Determining allowable CO2 emissions from regional- and impact-related climate targets

Transcription

1 Determining allowable CO2 emissions from regional- and impact-related climate targets Sonia I. Seneviratne Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland Acknowledgements: M. Donat, A.J. Pitman, R. Knutti, R. Wilby, E. Davin, A. Hirsch, Q. Lejeune, R. Orth, M. Vogel, and M. Wilhelm, France, Sonia Seneviratne / IAC ETH Zurich

2 2015 Paris agreement

3 COP21: 1.5 vs 2

4 Climate projections Agreement at COP21 to hold the increase in global temperature to well below 2 C above pre-industrial levels and to pursue efforts to limit increases to 1.5 (IPCC 2013)

5 Towards a world 3 questions using climate simulations: Identify optimal target between : Including the impact perspective How do we reduce uncertainties: Example: Land surface feedbacks for temperature extremes How do we reduce regional impacts?

6 Allowable CO 2 emissions based on regional targets? (Seneviratne et al. 2016, Nature)

7 Link between cumulative CO 2 emissions and global T Direct link between cumulative CO 2 emissions and climate response A global T target can be linked to cumulative emissions target (IPCC 2013)

8 What are implications of global temperature changes? People are not killed by the global temperature what matters are regional changes in extremes and impacts How do these relate to the projected global temperature changes? Sonia Seneviratne / IAC ETH Zurich

9 1.5 C and 2 C targets: reasons for concern (IPCC 2014, WG2)

10 1.5 C and 2 C targets: reasons for concern Can we be more quantitative? (IPCC 2014, WG2)

11 Scaling relationships for extremes Can these scaling relationships be used to relate regional changes with global T changes and thus with cumulative CO 2 emissions targets? (Seneviratne et al. 2016, Nature)

12 Relating regional climate targets with CO 2 emissions RCP8.5 RCP4.5 (Seneviratne et al. 2016, Nature)

13 Relating regional climate targets with CO 2 emissions RCP8.5 RCP4.5 Interesting results: Almost linear scaling for multi-model mean (see also Fischer et al. 2014, GRL) (Seneviratne et al. 2016, Nature)

14 Relating regional climate targets with CO 2 emissions RCP8.5 RCP4.5 Interesting results: Almost linear scaling for multi-model mean (see also Fischer et al. 2014, GRL) Pattern independent of emissions scenario! (Seneviratne et al. 2016, Nature)

15 Relating regional climate targets with CO 2 emissions RCP8.5 RCP4.5 Interesting results: Almost linear scaling for multi-model mean (see also Fischer et al. 2014, GRL) Pattern independent of emissions scenario! Tool to define impactbased targets? (Seneviratne et al. 2016, Nature)

16 Relating regional climate targets with CO 2 emissions Also scaling found for warming of minimum temperatures Rx5day Southern Asia RCP8.5 RCP4.5 (Seneviratne et al. 2016, Nature)

17 Relating regional climate targets with CO 2 emissions Also scaling found for warming of minimum temperatures and changes in heavy precipitation Rx5day Southern Asia RCP8.5 RCP4.5 (Seneviratne et al. 2016, Nature)

18 Relating regional climate targets with CO 2 emissions Advantages: 1. Provides a better quantitative understanding of relation between emissions and impacts for stakeholders 2. Independent of emissions scenario, direct link between political decisions and impacts 3. Help linkage between costs of emissions reduction and avoided costs of impacts

19 Relating regional climate targets with CO 2 emissions Advantages: 1. Provides a better quantitative understanding of relation between emissions and impacts for stakeholders 2. Independent of emissions scenario, direct link between political decisions and impacts 3. Help linkage between costs of emissions reduction and avoided costs of impacts Caveats: Large uncertainty ranges in some cases (e.g. droughts) Shared model biases Does not consider the impact of local forcing (land use, aerosols) Does not include uncertainty of scaling of CO 2 emissions with global T

20 Towards a world 3 questions using climate simulations: Identify optimal target between : Including the impact perspective How do we reduce uncertainties: Example: Land surface feedbacks for temperature extremes How do we reduce regional impacts?

21 Uncertainties in scaling: Example from 2 regions Contiguous US Central Europe IPCC SREX regions

22 Uncertainties in scaling: Example from 2 regions Txx, CEU

23 Role of soil moisture temperature feedbacks GHG GHG T+ T++ è evidence in projections: Seneviratne et al. 2006, Nature; Diffenbaugh et al. 2007, GRL; Seneviratne et al. 2013, GRL è observational evidence: Hirschi et al. 2011, Nature Geoscience; Quesada et al. 2012, Nature Climate Change; Mueller and Seneviratne 2012, PNAS; Miralles et al. 2014, Nature Geoscience

24 Soil moisture temperature feedbacks: Observations Analysis for Southeastern Europe Impact of soil moisture on hot extremes Quantile regression of %HD with 6- month SPI (Hirschi et al. 2011, Nature Geoscience)

25 Soil moisture temperature feedbacks: Observations Analysis for Southeastern Europe Quantile regression of %HD with 6- month SPI Impact of soil moisture on hot extremes Conditional probability: Higher probability of occurrence with drier springs (Hirschi et al. 2011, Nature Geoscience)

26 Soil moisture temperature feedbacks: Observations NHD: # hot days SPI: Standardized Precipitation Index (Mueller and Seneviratne 2012, PNAS)

27 Soil moisture temperature feedbacks: Observations Generally strong lag relationship between precipitation deficits and temperature extremes in transitional regions between dry and wet climates NHD: # hot days SPI: Standardized Precipitation Index (Mueller and Seneviratne 2012, PNAS)

28 Soil moisture-temperature feedbacks in global climate models GLACE-CMIP5 experiment Soil moisture (point in Central Europe) GLACE-CMIP5 investigates the impact of decadal changes in soil moisture on climate 5 CMIP5 models (CESM, EC-EARTH, GFDL, IPSL, MPI-ESM) (Seneviratne et al. 2013, GRL)

29 Role of soil moisture feedbacks Mean drying of the soil is explaining added warming in extremes in several land regions (GLACE-CMIP5 experiments, Seneviratne et al. 2013, GRL)

30 Role of soil moisture feedbacks Mean drying of the soil is explaining added warming in extremes in several land regions (GLACE-CMIP5 experiments, Seneviratne et al. 2013, GRL) Regions with strong soil moisture effects in projections correspond well to those showing a stronger warming of extremes

31 Uncertainties in scaling: Example from 2 regions By how much can we reduce the uncertainty in projections (e.g. using ground and remote sensing observations of land variables)? Txx, CEU ERC DROUGHT-HEAT project

32 Uncertainties in scaling: Example from 2 regions By how much can we reduce the uncertainty in projections (e.g. using ground and remote sensing observations of land variables)? Txx, CEU ERC DROUGHT-HEAT project

33 Systematic biases in climate models Evidence of systematic biases in current climate models (Mueller and Seneviratne 2014, GRL)

34 Towards a world 3 questions using multi-model climate simulations: Identify optimal target between : Including the impact perspective How do we reduce uncertainties: Example: Land surface feedbacks for temperature extremes How do we reduce regional impacts?

35 Reducing impacts RCP8.5 RCP4.5

36 RCP2.6 scenario (VanVuuren et al. 2011, Clim. Change)

37 RCP2.6 scenario e.g. reforestation leading to warming in high-latitudes! Present simulations do not include biophysical impacts of land use (will be investigated in CMIP6 LUMIP experiment) (VanVuuren et al. 2011, Clim. Change)

38 Impact of land use and land cover changes on climate Impact of land cover type on surface fluxes during heatwaves Forests lead to a warming compared to grasslands! (Teuling et al. 2010, Nature Geoscience)

39 Impact of land use and land cover changes on climate Impact of land cover type on surface fluxes during heatwaves Forests lead to a warming compared to grasslands! NB: Behaviour may reverse under long droughts (Teuling et al. 2010, Nature Geoscience)

40 Impact of land use and land cover changes on climate NB: Behaviour may reverse under long droughts (Teuling et al. 2010, Nature Geoscience)

41 Changes in albedo induced by agricultural management Differences in surface albedo from no-till farming Photograph by Jim Richardson (National Geographic) (Davin et al. 2014, PNAS)

42 Summer mean temperature changes Crop distribution (%) (Davin et al. 2014, PNAS)

43 Changes in albedo induced by agricultural management Preferential cooling of hot extremes when considering combined albedo and evaporation effects! (Davin et al. 2014, PNAS)

44 Reducing impacts RCP8.5 RCP4.5 Regional scale increases in temperature could also be reduced through regional measures (e.g. irrigation, changes in surface reflectivity): Regional land climate engineering

45 Reducing impacts RCP8.5 RCP4.5 Regional scale increases in temperature could also be reduced through regional measures (e.g. irrigation, changes in surface reflectivity): Regional land climate engineering But no/little effects on ocean acidification, sea level rise

46 ERC DROUGHT-HEAT project ERC consolidator grant ( )

47 Conclusions and outlook Scaling of regional changes in extremes with changes in global temperature (and cumulative global CO2 emissions) Relationship can be used to: Inform choice of global temperature targets Reduce uncertainties in projections Link costs of adaptation and mitigation Design strategies for regional adaptation Soil moisture and land albedo effects are important for land climate and in particular for temperature extremes èrelevant for projections, mitigation and adaptation Contact: Sonia Seneviratne / IAC ETH Zurich