Since LICOM2.0 (Liu et al., 2012), LICOM has been substantially upgraded in the interface with the flux coupler, the dynamic core, and the physical packages (Table 1). First, we upgraded the LICOM interface from the NCAR flux coupler 6 to coupler 7 (Lin et al., 2016), because the new version has been optimized for high-resolution modeling (Craig et al., 2012). Here, LICOM3 coupled with the Community Ice Code, version 4 (CICE4), i.e., the ocean–ice coupled model, is used to conduct the OMIP experiments. The prescribed atmospheric data have been input from the atmospheric data model and then passed to the coupler to drive the ocean–sea-ice coupled model.
Configuration LICOM2.0 LICOM3 Grid Grid Longitude/Latitude Tripolar Resolution ~1°, 30 levels ~1°, 30 or 80 levels Dynamic core Tracer advection Central differential scheme Preserved shape scheme (Yu, 1994) Momentum time integration Explicit Implicit Physics Diapycnal mixing Mixing in the mixed layer (Canuto et al., 2001, 2002) Mixing in the mixed layer (Canuto et al., 2001) and internal tide mixing (St. Laurent et al., 2002) Isopycnal mixing Isopycnal mixing (Redi, 1982) and advection (Gent and McWilliams, 1990) Isopycnal mixing (Redi, 1982) and advection (Gent and McWilliams, 1990) with N2 thickness diffusivity (Ferreira et al., 2005) Computing technics Coupler interface NCAR Flux Coupler 6 NCAR Flux Coupler 7 Parallel 1D MPI and OMP 2D MPI and OMP Data Initial condition WOA01 (Conkright et al., 2002) PHC3.0 (Steele et al., 2001) Bathymetry DBDB5 (https://www.bodc.ac.uk/resources/inventories/edmed/report/356/) ETOPO2 (https://ngdc.noaa.gov/mgg/global/etopo2.html)
Table 1. Comparison of model configurations between two versions of LICOM (LICOM2.0 and LICOM3).
Second, the orthogonal curvilinear coordinate (Madec and Imbard, 1996; Murray, 1996) has been introduced in LICOM. The tripolar grid can be used with the North Pole split into two poles on the land in the Northern Hemisphere (NH) at (65°N, 65°E) and (65°N, 115°W). This improvement has solved the problem of the singularity of the North Pole in the normal longitude–latitude grid. Meanwhile, the spatial filter in the high latitudes of LICOM has also been eliminated, and the scalability and efficiency of the parallel algorithm has been extensively improved. Besides, preserved shape advection in the tracer formulation (Xiao, 2006) and implicit vertical viscosity (Yu et al., 2018) are also employed in the present version.
Third, the tidal mixing of St. Laurent et al. (2002) and the buoyancy frequency (N2)–related thickness diffusivity of Ferreira et al. (2005) have been introduced into LICOM after CMIP5. The effects of tidal mixing on the Atlantic meridional overturning circulation (AMOC) was preliminary evaluated by Yu et al. (2017). The effects of thickness diffusivity with temporal and spatial variation were evaluated by Li et al. (2019). Besides, the chlorophyll-a-dependent solar penetration of Ohlmann (2003), the vertical diffusivity of Canuto et al. (2001, 2002), and the isopycnal mixing of Redi (1982) and Gent and McWilliams (1990, GM90 hereafter) are also used in LICOM3. The isopycnal mixing coefficient is constant, with a value of 300 m2 s−1. The thickness mixing coefficient (i.e., diffusivity) for GM90 employs the scheme of Ferreira et al. (2005), in which the coefficient is dependent on the spatial distribution of N2 and varies with location and time. The coefficient is set to 300 m2 s−1 within the mixed layer or in the coastal region where the water depth is shallower than 60 m, while it varies between 300 and 2000 m2 s−1 in other places.
The virtual salinity flux is computed as the freshwater flux multiplied by a constant salinity of 34.7 psu. A restoring term with a piston velocity of 20 m yr−1 has been applied to the virtual salinity flux. If there is sea ice, a piston velocity of 50 m (20 d)−1 is applied under sea ice.
Here, the low-resolution LICOM3, which is used both for CMIP6 and OMIP, has 360 and 218 grid numbers for the zonal and the meridional directions, respectively. LICOM3 has two resolutions in the vertical (30 and 80 levels), but only the 30-level resolution is used for OMIP and CMIP6 to save computing resources. The depths of the W-grid and T-grid are shown in Table 2. At the same time, an eddy-resolving version of LICOM3 has also been developed, with a horizontal resolution of about 10 km at the equator and 2.7 km around the Antarctic, and 55 levels in the vertical. This version has also been implemented in an ocean forecast system for short-term ocean prediction①.
Level Depth for T Depths for W 1 −5 0 2 −15 −10 3 −25 −20 4 −35 −30 5 −45 −40 6 −55 −50 7 −65 −60 8 −75 −70 9 −85 −80 10 −95 −90 11 −105 −100 12 −115 −110 13 −125 −120 14 −135 −130 15 −145 −140 16 −156.9303 −150 17 −178.4277 −163.8606 18 −222.5018 −192.9948 19 −303.1057 −252.0088 20 −432.5961 −354.2027 21 −621.1931 −510.9896 22 −876.5334 −731.3966 23 −1203.337 −1021.67 24 −1603.2 −1385.003 25 −2074.526 −1821.396 26 −2612.596 −2327.656 27 −3209.772 −2897.536 28 −3855.835 −3522.009 29 −4538.428 −4189.662 30 −5243.597 −4887.194 31 − −5600
Table 2. Depths of model levels for the T- and W-grid. Positive is upward.
The OMIP experiment follows the protocol of CORE-II, which is an ocean–sea-ice coupled hindcast simulation forced by about 60 years of modified reanalysis atmospheric variables with diurnal to decadal signals. Usually, the experiment is conducted for five or six cycles to reach an equilibrium state. Details of the experiments are shown in Table 3. Here, LICOM3 is coupled with CICE4 using the NCAR flux coupler 7. Two standard OMIP experiments have been conducted: one forced with CORE-II data derived from NCEP–NCAR reanalysis (Large and Yeager, 2004), named OMIP1; and the other forced with the surface dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis (JRA55-do, Tsujino et al., 2018), named OMIP2. The atmospheric variables include atmospheric surface wind vectors at 10 m, temperature at 10 m, specific humidity at 10 m, air density at 10 m, precipitation (both rain and snow), surface downward shortwave radiation, downward longwave radiation, and sea level pressure. The period of the forcing data is 62 years (1948–2009) for CORE-II, while the period is 61 years (1958–2018) for JRA55-do. Although the frequencies of the two datasets are different, we use 6-h intervals for both datasets to force the model. Here, experiments with six cycles (one cycle corresponds to 1948-2009 for CORE-II and 1958−2018 for JRA55-do) have been completed and uploaded onto ESG nodes for both OMIP1 and OMIP2. Details of the primary output and diagnostic variables are given in Table 4.
Experiment_id Model Initial condition (TS/currents) Forcing data Period Frequency OMIP1 LICOM3/CICE4.0 PHC3.0/Zero CORE-II 1948–2009 (6 cycles) 6 h OMIP2 LICOM3/CICE4.0 PHC3.0/Zero JRA55-do 1958–2018 (6 cycles) 6 h
Table 3. Descriptions of the experiments of LICOM3.
Name Description Frequency hfbasin Northward ocean heat transport Monthly hfbasinpmadv Northward ocean heat transport due to parameterized mesoscale advection Monthly hfbasinpmdiff Northward ocean heat transport due to parameterized mesoscale diffusion Monthly hfds Downward heat flux at sea water surface Monthly masscello Ocean grid-cell mass per area Monthly mlotst Ocean mixed-layer thickness defined by sigma T Monthly msftbarot Ocean barotropic mass streamfunction Monthly msftmz Ocean meridional overturning mass streamfunction Monthly msftmzmpa Ocean meridional overturning mass streamfunction due to parameterized mesoscale advection Monthly obvfsq Square of Brunt–Vaisala frequency in sea water Monthly pbo Sea water pressure at sea floor Monthly pso Sea water pressure at sea water surface Monthly so Sea water salinity Monthly sob Sea water salinity at sea floor Monthly soga Global mean sea water salinity Monthly sos Sea surface salinity Monthly sosga Global average sea surface salinity Monthly thetao Sea water potential temperature Monthly thetaoga Global average sea water potential temperature Monthly tob Sea water potential temperature at sea floor Monthly tos Sea surface temperature Monthly tosga Global average sea surface temperature Monthly uo Sea water X velocity Monthly umo Ocean mass X transport Monthly vo Sea water Y velocity Monthly vmo Ocean mass Y transport Monthly wfo Water flux into sea water Monthly wo Sea water vertical velocity Monthly wmo Upward ocean mass transport Monthly zos Sea surface height above geoid Monthly omldamax Mean daily maximum ocean mixed-layer thickness defined by mixing scheme Daily areacello Grid-cell area for ocean variables Fixed deptho Sea floor depth below geoid Fixed thkcello Ocean model cell thickness Fixed ugrido UGRID grid specification Fixed volcello Ocean grid-cell volume Fixed
Table 4. Descriptions of dataset variables of Priority 1.
|Resolution||~1°, 30 levels||~1°, 30 or 80 levels|
|Dynamic core||Tracer advection||Central differential scheme||Preserved shape scheme (Yu, 1994)|
|Momentum time integration||Explicit||Implicit|
|Physics||Diapycnal mixing||Mixing in the mixed layer (Canuto et al., 2001, 2002)||Mixing in the mixed layer (Canuto et al., 2001) and internal tide mixing (St. Laurent et al., 2002)|
|Isopycnal mixing||Isopycnal mixing (Redi, 1982) and advection (Gent and McWilliams, 1990)||Isopycnal mixing (Redi, 1982) and advection (Gent and McWilliams, 1990) with N2 thickness diffusivity (Ferreira et al., 2005)|
|Computing technics||Coupler interface||NCAR Flux Coupler 6||NCAR Flux Coupler 7|
|Parallel||1D MPI and OMP||2D MPI and OMP|
|Data||Initial condition||WOA01 (Conkright et al., 2002)||PHC3.0 (Steele et al., 2001)|
|Bathymetry||DBDB5 (https://www.bodc.ac.uk/resources/inventories/edmed/report/356/)||ETOPO2 (https://ngdc.noaa.gov/mgg/global/etopo2.html)|