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IICWG 5th Science Workshop, April 19-21 - 2004
Sea ice modelling and data assimilation in the
TOPAZ system
Knut A. Lisæter and
Laurent Bertino
IICWG 5th Science Workshop, April 19-21 - 2004
Acknowledgement Funding from projects
• European Commission– DIADEM (Mast-III 1998-2000)– TOPAZ (FP5 2000-2003) MERSEA IP (FP6 2004-2008)
• ESA– SIREOC (2001-2002)– EMOFOR (2003-2005) Gulf of Mexico– ROSES
• Industry (NWAG, WANE…)• Norwegian research council
IICWG 5th Science Workshop, April 19-21 - 2004
Ingredients of a ocean forecasting system
• Numerical models– HYCOM + KPP (U.
Miami - LANL,USA) – Sea Ice
thermodynamics model – Sea Ice Dynamics
model (EVP, Hunke & Dukowicz 1997)
– Ecosystem models (AWI, D)
IICWG 5th Science Workshop, April 19-21 - 2004
Ingredients of a ocean forecasting system
• Observations– Altimetry, SST (CLS, F)– Sea Ice concentration (NSIDC, USA)– In-situ T & S (CORIOLIS, F)
• Data assimilation– Ensemble Kalman Filter (Evensen 1994,
2003)– OI
IICWG 5th Science Workshop, April 19-21 - 2004
TOPAZ model system• Atlantic and Arctic: 18-30 km
resolution. • EnKF data assimilation (SLA,
SST and Ice concentration)• Downscaling: high resolution
regional models (4-5 km)• A flexible modular system
used for hindcast studies• Real-time operations
– DIADEM: 1999-2000– TOPAZ: Jan. 2003 -> now – MERSEA IP: 2004 onwards
• http://topaz.nersc.no
IICWG 5th Science Workshop, April 19-21 - 2004
Advanced Data Assimilation
How observations should influence the model
• The bottleneck of numerical weather forecasts?• Theory: system control + spatial statistics• Ensemble Kalman filter
– “The model has the best knowledge of the ocean processes”– Forecast + the related uncertainty– Assumes errors in atm. fields – Robust and flexible (SLA, SST, ice concentrations and
thickness, in-situ T-S profiles, Ocean color, TB, ..)
IICWG 5th Science Workshop, April 19-21 - 2004
Assimilating data with holes
• Example of AVHRR SST
• Weekly averages• 1/3rd degree• Processed by CLS• No need to fill in
the holes …
IICWG 5th Science Workshop, April 19-21 - 2004
Analysis Nowcast
Forecast
Weekly Forecast Cycle
Analysis Nowcast
Forecast
• Atlantic, North Sea and Gulf of Mexico models– Same cycle, different forecast length– Atmospheric forcing fields from ECMWF (10d Forecast,
reverts to Climatology 28 days)
d-7 d-0
d+10
IICWG 5th Science Workshop, April 19-21 - 2004
Sea Ice assimilation in TOPAZ
• Observations - ice concentration– Near Real-time TB data from NSIDC (SSM/I)– Conversion to ice concentrations at NERSC
• Sea Surface Temperature must be considered– Assimilation without SST correction can quickly melt ice
• The influence on e.g. salinity is PROCESS dependent:– “Local” ice melting/freezing– Transport through thermal fronts
• Requires dynamical error handling• Assimilation of CRYOSAT-like ice thickness evaluated
IICWG 5th Science Workshop, April 19-21 - 2004
Ice concentration Maps
• Examples 31st March 2004• Comparison of
– Observations– Forecast– Analysis
• Assimilation affects the position of the ice edge
• Analysis and forecasts similar on large scale, details are different
IICWG 5th Science Workshop, April 19-21 - 2004
Ice concentration 31. March 2004
Observations 10 day Forecast
IICWG 5th Science Workshop, April 19-21 - 2004
Sea ice information available from TOPAZ
• Model fields of– Ice concentration– Ice thickness– Ice drift– Ice temperature
• Categories-daily fields– Analysis– Forecasts
• Regional models– Barents sea (to come)
• Rheology• nesting
IICWG 5th Science Workshop, April 19-21 - 2004
Examples of ice assimilation updates
• Illustrates the effect of assimilating ice concentration– Updates: After assim. - Before assim– “Typical” winter and summer situations– Shows the impact assimilation has on T & S– Different behavior at different times of the
year– Strongest effect on the ice edge, especially
in winter– From Lisæter et al. 2003
IICWG 5th Science Workshop, April 19-21 - 2004
Ice concentration assimilation - winter
Ice concentration Surface temperature
IICWG 5th Science Workshop, April 19-21 - 2004
Ice concentration assimilation - winter
Ice concentration Surface salinity
IICWG 5th Science Workshop, April 19-21 - 2004
Ice concentration assimilation - summer
Ice concentration Surface temperature
IICWG 5th Science Workshop, April 19-21 - 2004
Ice concentration assimilation - summer
Ice concentration Surface salinity
IICWG 5th Science Workshop, April 19-21 - 2004
Ice concentration assimilation experiment -
cumulative effect• RMS Difference model-
observations– Assimilation corrects model
behavior– Strongest effect in summer– Sawtooth effect due to
assimilation– Winter forcing provides
“relaxation” in both runs…– Observations problematic in
summer
IICWG 5th Science Workshop, April 19-21 - 2004
Ice thickness assimilation experiment
• SIREOC Project(ESA)• Used “cryosat-like”
synthetic ice thickness
• Assimilated with EnKF
• Coarse model grid (not the TOPAZ grid)
IICWG 5th Science Workshop, April 19-21 - 2004
• EnKF provides time-varying statistics
• Highest error near the ice edge
• Decreasing error within the ice pack(bias)
• Region of high error variance “follows” the ice edge
• Similar behavior for ice concentration errors
Evolution of model ice thickness error
IICWG 5th Science Workshop, April 19-21 - 2004
Important for ice assimilation
• The ice and ocean are connected!– > multivariate assimilation – > “coupled” assimilation of variables in the
ice and ocean model
• Model error statistics are process-dependent– Transport across fronts + melting– “Local” melting
• Error statistics have highest magnitudes close to the ice edge
IICWG 5th Science Workshop, April 19-21 - 2004
Idealized view of forecasting
Decision making
User
Forecast
Researcher
IICWG 5th Science Workshop, April 19-21 - 2004
Why statistics again?
“As soon as a map is put out, everybody around the table tends to consider it as the
truth” (old saying from the mining industry)
IICWG 5th Science Workshop, April 19-21 - 2004
Risk Assessment
Assessing forecast uncertainty
a necessity
Decision making
User
Forecasts Uncertainty
Researcher
IICWG 5th Science Workshop, April 19-21 - 2004
Advantages of the NERSC/TOPAZ system
• Advanced data assimilation techniques– A physical view on the system uncertainty– Intensive machine use, but high reliability
• Model flexibility – General formulation(hybrid coordinate)– Easily relocatable: any sea in the world
• TOPAZ is the NERSC contribution to the – GMES – MERSEA and GODAE initiatives (Arctic
system)
IICWG 5th Science Workshop, April 19-21 - 2004
Plans
• Data assimilation:– In-situ + MDT products– Cryosat/ICESAT Ice Thickness– Ice Drift– Local assimilative systems– 100 down to 30 members?
• Model Improvements– New HYCOM version (MPI)– Multi-category Sea Ice model– Sea-Ice rheology suitable for small-scale modelling?
• Further applications– Ice forecasts, ship routing, oil spills, environmental monitoring