1. Guoping Gao 1, Changsheng Chen 1, Andrey Proshuntinsky 2 and Robert. C. Beardsley 2 1 Department of Fisheries Oceanography University of Massachusetts-Dartmouth (UMASSD), New Bedford, MA 02744 2 Department of Physical Oceanography Woods Hole Oceanographic Institution, Woods Hole, MA 02543 E-mail: ggao@umassd.edu; c1chen@umassd.edu (UMASSD) aproshuntinsky@whoi.edu; rbeardsley@whoi.edu(WHOI) Development of Unstructured-grid Version of CICE (UG-CICE): Validations and Applications

2. Outline 1.Motivation 2.Brief description of unstructured grid finite-volume algorithms used for UG-CICE 3.Validations for three idealized cases 4.Application to the Arctic Ocean 5.Summary

3. Greenland Canadian Archipelago Hudson Bay/Strait Iceland 1. Motivation Characteristics: 1.Irregular coastlines, particularly in the Canadian Archipelago; 2.Steep slope and deep ridges between the basins AO-FVCOM

4. The governing equation for the ice thickness distribution function (g) in CICE is given as: momentum equations of the sea-ice: 2. A brief description of the finite-volume algorithm for UG-CICE Governing equations for the sea ice follow Hunke and Dukowicz (1997), in which y u,vu,v u,vu,vu,vu,v u,vu,v u,vu,v g u,vu,v u,vu,v u,vu,v u,vu,v u,vu,v (Chen, et al,2006,FVCOM user manual) : The node of triangles where scalar variable is calculated  : The centroid of a triangle where the velocity is calculated.

5. Validation case 1: This case is a steady-state problem that has been used for the comparison of the behavior of the elastic- viscous-plastic (EVP) and viscous-plastic (VP) models.( Hunke & Dukowicz, 1997). x =0 x=L =508 km c= 0.9, H=0.6m, Hs =0.1 m u = 0 Analytical solutions: Set

6. CICE (Hunke&Dukowicz,1997,Fig.4.) UG-CICECICE (Hunke&Dukowicz,1997,Fig.4.) Distributions of the ice velocity from x = 0 to x = L UG-CICE reproduce the analytical solution as the same accuracy as CICE; Slight difference between analytical and numerical solutions are due to the resolution. As the resolution increases, the numerical solution tends to converge to the analytical solution.

7. Five categories:0.05, 0.10,0.30,0.35,0.2 Initial ice strengths is ~59 kN/m Validation case 2: Ocean velocity = 0, No Coriolis force and sea surface tilt This case was used to test ice ridging scheme and instability by Lipscomb et al(2007). In this case, the ice transport was included. 1D momentum equation is simplified as, Lipscomb et al(2007). where In steady state the relationship of u and P can be given as, x =0 x=1000 km H=2.73m u = 0

8. UG-CICECICE (Lipscomb et al,2007,Fig.3 ) Comparison of the ice velocity and ice strength between UG-CICE and CICE Distribution of ice velocity Distribution of ice strength UG-CICE reproduce the ice piling up by the wind as the same accuracy as CICE; The ice strain rate for mechanical redistribution calculated by UG-CICE is same as that from CICE.

9. Validation case 3 (Hunke,2001): This case was used to test “model behavior in two regimes, low ice concentration where occurs in the marginal ice zone, and very high ice concentration where the ice is nearly rigid” (Hunke 2001). Initial ice condition: the ice concentration varies linearly in the x-direction from 0 to 1 and is constant in the y direction; the ice thickness is 2 m everywhere. surface current Wind forcing Domain and resolution: CICE UG-CICE

10. Time: 4 days Ice velocity u component UG-CICE CICE ( Fig.2,Hunke,2001 ) UG-CICE result shows the same pattern of ice velocity u component as that of CICE In the rigid regime, both UG-CICE and CICE show the small velocity.

11. 4.Application of AO-FVCOM with UG-CICE for Arctic Ocean Initial conditions: 1.UG-CIECE is initialized using a default setup in CICE, with a uniform thickness ice of 2.53 m covering the ocean north of 70 o N; 2.The temperature and salinity were initialized using the January climatologic field from the Polar Science Center Hydrographic climatology (PHC, Steele et al 2001). Model forcing 1.Climatologic daily surface flux, wind stress, P-E, air pressures were specified using Ocean Model Intercomparison Project (OMIP, www.omip.zmaw.de) derived from the ECMWF reanalysis ERA-15 from 1978 to 1994. 2.River discharge is provided by Dr. Lucy F. Smedstad of NCOM Group. 3. Atmospheric and astronomic tidal loadings are taken into account in the model. Model configuration: 1.Resolution varies from 1~3 km to 25~50 km; 2.Hybrid coordinate in the vertical: 46 layers; 3.Bathymetry data are from 2-min resolution IBCAO and DBDBV databases.

12. Comparison of the ice concentration (March) Observation: The monthly averaged field from 1979 to 1994 (NSIDC) Model: The monthly averaged field from the model experiment driven with the daily climatologic forcing built using the field from 1979 to 1994. UG-CICEObservation UG-CICE show a reasonable agreement with the observation in the central Arctic Ocean. UG-CICE overestimate the ice coverage in the east region of Greenland.

13. Comparison of the ice concentration (September) ObservationUG-CICE  UG-CICE results show the reasonable agreement in the ice coverage with the observation.  UG-CICE did not show the large gradient from central ocean to marginal sea. Reasons: The inter-annual variability

14. 19791983 19871991 Monthly average fields of the ice concentration in Sept. 1979, 1983, 1987 and 1991 The ice coverage varies significantly from year to year, which is not resolved in the model run driven by the climatologic averaged forcing fields.

15. 1.The NSIDC monthly drifting data was averaged from Jan., 1979 to Dec. 1994. 2.Model results show similar pattern of anti-cyclonic circulation as the observation; 3.Model drifting velocity is close to the observation except the ice marginal zone. Comparison of ice drifting (March)

16. Model results show a similar pattern as the observation; Model drifting direction has some difference to the observation; Model drifting velocity is larger than the observation. Comparison of ice drifting (September)

17. Martin & Gerdes(2006) compared the notable differences of the ice drifting from different data sources. The accuracy of satellite observed drifting data Fig.1 Martin&Gerdes(2006)

18. 1979 1987 1983 1991 Inter-annual variability of ice drifting in observation. Ice drifting velocity in each year is much larger than that of the observation, particular in the marginal ice zone.

19. Summary UG-CICE has been developed and validated for the 3 benchmark tests. This model shows the same accuracy as the structure-grid CICE. Under a climatologic forcing condition, AO-FVCOM coupled with UG- CICE shows the reasonable results of the ice concentration, ice coverage and ice drifting. Acknowledgement: This work is funded by NSF. We thank Drs. Elizabeth Hunke and William H. Lipscomb for their sharing with the benchmark test case configuration. On-going Work The real-time simulation from 1978 to 2008.