sea ice thermodynamics and itd considerations
DESCRIPTION
Sea Ice Thermodynamics and ITD considerations. Marika Holland NCAR. F LW. F sw. F SH. F LH. F sw. h s. T 1. h i. T 2. T 3. T 4. F ocn. Sea ice thermodynamics. Simulate vertical heat transfer (conduction, SW absorption) - PowerPoint PPT PresentationTRANSCRIPT
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Sea Ice Thermodynamics and ITD considerations
Marika Holland
NCAR
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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
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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
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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)
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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)
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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)
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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
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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)
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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?
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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
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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
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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
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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)
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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
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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
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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
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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)
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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:
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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
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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)