Challenges in Modeling Global Sea Ice in a Changing Environment

Marika M HollandNational 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

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

Simulated Ice Thickness

Climatology1980-1999

Thickness varies

considerably across models

Differences in mean and distribution

Largest inter-model

scatter is in the Barents Sea region

Ensemble Mean Standard Deviation

3.02.01.0 m0.0

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

Ice volume change

Thermodynamic source

Divergence

Assessing Sea Ice Mass Budgets

Climate model archive of monthly averaged ice thickness and velocityAssess Arctic ice volume, transport through Arctic straits, and solve for ice growth/melt as residual

FramStrait

CAA

BarentsSea

BeringStrait

NorthAmerica

Eurasia

Holland et al., 2010

20th century mass budgets

Across the 14 models:Annual Ice melt varies from 0.6m-1.8mAnnual 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 fluxSuggests a dominant role for albedo variations across models, which may be caused by:

Albedo parameterizationsSimulated surface state (e.g. snowfall)

Correlation of ice melt and SHF

Regression of ice melt and SHF

Net SW

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

Ense

mbl

e Ra

nge

Average Arctic ice thickness change (SRES A1B Scenario)

Ice Mass Budget Change

Over 21st century, increased net ice melt occursPartially balanced by reduced divergence (less transport from Arctic to lower latitudes).

Multi-model ensemble meanMass Budget Change Relative to

1950-1970 mean

For different models:Nature of ice mass budget changes varies considerablyDifferent 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 fluxIce 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

MeltGrowth

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 FeedbackThe 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 FeedbackAnalysis

Assess the change in albedo per

change in surface temperature (Da/DT)

using transient climate integrations

DT

Da

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 thicknessSuggests 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 Da/DTThis 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 lossFor 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

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 ArcticModels 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

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

Simulated September Arctic Extent

(Updated from Stroeve et al., 2007)

Range in model 2007 extent from natural variability ~ 4.8 to 7 million km2

Arctic OceanSeptember Ice ExtentCCSM3 – Ensemble Members

Observations

Questions?

What stabilizes the ice cover?Run with increasing GHG

MeltGrowth

Divergence

Run with GHG stabilized after 2020

Melt

DivergenceGrowth

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 category1 category1cat 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

€

m ∂u∂t

= −mfk × u + τ a + τ o − mg∇H +∇ • σ

Coriolis Airstress

Oceanstress

Sea Slope

InternalIce Stress

Ice Thickness Distribution

Evolution depends on: Ice growth, lateral melt, ice divergence, and mechanical redistribution (riding/rafting)

(Thorndike et al., 1975)

€

∂g∂t

= − ∂∂h

( fg) + L(g) −∇ • (r v g) + Ψ(h,g,

r v )

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•

€

ρc ∂T∂t

= ∂∂z

k ∂T∂z

+ QSW

€

QSW = − ddz

ISW e−κzwhere

€

ISW = i0(1−α )FSW