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The quest for hydrological hyper-resolution modelling has been on-going for more than a decade. While global hydrological models (GHMs) have seen a reduction in grid size, they have thus far never been consistently applied at a hyper-resolution (<=1 km) at the large scale. Here, we present the first application of the GHM PCR-GLOBWB at 1 km over Europe. We thoroughly evaluated simulated discharge, evaporation, soil moisture, and terrestrial water storage anomalies against long-term observations and subsequently compared results with the established 10 and 50 km resolutions of PCR-GLOBWB. Subsequently, we could assess the added value of this first hyper-resolution version of PCR-GLOBWB and assess the scale dependencies of model and forcing resolution. Eventually, these insights can help us in understanding the current challenges and opportunities from hyper-resolution models and in formulating the model and data requirements for future improvements. We found that, for most variables, epistemic uncertainty is still large, and issues with scale commensurability exist with respect to the long-term yet coarse observations used. Merely for simulated discharge, we can confidently state that model output at hyper-resolution improves over coarser resolutions due to better representation of the river network at 1 km. However, currently available observations are not yet widely available at hyper-resolution or lack a sufficiently long time series, which makes it difficult to assess the performance of the model for other variables at hyper-resolution. Here, additional model validation efforts are needed. On the model side, hyper-resolution applications require careful revisiting of model parameterization and possibly the implementation of more physical processes to be able to resemble the dynamics and spatial heterogeneity at 1 km. With this first application of PCR-GLOBWB at 1 km, we contribute to meeting the grand challenge of hyper-resolution modelling. Even though the model was only assessed at the continental scale, valuable insights could be gained which have global validity. As such, it should be seen as a modest milestone on a longer journey towards locally relevant model output. This, however, requires a community effort from domain experts, model developers, research software engineers, and data providers. [ABSTRACT FROM AUTHOR]

Three consecutive dry summers in western Europe (2018–2019–2020) had widespread negative impacts on society and ecosystems, and started societal debate on (changing) drought vulnerability and adaptation measures. We investigate the occurrence of multi-year droughts in the Rhine basin, with a focus on event probability in the present and in future warmer climates. Additionally, we investigate the temporally compounding physical drivers of multi-year drought events. A combination of multiple reanalysis datasets and multi-model large ensemble climate model simulations was used to provide a robust analysis of the statistics and physical processes of these rare events. We identify two types of multi-year drought events (consecutive meteorological summer droughts and long-duration hydrological droughts), and show that these occur on average about twice in a 30 year period in the present climate, though natural variability is large (zero to five events can occur in a single 30 year period). Projected decreases in summer precipitation and increases in atmospheric evaporative demand, lead to a doubling of event probability at 1 ∘ C additional global warming relative to present-day and an increase in the average length of events. Consecutive meteorological summer droughts are forced by two, seemingly independent, summers of lower than normal precipitation and higher than normal evaporative demand. The soil moisture response to this temporally compound meteorological forcing has a clear multi-year imprint, resulting in a relatively larger reduction of soil moisture content in the second year of drought, and potentially more severe drought impacts. Long-duration hydrological droughts start with a severe summer drought followed by lingering meteorologically dry conditions. This limits and slows down the hydrological recovery of soil moisture content, leading to long-lasting drought conditions. This initial exploration provides avenues for further investigation of multi-year drought hazard and vulnerability in the region, which is advised given the projected trends and vulnerability of society and ecosystems. [ABSTRACT FROM AUTHOR]

We analysed gross primary productivity (GPP), total ecosystem respiration (TER) and the resulting net ecosystem exchange (NEE) of carbon dioxide (CO2) by the terrestrial biosphere during the summer of 2018 through observed changes across the Integrated Carbon Observation System (ICOS) network, through biosphere and inverse modelling, and through remote sensing. Highly correlated yet independently-derived reductions in productivity from sun-induced fluorescence, vegetative near-infrared reflectance, and GPP simulated by the Simple Biosphere model version 4 (SiB4) suggest a 130–340 TgC GPP reduction in July–August–September (JAS) of 2018. This occurs over an area of 1.6 × 106 km2 with anomalously low precipitation in northwestern and central Europe. In this drought-affected area, reduced GPP, TER, NEE and soil moisture at ICOS ecosystem sites are reproduced satisfactorily by the SiB4 model. We found that, in contrast to the preceding 5 years, low soil moisture is the main stress factor across the affected area. SiB4's NEE reduction by 57 TgC for JAS coincides with anomalously high atmospheric CO2 observations in 2018, and this is closely matched by the NEE anomaly derived by CarbonTracker Europe (52 to 83 TgC). Increased NEE during the spring (May–June) of 2018 (SiB4 −52 TgC; CTE −46 to −55 TgC) largely offset this loss, as ecosystems took advantage of favourable growth conditions. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'. [ABSTRACT FROM AUTHOR]

Simulations of water fluxes at high spatial resolution that consistently cover historical observations, seasonal forecasts, and future climate projections are key to providing climate services aimed at supporting operational and strategic planning, and developing mitigation and adaptation policies. The End-to-end Demonstrator for improved decision-making in the water sector in Europe (EDgE) is a proof-of-concept project funded by the Copernicus Climate Change Service program that addresses these requirements by combining a multimodel ensemble of state-of-the-art climate model outputs and hydrological models to deliver sectoral climate impact indicators (SCIIs) codesigned with private and public water sector stakeholders from three contrasting European countries. The final product of EDgE is a water-oriented information system implemented through a web application. Here, we present the underlying structure of the EDgE modeling chain, which is composed of four phases: 1) climate data processing, 2) hydrological modeling, 3) stakeholder codesign and SCII estimation, and 4) uncertainty and skill assessments. Daily temperature and precipitation from observational datasets, four climate models for seasonal forecasts, and five climate models under two emission scenarios are consistently downscaled to 5-km spatial resolution to ensure locally relevant simulations based on four hydrological models. The consistency of the hydrological models is guaranteed by using identical input data for land surface parameterizations. The multimodel outputs are composed of 65 years of historical observations, a 19-yr ensemble of seasonal hindcasts, and a century-long ensemble of climate impact projections. These unique, high-resolution hydroclimatic simulations and SCIIs provide an unprecedented information system for decision-making over Europe and can serve as a template for water-related climate services in other regions. [ABSTRACT FROM AUTHOR]

Hydrological forecasts with a high temporal and spatial resolution are required to provide the level of information needed by end users. So far high-resolution multimodel seasonal hydrological forecasts have been unavailable due to 1) lack of availability of high-resolution meteorological seasonal forecasts, requiring temporal and spatial downscaling; 2) a mismatch between the provided seasonal forecast information and the user needs; and 3) lack of consistency between the hydrological model outputs to generate multimodel seasonal hydrological forecasts. As part of the End-to-End Demonstrator for Improved Decision Making in the Water Sector in Europe (EDgE) project commissioned by the Copernicus Climate Change Service (ECMWF), this study provides a unique dataset of seasonal hydrological forecasts derived from four general circulation models [CanCM4, GFDL Forecast-Oriented Low Ocean Resolution version of CM2.5 (GFDL-FLOR), ECMWF Season Forecast System 4 (ECMWF-S4), and Météo-France LFPW] in combination with four hydrological models [mesoscale hydrologic model (mHM), Noah-MP, PCRaster Global Water Balance (PCR-GLOBWB), and VIC]. The forecasts are provided at daily resolution, 6-month lead time, and 5-km spatial resolution over the historical period from 1993 to 2012. Consistency in hydrological model parameterization ensures an increased consistency in the hydrological forecasts. Results show that skillful discharge forecasts can be made throughout Europe up to 3 months in advance, with predictability up to 6 months for northern Europe resulting from the improved predictability of the spring snowmelt. The new system provides an unprecedented ensemble of seasonal hydrological forecasts with significant skill over Europe to support water management. This study highlights the potential advantages of multimodel based forecasting system in providing skillful hydrological forecasts. [ABSTRACT FROM AUTHOR]

To support the decision-making process at seasonal time scales, hydrological forecasts with a high temporal and spatial resolution are required to provide the level of information needed by water managers. Following the 2018 Northwest European drought, seasonal forecasting became one of the major focus points of European water managers.As part of the EDgE (End-to-end Demonstrator for improved decision making in the water sector in Europe) project commissioned by ECMWF (C3S), we have created a unique dataset of hydrological seasonal forecasts derived from four global climate models (CanCM4, FLOR-B01, ECMF, LFPW) in combination with four global hydrological models (GHMs: PCR-GLOBWB, VIC, mHM, Noah-MP). The forecasts are provided at a daily temporal resolution and 5-km spatial resolution and are bias corrected against E-OBS meteorological observations.Results show that skillful discharge forecasts can be made throughout Europe 3 months in advance, with predictability up to 6 months for Northern Europe due to the impact of snow. Drought forecasts have high skill over Europe due to the large spatial and temporal extent of drought events that is picked up by the seasonal forecasts. The model forecast skill is model dependent, where some GHMs show high skill for high flows, whereas other GHMs have a superior performance with regard to seasonal forecasting of low flows. Finally, the results indicate that the initial model conditions can dominate the forecast skill for multiple months.Even though multi-model seasonal forecast systems like EDgE show a great potential, the communication of the skills of these multi-model systems remains challenging. For drought mitigation, water managers indicated that long lead times are required to deploy low cost, low regret mitigation strategies. Flood mitigation was not helped by the use of seasonal forecast, because the costs of preventive actions are high and the high uncertainty in the forecast made it unsuitable to support decision making. In the end, water managers indicated that they are helped by simplified metrics of uncertainty rather than getting the full uncertainty information for the forecast system.Overall, we conclude that multi-model systems have an advantage as they are better capable of capturing the uncertainty of a forecast, but are challenging when it comes to real-time decision making and operational applications. [ABSTRACT FROM AUTHOR]

Groundwater is the primary source of water supply for sustaining the lives of billion ofpeople and surrounding ecosystems around the Globe. Climate change and variabilitythreaten the sustainable use of renewable groundwater resources in many regions across theWorld. Yet the assessment on the effects of global warming on projected estimates ofrenewable groundwater resources and uncertainties surrounding those estimates at alocally relevant scale is lacking. Here, we provide a comprehensive, continental-scaleassessment of past, present, and future changes in renewable groundwater resources(as a form of groundwater recharge after being suitably aggregated to longer timescales) across Europe at an unprecedented spatial resolution of (5 X 5) km2 andlocal groundwater bodies as per the European Water Framework Directive (WFD).Specifically our aim here is to understand the response of Europe-wide groundwaterresources to different global warming levels in accordance to 2015 IPCC Parisagreement. Our analyses are based on multi-model ensemble simulations from theEDgE1 and HOKLIM2 projects (funded by ECMWF and BMBF-Germany) whichcomprises of four hydrologic and land-surface models (HMs: mHM, Noah-MP,PCR-GLOBWB, and VIC) driven by a suitably downscaled, observation basedE-OBS forcing data for the historical records (1950-2015) and five bias correctedCMIP5 GCMs datasets for the near-past to future climate conditions (1970-2100)under three representative concentration pathways (RCPs: 2.6, 6.0, and 8.5). Atime-sampling approach is applied to identify 30-year periods with distinct warming levelscorresponding to global surface air temperature increase of 1.5, 2.0, and 3.0 K compared tothe pre-industrial levels. We contrast the changes in the multi-model ensemblerecharge between the periods of distinct warming levels and to the contemporaryconditions (1971-2000). Our analyses show a clear North-South gradient of changes inmean annual recharge across Europe with declining trends being observed in theMediterranean region, and increased availability of groundwater resources in theNorth Scandinavian region with increased warming (at end of the Century). Thecontinental part of the Europe shows relatively lower changes in the mean renewablegroundwater resources. A greater sensitivity/amplifications in changes are noticed in theMediterranean region to the response of increased warming levels. Though limited, but ourensemble simulations allow disentangling the different sources of uncertainties(HMs vs. GCMs) – which generally pointed out a larger chunk of uncertainty inmodeling results arises due to differences among GCMs (forcings); but there are clearlyareas where the uncertainty due to (different process representation of) HMs issubstantial, and can not be neglected. Overall, our study underscores the need formulti-model ensembles for the assessment of future changes in renewable groundwaterresources across Europe, and discuss about related impacts avoided in higher warmingworlds. 1. www.edge.climate.copernicus.eu 2. www.ufz.de/hoklim [ABSTRACT FROM AUTHOR]

The link between soil moisture (SM) and maximum daily temperature (TX) leading to themutual enhancement of droughts and heatwaves has been established in the literature.Moreover, it is expected that the intensify of this feedback will increase in the futurebecause of climate change (1,2). This phenomenon will have serious consequencesfor the society and the ecosystems. For example, in extreme drought situations,ecosystems will be transformed from net carbon sinks to net carbon sources whilethe extreme heat and drought conditions will induce societal impacts that will becritical for the human health, food security and energy generation. Concludingstatements regarding the degree of enhancement caused by soil moisture droughtson heatwaves have not been drawn for several reasons. The main reasons for thelack of progress can be attributed to the large uncertainties in projected changesusing emission scenarios that cover a wide range of temperature projections, thecoarse spatial and temporal resolution of the existing simulations, and the lack of ametric tailored to quantify the SM-TX enhancement as a function of the degree ofwarming. Our analysis is driven by the hypothesis that mutual enhancement between soil moisturedroughts and heat waves is intensified as the climate warms. EDgE and HOKLIM (3,4)projects provide an unique opportunity to test this hypothesis because high-resolutionmulti-model hydrologic simulations over the Pan-EU domain at a scale of 5x5 km2 have beencompleted for the historical period 1955-2018 using the E-OBS data set and from 2000-2100based on five CMIP5 GCMs under three representative concentration pathways (2.6, 6.0, 8.5).All simulations were carried put with four hydrologic models: mHM, Noah-MP,PCR-GLOBWB and VIC. Using these unprecedented multi-model simulations, daily soilmoisture index (2) and a percentile based heat wave index (5) are estimated for thehistorical and future periods. A copula-based metric that estimate the strength of thestochastic dependence between these two indices is used to quantity their mutualenhancement for a given lag time. Additionally, based on these simulations, theevolution of past larger events (e.g., 1976, 2003, 2018) will be also analysed toestimate the size of areas enduring combined extreme drought&#x0026;heatwaves since1955. Results confirm the hypothesis that "rising global temperature will bring drier soils andhigher heatwave temperatures in Europe" at the daily time scale. The mean area underheatwaves with a magnitude of greater than 11 will increase from 5% under 1.5K to 18% under 3 K global warming. With respect to the mutual enhancement,at least 25% increase in the SM-TX feedback can be expected by 3 K warming.Ensemble results also show that the uncertainty of the enhancement decreases withlag time (up to 25 days) and the degree of warming level. Different HMs showvarying sensitivity to the enhancement metric at different SM lag times. Theseexpected changes would bring unprecedented socio-economic consequences toEurope. Being able to better predict such hot-spot regions will allow mitigatingtheir impacts and reducing socio-economic losses and saving human lives in theFuture. A. J. Teuling, https://www.nature.com/articles/s41558-018-0154-5 L. Samaniego et al. https://www.nature.com/articles/s41558-018-0138-5 edge.climate.copernicus.eu www.ufz.de/hoklim S. Russo et al. http://iopscience.iop.org/article/10.1088/1748-9326/10/12/124003/meta [ABSTRACT FROM AUTHOR]