Collaborative Research Agreement at the University of Victoria
on Behalf of the Canadian Institute for Climate Studies and Environment Canada
(CICS-Arctic Ocean; and subcomponent of CICS-Variability)
May 31, 2001
This progress report is available on the world wide web at:
1: Principal Investigator
Ed Carmack, Greg Flato, Lawrence Mysak
School of Earth & Ocean Sciences, University of Victoria
PO Box 3055, Victoria, BC, V8W 3P6
4: Research Progress
This progress report will discuss research conducted during the second year of financial support from the MSC/CICS Arctic Node of the Canadian Climate Research Network. The McGill component of this project will be reported on in a separate progress report.
Substantial leverage of the CICS grant occurred during the last fiscal year. In particular, Flato and Weaver received 100,000$ over two years to support a new research associate (Oleg Saenko) to assist in the implementation of the Bitz et al (2000) dynamic/thermodynamic sea ice model into the CCCma coupled model. In addition, A. Weaver and M. Holland at NCAR received a $100,000 US per year (for two years) grant from the International Arctic Research Center in Fairbanks Alaska. This grant will allow for the participation of M. Holland in the collaborative research conducted in the CICS Arctic Node.
The progress report below is broken up into a number of sections detailing progress towards different objectives. Progress is reported for the entire 2000-2001 fiscal year.
4.1 Sea ice model sensitivity analyses
Sea ice cover is an important factor in the climate system due to feedback mechanisms associated with its influence on the surface albedo and ice-ocean-atmosphere exchange. However, sea ice models in GCMs typically used relatively crude physics. Single column and basin scale ice models have attempted to assess the importance of different physical parameterizations, however, this has often been done in uncoupled systems which means that various coupled feedback mechanisms are missing.
We examined the sensitivity of climate change simulations in the UVic coupled model to different sea ice physics. In particular, we addressed the influences of ice dynamics and a sub-gridscale ice thickness distribution on the simulation of present-day climate conditions and the climate response to increasing atmospheric CO2 levels. Additionally, we examined the influence of the albedo feedback mechanism in climate change experiments.
As in several previous studies, we found that the sea-ice parameterizations have a significant influence on present-day climate simulations, modifying both the annual mean ice-ocean-atmosphere conditions and the seasonal variation of these properties. For example, in models with motionless sea ice (i.e., thermodynamic-only models) the ice volume increases significantly and undergoes a smaller seasonal cycle. Resolving the ice thickness distribution also increases the ice thickness, but acts to enhance the seasonal cycle. Additionally, the ocean circulation is modified due to different ice/ocean buoyancy fluxes, leading to different Antarctic Bottom Water formation rates.
The presence of ice dynamics and the sub-gridscale ice thickness distribution also influence the response of the system to climate perturbations. Under increased atmospheric CO2 forcing, simulating ice dynamics and the ice thickness distribution enhances the ice area response. However, the ice volume response is diminished when ice dynamics in included and is enhanced when the ice thickness distribution is resolved. The ocean response to global warming is also modified due to the changes in ice physics and the thermohaline circulation is less sensitive to climate change scenarios in models that resolve ice dynamics and the ice thickness distribution.
Additional simulations were performed to quantify the influence of the albedo feedback mechanism on climate change simulations. In increasing CO2 simulations, which neglected the influence of a changing surface albedo, amplified warming was still present (although reduced) at high latitudes due to the poleward retreat of the ice cover and larger ocean-atmosphere heat exchange. In these simulations, the albedo feedback has a considerable influence on the climate response to global warming, accounting for 17% of the global air temperature increase, 37% of the Northern Hemisphere ice area decrease and 31% of the Northern Hemisphere ice volume decrease.
The results of this study have been accepted for publication Holland et al (2000).
4.2: Projections of climate change onto modes of atmospheric variability
D. Stone, A Ph.D. student, has made substantial progress towards the completion of several of the goals of this project. One of the goals of this project was to verify the hypothesis that the Arctic Oscillation (AO) and other dominant patterns of variability remain important in climates with higher greenhouse gas concentrations. Another goal of this project was to determine if climate change induced by increased greenhouse gas concentrations projects onto the natural modes of climate variability.
Two possible interpretations of forced climate change view it as projecting, either linearly or nonlinearly, onto the dominant modes of variability of the climate system. An evaluation of these two interpretations was performed using sea level pressure (SLP) and surface air temperature (SAT) fields obtained from integrations of the Geophysical Fluid Dynamics Laboratory coupled general circulation model forced with varying concentrations of greenhouse gases.
The dominant modes of SLP both represent much of the total variability and remain important in warmer climates. With SAT, however, the dominant modes are often related to variations in the sea ice edge and so do not remain important since the ice retreats as the climate warms; those unrelated to sea ice remain dominant in the warmer climates, but represent smaller fractions of the total variability.
The change in SLP projects partially onto the AO-like mode in the Northern Hemisphere. In the Southern Hemisphere the change projects negligibly onto the dominant modes between equilibrium climates, but almost entirely onto the AAO-like mode in the transient integration. This difference between the transient and equilibrium responses arises from the substantial retreat of Antarctic sea ice and subsequent ocean warming. Unlike SLP, the changes in SAT do not project substantially onto any of the dominant patterns of variability. Changes appear to project strongly onto the ENSO-like mode, but in fact ~90% of this projection relates to the mean global warming associated with the mode, while only ~10% relates to the actual pattern.
In all cases examined the projection of climate change overwhelmingly manifests itself as a linear trend in the mode, with no important alteration of its behaviour. These results also demonstrate that recent observational studies supporting the nonlinear projection interpretation may instead be indicative of a linear projection of climate change onto the dominant modes.
This research has been published in Stone et al. (2001).
4.3 Fresh water fluxes through the Canadian Arctic Archipelago
As part of his MSc, Gilles Arfeuille participated in an Arctic cruise which completed 184 science stations in the western part of the Canadian Arctic Archipelago from the 23rd of August to the 25th of October 1999. During these sciences stations CTD/Rosette casts were conducted to infer the fresh water flux through the Canadian Arctic Archipelago, especially in its western part (i.e. Amundsen Gulf, Prince of Wales Strait, Dolphin and Union Strait, Coronation Gulf, Dease Strait, Queen Maud Gulf, Simpson Strait, Chantrey Inlet, Rae Strait, James Ross Strait, Peel Sound, and Bellot Strait), which has not been studied in detail in previous years. Using 1995, 1997 and this 1999 data, the fresh water flux by sea ice transport and buoyancy boundary currents will be inferred. The fresh water import into the North Atlantic via Baffin Bay is estimated to be 20% of the sea-ice export through Fram Strait. ThedO18 data from the water samples taken during the science cruise will reveal the origin of the fresh water forming the buoyancy boundary currents observed during the cruise using the CTD data (i.e. sea-ice melting or river runoff origin).
The post-cruise calibrations and the salinity measurements from the salinity samples have been calculated, and the data has been filtered. Initial results, which are promising, reveal the relative importance of fresh water input from rivers and sea-ice melting in the Archipelago and the transport of this fresh water via buoyancy boundary currents. One of the interesting results is the high variability of these buoyancy boundary currents. To infer more on the variability of the latter Gilles recently spent a two week period undertaking repeated transverse sections out of Cambridge Bay. He is currently writing up his MSc thesis which will lead to a journal article.
Julie Bacle, a new PhD student working with E. Carmack has also recently joined this project (Sept. 1, 2000). She is currently undertaking course work and recently came back from a cruise in the region. Her attention will be on biodiversity in the region as well as in Baffin Bay.
4.4 Importance of wind-driven sea ice motion for the formation of ocean water masses
An ocean-atmosphere-sea ice model was used to show the importance of wind-driven sea ice motion in the formation of low salinity Antarctic Intermediate Water (AAIW). The model was still able to reasonably simulate a tongue of relatively low salinity AAIW even when the direct momentum transfer from wind to the ocean was neglected, provided that the wind stress was applied to sea ice. In contrast, when the wind stress exclusively drove the ocean, the model failed to capture the properties of AAIW. The large-scale wind-driven sea ice motion preconditions the growth of sea ice in locations different from regions of ice melt on the annual mean basis. Melting of sea ice then provides fresh water to feed AAIW, whereas its growth makes near-surface Antarctic waters saltier, contributing to the formation of AABW. That is, the growth and subsequent offshore transport of sea ice acts as a freshwater conduit from near-shore regions, where AABW is formed, to subpolar regions, where AAIW is formed. Sea ice dynamics were also shown to be important in the simulation of a local salinity minimum at intermediate depths in the southern Indian Ocean and a local salinity maximum in the western Weddell Sea. We concluded that the proper representation of southern hemisphere ventilation processes in climate models requires the use of wind-driven sea ice dynamics.
4.5 Incorporation of a new sea ice model in the CCCma coupled model
The ‘elastic-viscous-plastic’ sea ice dynamics model of Hunke and Dukowicz (1997) was modified to operate as a module of the CCCma coupled model (versions CGCM2 and CGCM3). This module is now available for use in place of the existing ‘cavitating fluid’ sea ice dynamics model (Flato and Hibler, 1992; Flato and Boer, 2001). Several 10-year long integrations of the coupled model were conducted to test the new ice dynamics scheme and to compare the overall climate simulation obtained with the new scheme to that of the original model. These runs have been completed, and a paper describing the results is expected (to be completed under other funding).
The multi-layer vertical heat conduction component of the Bitz and Lipscomb (1998) thermodynamic model was isolated and modified to operate within the CCCma coupled model. Test integrations of the coupled model with this new heat conduction scheme were performed and results compared to the ‘single-layer’ scheme used in the original version of the CCCma model. These comparisons indicated rather small differences in the resulting sea-ice climate.
Many of the ice model’s thermodynamic parameters remain rather uncertain. The World Climate Research Programme (WCRP) ACSYS/CliC Sea Ice Model Intercomparison Project (SIMIP2 – lead by G. Flato) is aimed at evaluating sea-ice thermodynamic models and improving them for use in climate studies (http://www.cccma.bc.ec.gc.ca/acsys/simip2). In order to test both the original CCCma climate model thermodynamic scheme and the new Bitz/Lipscomb scheme in the context of this international effort, stand-alone versions of both sea-ice thermodynamic models were constructed and used to perform 1-year simulations of the evolving thickness of a multi-year ice floe. Direct comparisons to observations made during the SHEBA field experiment were also made. This work will continue under other funding.
Sub-grid-scale ice thickness variability can be represented in terms of a ‘thickness distribution function’. So-called ‘multi-category’ models have made use of such a scheme, but were computationally expensive. A novel numerical scheme developed by Bitz et al. (2001) reduces the computational expense and was therefore deemed suitable for possible use in a global climate model. Intial test calculations in a stand-alone sea-ice model were performed to assess the sensitivity of such a model to climate change. Results of these experiments are described in a paper just submitted (Saenko, Flato and Weaver, 2001). However, later work by Lipscomb (2001) uncovered wome numerical difficulties with the Bitz et al. scheme which, although not too significant in terms of computed mean ice thickness, do introduce spurious interannual variability. It was therefore decided not to introduce this multi-category scheme into the CCCma coupled model.
The ‘first-order’ effect of sub-grid-scale thickness variability is captured by a so-called ‘two-category’ model – one that represents the energy exchanges separately over the open water and ice fractions within a model grid cell. This was not done in the original CCCma coupled model. Substantial modifications were made to the atmospheric component of the coupled model to implement the two-category representation (it should be noted that this could be generalized to a multi-category approach at a later stage with rather modest incremental effort). Decade-long coupled model simulations were performed to evaluate the effect of this representation of sub-grid-scale effects on the surface energy balance. The differences in simulated ice climate are large, but further ‘tuning’ of model parameters may be necessary (to be done later in consultation with the developers of the atmospheric model). The initial results are being analyzed and a paper is expected (to be completed under other funding).
Heat transfer at the ice underside plays an important role in moderating ice growth. The scheme used in the original CCCma coupled model was modified to produce heat transfer rates more in line with what is expected from turbulent boundary layer theory. Decade-long coupled model integrations were conducted to evaluate the impact of such a change. The result was a significant improvement in modelled ice thickness.
The salt flux generated by growing ice in sea water acts to destabilize the water column and promote convective mixing with the underlying water. Since most ice growth occurs under leads, this salt flux is localized. A parameterization of the penetration of this salt via convection was proposed by Duffy et al. (1999; 2001). This parameterization was generalized for use in a multi-category sea-ice model, and test simulations were conducted. Results are summarized in Saenko et al. (2001).
Bitz, C.M. and W.H. Lipscomb, An energy-conserving thermodynamic model of sea ice. J. Geophys. Res., 104, 15,669-15,677, 1999.
Duffy, P.B., M. Eby and A.J. Weaver, Effects of sinking of salt rejected during formation of sea ice on results of a global ocean-atmosphere-sea ice climate model. Geophys. Res. Lett., 26, 1739-1742, 1999.
Flato, G.M. and G.J. Boer, Warming asymmetry in climate change simulations. Geophys. Res. Lett., 28(1),195-198, 2001.
Flato, G.M. and W.D. Hibler III, Modeling pack ice as a cavitating fluid. J. Phys. Oceanogr., 22, 626-651, 1992.
Hunke, E.C. and J.K. Dukowicz, An elastic-viscous-plastic model for sea ice dynamics. J. Phys. Oceanogr., 27, 1849-1867, 1997.
Lipscomb, W.H., Remapping the thickness distribution in sea ice models. J. Geophys. Res., in press, 2001.
Year 2000/01 Publications for Weaver. Those numbers in bold indicated publications supported by the CICS Arctic/Variability Projects.
1. Holland, M.M., A.J. Brasket and A.J. Weaver, 2000: The impact of rising atmospheric CO2 on low frequency North Atlantic climate variability. Geophysical Research Letters, 27, 1519–1522.
2. Weaver, A.J., P.B. Duffy, M. Eby and E.C. Wiebe, 2000: Evaluation of ocean and climate models using present-day observations and forcing. Atmosphere-Ocean, 38, 271–301.
3. Stone, D.A., A.J. Weaver and F.W. Zwiers, 2000: Trends in Canadian precipitation intensity. Atmosphere-Ocean, 38, 321–347.
4. Flato, G.M., G.J. Boer, W.G. Lee, N.A. McFarlane, D. Ramsden, M.C. Reader and A.J. Weaver, 2000: The Canadian Centre for Climate Modelling and Analysis global coupled model and its climate. Climate Dynamics, 16, 451–467.
5. Rutter, N.W., A.J. Weaver, D. Rokosh, A.F. Fanning and D.G. Wright, 2000: Data-model comparison of the Younger Dryas event. Canadian Journal of Earth Sciences, 37, 811–830.
6. Weaver, A.J., and F.W. Zwiers, 2000: Uncertainty in climate change Nature, 407, 571-572..
7. Zwiers, F.W., and A. J. Weaver, 2000: The causes of
8. Weaver, A.J. and H. Raptis, 2001: Gender differences in introductory atmospheric and oceanic science exams: Multiple choice versus constructed response questions. Journal of Science Education and Technology, 10, 115-126.
9. Duffy, P.B., M. Eby and A.J. Weaver, 2001: Climate model simulations of effects of increased atmospheric CO2 and loss of sea ice on ocean salinity and tracer uptake. Journal of Climate, 14, 520–532.
10. Bitz, C.M., M.M. Holland, A.J. Weaver and M. Eby, 2001: Simulating the ice-thickness distribution in a coupled climate model. Journal of Geophysical Research, 106, 2441–2463.
11. Schmittner, A. and A.J. Weaver, 2001: Dependence of multiple climate states on ocean mixing parameters. Geophysical Research Letters, 28, 1027–1030.
12. Holland, M.M., C.M. Bitz, M. Eby and A.J. Weaver, 2001: The role of ice ocean interactions in the variability of the North Atlantic thermohaline circulation. Journal of Climate, 14, 656–675.
13. Hillaire-Marcel, C., A. de Vernal, G. Bilodeau and A.J. Weaver, 2001: Absence of deep-water formation in the Labrador Sea during the last interglacial period. Nature, 410, 1073–1077.
14. Yoshimori, M., A.J. Weaver, S.J. Marshall and G.K.C. Clarke, 2001: Glacial termination: Sensitivity to orbital and CO2 forcing in a coupled climate system model. Climate Dynamics, 17, 571-588.
— Refereed Publications (in press)
15. McAvaney, B.J., C. Covey, S. Joussaume, V. Kattsov, A. Kitoh, W. Ogana, A.J. Pitman, A.J. Weaver, R.A. Wood, and Z.-C. Zhao, 2001: Model evaluation. In: Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, England.
16. Stone, D.A., A.J. Weaver and R.J. Stouffer, 2001: Projection of climate change onto modes of atmospheric variability. J. Climate, in press.
17. Weaver, A.J., M. Eby, E. C. Wiebe, C. M. Bitz, P. B. Duffy, T. L. Ewen, A. F. Fanning, M. M. Holland, A. MacFadyen, O. Saenko, A. Schmittner, H. Wang and M. Yoshimori, 2001: The UVic Earth System Climate Model: Model description, climatology and application to past, present and future climates. Atmosphere-Ocean, in press.
18. Saenko, O., G. M. Flato and A. J. Weaver, 2001: Improved representation of sea-ice processes in climate models. Atmosphere-Ocean, in press.
19. Yoshimori, M., M.C. Reader, A.J. Weaver and N.A. MacFarlane, 2001: On the causes of glacial inception at 116KaBP. Climate Dynamics, in press.
20. Holland, M.M., C.M. Bitz and A.J. Weaver, 2001: The influence of sea ice physics on simulations of climate change. Journal of Geophysical Research, in press.
— Refereed Publications (submitted)
21. McLaughlin, F. E. Carmack, R. Macdonald, A.J. Weaver and J. Smith, 2001: The Canada Basin 1989-1995: Upstream events and far-field effects of the Barents Sea branch. Journal of Geophysical Research., submitted.
22. Claussen, M., L. A. Mysak, A. J. Weaver, M. Crucifix, T. Fichefet, M.-F. Loutre, S. L. Weber, J. Alcamo, V.A. Alexeev, A. Berger, R. Calov, A. Ganopolski, H. Goosse, G. Lohman, F. Lunkeit, I.I. Mohkov, V. Petoukhov, P. Stone and Z. Wang, 2001: Earth System Models of Intermediate Complexity: Closing the gap in the spectrum of climate system models. Climate Dynamics, submitted.
23. Schmittner, A., K.J. Meissner, M. Eby and A. J. Weaver, 2001: Forcing of the deep ocean circulation in simulations of the Last Glacial Maximum. Paleoceanography, submitted.
24. Meissner, K.J., A. Schmittner, E.C. Wiebe and A.J. Weaver, 2001: Simulations of Heinrich Events in a coupled ocean-atmosphere-sea ice model. Geophysical Research Letters, submitted.
25. de Vernal, A., C. Hillaire-Marcel, W.R. Peltier and A.J. Weaver, 2001: The structure of the upper water column in the northwest North Atlantic: Modern vs. last glacial maximum conditions. Paleoceanography, submitted.
26. Schmittner, A., M. Yoshimori and A.J. Weaver, 2001: Instability of glacial climate in an Earth System climate model. Nature, submitted.
27. Clark, P.U., A.J. Weaver and N.G. Pisias, 2001: Abrupt climate change. Nature, submitted.
28. Saenko, O., and A. J. Weaver, 2001: Importance of wind-driven sea ice motion for the formation of Antarctic Intermediate Water in a global climate model. Geophysical Research Letters, submitted.