Skip to main content

Advertisement

SpringerLink
Log in

The transformation of Arctic clouds with warming

  • Published:
Climatic Change Aims and scope Submit manuscript

Abstract

The progressive loss of Arctic sea ice leads to increased surface emissions of Dimethyl Sulphide (DMS), which is the dominant local source of sulphate aerosols. We test the hypothesis that cloud condensation nuclei, derived from DMS, will increase cloud-top albedo in an earth-system global climate model. The earth-system model includes fully interactive ocean biology, DMS, atmospheric chemistry, aerosols and cloud microphysics. In an idealised warming scenario, the Arctic Ocean becomes ice-free in summer when atmospheric CO2 is increased by 1 % per year to four times the pre-industrial concentrations. The summer boundary layer near-surface inversion strengthens, increasing stratification with warming, whilst the autumn inversion weakens. We find that the dominant change in cloud albedo arises from the conversion of summer clouds from ice to liquid, reducing the solar flux at the surface by 27 W m−2. Only 1–2 W m−2 of the reduced solar flux is attributed to cloud condensation nuclei associated with sulphate aerosols derived from the 2–5 fold increase in DMS emissions that results from an ice-free ocean. We conclude that aerosol-cloud feedbacks originating from DMS production in the Arctic region are largely mitigated through increased wet deposition of sulphate aerosols by rainfall and as a result are not a significant component of changes in the surface radiation budget in our model.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Andrews T, Ringer MA (2014) Cloud feedbacks, rapid adjustments, and the forcing–response relationship in a transient CO2 reversibility scenario. J Clim 27:1799–1818. doi:10.1175/JCLI-D-13-00421.1

    Article  Google Scholar 

  • Andrews T, Ringer MA, Doutriaux-Boucher M, Webb MJ, Collins WJ (2012) Sensitivity of an earth system climate model to idealized radiative forcing. Geophys Res Lett 39:L10702. doi:10.1029/2012GL051942

    Google Scholar 

  • Beljaars ACM, Holtslag AAM (1991) Flux parameterisation over land surfaces for atmospheric models. J Appl Meteorol 30:327–341

    Article  Google Scholar 

  • Bellouin N, Rae J, Jones A, Johnson C, Haywood J, Boucher O (2011) Aerosol forcing in the climate model Intercomparison project (CMIP5) simulations by HadGEM2-ES and the role of ammonium nitrate. J Geophys Res 116:D20206. doi:10.1029/2011JD016074

    Article  Google Scholar 

  • Bodas-Salcedo A, Williams KD, Field PR and Lock AP (2012) The surface downwelling solar radiation surplus over the Southern Ocean in the Met Office model: the role of midlatitude cyclone clouds. J Clim, 25, 7467–7486. doi: 10.1175/JCLI-D-11-00702.1

  • Browse J, Carslaw KS, Mann GW, Birch CE, Arnold SR, Leck C (2014) The complex response of Arctic aerosol to sea-ice retreat. Atmos Chem Phys 14:7543–7557. doi:10.5194/acp-14-7543-2014

    Article  Google Scholar 

  • Bucciarelli E, Ridame C, Sunda WG, Dimier-Hugueney C, Cheize M, Belviso S (2013) Increased intracellular concentration of DMSP and DMSO in iron-limited oceanic phytoplankton Thalassiosira oceanica and Trichodesmium erythraeum. Limnol Oceanogr 58:1667–1679. doi:10.4319/lo.2013.58.5.1667

    Article  Google Scholar 

  • Charlson RJ, Lovelock JE, Andreaei MO, Warren SG (1987) Oceanic phytoplankton, atmospheric Sulphur, cloud. Nature 326:655–661. doi:10.1038/326655a0

    Article  Google Scholar 

  • Clarke DB, Ackley SF (1984) Sea ice structure and biological activity in the Antarctic marginal ice zone. J Geophys Res 89(C2):2087–2095. doi:10.1029/JC089iC02p02087

    Article  Google Scholar 

  • Collins WJ et al. (2011) Development and evaluation of an earth-system model – HadGEM2. Geosci Model Dev 4:1051–1075. doi:10.5194/gmd-4-1051-2011

    Article  Google Scholar 

  • Curry J, Rossow W, Randall D, Schramm J (1996) Overview of Arctic cloud and radiation characteristics. J Clim 9:1731–1764

    Article  Google Scholar 

  • Derwent R, Collins WJ, Jenkin ME, Johnson CE, Stevenson DS (2003) The global distribution of secondary particulate matter in a 3D Lagrangian chemistry transport model. J Atmos Chem 44:57–95

    Article  Google Scholar 

  • Dyer AJ (1974) A review of flux-profile relationships. Bound-Layer Meteorol 7:363–372

    Article  Google Scholar 

  • English JM, Gettelman A, Henderson GR (2015) Arctic radiative fluxes: present-day biases and future projections in CMIP5 models. J Clim 28:6019–6038

    Article  Google Scholar 

  • Glasow R v, Crutzen PJ (2004) Model study of multiphase DMS oxidation with a focus on halogens. Atmos Chem Phys 14:589–608. doi:10.5194/acp-4-589-2004

    Article  Google Scholar 

  • Halloran PR, Bell TG, Totterdell IJ (2010) Can we trust empirical marine DMS parameterisations within projections of future climate? Biogeosciences 7:1645–1656. doi:10.5194/bg-7-1645-2010

    Article  Google Scholar 

  • Harada N (2016) Review: potential catastrophic reduction of sea ice in the western Arctic Ocean: its impact on biogeochemical cycles and marine ecosystems. Glob Planet Chang 136:1–17

    Article  Google Scholar 

  • Hobbs PV, Rangno AL (1998) Microstructures of low and middle-level clouds over the Beaufort Sea. QJR Meteorol Soc 124:2035–2071. doi:10.1002/qj.49712455012

    Article  Google Scholar 

  • Intrieri J, Fairall CW, Shupe M, Persson P, Andreas E, Guest P, Moritz R (2002) An annual cycle of Arctic surface cloud forcing at SHEBA. J Geophys Res 107:8039. doi:10.1029/2000JC000439

    Article  Google Scholar 

  • Kahl JD, Martinez DA (1996) Long-term variability in the low level inversion layer over the Arctic Ocean. Int J Climatol 16:1297–1313

    Article  Google Scholar 

  • Kay JE, Holland MM and Jahn A (2011) Inter-annual to multi-decadal Arctic Sea ice extent trends in a warming world, Geophys Res Lett, 38, L15708, doi:10.1029/2011GL048008.

  • Kettle A et al. (1999) A global database of sea surface dimethylsulfide (DMS) measurements and a procedure to predict sea surface DMS as a function of latitude, longitude, and month. Glob Biogeochem Cycles 13:399–444

    Article  Google Scholar 

  • Lalande C, Nöthig EM, Somavilla R, Bauerfeind E, Shevshenko V, Okolodkov Y (2014) Variability in under-ice export fluxes of biogenic matter in the Arctic Ocean. Glob Biogeochem Cycles. doi:10.1002/2013GB004735

    Google Scholar 

  • Lawrence J, Popova E, Yool A, Srokosz M (2015) On the vertical phytoplankton response to an ice-free Arctic Ocean. J Geophys Res 120:8571–8582. doi:10.1002/2015JC011180

    Article  Google Scholar 

  • Leighton A et al. (2015) The climatic importance of uncertainties in regional aerosol–cloud radiative Forcings over recent decades. J Clim 28:6589–6607. doi:10.1175/JCLI-D-15-0127.1

    Article  Google Scholar 

  • Lock AP, Brown AR, Bush MR, Martin GM, Smith RNB (2000) A New Boundary Layer Mixing Scheme. Part I: Scheme Description and Single-Column Model Tests. Mon Weather Rev 128:3187–3199

    Article  Google Scholar 

  • Lunden J, Svensson G, Leck C (2007) Influence of meteorological processes on the spatial and temporal variability of atmospheric dimethyl sulfide in the high Arctic summer. J Geophys Res 112:D13308. doi:10.1029/2006JD008183

    Article  Google Scholar 

  • Martin GM, Milton SF, Senior CA, Brooks ME, Ineson S, Reichler T, Kim J (2010) Analysis and reduction of systematic errors through a seamless approach to modelling weather and climate. J Clim 23:5933–5957. doi:10.1175/2010JCLI3541.1

    Article  Google Scholar 

  • Martin GM et al. (2011) The HadGEM2 family of Met Office unified model climate configurations. Geosci Model Dev 4:723–757. doi:10.5194/gmd-4-723-2011

    Article  Google Scholar 

  • Monin AS, Obukhov AM (1954) Basic regularity in turbulent mixing in the surface layer of the atmosphere, Moscow, Ak. Nauk. Geof Inst 24:163–187

    Google Scholar 

  • O’Dowd CD, Smith MH, Consterdine IE, Lowe JA (1997) Marine aerosol, sea-salt, and the marine Sulphur cycle: a short review. Atmos Environ 31:73–80

    Article  Google Scholar 

  • O'Connor FM et al. (2014) Evaluation of the new UKCA climate-composition model – part 2: the troposphere. Geosci Model Dev 7:41–91

    Article  Google Scholar 

  • Penner JE (2004) Climate change: the cloud conundrum. Nature 432:962–963

    Article  Google Scholar 

  • Quinn PK, Bates TS (2011) The case against climate regulation via oceanic phytoplankton Sulphur emissions. Nature 480:51–56. doi:10.1038/nature10580

    Article  Google Scholar 

  • Rasmussen RM, Geresdi I, Thompson G, Manning K, Karplus E (2002) Freezing drizzle formation in stably stratified layer clouds: the role of radiative cooling of cloud droplets, cloud condensation nuclei, and ice initiation. J Atmos Sci 59:837–860

    Article  Google Scholar 

  • Seinfeld JH, Pandis SN (2006) .: Atmospheric Chemistry and Physics. In: From Air Pollution To Climate Change. John Wiley and Sons, New Jersey, pp. 902–906

    Google Scholar 

  • Simo R (2001) Production of atmospheric sulfur by oceanic plankton: biogeochemical, ecological, and evolutionary links. Trends Ecol Evol 16:287–294. doi:10.1016/S0169-5347(01)02152-8

    Article  Google Scholar 

  • Simo R, Dachs J (2002) Global Ocean emission of dimethylsulfide predicted from biogeophysical data. Glob Biogeochem Cycles 16:1078. doi:10.1029/2001GB001829

    Article  Google Scholar 

  • Sunda W, Kieber DJ, Kiene RP, Huntsman S (2002) An antioxidant function for DMSP and DMS in marine algae. Nature 418:317–320. doi:10.1038/nature00851

    Article  Google Scholar 

  • Tjernström M et al. (2012) Central Arctic atmospheric summer conditions during the Arctic summer Cloud Ocean study (ASCOS): contrasting to previous expeditions. Atmos Chem Phys Discuss 12:4101–4164. doi:10.5194/acpd12-4101-2012

    Article  Google Scholar 

  • Twomey S (1974) Pollution and the planetary albedo. Atmos Environ 8:1251–1256

    Article  Google Scholar 

  • Twomey S, Piepgrass M, Wolfe TL (1984) An assessment of the impact on global cloud albedo. Tellus 36B:356–366

    Article  Google Scholar 

  • Webb M, Senior C, Bony S, Morcrette J-J (2001) Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models. Clim Dyn 17:905–922

    Article  Google Scholar 

  • Wilson DR, Ballard SP (1999) A microphysically based precipitation scheme for the UK meteorological office unified model. Q J R Meteorol Soc 125:1607–1636. doi:10.1002/qj.49712555707

    Article  Google Scholar 

  • Yool A, Popova EE, Coward AC (2015) Future change in ocean productivity: is the Arctic the new Atlantic? J Geophys Res 120:7771–7790. doi:10.1002/2015JC011167

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the Joint UK BEIS/Defra Met Office Hadley Centre Climate Programme (GA01101). W thank the anonymous reviewers for their insightful comments.

Author information

Authors and Affiliations

  1. Met Office, FitzRoy Road, Exeter, EX1 3PB, UK

    J. K. Ridley, M. A. Ringer & R. M. Sheward

  2. Institute of Geosciences, Goethe University Frankfurt, Altenhöferallee 1, D-60438, Frankfurt am Main, Germany

    R. M. Sheward

Authors
  1. J. K. Ridley
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. A. Ringer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. R. M. Sheward
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to J. K. Ridley.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ridley, J.K., Ringer, M.A. & Sheward, R.M. The transformation of Arctic clouds with warming. Climatic Change 139, 325–337 (2016). https://doi.org/10.1007/s10584-016-1772-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10584-016-1772-4

Keywords

Search

Navigation