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AVOID Work Stream 1: THE ECONOMICS AND CLIMATE CHANGE IMPACTS OF GREENHOUSE GAS EMISSION PATHWAYS: COMPARISON BETWEEN BASELINE & POLICY EMISSION SCENARIOS Rachel Warren (Lead WS1 and CIAS), Tyndall Centre, School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ Nigel Arnell (QUEST-GSI), Walker Institute, University of Reading, Earley Gate, Reading Pam Berry, Environmental Change Institute, University of Oxford, Dyson Perrins Building, South Parks Road, Oxford OX1 3QY Lynn Dicks and Serban Scriecru, 4CMR, Dept of Land Economy, University of Cambridge, 19 Silver St., Cambridge Chris Hope, 4 Judge Business School, University of Cambridge Jason Lowe, Met Office Hadley Centre (Reading Unit), Department of Meteorology, University of Reading, Reading, RG6 6BB Kenichi Matsumoto and Toshihiko Masui Climate Policy Assessment Section, Center for Global Environmental Research, National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba, Ibaraki, 305-8506, Japan Robert Nicholls, School of Civil Engineering and the Environment and Tyndall Centre, University of Southampton, Southampton SO17 1BJ Jesse O’Hanley, Kent Business School, University of Kent, Canterbury CT2 7PE Tim Osborn and Sarah Raper, Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ AVOID is funded by the Department of Energy and Climate Change and the Department for Environment, Food and Rural Affairs The modelling approach • Consistent climate scenarios • IPCC AR4 runs pattern-scaled to AVOID global temperature change • Monthly climate changes from downscaling (e.g. precipitation, temperature) • Consistent socio-economic scenarios • A1B baseline – median temperature rise of 4°C in 2100 above pre-industrial levels • Global-scale impacts models • Applied tools produced by QUEST-gsi and CIAS The Scenarios • Emission scenarios: varied year in which emissions peak globally, the rate of emission reduction (R), and the minimum level to which emissions are eventually reduced (H or L). • Focused on 2015-2044 (centred on 2030) 2035-2064 (centred on 2050) 2070-2099 (centred on 2085) Scenarios: A1B, and policy scenarios • 2030.R2.H, 2030.R5.L, • 2016.R2.H, 2016.R4.L and 2016.R.Low Temperature implications: Jason Lowe’s analysis showed that … Probability Year … A1B 2016.R 2030.R (2%H, 4%L, 5%L) (2%H, 5%L) of remaining below 2 degrees 2100 1% 30, 43, 45% 7, 17% of remaining below 3 degrees 2100 1% 87, 91, 91% 63, 76% of remaining below 4 degrees 2100 46% 98, 99, 99% 93, 96% Temperature implications Jason Lowe’s work told us: • Under A1B temperatures are likely to reach 34C • 2030 peaking insufficient for 2C and have chance of 1 in 3 to 4 of exceeding 3C • 2016 targets effective at avoiding 3C, chance of exceeding falls to 1 in 10 • Only most stringent R=5% 2016 scenario has 45% chance to meet 2C target • All avoid temperatures reaching 4 degrees with high confidence (>=98%) except for 2030 2% L which leaves a 7% chance of more than 4C. Key benefit: Avoiding esclating risks of breach of tipping points • Since under A1B temperatures are likely to reach 3-4C breaching of several tipping points in the earth system is likely. • This would raise temperatures above 4C since many act as feedbacks and are not included in climate models presently • Breaching range of several key tipping points may occur at 3C • 2016 scenarios effective at avoiding entering this range, chance of exceeding falls to 1 in 10 • 2030 scenarios only reduce it to 1 in 3 or4 Key benefit : Avoiding increases in extreme weather • Most immediately felt climate change impacts will be those due to increased extreme weather and its impacts upon infrastructure, agriculture and ecosystems • May be as/more important than climate impacts simulated for continuous warming • Fluvial & coastal flood only included here • A related study shows drought frequency in Europe can be greatly reduced by stabilization at 450 ppm CO2-e. Sectors and impacts indicators WATER water resources coastal flood FOOD crop suitability ENVIRONMENT soil carbon, ecosystem productivity biodiversity fluvial flood crop productivity HEALTH INFRASTRUCTURE heat effects heating/cooling needs Impacts simulation methods • Off-line, spatially-explicit (usually 0.5x0.5o) impacts models, with indicators aggregated to larger geographic regions • Indicators characterise exposure to impact, not estimated actual impact = “adaptation+residual impact” • Indicators show exposure relative to the situation at the same time without climate change Key findings • Strong mitigation action to limit temperature rise to below 2°C avoids many of the climate impacts. • …but not all the impacts are avoided. • Some benefits of mitigation policy are realised by the 2050s. Benefits continue to increase in the second half of the century. • There is considerable regional variation in avoided impacts. Key findings • Strong mitigation action to limit temperature rise to below 2°C avoids many of the climate impacts. • …but not all the impacts are avoided. • Some benefits of mitigation policy are realised by the 2050s. Benefits continue to increase in the second half of the century. • There is considerable regional variation in avoided impacts. Strong action to limit to below 2°C avoid a large amount of the climate impacts that would otherwise accrue by the 2080s… 80 70 60 50 40 30 20 Cooling requirements Soybean productivity Decreased crop suitability Coastal mangrove Coastal flood risk Fluvial flood risk 10 0 Increased water scarcity % of impacts avoided % of impacts avoided 2016-5-L AVOID is funded by the Department of Energy and Climate Change and the Department for Environment, Food and Rural Affairs Strong action to limit to below 2°C avoid a large amount of the climate impacts that would otherwise accrue by the 2080s… …… but even the most stringent mitigation will not avoid all impacts 80 70 60 50 40 30 20 2016-5-L Cooling requirements Soybean productivity Decreased crop suitability Coastal mangrove Coastal flood risk Fluvial flood risk 10 0 Increased water scarcity % of impacts avoided % of impacts avoided … but even the most stringent mitigation will not avoid all impacts Increase in water resources stress Population exposed to increased % of global population water resources stress 14 12 10 8 6 4 2 0 2000 2010 2020 2030 2040 2050 2060 2070 2080 A1b A1b-2016-2-H A1b-2016-4-L A1b-2016-5-L A1b-2030-2-H A1b-2030-5-L 2090 2100 AVOID is funded by the Department of Energy and Climate Change and the Department for Environment, Food and Rural Affairs … but even the most stringent mitigation will not avoid all impacts Decrease in crop suitability 60 % of cropland 50 40 30 20 10 0 2000 2010 2020 2030 2040 A1b A1b-2016-2-H A1b-2030-2-H A1b-2030-5-L 2050 2060 2070 A1b-2016-4-L Area with decrease in crop suitability HadCM3 2080 2090 A1b-2016-5-L 2100 Key findings • Strong mitigation action to limit temperature rise to below 2°C avoids many of the climate impacts. • …but not all the impacts are avoided. • Some benefits of mitigation policy are realised by the 2050s. Benefits continue to increase in the second half to the century. • There is considerable regional variation in avoided impacts. Some benefits of mitigation policy are realised by the 2050s. Benefits continue to increase in the second half of the century. % change in flood risk Change in fluvial flood risk 300 250 200 150 100 50 0 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 Year A1b 2016-2-H 2030-5-L 2030-2-H 2016-4-L 2016-5-L 2100 Some benefits of mitigation policy are realised by the 2050s. Benefits continue to increase in the second half of the century. Decrease in crop suitability 60 % of cropland 50 40 30 20 10 0 2000 2010 2020 2030 2040 A1b A1b-2016-2-H A1b-2030-2-H A1b-2030-5-L 2050 2060 2070 A1b-2016-4-L Area with decrease in crop suitability HadCM3 2080 2090 A1b-2016-5-L 2100 Key findings • Strong mitigation action to limit temperature rise to below 2°C avoids many of the climate impacts. • …but not all the impacts are avoided. • Some benefits of mitigation policy are realised by the 2050s. Benefits continue to increase in the second half to the century. • There is considerable regional variation in avoided impacts. Percentage of flood-prone population exposed to an increase in flood hazard A1B 2100 % Percentage of flood-prone population exposed to an increase in flood hazard 2016.R5.L 2100 % Sources of uncertainty Estimates of avoided impacts are uncertain due to uncertainty in: 1. global mean temperature change 2. regional pattern of change in climate 3. socio-economic conditions Key findings • Strong mitigation action to limit temperature rise to below 2°C avoids many of the climate impacts. • …but not all the impacts are avoided. • Some benefits of mitigation policy are realised by the 2050s. Benefits continue to increase in the second half of the century. • There is considerable regional variation in avoided impacts. Thank you for your attention… Contact Jolene Cook ([email protected]) for more information on how to join us as a stakeholder Contact Rachel Warren ([email protected]) for more information about work stream 1 Contact Jason Lowe ([email protected]) for more information on the scientific content of AVOID www.avoid.uk.net AVOID is funded by the Department of Energy and Climate Change and the Department for Environment, Food and Rural Affairs