of such events are central to the management and conservation of this remote yet crucial ecosystem.

Extreme meteorological events are most likely to occur more often with climate change, leading to a further acceleration of climate change through potentially devastating effects on terrestrial ecosystems. But not all extreme meteorological events lead to extreme ecosystem response. Unlike most current studies, we therefore focus on pre-defined hazardous ecosystem behaviour and the identification of coinciding meteorological conditions, instead of expected ecosystem damage for a pre-defined meteorological event. We use a simple probabilistic risk assessment based on time series of ecosystem behaviour and meteorological conditions. Given the risk assessment terminology, vulnerability and risk for the previously defined hazard are, thus, estimated on the basis of observed hazardous ecosystem behaviour. We first adapt this generic approach to extreme responses of terrestrial ecosystems to drought and high temperatures, with defining the hazard as a negative net biome productivity over a 12 months period. Further, we show an instructive application for two selected sites using data for 1981–2010; and then apply the method on pan-European scale addressing the 1981–2010 period and future projections for 2071–2100, both based on numerical modelling results (LPJmL for ecosystem behaviour; REMO-SRES A1B for climate). Our site-specific results demonstrate the applicability of the proposed method, using the SPEI index to describe the meteorological condition. They also provide examples for their interpretation in case of vulnerability to drought for Spain with the expected value of the SPEI being 0.4 lower for hazardous than for non-hazardous ecosystem behaviour, and of non-vulnerability for Northern Germany, where the expected drought index value for hazard observations relates to wetter conditions than for the non-hazard observations. The pan-European assessment shows that significant results could be obtained for large areas within Europe. For 2071–2100 they indicate a shift towards vulnerability to drought, mainly in the central and north-eastern parts of Europe, where negative net biome productivity was not used to be associated with drought. In Southern parts of Europe, considerable vulnerability and risk to drought have been identified already under current conditions; in future, the difference in SPEI between hazardous and non-hazardous ecosystem behaviour as well as the frequency of hazardous ecosystem behaviour will increase further. Vulnerability decreased only for the border region between Ukraine, Russia and Belarus, where a change in ecosystem types occurred with less vulnerable plant species in the future. These first model-based applications indicate the conceptional advantages of the proposed method by focusing on the identification of critical meteorological conditions for which we observe hazardous ecosystem behaviour in the analysed dataset. Application of the method to empirical time series would be an important next step to test the methods.