Previously ,

1. Previously, In the sea-ice group seminars…

2. November 17 Role of resolution and complexity on model performance Introduction

3. December 1 Ocean and sea-ice modelling in the Southern Ocean Data assimilation in NEMO-LIM2

4. December 8 Finite elements methods for sea ice New sea-ice rheology

5. Today, Episodes 7 & 8: Role of snow physics Sea-ice ecosystem modelling

6. Season 1 – episode 7:On the improvement of the snow component in large-scale sea ice models Olivier Lecomte(1), Martin Vancoppenolle(1), Thierry Fichefet(1), HuguesGoosse(1), Hubert Gallée(2). (1) UCL TECLIM, ELIC. (2) LGGE, Laboratoire de Glaciologie et de Géophysique de l’environnement, Grenoble.

7. Introduction

8. Snow enhances the Introduction Importance of seaice Solar radiation • Strongeralbedo • Betterinsulator • Response to wind forcing • Presence of melt ponds whensnowmeltsaway • Contributes to ice production (surface) • Interactions Reflection Snow accumulates on the edges of topographic reliefs : Wind stress • Strongreflector • Heatinsulator • Ocean circulation • Feedbacks Snow Seaice Ocean

9. Synopsis • Once upon a time, a snowflake… • Sea-icesnowcovermacroscaleproperties • Moral of the story (for large scalesea-icemodelling) • Snow modelling issues in LIM1D/LIM3 • Conclusions

10. Stellar dendrite (branchedsnowflake) - Vapour diffusion by curvatureeffect Heat transport through the sea-icesnowcover Once upon a time, a snowflake… Metamorphism Schematicfrom Sturm and Massom 2009. Pictures

11. Sea-icesnowcovermacroscaleproperties Snow Layering / Stratigraphy “With respect to the sea ice snow cover, it hardly matters which class or type of snowflake falls. What is important are: (1) the amount that falls, (2) the rate of snow accumulation and (3) whether the snow falls with or without wind.” Sturm & Massom, 2009. From Massom et al. 2001 • Stratified Snow pack + importance of sea-icethickness

12. Sea-icesnowcovermacroscaleproperties • Sea-icesnowcoverheterogeneity • Wind transport (blowingsnow) • Sea-icethickness distribution • Sea-icedynamics Snow depth distribution on the ice of the Chukchi Sea, Arctic (from SHEBA campaign, Sturm et al. 2002a).

13. Sea-icesnowcovermacroscaleproperties Feedbacks Atmosphere Snow Pack microscale & macroscaleproperties IceGrowth and Melt Metamorphism Ocean

14. Moral of the story (for large scalesea-icemodelling) Moral : Snow on seaiceis a Holy Mess. • Includingsnow components in large scalesea-ice/oceanmodelsimplieschoosing the most important snowprocesses, on the basis of : • What isbound to affect large scalesnow/sea-iceproperties (evaluatemean state) on relatively long periods (capture trends) • Models’ structure • Models’ sensitivity to snowparameterizations

15. Snow modelling issues in LIM3 Snow representation in LIM3 Current state : one layer, constant physicalproperties. Sensitive to : - Snow depth (1) - Snow radiative properties (2) - Snow thermal conductivity (3) => Driven by snowfall and wind transport (blowingsnow) (2) => Albedo, snowscatteringproperties (3) => Function of density => density stratification

16. Snow modelling issues in LIM3 How to improve things? - Snow depth (1) - Snow radiative properties (2) - Snow thermal conductivity (3) => Blowing snowparameterization (2) => Improve radiative scheme => Parameterizesnow thermal conductivity as a function of density and try to betterrepresent the snowstratigraphy. Impact on vertical heat conduction in the snow / sea-ice pack -> 1D process

17. Snow modelling issues in LIM3 Multi-layer snowscheme in LIM1D Snowfall density parameterized as a function of wind speed (linear relationship) - Assumptionfrom Jordan et al., 1999 Lecomte et al., 2010

18. Snow modelling issues in LIM3 Validation at Point Barrow (Alaska) - Seasonal Landfastsea-ice - Comparison of model results with observedsnow/sea-icetemperature profiles and thicknessmeasurements • Ice thickness average deviation : - 2,2 cm • Correlation betweenobserved and simulatedsnowtemperature profiles 27% bettercompared to reference run • 3 layers = required minimum 0 0,2 -5 0 -0,2 -15 Temperature – [°C] Snow depth & Ice thickness –[m] -0,6 -25 -1 -35 -1,4 01/16 03/12 04/30 06/16 Date (mm/dd)

19. Snow modelling issues in LIM3 Sensitivityexperiments on snowdensity 10 layers, snow density gradient = 450 kg.m-4 upwards, mean = 290 kg.m-3 ~12% thickersea-ice 1 layer, snow density = 290 kg.m-3 • 10 layers, snow density gradient = 450 kg.m-4 downwards, mean = 290 kg.m-3 • ~12% thinnersea-ice 10 layers, snow density = 290 kg.m-3

20. Snow modelling issues in LIM3 Sensitivityexperiments on snowdensity • 10 layers, snow density = 290 kg.m-3 • Density of layers 4,5,6 = 350 kg.m-3 • ~8% thickersea-ice • 10 layers, snow density = 290 kg.m-3 • Surface density (layers 1,2,3) = 350 kg.m-3 • ~10% thickersea-ice Model validation run Surface density (snowfall) as a function of wind speed • Model validation run • Prescribed snowfalldensity : 330 kg.m-3 • Impact on bothsnowdepth & conductiveheat fluxes

21. Snow modelling issues in LIM3 • Ongoingwork: • Implementation of a multi-layer snowscheme in NEMO-LIM3 with : • - Prescribed vertical density profile • Surface layer densityadjusted with respect to wind speed • Refinement of vertical grid in thermodynamical routines DEBUG STAGE Crashed Programming Compiling Debugging Time line

22. Conclusions IF (ever) youwant to remembersomething… • Sea-icesnowcoveris an important component to account for in climate simulations • It’sdamncomplicated • Snow representation in global scalesea-icemodelsisso simple thatimprovementcanbedonewith respect to real life snowphysics • Levers on whichwecanplay : depth – albedo – Stratigraphy • Importance of density profile, special importance of the surface layer properties. • Ongoingwork on these aspects with LIM3

23. Thanks! What about the density of this one, MAAAAN!!

24. Questions Nicolaus et al., 2009

25. Questions Snow in LIM1D

26. Questions

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