IPCC AR5 WGI. Chapter 10 Detection and Attribution of Climate Change : from Global to Regional. First Lead Author meeting Kunming 8-11 November, 2010

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1 IPCC AR5 WGI Chapter 10 Detection and Attribution of Climate Change : from Global to Regional First Lead Author meeting Kunming 8-11 November, 2010 Deadline for delivery of zod to TSU 18 March, 2011

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3 Chapter 10 Detection and Attribution of Climate Change: from Global to Regional Author Team Coordinating Lead Authors: Nathan Bindoff and Peter Stott Lead Authors: Krishna Achutarao, Myles Allen, Nathan Gillett, David Gutzler, Kabumbwe Hansingo, Gabi Hegerl, Yongyun Hu, Suman Jain, Igor Mokhov, James Overland, Judith Perlwitz, Rachid Sebbari, Xuebin Zhang Review Editors: Judit Bartholy, Robert Vautard, Tetsuzo Yasunari

4 IPCCC AR5 WGI 1. Introduction 2. Observations: Atmosphere and surface 3. Observations: Ocean 4. Observations: Cryosphere 5. Information from Paleoclimate Archives 6. Carbon and Other Biogechemical cycles 7. Clouds and Aerosols 8. Anthropogenic and Natural Radiative Forcing 9. Evaluation of Climate Models 10. Detection and Attribution of Climate Change: from Global to Regional 11. Near-term Climate Change: Projections and Predictability 12. Long-term Climate Change: Projections, Commitments and Irreversibility 13. Sea Level Change 14. Climate Phenomena and their Relevance for Future Regional Climate Change

5 Chapter 10 Detection and Attribution of Climate Change : from Global to Regional Detection : An identified change is detected in observations if its likelihood of occurrence by change due to internal variability is small. Attribution : The process of evaluating the relative contributions of multiple causal factors to a change or event with an assignment of statistical confidence. The process of attribution requires the detection of a change in the variable or closely related variables. From Global to Regional Assess to what extent systematic changes are emerging across the climate system that enable robust attribution of observed changes to anthropogenic and natural causes Adopt a process based approach to assess extent to which detected changes are consistent with physical understanding Link across variables and scales - from global to regional Identify where robust attribution of extremes can be made, including use of odds-based and multi-step approaches Develop compelling ways of visually illustrating attributable changes

6 10.1 Introduction 10.2 Evaluation of D+A Methodologies Myles Conceptual approach to d+a Methods 10.3 Atmosphere and surface Judith and Nathan Temperature Surface (air temperature and SST) Atmosphere Water cycle Changes in circulation and climate phenomena 10.4 Changes in Ocean Properties Krishna AchutaRao Ocean temperature and heat content Ocean salinity and freshwater fluxes Sea level Other ocean properties Chapter 10: Chapter outlines

7 Chapter 10: Chapter outlines 10.5 Cryosphere James Overland Sea ice Ice sheets and ice shelves, and glaciers Snow cover and Permafrost 10.6 Extremes Xuebin Attribution of changes in frequency/occurrence and intensity of extremes Attribution of observed weather and climate events 10.7 Millennia to multi century perspective Gabi 10.8 Whole system attribution Peter 10.9 Implications for projections Gabi Near term near-surface temperature change Long Term Other aspects of the climate system Synthesis

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9 HadGEM2-ES

10 CanESM2

11 Attribution and link to decadal prediction and Transient Climate Response How has new evidence, including More observations Better observational datasets and models Improved characterisation of observational and modelling uncertainty affected : Attributable warming estimates? Decadal predictions? Estimates of Transient Climate Response? Allen et al, Observational uncertainty Attributable warming trends AR4 WGI Fig 9.9

12 Boxes Understanding the increased spread of 20 th century simulations.

13 Boxes Understanding the increased spread of 20 th century simulations. What is optimal detection?

14 Anthropogenically-forced model Naturally-forced model Global climate observations MASKING BY MISSING DATA IN OBSERVATIONS

15 Regional changes and Extremes European summer temperatures. Current World (red) vs the World that might have been (green); Christidis et al, 2010 Estimated 1990s waiting times for 1960s 20-year return values; Zwiers et al, 2010 How have odds of exceeding a particular threshold changed? How have waiting times changed? Do models capture the relevant processes? Which changes can be robustly attributed to human and natural influences? Attribution of Autumn 2000 UK flooding; Pall et al, 2011 Return period (years)

16 Whole system attribution Zhang et al Barnett et al Helm et al

17 FAQs Chapter : Climate is always changing how do we determine the most likely causes of observed changes? 10.2: When will human influences on climate be obvious on local scales? Other chapters 2.4: How do we know the World is warming? 4.4: How is sea-ice changing in Arctic and around Antarctic?

18 Timeline ZOD to TSU, 18 March, 2011 Review of ZOD, 15 April 10 June, nd LA meeting, July, 2011 FOD to TSU. 18 November, 2011 Review of FOD, 16 December February, rd LA meeting, April, 2012 WGI cut off for submitted papers, 31 July 2012 SOD to TSU, 10 August 2012 WG1 cut off for accepted papers, 15 March 2013 Final draft to TSU, 13 May 2013 WGI Plenary, September 2013

19 HadCM3, GEM1, 2 CanESM2

20 Issues: Chapter 10: Chapter Issues End to end chapters Sea Level Rise in D and A chapter or Sea Level Rise chapter (Chapter13) Chapter 14 D and A in this chapter or our 10. Chapter 10 has Fractional Attributable Risk on extremes events Reproducibility of figures (ie underlying data and code?) Agreement to show some standard seasons

21 Chapter 10 Detection and Attribution of Climate Change: from Global to Regional Frequently asked questions 1. Has global warming stopped? (linked to ch2) 2. How is climate change affecting our weather? (Chapter 9 and14) 3. Climate is always changing. How is it possible to prove or disprove observed changes are due to human influence? 4. Why has Antarctic sea ice not decreased but Arctic sea ice has? (Antarctic unresolved) 5. When will human influence on local climate be detected? (link Chapter 2/10/11) 6. Why has rainfall increased in some places and decreased in others? 7. What do observed changes tell us about the future? Contact: David Gutzler

22 Chapter 10 Detection and Attribution of Climate Change: from Global to Regional Chapter linkages (table). Chapter Topic Person in chapter Person in DandA Chapter Chapter2 Atmosphere Xuebin Zhang Surface Chapter 3 Heat content Greg Johnson Salinity/freshwater Shigeru Aoki Chapter 4 Sea ice Igor Mokhov/James Overland Snow Cover and permafrost Phil Mote? Xuebin Zhang and or Igor Mokhov Mountain Glaciers Georg Kaser James Overland Ice Sheets Konni Steffen James Overland Chapter 5 Hegerl Chapter 9 Climate sensitivity, recent trends Chris Forrest (?) Hegerl Chapter 10 Chapter 11 Trends predictions and initialsiesd predictions Geert Jan van Oldenborgh Nathan Gillet/ Myles Allen Chapter 12 Extremes Xeubin Zhang Sentivity Gabi Hegerl Chapter 13 Chapter 14

23 Chapter 10 Detection and Attribution of Climate Change: from Global to Regional Section No. Heading LA in-charge Co-LAs 10.1 Introduction Writing assignments 10.2 Evaluation of D&A Methodologies Myles Allen Nathan Gillet, Igor Mokhov, Gabi Hegerl 10.3 Atmosphere and Surface Judith Perlwitz Temperature Surface Nathan Gillet Yongyun Hu, Suman Jain, Kabumbwe Hansingo, Peter Stott, Gabi Hegerl Atmosphere Judith Perlwitz Nathan Gillett, Yongyun Hu Water Cycle David Gutzler Xeubin Zhang, Gabi Hegerl Changes in circulation and climate phenomena Yongyun Hu Judith Perlwitz, Nathan Gillett Igor Mokhov 10.4 Changes in ocean properties Krishna Achutarao James Overland, Nathan Bindoff? Ocean temperature and heat content Krishna Achutarao Krishna Achutarao, Nathan Bindoff, Kabumbwe Hansingo Ocean salinity and freshwater fluxes Nathan Bindoff Krishna Achutarao Sea level Krishna Achutarao Other ocean properties 10.5 Cryosphere Sea-ice James Overalnd Igor Mokhov Ice sheets and ice shelves James Overland Contributing Author and NathanBindoff Snow cover and permafrost Xeubin Zhang Igor Mokhov 10.6 Extremes Attribution of changes in frequency/occurrence and intensity of extremes Attribution of observed weather and climate events Xeubin Zhang Myles Allen Rachid Sebbari, Gabi Hegerl Judith Perlwitz, Peter Stott, Yongyun Hu, Suman Jain 10.7 Millennia to [multi]century perspective Gabi Hegerl David Gutzler, Tim Osborn (CA) 10.8 Whole system attribution Peter Stott David Gutzler, Myles Allen, Nathan Bindoff 10.9 Implications for projections Gabi Hegerl Myles Allen, Peter Stott, Krishna AchutaRao, Yongyun Hu, Nathan Gillet Synthesis Peter Stott and Nathan Bindoff All

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25 Chapter 10 Detection and Attribution of Climate Change : from Global to Regional Detection : An identified change is detected in observations if its likelihood of occurrence by change due to internal variability is small. Attribution : The process of evaluating the relative contributions of multiple causal factors to a change or event with an assignment of statistical confidence From Global to Regional Assess to what extent systematic changes are emerging across the climate system that enable robust attribution of observed changes to anthropogenic and natural causes Adopt a process based approach to assess extent to which detected changes are consistent with physical understanding Link across variables and scales - from global to regional Identify where robust attribution of extremes can be made, including use of odds-based and multi-step approaches Develop compelling ways of visually illustrating attributable changes

26 Differences in global temperature estimates related to coverage in polar regions Arctic and Antarctic sea ice Polar regions What is the contribution of sea ice loss to Arctic amplification? What are the causes for the lack of Antarctic sea ice reduction? Is climate change accelerating in the Arctic?

27 Hydrological cycle Global precipitation trends Zhang et al, 2007 P-E inferred from ocean changes Bindoff, Helm, Church, 2010 Is the hydrological cycle changing faster than models predict? Can we identify process based fingerprints that better identify how rapidly the hydrological cycle is changing? How best to identify regional hydroclimatic changes? Regional changes in Western USA, Barnett et al, 2008 Snow pack Jan - March minimum temperature River flow

28 Oceans: Surface salinity pattern amplification SSS change (Durack & Wijffels, 2010) mean salinty pattern is amplified SSS pattern amplification rates: CMIP3 compared to observations: only strongly warming models show clear SSS pattern amplification Paul Durack

29 Regional changes and Extremes European summer temperatures. Current World (red) vs the World that might have been (green); Christidis et al, 2010 Estimated 1990s waiting times for 1960s 20-year return values; Ziwers et al, 2010 How have odds of exceeding a particular threshold changed? How have waiting times changed? Do models capture the relevant processes? Which changes can be robustly attributed to human and natural influences? Attribution of Autumn 2000 UK flooding; Pardeep et al, 2010 Return period (years)

30 Attribution and link to decadal prediction and Transient Climate Response How has new evidence, including More observations Better observational datasets and models Improved characterisation of observational and modelling uncertainty affected : Attributable warming estimates? Decadal predictions? Estimates of Transient Climate Response? Allen et al, New model simulations in CMIP5: eg HadGEM2 Earth System model Attributable warming trends AR4 WGI Fig 9.9

31 Differences in global temperature estimates related to coverage in polar regions Arctic and Antarctic sea ice Polar regions What is the contribution of sea ice loss to Arctic amplification? What are the causes for the lack of Antarctic sea ice reduction? Is climate change accelerating in the Arctic?

32 Hydrological cycle Global precipitation trends Zhang et al, 2007 P-E inferred from ocean changes Bindoff, Helm, Church, 2010 Is the hydrological cycle changing faster than models predict? Can we identify process based fingerprints that better identify how rapidly the hydrological cycle is changing? How best to identify regional hydroclimatic changes? Regional changes in Western USA, Barnett et al, 2008 Snow pack Jan - March minimum temperature River flow

33 Oceans: Surface salinity pattern amplification SSS change (Durack & Wijffels, 2010) mean salinity pattern is amplified SSS pattern amplification rates: CMIP3 compared to observations: only strongly warming models show clear SSS pattern amplification Paul Durack

34 Detection and Attribution of Climate Change : from Global to Regional Sub-continental scale temperatures Temperature extremes Ocean warming Increases in atmospheric humidity Salinity changes in the oceans Increasing drought Reducing Arctic sea-ice Changing rainfall patterns Attribution of extreme weather events Vision : Towards a robust multi-component attribution across variables and scales Evaluation of decadal scale internal variability critical Scope : Quantitative evaluation of relative contributions of external forcings to a change or probability of an event

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36 Detection and Attribution runs of HadGEM2-ES NH - SH Land - Ocean Crown copyright Met Office

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