Systemic risks emerging from global climate hotspots and their impacts on Europe

In a globalized world, Europe is increasingly affected by climate change events beyond its borders that propagate through our interconnected systems impacting the socio-economic welfare in Europe. The REmote Climate Effects and their Impact on European sustainability, Policy and Trade (RECEIPT) project uses a novel stakeholder-driven storytelling approach that maps representative connections between remote climate hazards such as droughts or hurricanes and European socio-economic activities in the agricultural, finance, development, shipping and manufacturing sectors. As part of RECEIPT, this work focuses on systemic risks in global climate risk hotspots and their knock-on effects on the European economy. In five stakeholder workshops, expert elicitation methods are used to identify and map sector- and storyline-specific systemic risks: interlinkages between different events, hidden causes and consequences, potential feedback loops, uncertainties and other systemic risk characteristics will be investigated. A special focus lies on “gray rhino” events, “foreseeable random surprises” that follow clear warning signs but are only known to a smaller group of people. Results reveal sector-specific “topographies of risk” within the storylines identified by stakeholders

Present and future atmospheric blocking and its impact on European mean and extreme climate

Atmospheric blocking plays an important role in the mid-latitude climate variability and can be responsible for anomalous mean and/or extreme climate. In this study, a potential vorticity based blocking indicator is used to investigate the representation of Euro-Atlantic atmospheric blocking events in the ECHAM5/MPI-OM climate model. The impact of blocking events on present and future mean and extreme climate is studied by means of composite maps and correlation analyses. In comparison to ERA-40 re-analysis, the model represents the blocking frequency and seasonal distribution well. We show that European blocking events have a sustained influence particularly on anomalous cold winter temperatures in Europe. In a future climate, the blocking frequency is slightly diminished but the influence on the European winter climate remains robust. Due to a northeastward shift of the blocking pattern and an increase in maximum blocking duration, cold winter temperature extremes can still be expected in a future climat

Better seasonal forecasts for the renewable energy industry

Anomalous seasons such as extremely cold winters or low-wind summers can seriously disrupt renewable energy productivity and reliability. Better seasonal forecasts providing more accurate information tailored to stakeholder needs can help the renewable energy industry prepare for such extremes.The authors acknowledge funding from the EU Horizon 2020 project “Sub-seasonal to seasonal climate forecasting for energy (S2S4E)” (GA776787).Peer ReviewedPostprint (author's final draft

When will unusual heat waves become normal in a warming Africa?

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Slow and fast response of mean and extreme precipitation to different forcing in CMIP5 simulations

We are investigating the fast and slow responses of changes in mean and extreme precipitation to different climate forcing mechanisms, such as greenhouse gas and solar forcing, to understand whether rapid adjustments are important for extreme precipitation. To disentangle the effect of rapid adjustment to a given forcing on the overall change in extreme precipitation we use a linear regression method that has been previously applied to mean precipitation. Equilibrium experiments with preindustrial CO2 concentrations and reduced solar constant were compared with a four times CO2 concentration experiment for 10 state-of-the-art climate models. We find that the two forcing mechanisms, greenhouse gases and solar, impose clearly different rapid adjustment signals in the mean precipitation, while such difference is difficult to discern for extreme precipitation due to large internal variability. In contrast to mean precipitation, changes in extreme precipitation scale with surface temperature trends and do not seem to depend on the forcing mechanism

Local biomass burning is a dominant cause of the observed precipitation reduction in southern Africa

Observations indicate a precipitation decline over large parts of southern Africa since the 1950s. Concurrently, atmospheric concentrations of greenhouse gases and aerosols have increased due to anthropogenic activities. Here we show that local black carbon and organic carbon aerosol emissions from biomass burning activities are a main cause of the observed decline in southern African dry season precipitation over the last century. Near the main biomass burning regions, global and regional modelling indicates precipitation decreases of 20–30%, with large spatial variability. Increasing global CO2 concentrations further contribute to precipitation reductions, somewhat less in magnitude but covering a larger area. Whereas precipitation changes from increased CO2 are driven by large-scale circulation changes, the increase in biomass burning aerosols causes local drying of the atmosphere. This study illustrates that reducing local biomass burning aerosol emissions may be a useful way to mitigate reduced rainfall in the region

Gaussian copula modeling of extreme cold and weak-wind events over Europe conditioned on winter weather regimes

A transition to renewable energy is needed to mitigate climate change. In Europe, this transition has been led by wind energy, which is one of the fastest growing energy sources. However, energy demand and production are sensitive to meteorological conditions and atmospheric variability at multiple time scales. To accomplish the required balance between these two variables, critical conditions of high demand and low wind energy supply must be considered in the design of energy systems. We describe a methodology for modeling joint distributions of meteorological variables without making any assumptions about their marginal distributions. In this context, Gaussian copulas are used to model the correlated nature of cold and weak-wind events. The marginal distributions are modeled with logistic regressions defining two sets of binary variables as predictors: four large-scale weather regimes and the months of the extended winter season. By applying this framework to ERA5 data, we can compute the joint probabilities of co-occurrence of cold and weak-wind events on a high-resolution grid (0.25 deg). Our results show that a) weather regimes must be considered when modeling cold and weak-wind events, b) it is essential to account for the correlations between these events when modeling their joint distribution, c) we need to analyze each month separately, and d) the highest estimated number of days with compound events are associated with the negative phase of the North Atlantic Oscillation (3 days on average over Finland, Ireland, and Lithuania in January, and France and Luxembourg in February) and the Scandinavian Blocking pattern (3 days on average over Ireland in January and Denmark in February). This information could be relevant for application in sub-seasonal to seasonal forecasts of such events

Aerosol effect on climate extremes in Europe under different future scenarios

This study investigates changes in extreme temperature and precipitation events under different future scenarios of anthropogenic aerosol emissions (i.e., SO2 and black and organic carbon) simulated with an aerosol-climate model (ECHAM5-HAM) with focus on Europe. The simulations include a maximum feasible aerosol reduction (MFR) scenario and a current legislation emission (CLEmod) scenario where Europe implements the MFR scenario, but the rest of the world follows the current legislation scenario and a greenhouse gas scenario. The strongest changes relative to the year 2000 are projected for the MFR scenario, in which the global aerosol reduction greatly enforces the general warming effect due to greenhouse gases and results in significant increases of temperature and precipitation extremes in Europe. Regional warming effects can also be identified from aerosol reductions under the CLEmodscenario. This becomes most obvious in the increase of the hottest summer daytime temperatures in Northern Europe. © 2013 American Geophysical Union. All Rights Reserved

The EU needs a demand-driven innovation policy for climate services

Climate services have climbed high on the agenda of EU research policy, yet few contributions have reflected on the actual usability of climate services from the perspectives of the intended users, let alone the implications for future EU research and innovation policy. This commentary reflects on four key lessons learnt from engagement in climate services research projects and discusses implications for future EU research policy: i) all end-users have pre-established decision-making processes and tools for their purposes, hence all new information needs to be adapted ii) one size fits none – and tailoring takes time iii) building trust between different actors, processes and confidence in new information is key in the tailoring process – and resource-demanding iv) purveyors and intermediaries can facilitate tailoring processes but need to finance their activities until end-users demonstrate willingness to pay and/or the climate service is readily implemented. The main argument is that more attention needs to be paid to the demand-side of climate services to help viable climate services make it through the innovation “valley of death” – that is, the twilight zone between technical invention and (commercially) successful innovation. EU Research and Innovation (R&I) funding streams and policies for establishing truly transdisciplinary learning loops driven by (actual) user needs can function as vehicles through the valley of death.This research was funded by the EU Horizon 2020 program under grant agreement number 776787.Peer ReviewedPostprint (published version

Gaussian copula modeling of extreme cold and weak-wind events over Europe conditioned on winter weather regimes

A transition to renewable energy is needed to mitigate climate change. In Europe, this transition has been led by wind energy, which is one of the fastest growing energy sources. However, energy demand and production are sensitive to meteorological conditions and atmospheric variability at multiple time scales. To accomplish the required balance between these two variables, critical conditions of high demand and low wind energy supply must be considered in the design of energy systems. We describe a methodology for modeling joint distributions of meteorological variables without making any assumptions about their marginal distributions. In this context, Gaussian copulas are used to model the correlated nature of cold and weak-wind events. The marginal distributions are modeled with logistic regressions defining two sets of binary variables as predictors: four large-scale weather regimes (WRs) and the months of the extended winter season. By applying this framework to ERA5 data, we can compute the joint probabilities of co-occurrence of cold and weak-wind events on a high-resolution grid .Our results show that (a) WRs must be considered when modeling cold and weak-wind events, (b) it is essential to account for the correlations between these events when modeling their joint distribution, (c) we need to analyze each month separately, and (d) the highest estimated number of days with compound events are associated with the negative phase of the North Atlantic Oscillation (3 days on average over Finland, Ireland, and Lithuania in January, and France and Luxembourg in February) and the Scandinavian blocking pattern (3 days on average over Ireland in January and Denmark in February). This information could be relevant for application in sub-seasonal to seasonal forecasts of such events