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

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 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 Coupled Climate Models

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 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

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

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 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 Ice volume change Thermodynamic source Divergence Assessing Sea Ice Mass Budgets 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 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 Fram Strait CAA Barents Sea Bering Strait North America Eurasia Holland et al., 2010

20th century mass budgets 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 Mean of 14 Models

20th century mass budgets 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) Correlation of ice melt and SHF Regression of ice melt and SHF Net SW Net Flux Mean of 14 Models

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)

Ice Mass Budget Change Over 21 st 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 mean

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

Model scatter in evolving ice mass budgets 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 Melt Change at 2050 Growth Change at 2050

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

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

Model scatter in evolving ice mass budgets Melt Change Growth Change Melt Growth Divergence 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 CCSM3 Model

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

Albedo Feedback Analysis Assess the change in albedo per change in surface temperature (  /  T) using transient climate integrations TT 

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

Evidence that model parameterizations influence feedback strength Enhanced albedo feedback in ITD run 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 ITD (5 cat) 1 cat. 1cat tuned Holland et al., 2006

Larger increase in net ice melt in models with larger  /  T 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 downwelling longwave (winter) Larger compensating increases in turbulent and longwave heat loss (cold season) For some changes, difficult to attribute cause-and-effect Scatter in net ice melt relative to surface heat flux changes

(Holland et al., 2010) 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 For 1-2m ice: large ice extent loss per ice volume change variable across models

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?

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 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

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 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

Simulated September Arctic Extent (Updated from Stroeve et al., 2007) Range in model 2007 extent from natural variability ~ 4.8 to 7 million km 2 Arctic Ocean September Ice Extent CCSM3 – Ensemble Members Observations

Questions?

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

Model parameterizations modify ice growth rate feedback 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 5 category 1 category 1cat tuned

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 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 Coriolis Air stress Ocean stress Sea Slope Internal Ice Stress

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

Vertical heat transfer (from Light, Maykut, Grenfell, 2003) (Maykut and Untersteiner, 1971; Bitz and Lipscomb, 1999; others) 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