Eddy-Resolving Ocean Modeling

Weather forecasting has beendeveloped into a fine art,with elaborate data collec-

tion systems feeding present conditionsinto detailed computer models. Despitethis great effort, it appears to be impos-sible to predict weather for more thanabout two weeks in advance. Yet wehope to predict the effects of green-house gas emissions and other human-induced effects on climate decades tocenturies into the future. This goalmay, in fact, be possible because whatwe call climate is really the statistical“envelope” of weather events, and thuswe are asking for much less detailedinformation than would be necessary toforecast weather.

Earth’s climate is controlled by thecomplex interaction of many physicalsystems, including the atmosphere,the ocean, the land surface, the bios-phere, and in the polar regions, seaice. To be able to predict future cli-mate change, or at least to determinewhat can and cannot be predicted, wehave to understand both the naturalvariability of the climate system andthe extent to which human activitiesaffect it. The ocean is of key impor-tance in understanding climate,because changes in ocean circulationpatterns are believed to be of primaryimportance in controlling climatevariability on time scales of decadesto centuries.

Unfortunately, realistic globalocean simulations pose a severe com-putational problem because the oceancontains both very small spatial scalesand very long time scales comparedwith the atmosphere. Most of thekinetic energy in the ocean is con-tained in the so-called “mesoscaleeddies,” whose sizes range from 10 to300 kilometers. These eddies consti-tute the “weather” of the ocean. Theyare the oceanic equivalent of high-and low-pressure systems in theatmosphere, where the spatial scalesare much larger. Weather fronts typi-cally extend over distances of 1000 to3000 kilometers.

Whereas the spatial scales aresmaller, the time scales in the oceanare much longer than in the atmos-phere. Temperature anomalies in theatmosphere persist for at most a fewmonths (unless they are associatedwith longer-term anomalies in theocean surface temperature, as occur inan El Niño event). The ocean, becauseof its inertia and large heat capacity,has a much longer memory. Watermass properties in the deep ocean canreflect conditions that existed at thesurface hundreds of years in the past.Residence times of deep-water massesare typically several hundred yearsand more than a thousand years in thedeep Pacific Ocean. Because of thisphenomenon, the integration time

required to “spin up” an ocean modelfrom an initial state of rest to a near-equilibrium state is several thousandsimulated years.

Using the computer resources avail-able today, it is not possible to integratea basin- or global-scale ocean modelwith a resolution of about 10 kilometers(or about 0.1° resolution in longitude)for 1000 years or more in a reasonableamount of time. On the machines avail-able in the United States, the global0.1° simulations discussed below typi-cally require about one week of com-puter time per simulated year, so a1000-year simulation would take nearly20 years to execute. On the JapaneseEarth Simulator, currently the world’sfastest supercomputer, the same modelruns more than 10 times faster. But westill need another factor of 50-to-100increase in computing power beforemulticentury, eddy-resolving climatesimulations become feasible, and it willlikely be at least a decade before suchresources become available.

Another major issue is data stor-age. Typical model output from a 0.1°global model is about 1 terabyte persimulation year, so archiving, analy-sis, and long-term data storage posesevere problems. Because of theselimitations, ocean models that are nowbeing used in multicentury global cli-mate simulations have spatial resolu-tions ranging between 1° and 4° (or

Number 28 2003 Los Alamos Science 223

Eddy-Resolving Ocean Modeling

Robert C. Malone, Richard D. Smith,Mathew E. Maltrud, and Matthew W. Hecht

about 100 to 400 kilometers), whereasmodels with resolutions of 0.1° (orabout 10 kilometers) can run simula-tions of decades only.

During the past 12 years, LosAlamos has built the Climate, Ocean,and Sea-Ice Modeling (COSIM) proj-ect, with support from theDepartment of Energy (DOE). Ouremphasis has been on the develop-ment and application of ocean andsea-ice models, but research is shift-ing toward fully coupled global cli-mate modeling. In collaboration withthe National Center for AtmosphericResearch (NCAR), we are develop-ing coupled climate models usinglow- to moderate-resolution oceancomponents. The NCAR communityclimate system model, which is themost widely used, fully coupled cli-mate model in the United States, usesthe Parallel Ocean Program (POP)model and the sea-ice model CICE,both developed at Los Alamos. Thesemodels were designed to run effi-ciently on parallel computer architec-tures and employ novel numericalalgorithms that improve both thenumerical efficiency and physicalaccuracy of the simulations. LosAlamos is also the home of theisopycnal ocean model HYCOM,which uses density instead of depthas the vertical coordinate (except inthe surface mixed layer). More infor-mation on climate, ocean, and sea-icemodeling at Los Alamos is availableon our web server:http://www.acl.lanl.gov/climate.

A major emphasis of our researchover the last decade has been tomake use of the supercomputingresources at Los Alamos for veryhigh resolution, eddy-resolvingocean simulations, albeit of relativelyshort duration, using the POP model.This approach is the main focus ofthis article. Ten to 20 simulationyears is sufficient time for the modelto reach a quasi-equilibrium state,where the velocity field has adjusted

to the initial density field. Theseshort simulations are thereforeappropriate for studying the dynam-ics of the ocean circulation on timescales of a decade or less, but theyare not appropriate for studying thelong-term evolution of deep-watermasses or climate variability on timescales of decades and longer.

Nevertheless, the high-resolutionsimulations are very important for cli-mate research since the model outputprovides realistic fields of turbulentstatistics (such as eddy fluxes of massand heat) that can be used to guide the

development of subgrid-scale (SGS)parameterizations for use in coarse-res-olution climate simulations.Understanding the behavior of thesemodels will also pave the way forfuture eddy-resolving climate simula-tions. Furthermore, the model providescomprehensive three-dimensionaldatasets that can aid in the interpretationof the extensive observations taken overthe last decade, such as high-qualitysatellite altimetry measurements and thevariety of in situ measurements collectedas part of the World Ocean CirculationExperiment (WOCE).

224 Los Alamos Science Number 28 2003


What Drives the Ocean Circulation?

The ocean circulation is driven by fluxes of momentum, heat, and freshwater at the air-sea interface. Fluxes of momentum are due to stress fromthe surface winds and from the movement of sea ice in polar regions. Thesurface wind stress is the primary driver of the upper-ocean circulationand is responsible for the major current systems, such as the midlatitudegyres with their associated strong western boundary currents (that is, theGulf Stream off the east coast of North America and the KuroshioCurrent in the Pacific off the east coast of Japan). Surface wind stressalso drives the complex system of equatorial currents in the tropics, aswell as the Antarctic Circumpolar Current in the Southern Ocean.

The other drivers of circulation—fluxes of heat and fresh water—are col-lectively known as buoyancy fluxes because they produce changes in thedensity of seawater, which depends on its temperature, salinity, and pres-sure. The surface heat flux is caused by incoming solar radiation, outgo-ing long-wave radiation, latent heat associated with evaporative cooling,and direct thermal transfer, also known as “sensible heat flux,” which isdue to differences in air and sea-surface temperatures. Fluxes of freshwater are primarily associated with precipitation and evaporation in theopen ocean but are also due to melting or freezing of sea ice in polarregions and river runoff in coastal regions. The heat flux modifies thedensity of seawater by altering its temperature, whereas the fresh-waterflux modifies the density by changing the salinity of seawater.

The buoyancy fluxes are the primary drivers of a circulation known as thethermohaline circulation, which is characterized by very localized sinkingof dense water in subpolar regions and broad upwelling at low and midlatitudes. The thermohaline circulation is a very important factor in theearth’s climate, because it controls the transport of heat by the ocean fromthe tropics to high latitudes, as well as the rate of formation of deep waterin subpolar regions.

The North Atlantic Ocean at 0.1° Resolution

Our first major simulation per-formed with the POP model was aglobal ocean simulation driven byobserved surface winds for thedecade 1985 to 1995 (Maltrud et al.1998). (The ocean circulation is driv-en primarily by surface winds, butsurface fluxes of heat and fresh waterare also important. See the box onthe opposite page.) This model had ahorizontal resolution of 0.28°, corre-sponding to a grid spacing rangingfrom about 30 kilometers at the equa-tor to about 10 kilometers at highlatitudes. (The variation in grid spac-ing occurs because this model uses aMercator grid, in which the grid res-olution in both the north-south andeast-west directions varies as thecosine of latitude. The grid spacing isshown as a function of latitude inFigure A on the next page). The

0.28° resolution was sufficient toallow the development of a weakeddy field, but the eddy energy wasmuch too low compared with obser-vations. Although it was able toreproduce many aspects of the wind-driven circulation, this simulation,like other “eddy-permitting” simula-tions conducted by differentresearchers, was unable to reproducebasic features of the mean circula-tion, such as the points at whichwestern boundary currents (for exam-ple, the Gulf Stream) separate fromthe coastlines or the observed pathsof major current systems such as theNorth Atlantic Current, which flowsnortheast along the Grand Banks eastof Newfoundland. Such errors canlead to huge mismatches betweenmodeled and observed air-sea heatfluxes and can lead to incorrect feed-back in coupled models.

The reasons for the deficiencies inthis and other eddy-permitting simula-

tions are still not completely under-stood, but detailed analysis of theglobal simulation compared withsatellite observations (Fu and Smith1996) clearly demonstrated the needfor even higher spatial resolution, andtheoretical arguments suggested a hor-izontal resolution of 0.1° or higherwould be needed to capture the bulkof the energy in the turbulentmesoscale eddy field. At that time(1997), a global simulation was notfeasible at this resolution, so we optedto conduct a limited-domain simula-tion of the North Atlantic Ocean at0.1°, using a grid containing about 50million ocean grid points. This model,also driven by observed winds, coversthe period 1985 through 2000 (Smithet al. 2000). The model domainextends from 20S in the SouthAtlantic to 72N, and includes the Gulfof Mexico and the western half of theMediterranean Sea.

Figure 1 shows a snapshot of the



Figure 1. Ocean Heat TransportIn Earth’s climate system, the ocean andthe atmosphere each contribute abouthalf the total transport of heat from thetropics to high latitudes. The figure is asnapshot of sea-surface temperaturefrom a 0.1° simulation of the NorthAtlantic Ocean. Red colors indicatewarm water, and blue colors, cold water.The Gulf Stream, which follows thecoastline of the southeastern UnitedStates, carries warm water from the trop-ics to high latitudes. (Inset) This magni-fied view focuses on the Gulf Stream. Inthis simulation, it correctly separatesfrom the coast at Cape Hatteras.

sea-surface temperature from a 0.1°North Atlantic simulation. The path ofthe Gulf Stream, which carries warmwater from the tropics to high lati-tudes, can be clearly seen. The currentfollows the coastline of the southeast-ern United States until it separatesfrom the coast at Cape Hatteras; fromthat point on, it begins to meander andpinch off warm and cold core eddies.In lower-resolution simulations, theGulf Stream does not separate at CapeHatteras as observed. This discrepancyhas been a long-standing problem withocean circulation models.

Eddy Variability. A remarkablefeature of the 0.1° simulation is theemergence of a ubiquitous mesoscaleeddy field that is substantiallystronger than had been seen in previ-ous simulations and which is, bymany measures, in good agreementwith observations. The eddy kineticenergy constitutes about 70 percentof the total basin-averaged kineticenergy in the North Atlantic. Themodel results agree well with obser-vations of the magnitude and geo-graphical distribution of near-surfaceeddy kinetic energy and sea-surface-height (SSH) variability. (Regions ofstrong SSH variability correspond toregions of strong, highly variable cur-rents and turbulent flow. See the boxon this page.). The model results alsoagree with the wave number versusfrequency spectrum of surface heightvariations in the Gulf Stream, as wellas with measurements of the eddykinetic energy as a function of depthin the more quiescent eastern basin.The model appears to be simulatingrealistic values of kinetic energy overa broad range of space and timescales.

Figure 2 shows the root-mean-square (rms) SSH variability from themodel, averaged over a 4-year period,as well as a recent high-quality blendof altimeter data from the TOPEX/Poseidon satellite and the satellites



Currents, Sea-Surface Height, and Satellite Altimetry

The leading-order balance of forces in both the atmosphere and the oceanis between the Coriolis force, which is due to the earth’s rotation, andhorizontal pressure gradients. This state is known as geostrophic balance.The Coriolis force is proportional to the earth’s rotational frequency andto the magnitude of the local current velocity, but it is directed perpendi-cular to the velocity (to the right in the Northern Hemisphere).

In the ocean, the Coriolis force associated with a near-surface current isin geostrophic balance with the horizontal pressure gradient because ofchanges in sea-surface height (SSH), as shown in the figure in this box.Thus, the near-surface pressure gradients are proportional to gradients ofSSH. As a result, contours of constant SSH approximate streamlines ofthe near-surface flow, just as, in the atmosphere, contours of constantpressure (isobars) approximate streamlines of the winds.

In principle, an accurate map of the SSH would allow us to determine thenear-surface currents. In practice, absolute measurements of SSH are diffi-cult because the location of the sea surface in the absence of any flow ispoorly known. If the ocean were at rest, the sea surface would coincidewith a gravitational equipotential surface known as the geoid. Existingmeasurements of the geoid are not accurate enough to allow precise meas-urements of absolute surface height. However deviations of the SSH fromthe geoid can be made with much greater accuracy. Typical vertical fluctu-ations in the SSH associated with strong currents and eddies are about 1 to3 meters, whereas modern satellite altimeters can measure vertical changesin SSH relative to the geoid with an accuracy of about 1 to 2 centimeters.Thus, the noise in the measurements is an order of magnitude smaller thanthe signal, and this situation allows very accurate measurements of theSSH variability, such as those shown in Figures 2 and 4.

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Figure A. Geostrophically Balanced Near-Surface CurrentThe pressure at a given depth is, to leading order, given by the weightof the overlying water column, which varies with the SSH. A drop inthe SSH produces a horizontal pressure gradient that is balanced bythe Coriolis force, which is proportional to the current velocity.

sent by the European Remote-SensingSatellite (ERS) Programme (Le Traonand Ogor 1998, Le Traon et al. 1998).This type of satellite data has revolu-tionized our understanding of theworld ocean, because it provides atime series of surface properties withnear-global coverage (instead of, forexample, a snapshot of a limited sec-tion of the ocean resulting from aseries of instrument casts obtainedalong a research vessel cruise track).The level of agreement between modeland observations evident in Figure 2 isunprecedented. It represents a mile-stone for both numerical ocean model-ing and satellite altimetry. In fact, timeseries of two-dimensional fields ofsurface height from the model are nowbeing used by scientists in the UnitedStates and in France to help interpretthe existing satellite altimetry meas-urements and to aid in the develop-ment of the next generation of satellitealtimeter experiments.

Time-Mean Circulation. Althoughthe agreement between the model andobservations in eddy variability isimpressive, what is most remarkableabout the 0.1° simulation is that thetime-averaged, or time-mean, circula-tion exhibits several significantimprovements relative to previoussimulations. Figure 3 shows the time-mean SSH from the model. As dis-cussed in the box on the oppositepage, contours of constant SSHapproximate streamlines of the near-surface flow, and strong currents areassociated with sharp drops in SSHacross these contours (that is, instronger currents, the streamlines are“crowded together”). Major currentsystems such as the Gulf Stream andthe North Atlantic Current are clearlyvisible in the figure. The Gulf Streamseparates at Cape Hatteras, and itspeak velocities, transports, spatialscales, and the cross-stream structureof the current are in good agreementwith current-meter data. South of the



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Figure 2. SSH Variability in the North Atlantic OceanPanel (a) shows the 0.1° POP model simulation of SSH variability, whereas (b) showsaltimeter observations derived from data from the TOPEX/Poseidon, ERS-1, and ERS-2satellites.The SSH variability is related to mesoscale turbulence, which is generatedby instabilities of the mean flow, and hence the eddy field is most intense in regions ofstrong western boundary currents.The height variability is most intense in the regionof the Gulf Stream extension (around 30N to 45N latitude and 75W to 50W longitude)and in the vicinity of the North Atlantic Current (40N to 50N and 50W to 35W). Someregions of high variability that appear in the observations but not in the model (suchas off the west coast of South America near the equator and off the North Americancoast southwest of Nova Scotia) are residual errors associated with the removal oftides from the altimetry measurements.

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Grand Banks, the Gulf Stream splitsinto the northeast-flowing NorthAtlantic Current and a southward flowthat feeds the Azores Current. Thetime-mean path of the North AtlanticCurrent is in good agreement withobservations from float data, includ-ing the detailed positions of troughsand meanders. This is the first realis-tic simulation that correctly simulatesthe Azores Current, which flows east-ward at about 35N in the central andeastern basin. Its position, total trans-port, and eddy variability are consis-tent with observational estimates.(The surface height variability for thiscurrent can be seen in Figure 2 as atongue of high variability between30N to 35N and 40W to 20W thatappears in both model and observa-tions.)

This simulation is by no means per-fect; there are notable discrepancieswith observations in some areas. Forexample, the Gulf Stream separates atCape Hatteras, but its eastward pathafter separation is about 1.5° too farsouth. Nevertheless, the overallimprovement in the time-mean flowrelative to previous simulations indi-cates that we have crossed a thresholdin resolution and entered a new regimeof the flow that is much closer to thereal circulation of the North Atlantic.

What is responsible for this regimeshift? We do not yet know the com-plete answer to this question. It islikely that the increased resolutionalone is responsible for much of theimprovement. The resolution is highenough that we are able to resolve thetypical length scale of the eddies (theRossby radius) and hence capture thebulk of the energy in the eddy spec-trum. (See the box on the oppositepage.) The improvements in the meancirculation strongly suggest that theturbulent eddy field plays a crucialrole in determining the character ofthe mean flow. Another contributingfactor is undoubtedly the improve-ment in the representation of the bot-

tom topography. Unlike atmosphericcirculation, ocean circulation is verystrongly constrained by the bottomand coastal boundaries, and using thelatest high-resolution data sets forocean depth, we are much better ableto represent the coastal and sea-floortopography in this high-resolutionmodel. Another feature that changesdramatically at high resolution is thatcurrents like the Gulf Stream becomemuch stronger, narrower, and deeperthan in the lower-resolution simula-tions. These deep currents in manyareas reach the ocean floor (in agree-ment with observations) and are there-fore much more strongly influencedand steered by the bottom topography.In contrast, in coarse- and moderate-

resolution models, currents like theGulf Stream are unrealistically broadand shallow, and are not as stronglyinfluenced by the bottom topography.

It should be emphasized that goingto 0.1° or higher resolution is not initself a guarantee that the simulationwill show the same improvements wehave seen. Several other modelinggroups have now begun to carry outvery high resolution simulations, andnot all of these have had the samesuccess. An example is the global0.1° model discussed in the next sec-tion. Although simulations with thismodel do show improvements inmany areas, they have so far beenunable to reproduce the correct pathof the North Atlantic Current, which,



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Figure 3. Mean SSH in the North Atlantic Ocean Mean SSH from a 0.1° POP model simulation. Contours of constant SSH approxi-mate streamlines of the near-surface flow. Sharp drops in SSH across thesestreamlines indicate the presence of strong geostrophic currents.

instead of turning northeast at theGrand Banks, continues eastwardacross the Atlantic, as it does inlower-resolution models. This errorleads to large mismatches betweenthe modeled and observed surface

heat fluxes. We are in the process ofinvestigating the reasons for this dif-ference in the global and NorthAtlantic models.

Sensitivity Experiments. Onething we have discovered is that thesolutions are very sensitive to thechoice of SGS parameterizations ofhorizontal viscosity and diffusion.Initially, we had hoped that, at this



Geostrophic Turbulence: The Weather of the Ocean

Weather maps at midlatitudes show wavelike horizontal excursions of temperature and pressure contours super-posed on eastward mean flows such as the jet stream. These disturbances can “pinch off” and evolve into large-scale eddies that encompass the familiar high- andlow-pressure centers. Similar excursions of the meanflow are found in the ocean in eastward-flowing cur-rents such as the Gulf Stream. These disturbances aredue to an inherent instability of the midlatitude jetsknown as “baroclinic instability,” which occurs in thepresence of strong horizontal density gradients. It isbelieved that baroclinic instability is the dominantmechanism for generating turbulent motion in themidlatitude jets. (Another type of instability, knownas “barotropic instability,” can also generate large-scale turbulent flow in the atmosphere and ocean.This instability occurs in the presence of strong hori-zontal shear and is more dominant in the tropics.)

Baroclinic instability occurs in rotating, stratified flu-ids, with strong geostrophically balanced currents,which are associated with steeply sloping densitysurfaces. Turbulent energy is extracted from thepotential energy of the mean flow that is stored in thesloping density surfaces of geostrophic currents. Thenet effect of pinching off an eddy from an eastwardjet is to flatten the slope of the density surface, thus releasing potential energy. This instability is very differentfrom the more familiar shear-flow instabilities such as the Kelvin-Helmholtz instability, in which perturbationsgrow by extracting energy from the mean shear flow.

A key feature of baroclinically unstable flow, which distinguishes it from most other types of turbulence, is that ithas an inherent length scale, known as the “deformation radius” or “Rossby radius.” This radius is the horizontallength scale associated with unstable modes having the largest growth rate. Perturbations with wavelengths muchsmaller than the Rossby radius do not grow, whereas those with wavelengths much larger than the Rossby radiusgrow very slowly. The Rossby radius depends on the degree of stratification (or vertical density gradient) and onthe local vertical component of planetary rotation. The figure shows the Rossby radius in the ocean as a function oflatitude averaged over the east-west direction, computed by using a mean density field from the 0.1° North Atlanticsimulation. Also shown is the horizontal grid resolution in the 0.28° and 0.1° models discussed in the text. A keyfeature of the 0.1° simulation is that the grid resolution is less than or equal to the Rossby radius at all latitudes.Typical mesoscale eddies have horizontal diameters that are three to 10 times larger than the Rossby radius, so the0.1° grid is expected to allow at least marginally good resolution of the eddies at all latitudes. This fact is undoubt-edly a key reason that this simulation shows substantial improvements in eddy variability.

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high resolution, we would simply beable to pick the coefficients of viscos-ity and diffusivity to be as small aspossible to control numerical noisethat appears on the grid scale, but thatwas not the case. Using the smallestpossible mixing coefficients leads tounrealistic features, and the best solu-tions are obtained with larger values.This fact suggests that even at 0.1°resolution, we need to parameterizethe effects of unresolved physicalprocesses. We are investigating thesensitivity of the solution to differentvalues of the mixing coefficients—aswell as to different formulations of theSGS parameterizations—with a suiteof new 0.1° North Atlantic simula-tions. We have developed novel SGSparameterizations that use horizontallyanisotropic forms for viscosity anddiffusivity, and we have shown thatthese lead to improvements in thesolutions compared with the morestandard isotropic forms. What welearn from these sensitivity studies inthe North Atlantic model is beingtransferred to the more expensiveglobal 0.1° simulations.



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Figure 4. SSH Variability in a 0.1°Global SimulationThe rms SSH variability in the SouthernOcean near Australia is (a) from theglobal 0.1° POP model, (b) from theblended analysis of data from theTOPEX/Poseidon, ERS-1, and ERS-2satellites, and (c) from the global 0.28°POP simulation. The agreement withobservations is much better in the 0.1°model, especially in regions of strongcurrents such as the East AustraliaCurrent (near 30S, 155E) and theAntarctic Circumpolar Current (acrossthe domain between 45S and 60S). Thelocalized regions of high variabilityalong the northern coast of Australiaand south of New Guinea in the obser-vations are residual tidal errors.

Global Simulations

Spurred by the success of the 0.1°North Atlantic simulations, we haveconfigured a 0.1° global ocean model.It uses a “displaced-pole” grid devel-oped at Los Alamos (Smith et al.1995), similar to the one shown in theopening graphic. Standard grids thatuse lines of constant latitude and longi-tude as coordinates have a singularitythat is due to the convergence of merid-ians at the North Pole. The displaced-pole grid eliminates this singularity bydisplacing the northern grid pole intothe North American continent. Thisgrid includes the entire global oceanexcept for ocean points within the cir-cle surrounding Hudson Bay. Thismodel, containing more than 300 mil-lion grid points, is expensive to run.Both the Department of Defense(Navy) and the DOE provided compu-tational resources that allowed thecompletion of a 15-year simulation.More recently, several 15-year simula-tions have been run on the JapaneseEarth Simulator. Figure 4 shows therms SSH variability in a section of theSouthern Ocean surrounding Australiafrom both the 0.1° and 0.28° globalmodels and satellite observations. As inthe North Atlantic simulation (Figure2), the agreement with observations ismuch better in the 0.1° model.

The immense computationalresources required to run these simu-lations make sensitivity experimentsextremely difficult, not only becauseof the amount of computer timeinvolved but also because of thesevere problem of archiving and ana-lyzing the immense amount of dataproduced by each run. Each simula-tion must be carefully planned anddesigned. The next generation ofsupercomputers will make this taskmore tractable and allow us to movecloser to the goal of a fully coupled,global climate model with an eddy-resolving ocean component. Theexperience we are gaining today in

our basin- and global-scale oceansimulations will pave the way forthese future climate models. �

Acknowledgments

The 0.28° global simulations wereperformed in collaboration withProfessor Albert Semtner, NavalPostgraduate School, Monterey,California. The 0.1° North Atlanticsimulations were performed in collab-oration with Dr. Frank Bryan,National Center for AtmosphericResearch, Boulder, Colorado. The0.1° global simulations are being per-formed in collaboration with Dr. JulieMcClean, Naval Postgraduate School,Monterey, California.

References

Fu, L.-L., and R. D. Smith. 1996. Global OceanCirculation from Satellite Altimetry andHigh-Resolution Computer Simulation.Bull. Amer. Met. Soc. 77: 2625–2636.

Le Traon, P. Y., and F. Ogor. 1998. ERS1/2Orbit Error Improvement UsingTOPEX/POSEIDON: The 2 cm Challenge.J. Geophys. Res. 103: 8045–8057.

Le Traon, P. Y., F. Nadal, and N. Ducet. 1998.An Improved Mapping Method ofMultisatellite Altimeter Data. J. Atmos.Ocean. Tech. 15: 522–534.

Maltrud, M. E., R. D. Smith, A. J. Semtner, andR. C. Malone. 1998. Global Eddy-Resolving Ocean Simulations Driven by1985–1994 Atmospheric Winds. J. Geophys.Res. 102: 25203–25226.

Smith, R. D., M. E. Maltrud, F. O. Bryan, andM. W. Hecht. 2000. Numerical Simulationof the North Atlantic Ocean at 1/10°. J. Phys. Oceanogr. 30: 1532–1561.

Smith, R. D., S. Kortas, and B. Meltz. 1995.Curvilinear Coordinates for Global OceanModels. Los Alamos National Laboratorydocument LA-UR-95-1146.

For more information on POP, CICE, andclimate modeling at Los Alamos, including ref-erences and documentation for these models,see http://www.acl.lanl.gov/climate.

Richard Smith earned his Ph.D. in physicsfrom the University ofMaryland in 1984. Heworked as a postdoctoralresearcher in theoreticalnuclear physics atLawrence LivermoreNational Laboratorybefore coming to LosAlamos in 1987. Since1989, Richard has beena technical staff memberin the TheoreticalDivision. He is the principal developer of theLos Alamos Parallel Ocean Program (POP).



Robert Malone earned a Ph.D. in theoreticalphysics from Cornell University in 1973 andbecame a technical staff member at Los Alamos,where he has been work-ing on computationalmodeling of laser-drivenand magnetically con-fined plasmas for fusionresearch. Robert foundedthe Climate, Ocean, andSea-Ice ModelingProject, which has grownto include more than adozen scientists. LosAlamos is now the home of two global oceanmodels and one sea-ice model, all of which havelarge user communities.

Matthew Hecht obtained a Ph.D. in physicsfrom the University of Colorado in 1992, thenshifted focus from ele-mentary particle physicsto oceanography and geo-physical fluid dynamics.He was a postdoctoralresearcher and then apostdoctoral fellow, firstat the National Center forAtmospheric Researchand then at Los Alamos,where he is currently astaff member in the Computing andComputational Sciences Division.

Mathew Maltrud received a Ph.D. in oceanog-raphy from Scripps Institution of Oceanographyat the University ofCalifornia, Davis, in1992. He came to LosAlamos as a postdoctoralresearcher and soonbecame involved withdeveloping and runninghigh-resolution oceanmodels. He became a staffmember in the TheoreticalDivision in 1995.

Documents

Eddy-Resolving Ocean Modeling