Polar amplification of climate change in coupled models

Holland, Marika M.; Bitz, Cecilia M.

doi:10.1007/s00382-003-0332-6

Cited by 1,077 publications

(833 citation statements)

References 33 publications

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“…2004), similar to the annual losses of ice-volume ($2.8 mSv) estimated by Rothrock and Zhang (2005) for the past half-century . It has to be stated, however, that sea-ice parameters like thickness, extent and representation of the seasonal cycle from presently published coupled climate models differ greatly between themselves and in comparison with observations (Flato et al, 2004;Hu et al, 2004), as do atmospheric parameters such as air temperature (Holland and Bitz, 2003) and sea-level pressure. In their 52-year simulation, Rothrock and Zhang (2005) find that the wind-forced component of sea-ice volume has no substantial trend but the temperature-forced component has a significant downward trend of À3% per decade.…”

Section: The Futurementioning

confidence: 99%

Current estimates of freshwater flux through Arctic and subarctic seas

Dickson

Rudels²,

Dye

et al. 2007

Progress in Oceanography

242

227

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Section: The Futurementioning

confidence: 99%

Current estimates of freshwater flux through Arctic and subarctic seas

Dickson

Rudels²,

Dye

et al. 2007

Progress in Oceanography

242

227

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“…Past and on-going climatic changes are amplified in the polar regions [Holland and Bitz, 2003]. Current climate changes, associated with largescale anthropogenic emissions of greenhouse gases, involve a warming of the ocean, changes in its chemical composition, as well as a dramatic sea ice retreat in the Arctic [Comiso et al, 2010].…”

Section: Introductionmentioning

confidence: 99%

Role of sea ice in global biogeochemical cycles: emerging views and challenges

Vancoppenolle

Meiners

Michel

et al. 2013

Quaternary Science Reviews

212

211

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International audienceObservations from the last decade suggest an important role of sea ice in the global biogeochemical cycles, promoted by (i) active biological and chemical processes within the sea ice; (ii) fluid and gas exchanges at the sea ice interface through an often permeable sea ice cover; and (iii) tight physical, biological and chemical interactions between the sea ice, the ocean and the atmosphere. Photosynthetic micro-organisms in sea ice thrive in liquid brine inclusions encased in a pure ice matrix, where they find suitable light and nutrient levels. They extend the production season, provide a winter and early spring food source, and contribute to organic carbon export to depth. Under-ice and ice edge phytoplankton blooms occur when ice retreats, favoured by increasing light, stratification, and by the release of material into the water column. In particular, the release of iron - highly concentrated in sea ice - could have large effects in the iron-limited Southern Ocean. The export of inorganic carbon transport by brine sinking below the mixed layer, calcium carbonate precipitation in sea ice, as well as active ice-atmosphere carbon dioxide (CO₂) fluxes, could play a central role in the marine carbon cycle. Sea ice processes could also significantly contribute to the sulphur cycle through the large production by ice algae of dimethylsulfoniopropionate (DMSP), the precursor of sulphate aerosols, which as cloud condensation nuclei have a potential cooling effect on the planet. Finally, the sea ice zone supports significant ocean-atmosphere methane (CH₄) fluxes, while saline ice surfaces activate springtime atmospheric bromine chemistry, setting ground for tropospheric ozone depletion events observed near both poles. All these mechanisms are generally known, but neither precisely understood nor quantified at large scales. As polar regions are rapidly changing, understanding the large-scale polar marine biogeochemical processes and their future evolution is of high priority. Earth system models should in this context prove essential, but they currently represent sea ice as biologically and chemically inert. Palaeoclimatic proxies are also relevant, in particular the sea ice proxies, inferring past sea ice conditions from glacial and marine sediment core records and providing analogues for future changes. Being highly constrained by marine biogeochemistry, sea ice proxies would not only contribute to but also benefit from a better understanding of polar marine biogeochemical cycles

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“…The additional absorbed solar radiation results in more warming (Cubasch et al 2001;Holland and Bitz 2003). This positive feedback, the so-called snow albedo feedback, accounts for about half of the additional net incoming solar radiation associated with the NH cryosphere retreat in equilibrium climate change simulations (Hall 2004).…”

Section: Introductionmentioning

confidence: 99%

“…By correlating Earth Radiation Budget Experiment top-of-the-atmosphere shortwave fluxes and satellite-observed snow extent in the NH extratropics, Groisman et al (1994a,b) pointed out that a large portion of the NH warming for the last two decades of the twentieth century can be attributed to snow albedo changes. Despite the consensus on the sign of the feedback, its strength as seen in climate change simulations carried out over the past two decades varies significantly (Cess et al 1991;Randall et al 1994;Cubasch et al 2001;Holland and Bitz 2003). These differences become a source of divergence in simulated climate change (Cubasch et al 2001;Holland and Bitz 2003).…”

Section: Introductionmentioning

confidence: 99%

“…Despite the consensus on the sign of the feedback, its strength as seen in climate change simulations carried out over the past two decades varies significantly (Cess et al 1991;Randall et al 1994;Cubasch et al 2001;Holland and Bitz 2003). These differences become a source of divergence in simulated climate change (Cubasch et al 2001;Holland and Bitz 2003).…”

Section: Introductionmentioning

confidence: 99%

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Assessing Snow Albedo Feedback in Simulated Climate Change

Hall

2006

Journal of Climate

105

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In this paper, the two factors controlling Northern Hemisphere springtime snow albedo feedback in transient climate change are isolated and quantified based on scenario runs of 17 climate models used in the Intergovernmental Panel on Climate Change Fourth Assessment Report. The first factor is the dependence of planetary albedo on surface albedo, representing the atmosphere's attenuation effect on surface albedo anomalies. It is potentially a major source of divergence in simulations of snow albedo feedback because of large differences in simulated cloud fields in Northern Hemisphere land areas. To calculate the dependence, an analytical model governing planetary albedo was developed. Detailed validations of the analytical model for two of the simulations are shown, version 3 of the Community Climate System Model (CCSM3) and the Geophysical Fluid Dynamics Laboratory global coupled Climate Model 2.0 (CM2.0), demonstrating that it facilitates a highly accurate calculation of the dependence of planetary albedo on surface albedo given readily available simulation output. In all simulations it is found that surface albedo anomalies are attenuated by approximately half in Northern Hemisphere land areas as they are transformed into planetary albedo anomalies. The intermodel standard deviation in the dependence of planetary albedo on surface albedo is surprisingly small, less than 10% of the mean. Moreover, when an observational estimate of this factor is calculated by applying the same method to the satellite-based International Satellite Cloud Climatology Project (ISCCP) data, it is found that most simulations agree with ISCCP values to within about 10%, despite further disagreements between observed and simulated cloud fields. This suggests that even large relative errors in simulated cloud fields do not result in significant error in this factor, enhancing confidence in climate models. The second factor, related exclusively to surface processes, is the change in surface albedo associated with an anthropogenically induced temperature change in Northern Hemisphere land areas. It exhibits much more intermodel variability. The standard deviation is about 1 ⁄3 of the mean, with the largest value being approximately 3 times larger than the smallest. Therefore this factor is unquestionably the main source of the large divergence in simulations of snow albedo feedback. To reduce the divergence, attention should be focused on differing parameterizations of snow processes, rather than intermodel variations in the attenuation effect of the atmosphere on surface albedo anomalies.

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Polar amplification of climate change in coupled models

Cited by 1,077 publications

References 33 publications

Current estimates of freshwater flux through Arctic and subarctic seas

Current estimates of freshwater flux through Arctic and subarctic seas

Role of sea ice in global biogeochemical cycles: emerging views and challenges

Assessing Snow Albedo Feedback in Simulated Climate Change

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