Climate Dynamics

, Volume 38, Issue 5–6, pp 897–911 | Cite as

Dependence of climate forcing and response on the altitude of black carbon aerosols

  • George A. Ban-Weiss
  • Long Cao
  • G. Bala
  • Ken Caldeira
Article

Abstract

Black carbon aerosols absorb solar radiation and decrease planetary albedo, and thus can contribute to climate warming. In this paper, the dependence of equilibrium climate response on the altitude of black carbon is explored using an atmospheric general circulation model coupled to a mixed layer ocean model. The simulations model aerosol direct and semi-direct effects, but not indirect effects. Aerosol concentrations are prescribed and not interactive. It is shown that climate response of black carbon is highly dependent on the altitude of the aerosol. As the altitude of black carbon increases, surface temperatures decrease; black carbon near the surface causes surface warming, whereas black carbon near the tropopause and in the stratosphere causes surface cooling. This cooling occurs despite increasing planetary absorption of sunlight (i.e. decreasing planetary albedo). We find that the trend in surface air temperature response versus the altitude of black carbon is consistent with our calculations of radiative forcing after the troposphere, stratosphere, and land surface have undergone rapid adjustment, calculated as “regressed” radiative forcing. The variation in climate response from black carbon at different altitudes occurs largely from different fast climate responses; temperature dependent feedbacks are not statistically distinguishable. Impacts of black carbon at various altitudes on the hydrological cycle are also discussed; black carbon in the lowest atmospheric layer increases precipitation despite reductions in solar radiation reaching the surface, whereas black carbon at higher altitudes decreases precipitation.

Keywords

Black carbon Aerosol Soot Climate change Global warming Altitude Fast response Climate sensitivity Feedback parameter 

Supplementary material

382_2011_1052_MOESM1_ESM.pdf (410 kb)
Online Resource 1. Figure S1 Regressions of key climate variables versus changes in surface air temperature following the method of Gregory et al. (2004). Annual means of the first 20 years of the simulations are used in the regressions. To decrease uncertainty, we ran a total of three 20-year simulations for each case of increased black carbon. Thus the regressions are based on annual averages of the first 20 years of three ensemble members for each case. (PDF 409 kb)
382_2011_1052_MOESM2_ESM.pdf (34 kb)
Online Resource 2. Table S1 Numerical values of key climate variables for each simulation. All results presented represent global averages of the last 70 years of 100-year simulations. Altitudes given in the top row indicate the approximate altitude with additional black carbon in each simulation. Uncertainty is given by the standard error computed from 70 annual means using the Student t test. The standard error is corrected for autocorrelation (Zwiers and von Storch 1995). (PDF 33 kb)
382_2011_1052_MOESM3_ESM.tif (15.5 mb)
Online Resource 3. Figure S2 Changes in surface temperature, instantaneous forcing, adjusted forcing, fixed-SST radiative forcing, and regressed radiative forcing as reported in Table 2 of Hansen et al. (2005). Each simulation added black carbon aerosol to a different layer in the troposphere by increasing aerosol optical depth of that layer. (TIFF 15,890 kb)

References

  1. Ackerman AS, Toon OB, Stevens DE, Heymsfield AJ, Ramanathan V, Welton EJ (2000) Reduction of tropical cloudiness by soot. Science 288:1042–1047CrossRefGoogle Scholar
  2. Albrecht BA (1989) Aerosols, cloud microphysics, and fractional cloudiness. Science 245:1227–1230CrossRefGoogle Scholar
  3. Andrews T, Forster PM, Gregory JM (2009) A surface energy perspective on climate change. J Clim 22:2557–2570Google Scholar
  4. Bala G, Caldeira K, Nemani R (2009) Fast versus slow response in climate change: implications for the global hydrological cycle. Clim Dyn. doi:10.1007/s00382-00009-00583-y
  5. Bond TC, Streets DG, Yarber KF, Nelson SM, Woo JH, Klimont Z (2004) A technology-based global inventory of black and organic carbon emissions from combustion. J Geophys Res Atmos 109. doi:10.1029/2003JD003697
  6. Cess RD (1985) Nuclear-war—illustrative effects of atmospheric smoke and dust upon solar-radiation. Clim Change 7:237–251CrossRefGoogle Scholar
  7. Collins WD, Rasch PJ, Eaton BE, Khattatov BV, Lamarque JF, Zender CS (2001) Simulating aerosols using a chemical transport model with assimilation of satellite aerosol retrievals: methodology for INDOEX. J Geophys Res Atmos 106:7313–7336CrossRefGoogle Scholar
  8. Collins WD, Rasch PJ, Eaton BE, Fillmore DW, Kiehl JT, Beck CT, Zender CS (2002) Simulation of aerosol distributions and radiative forcing for INDOEX: regional climate impacts. J Geophys Res Atmos 107. doi:10.1029/2000JD000032
  9. Collins WD et al (2004) Description of the NCAR community atmosphere model (CAM 3.0). NCAR technical note NCAR/TN-464+STR. National Center for Atmospheric Research, Boulder, COGoogle Scholar
  10. Cook J, Highwood EJ (2004) Climate response to tropospheric absorbing aerosols in an intermediate general-circulation model. Q J R Meteorol Soc 130:175–191CrossRefGoogle Scholar
  11. Covey C, Schneider SH, Thompson SL (1984) Global atmospheric effects of massive smoke injections from a nuclear-war—results from general-circulation model simulations. Nature 308:21–25CrossRefGoogle Scholar
  12. Gregory JM, Ingram WJ, Palmer MA, Jones GS, Stott PA, Thorpe RB, Lowe JA, Johns TC, Williams KD (2004) A new method for diagnosing radiative forcing and climate sensitivity. Geophys Res Lett 31. doi:10.1029/2003GL018747
  13. Hansen J, Sato M, Ruedy R (1997) Radiative forcing and climate response. J Geophys Res Atmos 102:6831–6864CrossRefGoogle Scholar
  14. Hansen J et al. (2005) Efficacy of climate forcings. J Geophys Res Atmos 110. doi:10.1029/2005JD005776
  15. Haywood JM, Ramaswamy V (1998) Global sensitivity studies of the direct radiative forcing due to anthropogenic sulfate and black carbon aerosols. J Geophys Res Atmos 103:6043–6058CrossRefGoogle Scholar
  16. Haywood JM, Shine KP (1997) Multi-spectral calculations of the direct radiative forcing of tropospheric sulphate and soot aerosols using a column model. Q J R Meteorol Soc 123:1907–1930CrossRefGoogle Scholar
  17. Haywood JM, Roberts DL, Slingo A, Edwards JM, Shine KP (1997) General circulation model calculations of the direct radiative forcing by anthropogenic sulfate and fossil-fuel soot aerosol. J Climate 10:1562–1577CrossRefGoogle Scholar
  18. Haywood JM, Donner LJ, Jones A, Golaz J-C (2009) Gobal indirect radiative forcing caused by aerosols: IPCC (2007) and beyond. In: Heintzenberg J, Charlson R (eds) Clouds in the perturbed climate system. MIT Press, Cambridge, pp 451–467Google Scholar
  19. Held IM, Soden BJ (2006) Robust responses of the hydrological cycle to global warming. J Clim 19(21):5686–5699. doi:10.1175/JCLI3990.1 Google Scholar
  20. Hess M, Koepke P, Schult I (1998) Optical properties of aerosols and clouds: the software package OPAC. Bull Am Meteorol Soc 79:831–844CrossRefGoogle Scholar
  21. IPCC (1990) Climate change: the IPCC scientific assessment. Contribution of Working Group 1 to the first assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, CambridgeGoogle Scholar
  22. IPCC (2007) Climate change 2007: the physical science basis. Contribution of Working Group 1 to the fourth assessment report of the Intergovernmental Panel on Climate Change. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds). Cambridge University PressGoogle Scholar
  23. Johnson BT (2005) The semidirect aerosol effect: comparison of a single-column model with large eddy simulation for marine stratocumulus. J Climate 18:119–130CrossRefGoogle Scholar
  24. Johnson BT, Shine KP, Forster PM (2004) The semi-direct aerosol effect: impact of absorbing aerosols on marine stratocumulus. Q J R Meteorol Soc 130:1407–1422CrossRefGoogle Scholar
  25. Kalnay E et al (1996) The NCEP/NCAR 40-year reanalysis project. B Am Meteorol Soc 77:437–471CrossRefGoogle Scholar
  26. Lambert FH, Webb MJ (2008) Dependency of global mean precipitation on surface temperature. Geophys Res Lett 35:L16706Google Scholar
  27. Lohmann U, Rotstayn L, Storelvmo T, Jones A, Menon S, Quaas J, Ekman AML, Koch D, Ruedy R (2010) Total aerosol effect: radiative forcing or radiative flux perturbation? Atmos Chem Phys 10:3235–3246CrossRefGoogle Scholar
  28. Ming Y, Ramaswamy V, Ginoux PA, Horowitz LH (2005) Direct radiative forcing of anthropogenic organic aerosol. J Geophys Res Atmos 110. doi:10.1029/2004jd005573
  29. Ming Y, Ramaswamy V, Persad G (2010) Two opposing effects of absorbing aerosols on global-mean precipitation. Geophys Res Lett 37. doi:10.1029/2010GL042895
  30. Nenes A, Conant WC, Seinfeld JH (2002) Black carbon radiative heating effects on cloud microphysics and implications for the aerosol indirect effect—2. Cloud microphysics. J Geophys Res Atmos 107. doi:10.1029/2002jd002101
  31. Oleson KW et al (2004) Technical description of the community land model (CLM). NCAR technical note NCAR/TN-461+STR. National Center for Atmospheric Research, Boulder, COGoogle Scholar
  32. Penner JE, Zhang SY, Chuang CC (2003) Soot and smoke aerosol may not warm climate. J Geophys Res Atmos 108. doi:10.1029/2003JD003409
  33. Ramanathan V, Carmichael G (2008) Global and regional climate changes due to black carbon. Nature Geosci 1:221–227CrossRefGoogle Scholar
  34. Ramanathan V, Crutzen PJ, Kiehl JT, Rosenfeld D (2001a) Atmosphere—aerosols, climate, and the hydrological cycle. Science 294:2119–2124CrossRefGoogle Scholar
  35. Ramanathan V et al (2001b) Indian Ocean experiment: an integrated analysis of the climate forcing and effects of the great Indo-Asian haze. J Geophys Res Atmos 106:28371–28398CrossRefGoogle Scholar
  36. Ramaswamy V, Kiehl JT (1985) Sensitivities of the radiative forcing due to large loadings of smoke and dust aerosols. J Geophys Res Atmos 90:5597–5613CrossRefGoogle Scholar
  37. Rasch PJ, Mahowald NM, Eaton BE (1997) Representations of transport, convection, and the hydrologic cycle in chemical transport models: implications for the modeling of short-lived and soluble species. J Geophys Res Atmos 102:28127–28138CrossRefGoogle Scholar
  38. Satheesh S (2002) Aerosol radiative forcing over land: effect of surface and cloud reflection. Ann Geophys 20:2105–2109CrossRefGoogle Scholar
  39. Seinfeld J (2008) Atmospheric science—black carbon and brown clouds. Nature Geosci 1:15–16CrossRefGoogle Scholar
  40. Seinfeld JH, Pandis SN (1998) Atmospheric chemistry and physics: from air pollution to climate change. Wiley-Interscience Publication, HobokenGoogle Scholar
  41. Shine KP, Cook J, Highwood EJ, Joshi MM (2003) An alternative to radiative forcing for estimating the relative importance of climate change mechanisms. Geophys Res Lett 30:1–4CrossRefGoogle Scholar
  42. Stowe LL, Ignatov AM, Singh RR (1997) Development, validation, and potential enhancements to the second-generation operational aerosol product at the National Environmental Satellite, Data, and Information Service of the National Oceanic and Atmospheric Administration. J Geophys Res Atmos 102:16923–16934CrossRefGoogle Scholar
  43. Turco RP, Toon OB, Ackerman TP, Pollack JB, Sagan C (1983) Nuclear winter—global consequences of multiple nuclear-explosions. Science 222:1283–1292CrossRefGoogle Scholar
  44. Twomey S (1977) Influence of pollution on shortwave albedo of clouds. J Atmos Sci 34:1149–1152CrossRefGoogle Scholar
  45. Zwiers FW, von Storch H (1995) Taking serial-correlation into account in tests of the mean. J Climate 8:336–351CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • George A. Ban-Weiss
    • 1
  • Long Cao
    • 1
  • G. Bala
    • 2
  • Ken Caldeira
    • 1
  1. 1.Department of Global EcologyCarnegie InstitutionStanfordUSA
  2. 2.Divecha Center for Climate Change and Center for Atmospheric and Ocean SciencesIndian Institute of ScienceBangaloreIndia

Personalised recommendations