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Sea Ice Thermodynamics and ITD considerations

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)

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Sea Ice Thermodynamics and ITD considerations

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  1. Sea Ice Thermodynamics and ITD considerations Marika Holland NCAR

  2. FLW Fsw FSH FLH Fsw hs T1 hi T2 T3 T4 Focn 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) -k dT/dz

  3. 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 (Maykut and Untersteiner, 1971; Bitz and Lipscomb, 1999; others) (from Light, Maykut, Grenfell, 2003)

  4. Albedo (Perovich et al., 2002) 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

  5. 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)

  6. 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)

  7. Ice Thickness Distribution • Previous 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 circulation Schramm et al., 1997

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

  9. 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?

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

  11. 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

  12. 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

  13. 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)

  14. 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

  15. Enhanced albedo feedback in ITD run ITD (5 cat) 1 cat. 1cat tuned Larger albedo 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

  16. Fundamentals - Thermodynamics Vertical heat transfer (Beer’s Law) where Albedo Fraction transmitted below surface layer

  17. Fundamentals - Thermodynamics Vertical heat transfer and where (Maykut and Untersteiner, 1971) Non-varying density; assume brine filled pockets/channels (from Light, Maykut, Grenfell, 2003)

  18. Fundamentals - Thermodynamics Vertical heat transfer Boundary Conditions: Assume balance of fluxes at ice surface: And base: Where q(S,T) is the amount of energy needed to melt ice

  19. 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 Boundary layer exchange in presence of ITD

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

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