1. Black Carbon in Snow: Role in Arctic Climate, Uncertainties, and Future Scenarios Mark Flanner 1 Charlie Zender 2 Collaborators: Tami Bond, Jim Randerson, Phil Rasch 1 National Center for Atmospheric Research, Boulder CO 2 University of California - Irvine

2. 2 Talk Outline Positive feedback mechanisms Arctic climate response and efficacy Uncertainties and research possibilities Arctic shipping Arctic warming mitigation possibilities

3. 3 Aerosol-induced Snow Heating: Multiple Positive Feedbacks Snow/Ice Cover Albedo R_net (-) (+) (-) + Snow Grain Size (-) (+) +G Soot (-) (+) + (+) ? Concentration of hydrophobic and large impurities at the surface during melting? (+)

4. 4 Importance of Snow Aging Radiative intensity diminishes more slowly with depth in larger-grained snow because it is less extinctive and scatters more strongly in the forward direction. Hence photons tend to travel through a greater optical depth of (homogeneously-interspersed) BC. Albedo perturbation caused by a given mass of BC varies more than three-fold for a reasonable range of effective grain size. snow density = 150 kg m -3 zenith angle = 60 degrees wavelength = 550 nm

5. 5 Measurements and Model Estimates of BC in Snow Flanner et al. (2007) Present day climate forcing and response from black carbon in snow, J. Geophys. Res.

6. 6 Forcing Pattern of BC in Snow Forcing operates mostly in local springtime, when and where there is large snow cover exposed to intense insolation, coincidentally with peak snowmelt. Hence, it is a strong trigger of snow-albedo feedback, which is maximal in spring (Hall and Qu, 2006). Forcing is dominated by FF+BF sources, but strong biomass burning events can have significant impact on Arctic Flanner et al. (2007) Present day climate forcing and response from black carbon in snow, J. Geophys. Res.

7. 7 Climate Response from BC in Snow Earlier snowmelt Reduced surface albedo Surface air warming

8. 8 Arctic BC+OC forcing From policy perspective, interested in net effect of an anthropogenic activity on Arctic climate.  Aerosol direct effects (atm. and snow), indirect effects on cloud LW and SW forcing, and greenhouse gases Focus on BC+OC emitted from fossil fuel+biofuel burning. Direct Arctic effects:  Increase in solar energy absorbed at TOA Bright surfaces (clouds, snow) allow moderately absorbing aerosols to darken the atmosphere-surface column High BC:OC emission ratio from FF/BF combustion produces a relatively dark aerosol mixture  Decrease in solar energy absorbed by surface from atmospheric aerosols  Increase in solar energy absorbed by surface from snow darkening

9. 9 Arctic-wide FF+BF BC+OC forcing Atmospheric BC+OC, TOA:+0.30 W/m 2 (GISS=+0.53) Atmospheric BC+OC, SFC:- 0.08 W/m 2 (GISS=-0.25) Snow BC, SFC:+0.23 W/m 2 Small surface forcing from atmospheric soot because of high surface reflectance Surface darkening from soot exceeds surface dimming from atmospheric soot  Globally, not the case, but when averaged over only snow, darkening is greater than surface dimming by factor 2-3. Atmospheric heating, in spite of negative surface forcing, ultimately transfers thermal energy to surface – why TOA or “adjusted” forcing has been used in past.  Quinn et al. Report -∆T s before thermal transfer (?)  True for moderate aerosol burdens, but with very high optical thickness the atmosphere becomes decoupled from surface (Cess, 1983)

10. 10 Effective Arctic Forcings E atm =0.8 (Hansen et al., 2005) E snow =3.1 (Flanner et al., 2007) TOA atmospheric aerosol forcing:  +0.30 W/m 2 * E atm = +0.24 W/m 2 TOA snow forcing:  +0.21 W/m 2 * E snow = +0.65 W/m 2 Combined BC+OC Arctic effective forcing: +0.89 W/m 2 (> half of CO 2 )  Dominant forcing season: spring  Effect: earlier snowmelt Caution: These are global efficacy factors. How should we define “Arctic Efficacy”? Hansen, et al. (2005) The efficacy of climate forcings, J. Geophys. Res.

11. 11 Uncertainties Range in Global Forcing (Scalar) 1) BC Emissions0.54 – 2.00 2) Snow Aging0.58 – 1.58 3) Melt Scavenging0.69 – 1.08 4) BC Optical Properties0.88 – 1.12 5) Snow Cover Fraction0.83 – 1.08 6) Brown carbon (e.g., Sun et. al., 2007) ??? (Unaccounted absorption, Sato et. al., 2003)

12. 12 Constraining Direct Forcing Snow Aging  Need widespread observations of surface snow effective grain size (SSA) to constrain spatial and temporal variability New measurement techniques (Domine et al., 2007) are providing useful data Is there hope for remotely-sensed effective grain size (Painter et al., 2003 with AVIRIS)?  In theory, yes. However, snow BRDF is highly variable in direction. Potential problem: For apriori BRDF, current MODIS snow product assumes a globally-uniform grain size. Process-oriented experiments to quantify effects of:  Snow T, dT/dz, density, melt/freeze cycles, LWC, sintering, aerosol heating

13. 13 Detecting Snow Grain Size

14. 14 Constraining Direct Forcing Snow forcing – other factors  Closure studies: Measurements and modeling of multi- spectral snow reflectance and vertical absorption profile with known BC concentration, effective grain size – extending work from Grenfell et al., 1994  Scavenging of particles in the snowpack with meltwater (current constraint: 2 orders of magnitude)  Isolation/separation of forcing by BC, OC, dust, algae, other organic material

15. 15 Constraining Direct Forcing Atmospheric BC+OC  Significant difference in direct aerosol forcing between GISS and NCAR simulations. Measurements of column aerosol burdens in Arctic?  Barrow, new IPY measurements? Modeled AOT vs. satellite obs. (MODIS/MISR) Predicted BC in snow vs. observations Offline radiative forcing simulations with GCM column burdens Effect of surface reflectance on differences in surface forcing Comparison of prescribed optical properties Emissions Can we constrain forward estimates with inversion techniques? (e.g., examine AOT and column burdens in models driven with offline winds) Secondary organic aerosols present major obstacle!

16. 16 Arctic Shipping Experiment Concern because of proximal BC emission source to snow/ice Experiment: Emit 0.03/0.08 Tg of BC/OC along Northwest Passage during July, August, Sept. This is order 1% of total PD FF+BF emission, and 25% of 2050 shipping emissions (Eyring et al., 2005a,b)

17. 17 Arctic Shipping Experiment: Influence on Greenland Mean JAS BC/snow concentration increases from 16.5 to 21.8 ng/g Surface forcing increases from 0.52 to 0.63 W/m 2 Surface air warms by 0.22K Snow melt rate increases by 7%

18. 18 Mitigation Experiments Scenarios:  1. 50% global reduction in FF+BF BC+OC emissions  2. 50% reduction in FF+BF emissions N of 40°  3. 50% reduction from U.S., Canada, and Europe (from T. Bond) Arctic forcing (W/m 2 ) SnowAtmTOASno+atmTOA%Reduction%Rdc_anthro ================================================================= PD ff+bf+bb+0.34+0.61+0.92---- PD bb+0.11+0.31+0.41---- DIFF=ANTHRO+0.23+0.30+0.51 (55%tot)---- 50% global+0.23+0.48+0.69-25%-45% 50% N40+0.25+0.54+0.77-16%-29% 50% US/CAN/EU+0.28+0.57+0.82-11%-20% Points: 1) reducing global emissions by half reduces forcing by <half because of non-linear nature of radiative forcing 2) Snow forcing is reduced more than atmospheric aerosol forcing. Why? When considering efficacy, this means potentially greater warming reduction than these numbers would indicate.

19. 19 Snow vs. Atmosphere forcing Snow forcing peaks in May, when snow- coverage is still large, one month earlier than atmospheric forcing Greatest snow forcing reduction is during May- June, when it has greatest impact. Reduction in BC deposition during this time is greater than optical depth reduction, partially explaining greater reduction in snow forcing Forcing1 = Present-day, all sources Forcing2 = 50% reduction in NH sources

20. 20 Conclusions – BC in Snow Snow darkening is a significant component of carbon aerosol Arctic climate forcing High efficacy because of direct snow-albedo- feedback trigger, microphysical snow processes Reduced-emission scenarios suggest greater reduction in snow forcing than atmospheric aerosol forcing – more work needed Future research should focus on:  Constraining snow effective grain size at ground observatories and perhaps from space  Identifying snow aerosol constituents and their relative contributions to snow heating  Constraining the melt scavenging ratio of aerosols in snow

21. 21 Talking Points How to best define “Arctic Efficacy”?  Effectiveness of Arctic forcing agent in changing Arctic climate relative to Arctic CO 2  Effectiveness of global forcing agent in changing Arctic climate relative to global CO 2  Proposal: Define extrapolar and polar forcing efficacies with global simulations (Shindell, 2007). Change in Arctic T s per unit Arctic forcing Change in Arctic T s per unit extrapolar forcing I ndirect cloud/aerosol forcing is largest non-CO 2 forcing term in Arctic (-1.45 W/m 2 TOA, Quinn et al, 2007). What portion is due to BC+OC? Cloud emissivity (total~+1W/m 2 )?  Reducing high-latitude BC (only) emissions would likely slow Arctic warming  But reducing BC+OC (more realistic), if a large portion of indirect effect is from BC+OC, may not

22. 22 Measurements of BC in snow (and atm) Need agreement on, or new definitions of, BC, OC, LAC, brown carbon If widespread BC/snow measurements are made, a consistent technique should be applied, or methods should be calibrated against each other. (Utopic view) Wide range of measurement techniques  Filtration/optical (e.g., Grenfell, Warren)  Thermal/optical (e.g., Chylek et al.)  Chemical (e.g., Slater et al.)  LASER/optical (McConnell et al.)