Abstract. EURO-CORDEX (Coordinated Downscaling Experiment over Europe), a new generation of downscaled climate projections, has become available for climate change impact studies in Europe. New opportunities arise in the investigation of potential effects of a warmer world on meteorological and hydrological extremes at regional scales. In this work, an ensemble of EURO-CORDEX RCP8.5 scenarios is used to drive a distributed hydrological model and assess the projected changes in flood hazard in Europe through the current century. Changes in magnitude and frequency of extreme streamflow events are investigated by statistical distribution fitting and peak over threshold analysis. A consistent method is proposed to evaluate the agreement of ensemble projections. Results indicate that the change in frequency of discharge extremes is likely to have a larger impact on the overall flood hazard as compared to the change in their magnitude. On average, in Europe, flood peaks with return periods above 100 years are projected to double in frequency within 3 decades.

Changes in vegetation cover associated with the observed greening may affect several biophysical processes, whose net effects on climate are unclear. We analyzed remotely sensed dynamics in leaf area index (LAI) and energy fluxes in order to explore the associated variation in local climate. We show that the increasing trend in LAI contributed to the warming of boreal zones through a reduction of surface albedo and to an evaporation-driven cooling in arid regions. The interplay between LAI and surface biophysics is amplified up to five times under extreme warm-dry and cold-wet years. Altogether, these signals reveal that the recent dynamics in global vegetation have had relevant biophysical impacts on the local climates and should be considered in the design of local mitigation and adaptation plans.

Abstract. There is growing concern in Europe about the possible rise in the severity and frequency of extreme drought events as a manifestation of climate change. In order to plan suitable adaptation strategies it is important for decision makers to know how drought conditions will develop at regional scales. This paper therefore addresses the issue of future developments in streamflow drought characteristics across Europe. Through offline coupling of a hydrological model with an ensemble of bias-corrected climate simulations (IPCC SRES A1B) and a water use scenario (Economy First), long-term (1961-2100) ensemble streamflow simulations are generated that account for changes in climate, and the uncertainty therein, and in water consumption. Using extreme value analysis we derive minimum flow and deficit indices and evaluate how the magnitude and severity of lowflow conditions may evolve throughout the 21st century. This analysis shows that streamflow droughts will become more severe and persistent in many parts of Europe due to climate change, except for northern and northeastern parts of Europe. In particular, southern regions will face strong reductions in low flows. Future water use will aggravate the situation by 10-30 % in southern Europe, whereas in some sub-regions in western, central and eastern Europe a climate-driven signal of reduced droughts may be reversed due to intensive water use. The multi-model ensemble projections of more frequent and severe streamflow droughts in the south and decreasing drought hazard in the north are highly significant, while the projected changes are more dissonant in a transition zone in between.

European Commission.

While reported losses of climate-related hazards are at historically high levels, climate change is likely to enhance the risk posed by extreme weather events. Several regions are likely to be exposed to multiple climate hazards, yet their modeling in a joint scheme is still at the early stages. A multi-hazard framework to map exposure to multiple climate extremes in Europe along the twenty-first century is hereby presented. Using an ensemble of climate projections, changes in the frequency of heat and cold waves, river and coastal flooding, streamflow droughts, wildfires and windstorms are evaluated. Corresponding variations in expected annual exposure allow for a quantitative comparison of hazards described by different process characteristics and metrics. Projected changes in exposure depict important variations in hazard scenarios, especially those linked to rising temperatures, and spatial patterns largely modulated by local climate conditions. Results show that Europe will likely Climatic Change (2016)

No abstract

Forest ecosystems depend on their capacity to withstand and recover from natural and anthropogenic perturbations (that is, their resilience)1. Experimental evidence of sudden increases in tree mortality is raising concerns about variation in forest resilience2, yet little is known about how it is evolving in response to climate change. Here we integrate satellite-based vegetation indices with machine learning to show how forest resilience, quantified in terms of critical slowing down indicators3–5, has changed during the period 2000–2020. We show that tropical, arid and temperate forests are experiencing a significant decline in resilience, probably related to increased water limitations and climate variability. By contrast, boreal forests show divergent local patterns with an average increasing trend in resilience, probably benefiting from warming and CO2 fertilization, which may outweigh the adverse effects of climate change. These patterns emerge consistently in both managed and intact forests, corroborating the existence of common large-scale climate drivers. Reductions in resilience are statistically linked to abrupt declines in forest primary productivity, occurring in response to slow drifting towards a critical resilience threshold. Approximately 23% of intact undisturbed forests, corresponding to 3.32 Pg C of gross primary productivity, have already reached a critical threshold and are experiencing a further degradation in resilience. Together, these signals reveal a widespread decline in the capacity of forests to withstand perturbation that should be accounted for in the design of land-based mitigation and adaptation plans.

The North American monsoon (NAM) leads to a large increase in summer rainfall and a seasonal change in vegetation in the southwestern United States and northwestern Mexico. Understanding the interactions between NAM rainfall and vegetation dynamics is essential for improved climate and hydrologic prediction. In this work, the authors analyze long-term vegetation dynamics over the North American Monsoon Experiment (NAME) tier I domain (208-358N, 1058-1158W) using normalized difference vegetation index (NDVI) semimonthly composites at 8-km resolution from 1982 to 2006. The authors derive ecoregions with similar vegetation dynamics using principal component analysis and cluster identification. Based on ecoregion and pixel-scale analyses, this study quantifies the seasonal and interannual vegetation variations, their dependence on geographic position and terrain attributes, and the presence of long-term trends through a set of phenological vegetation metrics. Results reveal that seasonal biomass productivity, as captured by the timeintegrated NDVI (TINDVI), is an excellent means to synthesize vegetation dynamics. High TINDVI occurs for ecosystems with a short period of intense greening tuned to the NAM or with a prolonged period of moderate greenness continuing after the NAM. These cases represent different plant strategies (deciduous versus evergreen) that can be adjusted along spatial gradients to cope with seasonal water availability. Longterm trends in TINDVI may also indicate changing conditions favoring ecosystems that intensively use NAM rainfall for rapid productivity, as opposed to delayed and moderate greening. A persistence of these trends could potentially result in the spatial reorganization of ecosystems in the NAM region.