previously ,
DESCRIPTION
Previously ,. In the sea - ice group seminars …. November 17. Role of resolution and complexity on model performance. Introduction. December 1. Ocean and sea-ice modelling in the Southern Ocean. Data assimilation in NEMO-LIM2. December 8. Finite elements methods for sea ice. - PowerPoint PPT PresentationTRANSCRIPT
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Previously,
In the sea-ice group seminars…
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November 17
IntroductionRole of resolution and complexity on model
performance
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December 1
Data assimilation in NEMO-LIM2
Ocean and sea-ice modelling in the Southern Ocean
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December 8
Finite elements methods for sea ice
New sea-ice rheology
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Today, Episodes 7 & 8:
Role of snow physics Sea-ice ecosystem modelling
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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), Hugues Goosse (1), Hubert Gallée (2).
(1) UCL TECLIM, ELIC.(2) LGGE, Laboratoire de Glaciologie et de Géophysique de
l’environnement, Grenoble.
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Introduction
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Importance of sea ice
• Strong reflector
• Heat insulator
• Ocean circulation
• Feedbacks
Introduction
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Synopsis
• Once upon a time, a snowflake…
• Sea-ice snow cover macroscale properties
• Moral of the story (for large scale sea-ice modelling)
• Snow modelling issues in LIM1D/LIM3
• Conclusions
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Metamorphism
Pictures
Schematic from Sturm and Massom 2009.
Once upon a time, a snowflake…
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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.
Þ Stratified Snow pack
Sea-ice snow cover macroscale properties
From Massom et al. 2001
+ importance of sea-ice thickness
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Sea-ice snow cover heterogeneity
• Wind transport (blowing snow)• Sea-ice thickness distribution• Sea-ice dynamics
Sea-ice snow cover macroscale properties
Snow depth distribution on the ice of the Chukchi Sea, Arctic (from SHEBA campaign, Sturm et al. 2002a).
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Snow Pack microscale & macroscale properties
Met
amor
phis
m
Ice Growth and Melt
ATMOSPHERE
OCEAN
Sea-ice snow cover macroscale properties
Feedbacks
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Moral of the story (for large scale sea-ice modelling)
Moral :Snow on sea ice is a Holy Mess.
Including snow components in large scale sea-ice/ocean models implies choosing the most important snow processes, on the basis of :
• What is bound to affect large scale snow/sea-ice properties (evaluate mean state) on relatively long periods (capture trends)
• Models’ structure
• Models’ sensitivity to snow parameterizations
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Snow modelling issues in LIM3
Snow representation in LIM3
Current state : one layer, constant physical properties.
Sensitive to :
- Snow depth (1)
- Snow radiative properties (2)
- Snow thermal conductivity (3)
(1) => Driven by snowfall and wind transport (blowing snow)(2) => Albedo, snow scattering properties
(3) => Function of density => density stratification
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Snow modelling issues in LIM3
How to improve things?
- Snow depth (1)
- Snow radiative properties (2)
- Snow thermal conductivity (3)
(1) => Blowing snow parameterization(2) => Improve radiative scheme(3) => Parameterize snow thermal conductivity as a function of
density and try to better represent the snow stratigraphy.
Impact on vertical heat conduction in the snow / sea-ice pack -> 1D process
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Snow modelling issues in LIM3
Multi-layer snow scheme in LIM1D
Lecomte et al., 2010
Snowfall density parameterized as a
function of wind speed (linear relationship)
-Assumption from Jordan et al., 1999
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Date (mm/dd)
01/16 03/12 06/1604/30
Snow
dep
th &
Ice
thic
knes
s –[
m]
0,2
0
-0,2
-0,6
-1
-1,4
Temperature – [°C]
0
-5
-15
-25
-35
Snow modelling issues in LIM3
Validation at Point Barrow (Alaska)- Seasonal Landfast sea-ice- Comparison of model results with observed snow/sea-ice temperature profiles and thickness measurements
• Ice thickness average deviation : - 2,2 cm• Correlation between observed and simulated snow temperature profiles 27% better compared to reference run• 3 layers = required minimum
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Snow modelling issues in LIM3
Sensitivity experiments on snow density
1 layer, snow density = 290 kg.m-3
10 layers, snow density = 290 kg.m-3
10 layers, snow density gradient = 450 kg.m-4 upwards, mean = 290 kg.m-3
~12% thicker sea-ice
10 layers, snow density gradient = 450 kg.m-4 downwards, mean = 290 kg.m-3
Þ ~12% thinner sea-ice
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Snow modelling issues in LIM3
Sensitivity experiments on snow density 10 layers, snow density = 290 kg.m-3
Density of layers 4,5,6 = 350 kg.m-3
Þ ~8% thicker sea-ice
10 layers, snow density = 290 kg.m-3
Surface density (layers 1,2,3) = 350 kg.m-3
Þ ~10% thicker sea-ice
Model validation runSurface density (snowfall) as a function of
wind speed
Model validation runPrescribed snowfall density : 330 kg.m-3
Þ Impact on both snow depth & conductive heat fluxes
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Snow modelling issues in LIM3
Ongoing work:Implementation of a multi-layer snow scheme in NEMO-LIM3 with :- Prescribed vertical density profile
- Surface layer density adjusted with respect to wind speed
- Refinement of vertical grid in thermodynamical routines
DEBUG STAGE
Programming Compiling Debugging
Crashed
Time line
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Conclusions
IF (ever) you want to remember something…
• Sea-ice snow cover is an important component to account for in climate simulations
• It’s damn complicated
• Snow representation in global scale sea-ice models is so simple that improvement can be done with respect to real life snow physics
• Levers on which we can play : depth – albedo – Stratigraphy
ÞImportance of density profile, special importance of the surface layer properties.
• Ongoing work on these aspects with LIM3
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What about the density of
this one, MAAAAN!!
Thanks!
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Questions
Nicolaus et al., 2009
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Questions
Snow in LIM1D
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Questions
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xxx