Present, Past, and Future Climate Effects and Efficacy of Dirty Snow

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1 Present, Past, and Future Climate Effects and Efficacy of Dirty Snow Charlie Zender, Mark Flanner, and Jim Randerson Department of Earth System Science, University of California, Irvine Natalie Mahowald, Phil Rasch, and Masaru Yoshioka Climate and Global Dynamics Division, NCAR, Boulder, CO Ross Edwards and Joe McConnell Desert Research Institute, Reno, NV Contributions from: M. Andreae (MPI), T. Bond (UIUC), D. Bundy (NCAR), P. Khasibhatla (Duke) C. Luo (UCI), D. Muhs (USGS), T. Painter (NSIDC), T. Roush (NASA) IAMAS Earth System Interaction Symposium, Perugia, July 11, 2007

2 Figure 1: Photo unavailable for public viewing due to copyright restrictions.

3 1. Brief History of Dirty Snow Previous global studies focus on snowpack-mediated soot effects: 1. Jacobson (2004): FF/BF snowpack forcing warms climate 0.06 K 2. Hansen and Nazarenko (2004); Hansen et al. (2005): Soot-snowpack forcing 0.08 W m 2 warms climate K. Efficacy E a 1.7 CO 2 3. Krinner et al. (2006): Dusty snow helps keep LGM northern Asia icefree 4. Flanner et al. (2007): Soot-snowpack forcing Efficacy E a 3.0 CO 2 5. Zender et al. (2007): Dirty snow Efficacy E a 4.0 CO 2 How do soot and dust in snow affect climate as emissions change and snow cover decreases?

4 2. Global Dirty Snow Methods 1. SNow, ICe, and Aerosol Radiative model (SNICAR) (Flanner and Zender, 2005, 2006; Flanner et al., 2007) 2. Community Atmosphere Model with Slab Ocean Model (CAM/SOM) (a) Present Day (PD): Control (b) Pre-industrial (PI): 1870 GHGs, no FF/BF BC, 2000 BB (c) IPCC A2 Scenario: 2050 GHGs, BB = 1.5 PD (Flannigan et al., 2005) (d) Last Glacial Maximum (LGM): BB = 0.7 non-glacier PD (Thonicke et al., 2005), Glaciogenic dust sources (Mahowald et al., 2006) 3. Experiment(Control): Soot+Dust are (not) radiatively active in snowpack

5 Modeled BC in Snow (ng g 1 ) Greenland Arctic Continental Antarctica Observed BC in Snow (ng g 1 ) Figure 2: Observed and simulated BC concentrations (Flanner et al., 2007, JGR)

10 Latitude ( N) Latitude ( N) Present BC+Dust Snow Forcing (W m 2 ) 0 J F M A M J J A S O N D Month Pres. BC+Dust/Snow QMELT Change (mm day 1 ) J F M A M J J A S O N D Month Latitude ( N) Latitude ( N) Pres. BC+Dust/Snow ALBS Change 0 J F M A M J J A S O N D Month Pres. BC+Dust/Snow Temp. Change ( C) 0 J F M A M J J A S O N D Month

11 Figure 8: (a) Dirty snow surface forcing [W m 2 ] and (b) surface albedo, (c) snow melt, and (d) surface temperature responses for Present, 1870, and 2050 climates.

12 Figure 9: Predicted global mean temperature response [K] to snowpack heating by soot and dust during Pre-Industrial (1870), Present Day, and 2050 IPCC A2 climates.

13 D18104 HANSEN ET AL.: EFFICACY OF CLIMATE FORCINGS D18104 Efficacy E a : Response relative to response to equivalent CO 2 forcing Figure 25. Efficacy of various climate forcing agents for producing global temperature change relative Figureto10: the global Hansen temperature et al. (2005) change forcing produced efficacies. by an equal CO 2 forcing at today s CO 2 amount (mean for 1 CO 2 to 1.5 CO 2 ). The effective forcing is the product of the efficacy and the forcing. (a) Uses the standard definition of climate forcing, Fa, the adjusted forcing; (b) uses the fixed SST forcing, Fs. The fact that the different forcing agents cluster closer to the E = 1 line for fixed SST definition of forcing indicates that Fs provides a better measure of expected climate response than does Fa. The positive slope of efficacy curves for changes of solar irradiance or CO 2 amount indicates that (in our climate model, with fixed ice sheet area and fixed vegetation distribution) the 100-year climate response becomes more sensitive as the planet becomes warmer. Upturns in the efficacy at very small and very large solar irradiances or CO 2 amounts correspond to the snowball Earth and runaway greenhouse effects. E a λ(dirty snow) λ( CO 2 ) = ( T s/ F Trp ) R dirty snow (2.47 K)/(3.58 W m 2 ) = ( T s/ F Trp ) R dirty snow 0.69 K (W m 2 ) 1 Accounting for feedbacks between impurity concentration, heating, snow aging/metamorphism, and albedo increases dirty snow efficacy to 3 5 CO 2 definition (Table 1) and 2.37 W/m 2 for the tropopause used by Hansen et al. [2002]. Thus DTs/Fa C/W/m 2 for unforced variability in the calculation of Fs in a 100-year run with fixed SST is smaller than the variability in the

14 Figure 11: Predicted global mean forcing [W m 2 ], response [K], and efficacy of snowpack heating by soot and dust during Pre-Industrial (1870), Present Day, and 2050 IPCC A2 climates.

15 3. Conclusions: Climate Effects and Efficacy of Dirty Snow Present climate: Dirty snowpack forcing reversed from soot:dust 30:70% in Pre-industrial (1870) era to 70:30% currently Dust efficacy soot efficacy E a 3 5 Dirty snow warms climate K ( 60% by anthropogenic soot) Significant climate effects on NH albedo, melt seasonality, T Trends: Diminishing snowpack outweighs increased emissions, reduces forcing Temperature response largest in PD Efficacy increases monotonically to 2050 as snowpack warms, thins Overall: With forcing efficacy E a 3 5, Dirty snow is the most efficient climate forcing agent known. Reducing anthropogenic soot emissions may be an optimal strategy to mitigate cryospheric warming.

16 4. References References Flanner, M. G. and C. S. Zender, 2005: Snowpack radiative heating: Influence on Tibetan Plateau climate. Geophys. Res. Lett., 32(6), L06501, doi: /2004gl Flanner, M. G. and C. S. Zender, 2006: Linking snowpack microphysics and albedo evolution. J. Geophys. Res., 111(D12), D12208, doi: /2004gl Flanner, M. G., C. S. Zender, J. T. Randerson and P. J. Rasch, 2007: Presentday climate forcing and response from black carbon in snow. J. Geophys. Res., 112, D11202, doi: /2006jd Flannigan, M. D., K. A. Logan, B. D. Amiro, W. R. Skinner and B. J. Stocks, 2005: Future area burned in Canada. Climatic Change, 72(1 2), 1 16, doi: /s y.

17 Hansen, J. and L. Nazarenko, 2004: Soot climate forcing via snow and ice albedos. Proc. Natl. Acad. Sci., 101(2), Hansen, J., M. Sato, R. Ruedy, L. Nazarenko, A. Lacis, G. A. Schmidt, G. Russell, I. Aleinov, M. Bauer, S. Bauer, N. Bell, B. Cairns, V. Canuto, M. Chandler, Y. Cheng, A. D. Genio, G. Faluvegi, E. Fleming, A. Friend, T. Hall, C. Jackman, M. Kelley, N. Kiang, D. Koch, J. Lean, J. Lerner, K. Lo, S. Menon, R. Miller, P. Minnis, T. Novakov, V. Oinas, J. Perlwitz, J. Perlwitz, D. Rind, A. Romanou, D. Shindell, P. Stone, S. Sun, N. Tausnev, D. Thresher, B. Wielicki, T. Wong, M. Yao and S. Zhang, 2005: Efficacy of climate forcings. J. Geophys. Res., 110(D18104), doi: /2005jd Jacobson, M. Z., 2004: The climate response of fossil-fuel and biofuel soot, accounting for soot s feedback to snow and sea ice albedo and emissivity. J. Geophys. Res., 109, D21201, doi: /2004jd Krinner, G., O. Boucher and Y. Balkanski, 2006: Ice-free glacial northern Asia due to dust deposition on snow. Clim. Dyn., 27, , doi: /s z.

18 Mahowald, N. M., D. R. Muhs, S. Levis, P. J. Rasch, M. Yoshioka, C. S. Zender and C. Luo, 2006: Change in atmospheric mineral aerosols in response to climate: last glacial period, preindustrial, modern, and doubled carbon dioxide climates. J. Geophys. Res., 111(D10), D10202, doi: /2005jd Thonicke, K., I. C. Prentice and C. Hewitt, 2005: Modeling glacialinterglacial changes in global fire regimes and trace gas emissions. Global Biogeochem. Cycles, 19, GB3008, doi: /2004gb Zender, C. S., M. G. Flanner, J. T. Randerson, N. M. Mahowald, P. J. Rasch, M. Yoshioka and T. H. Painter, 2007: Climate effects of dust and soot in snow. In Preparation for Geophys. Res. Lett.

19 Figure 12: Predicted global mean temperature response [K] to snowpack heating by soot and dust during Last Glacial Maximum (LGM), Pre-Industrial (1870), Present Day, and 2050 IPCC A2 climates.

Dirty Snow and Arctic Climate

Dirty Snow and Arctic Climate Charlie Zender and Mark Flanner Department of Earth System Science, University of California, Irvine Laboratoire de Glaciologie Géophysique de l Environnement, (LGGE), Grenoble,