Suchergebnisse

Arctic feedbacks accelerate climate change through carbon releases from thawing permafrost and higher solar absorption from reductions in the surface albedo, following loss of sea ice and land snow. Here, we include dynamic emulators of complex physical models in the integrated assessment model PAGE-ICE to explore nonlinear transitions in the Arctic feedbacks and their subsequent impacts on the global climate and economy under the Paris Agreement scenarios. The permafrost feedback is increasingly positive in warmer climates, while the albedo feedback weakens as the ice and snow melt. Combined, these two factors lead to significant increases in the mean discounted economic effect of climate change: +4.0% ($24.8 trillion) under the 1.5 °C scenario, +5.5% ($33.8 trillion) under the 2 °C scenario, and +4.8% ($66.9 trillion) under mitigation levels consistent with the current national pledges. Considering the nonlinear Arctic feedbacks makes the 1.5 °C target marginally more economically attractive than the 2 °C target, although both are statistically equivalent. ; This work is part of the ICE-ARC project funded by the European Union's 7th Framework Programme, (grant 603887, contribution 006). D.Y. received additional funding from ERIM, Erasmus University Rotterdam, and Paul Ekins at the ISR, University College London. K.S. was funded by NSF (grant 1503559) and NASA (grants NNX14A154G, NNX17AC59A). E.J. was funded by the NGEE Arctic project supported by the BER Office of Science at the U.S. DOE. Y.E. was funded by the NSF (grant 1900795). E.B. was supported by the UK Met Office Hadley Centre Climate Programme funded by BEIS and DEFRA.

VTT Technology 43 ; This deliverable of EWENT project estimates the risks of extreme weather on European transport system. The main object of work package 5 in EWENT project was to perform a risk analysis based on impact and probability assessments carried out in earlier work packages (WP2-WP3). The results of WP 5 can be used as a starting point when deciding on the risk reduction measures, strategies and policies in the European Union. This deliverable also serves as a background material for the synthesis report (named shortly as Risk Panorama), which will summarise the findings of risk assessment and previous work packages. The methodological approach of EWENT is based on the generic risk management standard (IEC 60300-3-9) and starts with the identification of hazardous extreme weather phenomena, followed by an impact assessment and concluded by mitigation and risk control measures. This report pools the information from EWENT's earlier work packages, such as risk identification and estimation, into a 'risk panorama' and provides a holistic picture on the risks of extreme weather in different parts of Europe and EU transport network. The risk assessment is based on the definition of transport systems' vulnerability to extreme weather events in different countries and on calculations of the most probable causal chains, starting from adverse weather phenomena and ending up with events that pose harmful consequences to the transport systems in different climate regions. The latter part, the probabilistic section, is the hazard analysis. The vulnerability of a particular mode in a particular country is a function of exposure (indicated by transport or freight volumes and population density), susceptibility (infrastructure quality index, indicating overall resilience) and coping capacity (measured by GDP per capita). Hence, we define the extreme weather risk as Risk = hazard * vulnerability = P(negative consequences) * V[f(exposure, susceptibility, coping capacity)] Based on this analytical approach, risk indicators for each mode and country are presented. Due to the techniques used in calculations, the risk indicator is by definition a relative indicator, and must not be considered as an absolute measure of risk. It is a very robust ranking system, first and foremost. Country-specific vulnerability indicators and hazard indicators following the climatological division are also presented. In general, countries with poor quality infrastructures combined with high transport volumes and population densities are naturally at most risk. ; This deliverable of EWENT project estimates the risks of extreme weather on European transport system. The main object of work package 5 in EWENT project was to perform a risk analysis based on impact and probability assessments carried out in earlier work packages (WP2-WP3). The results of WP 5 can be used as a starting point when deciding on the risk reduction measures, strategies and policies in the European Union. This deliverable also serves as a background material for the synthesis report (named shortly as Risk Panorama), which will summarise the findings of risk assessment and previous work packages. The methodological approach of EWENT is based on the generic risk management standard (IEC 60300-3-9) and starts with the identification of hazardous extreme weather phenomena, followed by an impact assessment and concluded by mitigation and risk control measures. This report pools the information from EWENT's earlier work packages, such as risk identification and estimation, into a 'risk panorama' and provides a holistic picture on the risks of extreme weather in different parts of Europe and EU transport network. The risk assessment is based on the definition of transport systems' vulnerability to extreme weather events in different countries and on calculations of the most probable causal chains, starting from adverse weather phenomena and ending up with events that pose harmful consequences to the transport systems in different climate regions. The latter part, the probabilistic section, is the hazard analysis. The vulnerability of a particular mode in a particular country is a function of exposure (indicated by transport or freight volumes and population density), susceptibility (infrastructure quality index, indicating overall resilience) and coping capacity (measured by GDP per capita). Hence, we define the extreme weather risk as Risk = hazard * vulnerability = P(negative consequences) * V[f(exposure, susceptibility, coping capacity)] Based on this analytical approach, risk indicators for each mode and country are presented. Due to the techniques used in calculations, the risk indicator is by definition a relative indicator, and must not be considered as an absolute measure of risk. It is a very robust ranking system, first and foremost. Country-specific vulnerability indicators and hazard indicators following the climatological division are also presented. In general, countries with poor quality infrastructures combined with high transport volumes and population densities are naturally at most risk.