“Very high resolution global ocean and Arctic ocean-ice models being developed for climate study” by Albert Semtner

Extremely high resolution is required for dynamical ocean models, inorder to resolve high-speed currents, hydrodynamic instabilities, andthe inherent variability that can influence the evolution of climate.Ice models can also benefit from very high resolution on account ofsmall-scale structures such as leads and pressure ridges. New modelsconstructed by investigators with long-term support from the WorldOcean Circulation Experiment and the Climate Change Prediction Programscale well on clustered multiprocessor computers and will enable someclimate simulations to include mesoscale ocean and ice features thataffect predictability. One model, now tested in multi-year simulationsby Julie McClean of NPS and Mat Maltrud of LANL, has average horizontalgrid spacing of 6.5 km, 40 vertical levels, and global ocean coverage.Another model of the pan-Arctic ocean and dynamical sea ice has a 9-kmgrid and 45 levels. The Arctic effort, led by Wieslaw Maslowski ofNPS, is additionally supported by the Arctic System Science Program.This talk will describe the two models and quantitatively compare theirsimulations with observations. Some of the model output will beillustrated with animations.

GFDL Genealogy slide

From Semtner, 1997

Parallel Ocean Program (POP)

• Primitive equation z-level ocean model with a free-surface boundary condition.

• Approximations to governing fluid dynamics equations permit decoupling of model solution into barotropic (vertically-averaged) and baroclinic (deviations from vertically-averaged) components; solved using implicit elliptic and explicit hyperbolic equation systems, respectively

• Designed to run on multi-processor machines using domain decomposition in latitude and longitude.

• MPI for inter-processor communications on distributed memory machines and SHMEM on shared memory machines.

Global Ocean Objectives • Determine the ability of a high-resolution (0.1, 40 level) N.

Atlantic ocean model to reproduce features and processes important to climate prediction via comparisons with surface drifters, tide gauges, and altimetry.

• Assess the role of increased vertical (20 to 40 levels) and horizontal resolution (0.28º to 0.1º). Is it justified in terms of increased computer resources?

• Use these results to guide high-resolution global simulation.

Sea Surface Temperature over the North Atlantic model domain

North Atlantic (a) surface drifter tracks, (b) 0.28, and (c) 0.1 POP numerical trajectories for 1993-1997

Leading CCA modes of Sea Surface Height Anomaly (SSHA); canonical correlations are 0.9671, 0.9354, and 0.8988 respectively. Correlation coefficients for the first 7 modes are significant at the 95% level. These 7 modes explain about 30% and 34% of the total SSHA variance in POP and T/P, respectively. The CCA patterns between POP and T/P agree well for the leading 6 modes.

Canonical Correlation Analysis of NA 0.1 POP and T/P SSHA

Atlantic Model Conclusions

• Relative to surface drifters, Eulerian velocity statistics compare well, provided a grid size of 0.1 or better is used.

• Time-varying nature and amplitude of SSHA from tide gauges are also well reproduced by POP.

• Altimetry indicates that basin-scale modes of SSHA variability from T/P closely match those from POP.

Fully Global Displaced North Pole Grid 3600 x 2400 x 40

Performance Statistics

1

10

100 1000

3600x2400x40 Test Problemtotal (ibm)baroclinic (ibm)barotropic (ibm)total (sgi)baroclinic (sgi)barotropic (sgi)total (perfect)

cpu seconds/timestep

number of processors

Instantaneous motion field highlighting eddies

Sea surface height variability (cm) from global 0.1 POP (upper LHS), TOPEX-ERS1 (upper RHS), and near-global 0.28 POP (bottom LHS)

Global Model Conclusions

• Preliminary evaluations of the global spin-up show realistic development: boundary currents, marginal sea circulation, and mesoscale eddies.

• Mass transports and energy levels are realistic.

Simulated sea ice concentration in summer and winter

• Comparison of surface eddy kinetic energy (cm2/s2) in the Labrador Sea from the (a) 9-km and (b) 18-km model - ~10% of (a)

PIPS 3.0 Spinup Year 13, depth = 0-5 m

Max=1034.5, Mean=96.08 Max=74.43, Mean=9.02

PCAP18 Year 1997, depth = 0-20m

Arctic Model ConclusionsModels of the Arctic Ocean and sea ice:

- are converging on proper scales, intensities, and time variability of real ocean

- provide useful guidance to collection and interpretation/synthesis of field observations

- have potential to assess predictability and make predictions on short to long time scales when used with suitable atmospheric models