Dominance of the mean sea level in the high-percentile sea levels time evolution with respect to large-scale climate variability: a Bayesian statistical approach

International audienceChanges in mean sea level (MSL) are a major, but not the unique, cause of changes in high-percentile sea levels (HSL), e.g. the annual 99.9th quantile of sea level (among other factors, climate variability may also have huge influence). To unravel the respective influence of each contributor, we propose to use structural time series models considering six major climate indices (CI) (Artic Oscillation, North Atlantic Oscillation, Atlantic Multidecadal Oscillation, Southern Oscillation Index, Nino 1 + 2 and Nino 3.4) as well as a reconstruction of MSL. The method is applied to eight century-long tide gauges across the world (Brest (France), Newlyn (UK), Cuxhaven (Germany), Stockholm (Sweden), Gedser (Danemark), Halifax (Canada), San Francisco (US), and Honolulu (US)). The treatment within a Bayesian setting enables to derive an importance indicator, which measures how often the considered driver is included in the model. The application to the eight tide gauges outlines that MSL signal is a strong driver (except for Gedser), but is not unique. In particular, the influence of Artic Oscillation index at Cuxhaven, Stockholm and Halifax, and of Nino Sea Surface Temperature index 1 + 2 at San Francisco appear to be very strong as well. Asimilar analysis was conducted by restricting the time period of interest to the 1st part of the 20th century. Over this period, we show that the MSL dominance is lower, whereas an ensemble of CI contribute to a large part to HSL time evolution as well. The proposed setting is flexible and could be applied to incorporate any alternative predictive time series such as river discharge, tidal constituents or vertical ground motions where relevant

Addressing ambiguity in probabilistic assessments of future marine flooding using possibility distributions

International audienceToday, decision making in the area of coastal adaptation is facing a major challenge due to the deep uncertainties of sea level projections. These deep uncertainties (aka ambiguity or epistemic uncertainties), reflect the intrinsically imprecise nature of global sea level rise (GSLR) due to the lack of knowledge regarding the melting of ice, particularly in Antarctica. Possibility distributions are one of the mathematical tools enabling to overcome the ambiguity in the selection a unique probability laws by bounding all the plausible ones. By adopting this new mathematical tool, we aim at evaluating how GSLR uncertainties accumulate with other sources of uncertainties, namely: the choice in Representative Concentration Pathway (RCP) scenario, the ranking of high-end scenarios, the regional bias, the contributions of extremes and wave effects. The case study corresponds to a local low-lying coastal urban area exposed to storm surge and waves in the north-western Mediterranean coast. We focus on the probability of future flooding by 2100 defined as the probability of exceeding a critical threshold corresponding to the height of coastal defences. The joint sensitivity analysis of the probabilistic, possibilistic and scenario-like sources of uncertainty enables to highlight the key role of deep uncertainties of GSLR, of the statistical uncertainty related to extremes and to a lesser extent of the choice in the RCP scenario. These results heavily depend on the decision maker’s attitude to risk (neutral, averse), which suggests the importance of entering into a loop of interactions with users, in order to collect their requirements and feedbacks, and involves research at the interface between behavioural and decision analytics, climate and coastal science as well as applied statistics

Social science to accelerate coastal adaptation to sea-level rise

The latest IPCC report estimates that approximately 1 billion people will be at risk from coastal hazards in the near term due to coastal population increase, sea-level rise and other coastal changes. This will occur in a world that is changing rapidly due to climate change, ecosystem decline, human development and the projected transformations of the economy to meet the objectives of the Paris Agreement. In this context, social sciences provide a pivotal perspective to coastal adaptation, for example, while assessing barriers and opportunities across scales, from local to global. This scoping review explores how social sciences support coastal adaptation. We show that Political Sciences, Economics, Sociology and Geography are already supporting coastal adaptation. Yet, scientific fields such as legal sciences, psychology, history and archaeology as well as anthropology and ethnography are less developed in the context of coastal adaptation to sea-level rise. New research avenues could also integrate education, media and communication research and aim at truly interdisciplinary studies linking different branches of social sciences with coastal science and climate services. This effort could help moving from a coastal adaptation often focused on coastal engineering protection to a broader vision of coastal resilient development, also addressing the challenges of mitigation, sustainable development and coastal ecosystem decline

Climate change impact on waves in the Bay of Biscay, France

International audienceThe knowledge of offshore and coastal wave climate evolution towards the end of the twenty-first century is particularly important for human activities in a region such as the Bay of Biscay and the French Atlantic coast. Using dynamical downscaling, a high spatial resolution dataset of wave conditions in the Bay of Biscay is built for three future greenhouse gases emission scenarios. Projected wave heights, periods and directions are analysed at regional scale and more thoroughly at two buoys positions, offshore and along the coast. A general decrease of wave heights is identified (up to -20 cm during summer within the Bay of Biscay), as well as a clockwise shift of summer waves and winter swell coming from direction. The relation between those changes and wind changes is investigated and highlights a complex association of processes at several spatial scales. For instance, the intensification and the north-eastward shift of strong wind core in the North Atlantic Ocean explain the clockwise shift of winter swell directions. During summer, the decrease of the westerly winds in the Bay of Biscay explains the clockwise shift and the wave height decrease of wind sea and intermediate waves. Finally, the analysis reveals that the offshore changes in the wave height and the wave period as well as the clockwise shift in the wave direction continue toward the coast. This wave height decrease result is consistent with other regional projections and would impact the coastal dynamics by reducing the longshore sediment flux

Global Climate Services: A Typology of Global Decisions Influenced by Climate Risk

Climate services are ideally co-developed by scientists and stakeholders working together to identify decisions and user needs. Yet, while climate services have been developed at regional to local scales, relatively little attention has been paid to the global scale. Global climate services involve decisions that rely on climate information from many locations in different world regions, and are increasingly salient. Increasing interconnections in the global financial system and supply chains expose private companies and financial institutions to climate risk in multiple locations in different world regions. Further, multilateral decisions on greenhouse gas emission reduction targets, disaster risk finance or international migration should make use of global scale climate risk assessments. In order to advance global climate service development, we present a typology of decisions relying on global (i.e., non-local) climate risk information. We illustrate each decision type through examples of current practice from the coastal domain drawn from the literature and stakeholder interviews. We identify 8 types of decisions making use of global climate information. At a top-level, we distinguish between “multilateral climate policy decisions,” and “portfolio decisions involving multiple locations.” Multilateral climate policy decisions regard either “mitigation targets” or “multilateral adaptation” decisions. Portfolio decisions regard either “choice of location” or “choice of financial asset” decisions. Choice of location decisions can be further distinguished as to whether they involve “direct climate risks,” “supply chain risks” or “financial network risks.” Our survey of examples shows that global climate service development is more advanced for portfolio decisions taken by companies with experience in climate risk assessment, i.e., (re-)insurers, whereas many multilateral climate policy decisions are at an earlier stage of decision-making. Our typology thus provides an entry-point for global climate service development by pointing to promising research directions for supporting global (non-local) decisions that account for climate risks.Peer Reviewe

On the use of linear stability model to characterize the morphological behaviour of a double bar system. Application to Truc Vert Beach (France).

10 pages, 9 figures, 3 tableauxInternational audienceSandy barred beaches are often characterized by the presence of rhythmic patterns such as crescentic bars. In this paper, a linear stability analysis (LSA) model is used to characterize the morphological behaviour of the double bar system of Truc Vert beach. Using a limited number of combination of representative bathymetries, wave classes and water levels, the morphodynamic response of the system is analysed, focussing on the geometrical characteristics of 3D patterns generated with the model. These characteristics are described and then compared with available observations. The shapes and the wavelengths of the instabilities predicted by the model compare well with field observations. Thus, the use of linear stability model, with representative hydrodynamic conditions and bathymetries of the considered site, allows a characterization of the global morphodynamic behaviour of a double-barred system

Services climatiques pour l'adaptation au changement climatique

National audienceLe changement climatique constitue une problématique majeure perceptible dès aujourd'hui ; la société et l'ensemble de ses acteurs peuvent percevoir la nécessité de l'adaptation à cette nouvelle situation

Vagues sur la côte aquitaine : régionalisation dynamique de 1958 à 2002

National audienceUn système de modélisation de vagues, forcé uniquement par des champs de vent a été mis en place avec le code WAVEWATCH IIITM sur une période de 44 ans (1958 à 2002) en vue d'étudier l'impact de la variabilité climatique passée sur les états de mer et sur l'érosion de la côte aquitaine. Les emboîtements hauturiers forcés par les champs de vent de la réanalyse ERA-40 ont été calibrés sur la période 1998-2002 sur 8 points de mesures. Les résultats sur 44 ans ont ensuite été validés sur 11 bouée

An AHP-derived method for mapping the physical vulnerability of coastal areas at regional scales

International audienceAssessing coastal vulnerability to climate change at regional scales is now mandatory in France since the adoption of recent laws to support adaptation to climate change. However, there is presently no commonly recognised method to assess accurately how sea level rise will modify coastal processes in the coming decades. Therefore, many assessments of the physical component of coastal vulnerability are presently based on a combined use of data (e.g. digital elevation models, historical shoreline and coastal geomorphology datasets), simple models and expert opinion. In this study, we assess the applicability and usefulness of a multi-criteria decision-mapping method (the analytical hierarchy process, AHP) to map physical coastal vulnerability to erosion and flooding in a structured way. We apply the method in two regions of France: the coastal zones of Languedoc-Roussillon (north-western Mediterranean, France) and the island of La Réunion (south-western Indian Ocean), notably using the regional geological maps. As expected, the results show not only the greater vulnerability of sand spits, estuaries and low-lying areas near to coastal lagoons in both regions, but also that of a thin strip of erodible cliffs exposed to waves in La Réunion. Despite gaps in knowledge and data, the method is found to provide a flexible and transportable framework to represent and aggregate existing knowledge and to support long-term coastal zone planning through the integration of such studies into existing adaptation schemes

Management of uncertainties on parameters elicited by experts – Applications to sea-level rise and to CO 2 storage operations risk assessment

International audienceIn a context of high degree of uncertainty, when very few data are available, experts are commonly requested to provide their opinions on input parameters of risk assessment models. Not only might each expert express a certain degree of uncertainty on his/her own statements, but the set of information collected from the pool of experts introduces an additional level of uncertainty. It is indeed very unlikely that all experts agree on exactly the same data, especially regarding parameters needed for natural risk assessments. In some cases, their opinions may differ only slightly (e.g. the most plausible value for a parameter is similar for different experts, and they only disagree on the level of uncertainties that taint the said value) while on other cases they may express incompatible opinions for a same parameter. Dealing with these different kinds of uncertainties remains a challenge for assessing geological hazards or/and risks. Extra-probabilistic approaches (such as the Dempster-Shafer theory or the possibility theory) have shown to offer promising solutions for representing parameters on which the knowledge is limited. It is the case for instance when the available information prevents an expert from identifying a unique probability law to picture the total uncertainty. Moreover, such approaches are known to be particularly flexible when it comes to aggregating several and potentially conflicting opinions. We therefore propose to discuss the opportunity of applying these new theories for managing the uncertainties on parameters elicited by experts, by a comparison with the application of more classical probability approaches. The discussion is based on two different examples. The first example deals with the estimation of the injected CO 2 plume extent in a reservoir in the context of CO 2 geological storage. This estimation requires information on the effective porosity of the reservoir, which has been estimated by 14 different experts. The Dempster-Shafer theory has been used to represent and aggregate these pieces of information. The results of different aggregation rules as well as those of a classical probabilistic approach are compared with the purpose of highlighting the elements each of them could provide to the decision-maker (Manceau et al., 2016). The second example focuses on projections of future sea-level rise. Based on IPCC's constraints on the projection quantiles, and on the scientific community consensus level on the physical limits to future sea-level rise, a possibility distribution of the projections by 2100 under the RCP 8.5 scenario has been established. This possibility distribution has been confronted with a set of previously published probabilistic sea-level projections, with a focus on their ability to explore high ranges of sea-level rise (Le Cozannet et al., 2016). These two examples are complementary in the sense that they allow to address various aspects of the problem (e.g. representation of different types of information, conflict among experts, sources dependence). Moreover, we believe that the issues faced during these two experiences can be generalized to many risks/hazards assessment situations. References Manceau, JC., Loschetter, A., Rohmer, J., de Lary, L., Le Guénan, T., Hnottavange-Telleen, K. (2016). Dealing with uncertainty on parameters elicited from a pool of experts for CCS risk assessment. Congrès λµ 20 (St-Malo, France). Le Cozannet G., Manceau JC., Rohmer, J. (2016). Bounding probabilistic sea-level rise projections within the framework of the possibility theory. Accepted in Environmental Research Letters