Some Aspects of Uncertainty in Predicting Sea Ice Thinning - Arctic Sea Ice Decline: Observations, Projections, Mechanisms, and Implications - page 72

have argued that the principal cause is the growth-thickness
feedback, which is regulated by the conduction of heat
through the ice. This feedback controls the adjustment to
equilibrium and is strongly thickness-dependent. Heat con-
duction depends roughly on the inverse of thickness, or l/ h .
When surface fluxes are perturbed, the ice thickness adjusts
until the conduction of heat through the ice achieves surface
energy balance. The thickness need not adjust very much for
thin ice owing to the l/ h dependence. Consequently, when
the thickness is biased, the thickness change in response to
a perturbation is also biased. A bias of ± 0.77m, as from the
CMIP3 models, gives rise to an uncertainty of more than
± 1m for the thickness change because of doubling CO 2 .
I have not explained why the models have so much spread
in the mean state. Another paper in this monograph argues that
a large portion of the error can be explained by the summer-
time atmospheric energy fluxes and the surface albedo in par-
ticular [ DeWeaver et al. , this volume]. If this is the case, then
modelers should do a better job reducing biases in the atmo-
sphere and tuning the surface albedo to reduce the spread in
model uncertainty for present and future prediction.

Bony, S., et al. (2006), How well do we undersand and evaluate
climate change feedback processes?, J. Clim. , 19 , 3445-3482,
doi:10.1175/JCLI3819.1.
Collins, W. D., et al. (2006), The Community Climate System
Model Version 3 (CCSM3), J. Clim. , 19 , 2122-2143.
Comiso, J. C. (1995), SSM/I sea ice concentrations using the boot-
strap algorithm, NASA Tech. Rep., RP 1380 , 40 pp.
DeWeaver, E., and C. M. Bitz (2006), Atmospheric circulation
and Arctic sea ice in CCSM3 at medium and high resolution, J.
Clim. , 19 , 2415-2436.
DeWeaver, E., E. C. Hunke, and M. M. Holland (2008), Sensitivity
of Arctic sea ice thickness to intermodel variations in the surface
energy budget simulation, this volume.
Gregory, J. M., P. A. Stott, D. J. Cresswell, N. A. Rayner, C. Gor-
don, and D. M. H. Sexton (2002), Recent and future changes in
Arctic sea ice simulated by the HadCM3 AOGCM, Geophys.
Res. Lett., 29 (24), 2175, doi:10.1029/2001GL014575.
Hibler, W. D., and J. K. Hutchings (2002), Multiple equilibrium
Arctic ice cover states induced by ice mechanics, paper pre-
sented at Ice in the Environment: Proceedings of the 16th IAHR
International Symposium on Ice, Int. Assoc. of Hydraul. Eng.
and Res., Dunedin, New Zealand.
Hibler, W. D., J. K. Hutchings, and C. F. Ip (2006), Sea ice arching
and multiple flow states of Arctic pack ice, Ann. Glaciol. , 44 ,
339-344.
Holland, M. M., and C. M. Bitz (2003), Polar amplification of cli-
mate change in coupled models, Clim. Dyn. , 21 , 221-232.
Holland, M. M., C. Bitz, and A. Weaver (2001), The influence of
sea ice physics on simulations of climate change, J. Geophys.
Res. , 106 , 2441-2464.
Holland, M. M., C. M. Bitz, E. C. Hunke, W. H. Lipscomb,
and J. L. Schramm (2006a), Influence of the sea ice thick-
ness distribution on polar climate in CCSM3, J. Clim. , 19 ,
2398-2414.
Holland, M. M., C. M. Bitz, and B. Tremblay (2006b), Future
abrupt reductions in the summer Arctic sea ice, Geophys. Res.
Lett. , 33 , L23503, doi:10.1029/2006GL028024.
Hunke, E. C., and J. K. Dukowicz (2002), The elastic-viscous-
plastic sea ice dynamics model in general orthogonal curvilinear
coordinates on a sphere—Incorporation of metric terms, Mon.
Weather Rev. , 130 , 1848-1865.
Lipscomb, W. H. (2001), Remapping the thickness distribution in
sea ice models, J. Geophys. Res. , 106 , 13,989-14,000.
Meehl, G. A., W. M. Washington, B. D. Santer, W. D. Collins, J. M.
Arblaster, A. Hu, D. M. Lawrence, H. Teng, L. E. Buja, and
W. G. Strand (2006), Climate change projections for the twenty-
first century and climate change commitment in the CCSM3, J.
Clim. , 19 , 2597-2616.
Roe, G. H., and M. B. Baker (2007), Why is climate sensitivity
so unpredictable?, Science , 218 , 629-632, doi:10.1126/science.
1144735.
Springer, M. D. (1979), The Algebra of Random Variables , 470
pp., John Wiley, New York.
Stroeve, J., M. M. Holland, W. Meier, T. Scambos, and M. Serreze
(2007), Arctic sea ice decline: Faster than forecast, Geophys.
Res. Lett. , 34 , L09501, doi:10.1029/2007GL029703.

Acknowledgments. I am grateful for support from the National
Science Foundation through grants ATM0304662 and OPP0454843.
I thank Gerard Roe and Eric DeWeaver for helpful conversations
and two anonymous reviewers whose comments greatly improved
this paper. I thank the modeling groups, the Program for Climate
Model Diagnosis and Intercomparison (PCMDI) and the WCRP's
Working Group on Coupled Modeling (WGCM), for their roles in
making available the WCRP CMIP3 multimodel data set. Support
of this data set is provided by the Office of Science, U.S. Depart-
ment of Energy.

REFERENCES

Arzel, O., T. Fichefet, and H. Goosse (2006), Sea ice evolution over
the 20th and 21st centuries as simulated by current AOGCMs,
Ocean. Modell. , 12 , 401-415.
Bitz, C. M., and W. H. Lipscomb (1999), An energy-conserving
thermodynamic model of sea ice, J. Geophys. Res. , 104 , 15,669-
15,677.
Bitz, C. M., and G. H. Roe (2004), A mechanism for the high rate
of sea ice thinning in the Arctic ocean, J. Clim. , 17 , 3623-3632.
Bitz, C. M., D. S. Battisti, R. E. Moritz, and J. A. Beesley (1996),
Low-frequency variability in the Arctic atmosphere, sea ice, and
upper-ocean system, J. Clim. , 9 , 394-408.
Bitz, C. M., M. M. Holland, A. J. Weaver, and M. Eby (2001),
Simulating the ice-thickness distribution in a coupled climate
model, J. Geophys. Res. , 106 , 2441-2463.
Bitz, C. M., J. K. Ridley, M. M. Holland, and H. Cattle (2008), Global
climate models and 20th and 21st century Arctic climate change,
in Arctic Climate Change—The ACSYS Decade and Beyond ,
edited by P. Lemke, Springer, Heidelberg, Germany, in press.