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Projections of changes in extreme droughts under future climate conditions are associated with large uncertainties, owing to the complex genesis of droughts and large model uncertainty in the atmospheric dynamics. In this study we investigate the impact of global warming on soil moisture drought severity in west-central Europe by employing pseudo global warming (PGW) experiments, which project the 1980–2020 period in a globally warmer world. The future analogues of present-day drought episodes allow for investigation of changes in drought severity conditional on the historic day-to-day evolution of the atmospheric circulation. The 2018 west-central European drought is the most severe drought in the 1980–2020 reference period in this region. Under 1.5, 2 and 3 ∘C global warming, this drought episode experiences strongly enhanced summer temperatures but a fairly modest soil moisture drying response compared to the change in climatology. This is primarily because evaporation is already strongly moisture-constrained during present-day conditions, limiting the increase in evaporation and thus the modulation of the temperature response under PGW. Increasing precipitation in winter, spring and autumn limits or prevents an earlier drought onset and duration. Nevertheless, the drought severity, defined as the cumulative soil moisture deficit volume, increases considerably, with 20 % to 39 % under 2 ∘C warming. The extreme drought frequency in the 1980–2020 period strongly increases under 2 ∘C warming. Several years without noticeable droughts under present-day conditions show very strong drying and warming. This results in an increase in 2003-like drought occurrences, compounding with local summer temperature increases considerably above 2 ∘C. Even without taking into account a (potentially large) dynamical response to climate change, drought risk in west-central Europe is strongly enhanced under global warming. Owing to increases in drought frequency, severity and compounding heat, a reduction in recovery times between drought episodes is expected to occur. Our physical climate storyline provides evidence complementing conventional large-ensemble approaches and is intended to contribute to the formulation of effective adaptation strategies.

Abstract. Storm surges represent a major threat to many low-lying coastal areas in the world. In the aftermath of an extreme event, the extent to which the event was unusual and the potential contribution of climate change in shaping the event are often debated. Commonly analyzes that allow for such assessments are not available right away but are only provided with often considerable time delay. To address this gap, a new tool was developed and applied to storm surges along the German North Sea and Baltic Sea coasts. The tool integrates real-time measurements with long-term statistics to put ongoing extremes or the course of a storm surge season into a climatological perspective in near real time. The approach and the concept of the tool are described and discussed. To illustrate the capabilities, several exemplary cases from the storm surge seasons 2018/2019 and 2019/2020 are discussed. It is concluded that the tool provides support in the near-real-time assessment and evaluation of storm surge extremes. It is further argued that the concept is transferable to other regions and/or coastal hazards.

This paper presents a phenomenological framework for forecasting the area-integrated fire radiative power from wildfires. In the method, a region of interest is covered with a regular grid, whose cells are uniquely and independently parameterized with regard to the fire intensity according to (i) the fire incidence history, (ii) the retrospective meteorological information, and (iii) remotely sensed high-temporal-resolution fire radiative power taken together with (iv) consistent cloud mask data. The parameterization is realized by fitting the predetermined functions for diurnal and annual profiles of fire radiative power to the remote-sensing observations. After the parametrization, the input for the fire radiative power forecast is the meteorological data alone, i.e. the weather forecast. The method is tested retrospectively for south-central African savannah areas with the grid cell size of 1.5∘×1.5∘. The input data included ECMWF ERA5 meteorological reanalysis and SEVIRI/MSG (Spinning Enhanced Visible and Infra-Red Imager on board Meteosat Second Generation) fire radiative power and cloud mask data. It has been found that in the areas with a large number of wildfires regularly ignited on a daily basis during dry seasons from year to year, the temporal fire radiative power evolution is quite predictable, whereas the areas with irregular fire behaviour, predictability was low. The predictive power of the method is demonstrated by comparing the predicted fire radiative power patterns and fire radiative energy values against the corresponding remote-sensing observations. The current method showed good skills for the considered African regions and was useful in understanding the challenges in predicting the wildfires in a more general case.

Abstract. Sea-level rise due to anthropogenic climate change is projected not only to exacerbate extreme events such as cyclones and storms but also to cause more frequent chronic flooding occurring at high tides under calm weather conditions. Chronic flooding occasionally takes place today in the low-lying areas of the Petit Cul-de-sac marin (Guadeloupe, West Indies, French Antilles). This area includes critical industrial and harbor and major economic infrastructures for the islands. As sea level rises, concerns are growing regarding the possibility of repeated chronic flooding events, which would alter the operations at these critical coastal infrastructures without appropriate adaptation. Here, we use information on past and future sea levels, vertical ground motion, and tides to assess times of emergence of chronic flooding in the Petit Cul-de-sac marin. For RCP8.5 (Representative Concentration Pathway 8.5; i.e., continued growth of greenhouse gas emissions), the number of flood days is projected to increase rapidly after the emergence of the process so that coastal sites will be flooded 180 d a year within 2 decades of the onset of chronic flooding. For coastal locations with the lowest altitude, we show that the reconstructed number of floods is consistent with observations known from a previous survey. Vertical ground motions are a key source of uncertainty in our projections. Yet, our satellite interferometric synthetic-aperture radar results show that the local variability in this subsidence is smaller than the uncertainties in the technique, which we estimate to be between 1 (standard deviation of measurements) and 5 mm/yr (upper theoretical bound). Despite these uncertainties, our results imply that adaptation pathways considering a rapid increase in recurrent chronic flooding are required for the critical port and industrial and commercial center of Guadeloupe. Similar processes are expected to take place in many low-elevation coastal zones worldwide, including on other tropical islands. The method used in this study can be applied to other locations, provided tide gauge records and local knowledge of vertical ground motions are available. We argue that identifying times of emergence of chronic flooding events is urgently needed in most low-lying coastal areas, because adaptation requires decades to be implemented, whereas chronic flooding hazards can worsen drastically within years of the first event being observed.

ABSTRACT:Global mean sea level rise and its acceleration are projected to aggravate coastal erosion over the 21st century, which constitutes a major challenge for coastal adaptation. Projections of shoreline retreat are highly uncertain, however, namely due to deeply uncertain mean sea level projections and the absence of consensus on a coastal impact model. An improved understanding and a better quantification of these sources of deep uncertainty are hence required to improve coastal risk management and inform adaptation decisions. In this work we present and apply a new extraprobabilistic framework to develop shoreline change projections of sandy coasts that allows consideration of intrinsic (or aleatory) and knowledge-based (or epistemic) uncertainties exhaustively and transparently. This framework builds upon an empirical shoreline change model to which we ascribe possibility functions to represent deeply uncertain variables. The model is applied to two local sites in Aquitaine (France) and Castellón (Spain). First, we validate the framework against historical shoreline observations and then develop shoreline change projections that account for possible (although unlikely) low-end and high-end mean sea level scenarios. Our high-end projections show for instance that shoreline retreats of up to 200m in Aquitaine and 130m in Castellón are plausible by 2100, while low-end projections revealed that 58 and 37m modest shoreline retreats, respectively, are also plausible. Such extended intervals of possible future shoreline changes reflect an ambiguity in the probabilistic description of shoreline change projections, which could be substantially reduced by better constraining sea level rise (SLR) projections and improving coastal impact models. We found for instance that if mean sea level by 2100 does not exceed 1m, the ambiguity can be reduced by more than 50%. This could be achieved through an ambitious climate mitigation policy and improved knowledge on ice sheets. This research has been supported by the BRGM, IHCantabria and the ERA4CS-ECLISEA project (grant no. 690462).

Abstract. Chronic flooding, occurring at high tides under calm weather conditions, is occasionally taking place today in the low-lying areas of the Petit-Cul-de-sac marin (Guadeloupe, West Indies, French Antilles). This area includes critical industrial, harbor and major economic infrastructures for the island. As sea level rises, concerns are growing regarding the possibility for repeated chronic flooding events, which would alter the operations at these critical coastal infrastructures without appropriate adaptation. Here, we use information on past and future sea levels, vertical ground motion and tides to assess times of emergence of chronic flooding in the Petit-Cul-de-sac marin. For RCP8.5 (i.e., continued growth of greenhouse gas emissions), the number of flood days is projected to increase rapidly after the emergence of the process, so that coastal sites will be flooded every two days within 2 decades after the onset of chronic flooding. For coastal locations with the smallest altitude, we show that the reconstructed number of floods are consistent with observations known from a previous survey. One key uncertainty of our result is the actual rate of subsidence of the island. However, our satellite interferometric synthetic-aperture radar results show that the local variability of this subsidence is smaller than the uncertainties of the technique, which we estimate between 1 (standard deviation of measurements) and 5 mm/yr (upper theoretical bound). Our results imply that adaptation pathways considering a rapid increase of recurrent chronic flooding are required in the critical port, industrial and commercial center of Guadeloupe, as well as presumably in many low-elevation coastal zones of other tropical islands.