Sea Ice Thermodynamics and ITD considerations

Marika Holland

NCAR

Sea ice thermodynamics

• Simulate vertical heat transfer (conduction, SW absorption)

• Balance of fluxes at ice surface (ice-atm exchange, conduction, ice melt)

• Balance of fluxes at ice base (ice-ocn exchange, conduction, ice melt/growth)

Focn

Fsw

Fsw

FLW

FSH FLH

hi

hs

T1

T2

T3

T4 -k dT/dz

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

Albedo

Parameterized albedo depends on surface state (snow, temp, hi).

Issues: Implicit ponds, optically thick snow, no snow aging, constant fraction

of SW absorbed in surface layer, constant extinction coefficients

(Perovich et al., 2002)

New Albedo Formulation• High ice/snow albedo due to multiple scattering associated

with individual snow grains, inclusions of gas, brine, etc.

• New multiple-scattering sea ice radiative transfer has been developed by Bruce Briegleb and Bonnie Light

• Dependent on snow/ice inherent optical (microscopic) properties

• Allows for inclusion of soot, algae, etc in a general and consistent manner (biological implications)

• Allows for improvements to numerous parameterizations (e.g. snow aging effects, melt ponds)

(currently being tested within CCSM)

Melt Pond Albedo Parameterization

• Accumulate fraction of snow and surface ice melt into pond volume reservoir.

• Compute pond area/depth from simple empirically-based relationship.

• Pond volume advected as a tracer.

• Albedo depends on pond fraction and depth.

July Pond Concentration(Based on Ebert and Curry, 1993)

Ice Thickness DistributionPrevious studies with • Single Column Models (Maykut, 1982)• Basin-scale models (Hibler, 1980) • Coupled models of intermediate

complexity (simplified atmos)• Fully coupled models (Holland et al)

Have shown ITD influences mean climate state:

• Thicker ice• Warmer SAT• More saline Arctic Ocean• Changes in atmosphere, ocean

circulationSchramm et al., 1997

Ice Thickness Distribution

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

(Thorndike et al., 1975)

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

Calculation of ITD - Mechanical Redistribution

• Parameterized after Rothrock ,1975; Thorndike et al., 1975; Hibler, 1980; Flato and Hibler, 1995

• Convergence and shear produce ridges• Thin ice replaced by smaller area of thicker, ridged ice• Thinnest 15% of ice participates in ridging• Distribution of ridged ice results

• Assumptions regarding ridge formation (participation function, ridged distribution, etc.) and its relationship to ice strength

• Sea ice simulations sensitive to these assumptions• For example - What to do with snow on ridging ice?

Boundary layer exchange in presence of ITD• Resolving an ITD improves ice-ocn-atm exchange• But ocean and atmospheric boundary layers do not differentiate

between lead and ice covered surfaces

Near-term improvements for thermo/ITD• SNOW - metamorphosis (aging, etc - important for

radiation), blowing snow, others?

• Soot, algae, other impurities in ice - important for coupling to biology

• Sea ice "hydrology”: including melt ponds, brine pockets and drainage, percolation and snow-ice formation

• Exchange with ocean/atm - new possibilities with ITD, improvements based on observations (e.g. exchange coefficients, double diffusion)

• Mechanical redistribution - observed studies to refine and improve parameterizations

Albedo

• Most climate models use

- empirical formulae to calculate albedo (function of surface state)

- optically thick snow

- constant fraction of radiation absorbed in surface layer (1-io)

- constant extinction coefficient within ice

- tuned ice albedo to implicitly include effects of surface melt water

• Not consistently related to inherent optical properties of snow/ice

• Only loosely tied to physical properties of snow/ice system

• Difficult to generalize for improved treatments of snow, meltwater,

and impurities

Albedo

1. Existing scheme emphasizes albedo, absorption within ice and transmission to

ocean are secondary

• Absorption and transmittance are difficult to validate, yet important!

• Absorbed light immediately available for melting

• Transmitted light heats upper ocean, available for primary productivity

2. While a tuned albedo parameterization may produce reasonable results for a sea ice

model, the strength of the ice-albedo feedback and the character of radiative

interactions with the atmosphere may require a more complex treatment of shortwave

radiation (Curry et al., 2001)

For climate studies Need to include processes that are important for:

• Representing climatological state

• Representing feedbacks

– realistic variability and sensitivity

• Physics appropriate to the models spatial scale

• Parameterize important non-resolved processes

Trade off between complexity and computational cost

Enhanced albedo feedback in ITD run

Larger albedo 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

Fundamentals - Thermodynamics

€

ρc∂T

∂t=

∂

∂zk

∂T

∂z+ QSW

€

QSW = −d

dzISWe−κz

(Beer’s Law)

where

€

ISW = i0(1−α )FSW

Fraction transmitted below surface layer

Albedo

Vertical heat transfer

Fundamentals - Thermodynamics

€

ρc∂T

∂t=

∂

∂zk

∂T

∂z+ QSW Vertical heat transfer

€

c(T,S) = c0 +γS

T 2

€

k(T,S) = k0 +βS

T

(from Light, Maykut, Grenfell, 2003)

where

€

γ=L0μ and

€

Tm = −μS

Non-varying density; assume brine filled pockets/channels

(Maykut and Untersteiner, 1971)

Fundamentals - Thermodynamics

€

ρc∂T

∂t=

∂

∂zk

∂T

∂z+ QSW Vertical heat transfer

Boundary Conditions:Assume balance of fluxes at ice surface:

€

Focn − k∂T

∂z= −q(S,T)

dh

dt€

(1− i0)(1−α )FSW + FLW + FSH + FLH + kdT

dz= q(S,T)

dh

dt

Where q(S,T) is the amount of energy needed to melt ice

And base:

Boundary layer exchange in presence of ITD• Resolving an ITD improves ice-ocn-atm exchange• But ocean and atmospheric boundary layers do not differentiate

between lead and ice covered surfaces• Observations indicate that this can be important

Ice Thickness Distribution

€

∂g

∂t= −

∂

∂h( fg) + L(g) −∇ • (

r v g) + Ψ(h,g,

r v )

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

(Thorndike et al., 1975)

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