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Effects of Airborne Particles on Climate: an Expert Elicitation M. Granger Morgan, Peter J. Adams, and David W. Keith 7 March 2006.

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Presentation on theme: "Effects of Airborne Particles on Climate: an Expert Elicitation M. Granger Morgan, Peter J. Adams, and David W. Keith 7 March 2006."— Presentation transcript:

1 Effects of Airborne Particles on Climate: an Expert Elicitation M. Granger Morgan, Peter J. Adams, and David W. Keith 7 March 2006

2 2 Overview  Background Radiative forcing Aerosol (airborne particles) climate effects Previous assessments (IPCC TAR) Aerosols and climate uncertainty  Expert Elicitation Design Results  Lessons Learned

3 3 Overview  Background Radiative forcing Aerosol (airborne particles) climate effects Previous assessments (IPCC TAR) Aerosols and climate uncertainty  Expert Elicitation Design Results  Lessons Learned

4 4 Earth’s Energy Balance Sunlight (Shortwave, visible radiation) 235 Watts per square meter (W/m 2 ) Heat (Longwave, infrared radiation) 235 Watts per square meter (W/m 2 ) Perturbations to energy balance are known as “radiative forcings”

5 5 Radiative Forcings  Shortwave (incoming) or longwave (outgoing)  Both positive (warming) and negative (cooling)  Computed at various altitudes Top-of-atmosphere (TOA): most useful metric for global average temperature Surface: useful metric for evaporation / changes to hydrological cycle

6 6 Source: IPCC Third Assessment Report

7 7 Overview  Background Radiative forcing Aerosol (airborne particles) climate effects Previous assessments (IPCC TAR) Aerosols and climate uncertainty  Expert Elicitation Design Results  Lessons Learned

8 8 Aerosols Scattering Sunlight Dust and smoke over Australia (Terra)

9 9 Aerosols Absorbing Sunlight Kuwaiti oil fires photo courtesy of Jay Apt (via Steve Schwartz)

10 10 Aerosols and Clouds AVHRR satellite “false color” image Red: darker clouds (large droplets) Green: brighter clouds (small droplets) Blue: clear sky Power plant Lead smelter Port Oil refineries Rosenfeld, Science (2000)

11 11 Aerosols and Clouds Clean Air Polluted Air Aerosol Particles Cloud Droplets Brighter, more persistent clouds

12 12 How direct is direct?  Direct effect: scattering/absorbing sunlight  Semi-direct effect: aerosol absorption heats atmospheric layer warmer air → lower relative humidity → less/no cloud  Indirect effect: modifying cloud properties “brightness (first) effect” “lifetime (second) effect”

13 13 Overview  Background Radiative forcing Aerosol (airborne particles) climate effects Previous assessments (IPCC TAR) Aerosols and climate uncertainty  Expert Elicitation Design Results  Lessons Learned

14 14 Source: IPCC Third Assessment Report Indirect effect(s): TAR figure shows “brightness” effect only “lifetime” effect potentially comparable discussion buried in text Direct effect(s): best understood divided by aerosol type Semi-direct effect(s): not shown on TAR figure postulated in 2000 discussed in text but no global estimate given

15 15 Overview  Background Radiative forcing Aerosol (airborne particles) climate effects Previous assessments (IPCC TAR) Aerosols and climate uncertainty  Expert Elicitation Design Results  Lessons Learned

16 16 Climate Change Uncertainty  “Climate sensitivity” is a key parameter  is “climate sensitivity” 0.3 to 1 °C per W/m °C for doubling of CO 2  In climate models, representation of cloud feedback is largest source of uncertainty  In retrospective studies, knowledge of aerosol forcing is lacking global average temperature change global average radiative forcing

17 17 Aerosols and Climate Uncertainty High sensitivity Low sensitivity GHG forcing 20 th century T increase Aerosol + GHG forcing ??

18 18 Aerosols and Climate Uncertainty  Uncertainty in aerosol forcing makes testing climate models against 20 th century temperature record almost meaningless  Nevertheless all climate models do this test and claim good agreement as “validation” of their model  Aerosol forcing is a “tunable” parameter  High sensitivity models ↔ Strong aerosol cooling  Low sensitivity models ↔ Weak aerosol cooling

19 19 NH/SH mixing intra- hemispheric mixing Challenges  Need to characterize particle mass/number concentration size distribution: ~10 nm to 10  m chemical composition: >hundreds compounds mixing state interactions with clouds  Highly variable in space and time: centurydecadalannualdailymonthlyhourly Mean CO 2 residence Mean aerosol residence

20 20 Overview  Background Radiative forcing Aerosol (airborne particles) climate effects Previous assessments (IPCC TAR) Aerosols and climate uncertainty  Expert Elicitation Design Results  Lessons Learned

21 21 Expert Elicitation  Granger Morgan “unofficially” invited by IPCC to survey expert opinion  Not intended to replace peer-reviewed scientific studies in literature  Usefulness reveal agreement/disagreement between experts little systematic work on uncertainty in aerosol forcing

22 22 Elicitation Methodology  Administered by mail  52 experts invited from broad base of expertise types Aerosols, clouds, and climate Modeling, experimental Global to micro scale  29 agreed 2 said they lacked expertise 3 did not complete  24 useable responses  Participants acknowledged but responses are anonymous

23 23 Elicitation Methodology  Six parts 1.Direct: scattering/absorption of sunlight 2.Semi-direct: change in clouds as absorbing aerosols heat atmosphere 3.Cloud brightness (first indirect): smaller droplets → brighter clouds 4.Cloud lifetime (second indirect): smaller droplets → less precipitation 5.Total: net effect of above at top-of-atmosphere 6.Surface: net effect of above at surface

24 24 Elicitation Methodology For each part/effect: a)list top factors contributing to uncertainties b)estimate radiative forcing probability distributions  upper/lower bounds  “counterfactual” question  5/95% confidence intervals  25/75% confidence intervals  best estimate c)probability uncertainty will (in 20 years)  increase  shrink by 0-50%  shrink by 50-80%  shrink more than 80%

25 25 Overview  Background Radiative forcing Aerosol (airborne particles) climate effects Previous assessments (IPCC TAR) Aerosols and climate uncertainty  Expert Elicitation Design Results  Lessons Learned

26 Best understood Responses broadly consistent with IPCC TAR

27 One respondent: “semi-direct effect is positive by definition” Absorbing aerosols above marine stratocumulus increase reflectivity via dynamical effects – “still semi-direct”? Forcing or feedback?

28 Most experts mostly in 0 to -2 W m -2 range of IPCC TAR A minority suggest possible effects of -3 to -4 W m -2

29 Omitted from IPCC TAR Many reflect “conventional wisdom” of 0 to -2 W m -2 Significant minority give wider uncertainties Believers in positive – an enlightened minority?

30 “Forward” modeling: estimate forcing based on aerosol physics “Reverse” modeling: estimate aerosol forcing as that needed to match historical temperature trends

31

32 32 Conclusions  IPCC TAR assessment ok for what was reported  Significant uncertainties (cloud lifetime and semi-direct) unreported  Field is not “mature”: new physical mechanisms being uncovered/studied, significant chances of uncertainty increasing  Terminology is ambiguous (as well as confusing)  Lines between “forcings” and “feedbacks” blurred  Aerosols are part of the (irreducible?) climate uncertainty


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