Search

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 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 °C, 2 °C 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 limit or prevent 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 FROM AUTHOR]

To predict future hydrological behavior in a changing world, often use is made of models calibrated on past observations, disregarding that hydrological systems, hence model parameters, will change as well. Yet, ecosystems likely adjust their root-zone storage capacity, which is the key parameter of any hydrological system, in response to climate change. In addition, other species might become dominant, both under natural and anthropogenic influence. In this study, we propose a top-down approach, which directly uses projected climate data to estimate how vegetation adapts its root-zone storage capacity at the catchment scale in response to changes in magnitude and seasonality of hydro-climatic variables. Additionally, the Budyko characteristics of different dominant ecosystems in sub-catchments are used to simulate the hydrological behavior of potential future land-use change, in a space-for-time exchange. We hypothesize that changes in the predicted hydrological response as a result of 2K global warming are more pronounced when explicitly considering changes in the sub-surface system properties induced by vegetation adaptation to changing environmental conditions. We test our hypothesis in the Meuse basin in four scenarios designed to predict the hydrological response to 2K global warming in comparison to current-day conditions using a process-based hydrological model with (a) a stationary system, i.e. no changes in the root-zone storage capacity of vegetation and historical land use, (b) an adapted root-zone storage capacity in response to a changing climate but with historical land use, and (c,d) an adapted root-zone storage capacity considering two hypothetical changes in land use from coniferous plantations/agriculture towards broadleaved forest and vice-versa. We found that the larger root-zone storage capacities (+34%) in response to a more pronounced seasonality with drier summers under 2K global warming strongly alter seasonal patterns of the hydrological response, with an overall increase in mean annual evaporation (+4%), a decrease in recharge (-6%) and a decrease in streamflow (-7%), compared to predictions with a stationary system. By integrating a time-dynamic representation of changing vegetation properties in hydrological models, we make a potential step towards more reliable hydrological predictions under change. [ABSTRACT FROM AUTHOR]

Single model large ensembles are widely used model experiments to estimate internal climate variability. The underlying assumption is that the internal variability (here: inter-annual variability) of the chosen model is a good approximation of the observed natural (inter-annual) variability. In this study, we test this assumption based on three regional climate model large ensembles (16 members of an EC-EARTH-RACMO ensemble, 21 members of a CESM-CCLM ensemble, 50 members of a CanESM-CRCM ensemble) for four European domains (British Isles, France, Mid-Europe, Alps). Simulated inter-annual variability is evaluated against E-OBS and the inter-annunal variability and its future change are compared across the ensembles. To the knowledge of the authors, this is the first comparison of regional large ensembles over Europe. Analysis comprises seasonal temperature and precipitation, as well as indicators for dry periods and heat waves. Results show a large consistency of all three ensembles with E-OBS data for most indicators and regions, validating the abilities of these ensembles to represent natural variability on the annual scale. EC-EARTH-RACMO shows the highest inter-annual variability for winter temperature and precipitation, whereas CESM-CCLM shows the highest variability for summer temperature and precipitation, as well as for heatwaves and dry periods. Despite these model differences, the sign of the future changes in internal variability is largely the same in all models: for summer temperature, summer precipitation and the number of heat waves, the internal variability increases, while it decreases for winter temperature. Changes of winter precipitation and dry periods are a bit unclear, with a tendency to increase for dry periods. The overall consistency across single model large ensembles and observations strengthens the concept of large ensembles, and underlines their great potential for understanding and quantifying the role of internal climate variability. [ABSTRACT FROM AUTHOR]

The extreme precipitation that would result in historic flooding across areas of northeastern France and southern Germany began on May 26th when a large cut-off low spurred the development of several slow moving low pressure disturbances. The precipitation took different forms in each country. Warm and humid air from the south fueled sustained, large-scale, heavy rainfall over France resulting in significant river flooding on the Seine and Loire (and their tributaries), whereas the rain came from smaller clusters of intense thunderstorms in Germany triggering flash floods in mountainous areas. The floods left tens of thousands without power, caused over a billion Euros in damage in France alone, and are reported to have killed at least 18 people in Germany, France, Romania, and Belgium. The extreme nature of this event left many asking whether anthropogenic climate change may have played a role. To answer this question objectively, a rapid attribution analysis was performed in near-real time, using the best available observational data and climate models. In this rapid attribution study, where results were completed and released to the public in one week and an additional week to finalise this article, we present a first estimate of how anthropogenic climate change affected the likelihood of meteorological variables corresponding to the event, 3-day precipitation averaged over the Seine and Loire basins and the spatial maximum of 1-day precipitation over southern Germany (excluding the Alps). We find that the precipitation in the Seine basin was very rare in April-June, with a return time of hundreds of years in this season. It was less rare on the Loire, roughly 1 in 50 years in April-June. At a given location the return times for 1-day precipitation as heavy as the highest observed in southern Germany is 1 in 3000 years in April-June. This translates to once roughly every 20 years somewhere in this region and season. The probability of 3-day extreme rainfall in this season has increased by about a factor 2.3 (> 1.6) on the Seine a factor 2.0 (> 1.4) on the Loire, with all four climate models that simulated the statistical properties of the extremes agreeing. The observed trend of heavy 1-day precipitation in southern Germany is significantly negative, whereas the one model that has the correct distribution simulates a significant positive trend, making an attribution statement for these thunderstorms impossible at this time. [ABSTRACT FROM AUTHOR]

In this contribution four case studies in the Netherlands are discussed, investigating the role of atmospheric drivers, the probability of occurrence of compound flood events and their impact on regional water systems, and the potential changes therein in a warming climate. Observations of extreme compound events are rare by definition and observational datasets are often too short to look far in the tail of the probability distribution of the relevant variables. Here we use a 16-member initial-condition ensemble generated with the global climate model EC-EARTH and further downscaled with the regional climate model KNMI-RACMO2 over Western Europe at 12 km spatial resolution for the period 1950-2100, forced with historical emissions until 2005, and the RCP8.5 emission scenario thereafter. Model time series are used to drive a North Sea surge model. The periods 1951-2000 and 2026-2075 were selected to study 16 x 50 years of current and future climate, respectively. Two of the case studies concern water systems in the north of the Netherlands for which discharge to sea under gravity is blocked when sea levels are too high. Historical data suggest a correlation between storm surges and precipitation. The RACMO EC-EARTH simulations are used to investigate this relation for the present-day and future climate. The relation found in the current climate simulations is similar to the relation in the observations, with the exception of the far tails of the probability distribution. We currently investigate whether the climate model is realistically capturing the synoptic-scale patterns associated to the most extreme observed events. Hydrological and hydraulic models are used to study the impact of compound flood events on the regional water systems and the effect of potential measures against flood risks. The third case study considers the Dommel and Aa rivers, which both discharge under gravity to the river Meuse. In 1993 and 1995 high discharges from these rivers occurred simultaneously with high Meuse water levels, which resulted in large inundations around the city of Den Bosch. Correlations between precipitation in the three river basins and the timing of peak discharges in RACMO EC-EARTH correspond to historical observations. The effect of joint occurrence of high discharges in the three rivers on water level statistics in the city is assessed using hydraulic models.The final case study considers the area of Brabantse Delta. In case of extreme storm surge at the North Sea, the coastal flood defense structures are closed and Rhine and Meuse rivers cannot discharge to the sea. When this jointly occurs with extreme discharges, the Rhine and Meuse are forced to discharge into lake Volkerak. Discharge of smaller local rivers into this lake is blocked when lake water levels rise too high, posing flood risk in the area. Hydrological, hydrologic and hydrodynamic models are used to investigated the joint occurrence of high sea water levels, high Rhine river discharges and high local river discharges. [ABSTRACT FROM AUTHOR]