Sea ice modeling at met.no Keguang Wang Norwegian Meteorological Institute.

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Presentation transcript:

Sea ice modeling at met.no Keguang Wang Norwegian Meteorological Institute

Sea ice models at met.no NorESM (Jens)  TOPAZ (Magnus)  ROMS (Keguang)  FRAMPS (Keguang)  ROMS-CICE (Jens, Keguang,...)

FRAMPS model description Granular ice dynamics –2-level ice category –Curved diamond yield curve [Wang, 2007, JGR] –Levy flow rule [Wang, 2006, Annals of Glaciol.], with modifications –Particle-in-cell for advection [Wang and Wang, 2009, JGR]. Comparison between RGPS-derived and modeled shear deformations (Wang and Wang, 2009)

Prediction domain Pan-Arctic –10 km resolution European Arctic –Fram Strait, Svalbard, Barents Sea –2 km resolution

Initial sea ice concentration AMSR-2 NIC ice chart CIS ice chart interpolation for North Pole

Initial sea ice thickness SMOS OSISAF ice type interpolation for North Pole

48 hours forecast

forecast drift vs. CALIB_2015a (1st leg)

forecast drift vs. CALIB_2015c (2nd leg)

ROMS Nordic-4km data assimilation Operational ocean-sea ice model in met.no –TOPAZ –MIPOM –ROMS –FRAMPS Background –operational sea ice forecast system transfered from MIPOM to ROMS in 2013 –Sea ice concentration assimilated for ROMS Arctic-20km, but no yet for Nordic-4km –need for high accuracy sea ice forecast for shipping, fishing and oil and gas exploration

ROMS brief free-surface, terrain-following, primitive equations ocean model Very modern code, uses C-preprocessing to activate the various physical and numerical options Coupling modules for atmosphere, wave, biogeochemical, bio-optical, sediment, and sea ice applications

ROMS framework disgram

ROMS sea ice module Main developer: Budgell (2005) Two-level sea ice state EVP rheology MPDATA advection scheme One-layer ice and snow thermodynamics (Mellor and Kantha, 1989) Plume model between sea ice and water frazil ice formation (Steele et al., 1989)

ROMS operational system in met.no  A triply nested system: –Arctic-20km → Nordic-4km → NorKyst-800m  The global ocean model FOAM from UK Met Office gives the lateral boundary conditions to Arctic 20 km  ECMWF forcing for Arctic-20km and Nordic-4km

ROMS Arctic-20km

ROMS Arctic-20km + Nordic-4km

Arctic20 + Nordic4 + NorKyst800

Previous Nordic-4km vs. Arctic-20km

Nordic-4km sea ice extent vs. ice chart ice conditions on

available data and uncertainties

combined data and std

Combined optimal interpolation and nudging scheme (Wang et al., 2013) Optimal Interpolation: Nudging:

assimilation method COIN scheme –cheap computation –no abrupt shock to the model simulation –OSISAF and ice chart are daily averaged products based on multi-sensors and multi-time –observations usually has similar or even higher spatial resolution than model –weak stability, homogeneity, isotropy of the error covariance –no spatial variation of nudging coefficient make a 5-year simulation of ROMS Arctic-20km interpolate the Arctic-20km results to Nordic-4km domain for boundary and initial fields

assimilated sea ice extent and mean std

correct rate of the simulation

Nordic-4km 1-day forecast skill Ice edge position ice concentration ice extent

Nordic-4km vs TOPAZ

Thanks for your attention !!!