Challenges in Modeling Global Sea Ice in a Changing Environment

1. Challenges in Modeling Global Sea Ice in a Changing Environment Marika M Holland National Center for Atmospheric Research

2. Coupled Climate Models • Systems of equations that describe fluid motion, radiative transfer, etc. • Include ocean, atmosphere, land, sea ice components • Conservative exchange of heat, water, momentum across components • Unresolved processes are parameterized

3. Sea Ice Models Used in Climate Simulations • Two primary components • Dynamics • Solves force balance to determine sea ice motion • Thermodynamics • Solves for vertical ice temperature profile • Vertical/lateral melt and growth rates • Some (about 30% of IPCC-AR4) models also include • Ice Thickness Distribution • Subgridscale parameterization • Accounts for high spatial heterogeneity in ice

4. Simulated Ice Thickness Climatology 1980-1999 Thickness varies considerably across models Differences in mean and distribution Largest inter-model scatter is in the Barents Sea region Ensemble Mean Standard Deviation 2.0 m 1.0 0.0 3.0

5. Ice Thickness • Equilibrium Reached when • Ice growth is balanced by ice melt + ice divergence • Illustrative to consider how different models achieve this balance and how mass budgets change over time Assessing Sea Ice Mass Budgets North America Bering Strait CAA Eurasia Fram Strait Barents Sea Thermodynamic source Divergence Ice volume change Climate model archive of monthly averaged ice thickness and velocity Assess Arctic ice volume, transport through Arctic straits, and solve for ice growth/melt as residual Holland et al., 2010

6. 20th century mass budgets Mean of 14 Models Across the 14 models: Annual Ice melt varies from 0.6m-1.8m Annual growth has a similar range (0.9m-1.9m) Annual ice divergence varies from 0.03m-0.6m

7. 20th century mass budgets Net SW Net Flux Correlation of ice melt and SHF Mean of 14 Models Regression of ice melt and SHF • Intermodel scatter in ice melt strongly related to net SW flux • Suggests a dominant role for albedo variations across models, which may be caused by: • Albedo parameterizations • Simulated surface state (e.g. snowfall) Net SW

8. Arctic Ice Thickness Change • By 2100, in response to rising GHGs, considerable ice volume loss of about 1.5m on annual average • Large intermodel scatter in ice loss is strongly related to initial ice thickness • Models with initially thicker ice have larger ice volume loss Ensemble Mean Ensemble Range Average Arctic ice thickness change (SRES A1B Scenario)

9. Ice Mass Budget Change Over 21st century, increased net ice melt occurs Partially balanced by reduced divergence (less transport from Arctic to lower latitudes). Multi-model ensemble mean Mass Budget Change Relative to 1950-1970 mean

10. For different models: • Nature of ice mass budget changes varies considerably • Different in • Magnitude of net change • Magnitude and sign of terms that produce change

11. Model scatter in evolving ice mass budgets Melt Change at 2050 • All models exhibit reduced ice transport, related to thinning ice • Net melt increase strongly related to initial thickness (thicker models have more melt) • Relative role of changes in melt and growth are related to evolving September ice extent • Increases in ice melt give way to decreases in ice growth as Arctic loses the summer ice cover Growth Change at 2050

12. Ice mass budgets affected by climate feedbacks • Fundamental sea ice thermodynamics gives rise to a number of important feedbacks Surface albedo changes modify SW absorption in ice and ocean heat flux Ice loss lowers albedo – positive feedback

13. Ice mass budgets affected by climate feedbacks • Fundamental sea ice thermodynamics gives rise to a number of important feedbacks Heat conduction related to vertical temperature gradient Causes ice growth to vary as 1/h Has a stabilizing effect on ice thickness since thin ice grows more rapidly

14. Model scatter in evolving ice mass budgets Melt Change • Influence of ice thickness on ice growth rates causes ice growth to increase (for some models) even with large Arctic warming • However, when summer ice cover becomes sufficiently low, the albedo feedback overwhelms this and results in ice growth reductions Growth Change Divergence Growth Melt CCSM3 Model

15. Albedo Feedback The surface albedo feedback can be isolated as: Importance of surface albedo changes is assessed from: where • Changes potentially due to: • Changing area of open water • Changing albedo of sea ice

16. Albedo FeedbackAnalysis  Assess the change in albedo per change in surface temperature (Da/DT) using transient climate integrations T

17. Surface Albedo Feedback Analysis For Arctic Ocean domain, sensitivity of surface albedo to air temperature change exhibits a three-fold variation across models By year 2100, 80% of intermodel scatter related to scatter in summer open water area change At year 2050, changes in sea ice albedo play a larger role

18. Evidence that model parameterizations influence feedback strengthEnhanced albedo feedback in ITD run ITD (5 cat) 1 cat. 1cat tuned Larger albedo change per temperature change for thinner initial ice With ITD have larger a change for ice with same initial thickness Suggests surface albedo feedback enhanced in ITD run Holland et al., 2006

19. Scatter in net ice melt relative to surface heat flux changes • Larger increase in net ice melt in models with larger Da/DT • This is consistent with analysis of surface heat flux changes. • Models with larger net ice melt increases exhibit: • Larger increases in net SW • Larger increases in downwellinglongwave (winter) • Larger compensating increases in turbulent and longwave heat loss (cold season) • For some changes, difficult to attribute cause-and-effect

20. Translating ice volume change to ice extent loss For thick ice: small extent loss per meter of ice thickness loss • For 1-2m ice: • large ice extent loss per ice volume change • variable across models (Holland et al., 2010)

21. How do changes in ice volume translate into ice extent loss? For 1-2m thickness, scatter in ice extent loss per thickness change is related to the distribution of ice thickness within the Arctic Models with a broader distribution have smaller ice extent loss per ice thickness change. Stabilizing effect of thick ice regions?

22. Challenges in Modeling Sea Ice in a Changing Environment • Sea ice is a complex material and numerous processes are excluded/idealized in models • However these models are based on physical principals and validated against observations • Climate models differ widely in their simulation of sea ice – both climatology and change • Simulated feedbacks vary considerably and can be parameterization dependent • However, even models with nearly identical sea ice components can have large differences as simulated sea ice is highly dependent on atmosphere and ocean conditions • To model correct sea ice requires adequate simulations of atmosphere and oceans

23. Challenges in Modeling Sea Ice in a Changing Environment • So, is it all hopeless? • Recent studies providing insight on what is needed if we are to accurately simulate sea ice change: • present day ice conditions, including extent and the spatial distribution of ice thickness; • the evolving surface energy budget • To achieve this involves numerous and interacting factors across the coupled system • Models are continuously improving and have provided considerable insight into the functioning of sea ice and its role in the climate system

24. Range in model 2007 extent from natural variability ~ 4.8 to 7 million km2 Simulated September Arctic Extent Observations Arctic Ocean September Ice Extent CCSM3 – Ensemble Members (Updated from Stroeve et al., 2007)

25. Questions?

26. What stabilizes the ice cover? Run with increasing GHG Run with GHG stabilized after 2020 Divergence Growth Divergence Growth Melt Melt

27. Model parameterizations modify ice growth rate feedback 5 category 1 category 1cat tuned • For ice of the same mean thickness, • The ITD has fewer locations with increased ice growth. • This suggests a reduced negative feedback on ice thickness

28. Sea Ice Model - Dynamics • Ice treated as a continuum with an effective large-scale rheology describing the relationship between stress and flow • Force balance between wind stress, water stress, internal ice stress, coriolis and stress associated with sea surface slope • Ice freely diverges (no tensile strength) • Ice resists convergence and shear • Multiple ice categories advected with same velocity field Internal Ice Stress Air stress Ocean stress Sea Slope Coriolis

29. Ice Thickness Distribution (Thorndike et al., 1975) Evolution depends on: Ice growth, lateral melt, ice divergence, and mechanical redistribution (riding/rafting)

30. Vertical heat transfer • Assume brine pockets are in thermal equilibrium with ice • Heat capacity and conductivity are functions of T/S of ice • Assume constant salinity profile • Assume non-varying density • Assume pockets/channels are brine filled where (from Light, Maykut, Grenfell, 2003) (Maykut and Untersteiner, 1971; Bitz and Lipscomb, 1999; others)