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Advances in the field of extreme event attribution allow to estimate how anthropogenic global warming affects the odds of individual climate disasters, such as river floods. Extreme event attribution typically uses precipitation as proxy for flooding. However, hydrological processes and antecedent conditions make the relation between precipitation and floods highly nonlinear. In addition, hydrology acknowledges that changes in floods can be strongly driven by changes in land‐cover and by other human interventions in the hydrological system, such as irrigation and construction of dams. These drivers can either amplify, dampen or outweigh the effect of climate change on local flood occurrence. Neglecting these processes and drivers can lead to incorrect flood attribution. Including flooding explicitly, that is, using data and models of hydrology and hydrodynamics that can represent the relevant hydrological processes, will lead to more robust event attribution, and will account for the role of other drivers beyond climate change. Existing attempts are incomplete. We argue that the existing probabilistic framework for extreme event attribution can be extended to explicitly include floods for near‐natural cases, where flood occurrence was unlikely to be influenced by land‐cover change and human hydrological interventions. However, for the many cases where this assumption is not valid, a multi‐driver framework for conditional event attribution needs to be established. Explicit flood attribution will have to grapple with uncertainties from lack of observations and compounding from the many processes involved. Further, it requires collaboration between climatologists and hydrologists, and promises to better address the needs of flood risk management. This article is categorized under:Paleoclimates and Current Trends > Modern Climate ChangePaleoclimates and Current Trends > Detection and AttributionAssessing Impacts of Climate Change > Observed Impacts of Climate Change Drivers of river floods change through time. Global warming, and associated changes in temperature and precipitation, often overlap with changes in the hydrology, such as land‐cover change, construction of levees and large‐scale irrigation. This poses a special challenge to the attribution of flood events.

The temporal trend of wind speed near the surface over land has been investigated over recent decades. A prevailing trend of decline was found in several studies for most areas in the Northern hemisphere, denoted as terrestrial stilling, with multiple causes being discussed. In this study, we focus on the impact of changes of surface roughness due to changes in land‐use and vegetation cover on this variable for western Europe using the regional climate model RACMO driven by ERA5 reanalysis. We conduct two simulations at climate scale, with and without changes in land‐use and vegetation on a yearly basis. We find that upper level large‐scale circulation slowing down results in declining near surface mean wind speed, and that increases in surface roughness due to changes in land use and vegetation cover play an important role in intensifying this declining trend from our simulations with RACMO. However, the trends inferred from the model simulations and ERA5 are not consistent with trends derived from gridded observations database E‐OBS. This could come from the complexity of integrating in‐situ measurements with uncorrectable inhomogeneity to derive E‐OBS. Wind speed near the surface (10 m above ground) has been declining over many areas in the Northern hemisphere, denoted as terrestrial stilling. This declining trend can be affected by different factors such as increase in surface roughness due to land‐use and vegetation cover changes, large‐scale circulation changes, anthropogenic aerosols and climate change due to greenhouse gas concentration increase. In this study, we focus on the impact of changes in land‐use and vegetation cover on this variable for western Europe using a regional climate model RACMO. We simulate wind speed using two model setups, with and without changes in land‐use and vegetation on a yearly basis. We find that a slowing down of the upper level large‐scale circulation results in a decline of the near‐surface mean wind speed. In addition, we find that based on the difference between our two simulations with RACMO, increases in surface roughness due to changes in land use and vegetation cover intensify this declining trend in near‐surface mean wind speed. Wind speed has been decreasing over a large part of western Europe from the surface to 500 hPa according to ERA5 reanalysisRegional climate model simulations forced by ERA5 can reproduce those large‐scale features of wind speed wellThe increase in surface roughness intensifies those large‐scale decreasing trends of near surface wind speed at regional and local scales Wind speed has been decreasing over a large part of western Europe from the surface to 500 hPa according to ERA5 reanalysis Regional climate model simulations forced by ERA5 can reproduce those large‐scale features of wind speed well The increase in surface roughness intensifies those large‐scale decreasing trends of near surface wind speed at regional and local scales

For Northern Hemisphere extra-tropical cyclone activity, the dependency of a potential anthropogenic climate change signal on the identification method applied is analysed. This study investigates the impact of the used algorithm on the changing signal, not the robustness of the climate change signal itself. Using one single transient AOGCM simulation as standard input for eleven state-of-the-art identification methods, the patterns of model simulated present day climatologies are found to be close to those computed from re-analysis, independent of the method applied. Although differences in the total number of cyclones identified exist, the climate change signals (IPCC SRES A1B) in the model run considered are largely similar between methods for all cyclones. Taking into account all tracks, decreasing numbers are found in the Mediterranean, the Arctic in the Barents and Greenland Seas, the mid-latitude Pacific and North America. Changing patterns are even more similar, if only the most severe systems are considered: the methods reveal a coherent statistically significant increase in frequency over the eastern North Atlantic and North Pacific. We found that the differences between the methods considered are largely due to the different role of weaker systems in the specific methods.