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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

The roles of vertical mixing, solar radiation, and wind stress in a model simulation of the sea surface temperature seasonal cycle in the tropical Pacfic Ocean

The climatological seasonal cycle of sea surface temperature (SST) in the tropical Pacific is simulated using a newly developed upper ocean model. The roles of vertical mixing, solar radiation, and wind stress are investigated in a hierarchy of numerical experiments with various combinations of vertical mixing algorithms and surface-forcing products. It is found that the large SST annual cycle in the eastern equatorial Pacific is, to a large extent, controlled by the annually varying mixed layer depth which, in turn, is mainly determined by the competing effects of solar radiation and wind forcing. With the application of our hybrid vertical mixing scheme the model-simulated SST annual cycle is much improved in both amplitude and phase as compared to the case of a constant mixed layer depth. Beside the strong effects on vertical mixing, solar radiation is the primary heating term in the surface layer heat budget, and wind forcing influences SST by driving oceanic advective processes that redistribute heat in the upper ocean. For example, the SST seasonal cycle in the western Pacific basically follows the semiannual variation of solar heating, and the cycle in the central equatorial region is significantly affected by the zonal advective heat flux associated with the seasonally reversing South Equatorial Current. It has been shown in our experiments that the amount of heat flux modification needed to eliminate the annual mean SST errors in the model is, on average, no larger than the annual mean uncertainties among the various surface flux products used in this study. Whereas a bias correction is needed to account for remaining uncertainties in the annual mean heat flux, this study demonstrates that with proper treatment of mixed layer physics and realistic forcing functions the seasonal variability of SST is capable of being simulated successfully in response to external forcing without relying on a relaxation or damping formulation for the dominant surface heat flux contributions.

Chen, Dake↗
NASA NTRS2009

Detection of Rossby Waves in Multi-Parameters in Multi-Mission Satellite Observations and HYCOM Simulations in the Indian Ocean

Rossby waves are difficult to detect with in situ methods. However, as we show in this paper, they can be clearly identified in multi-parameters in multi-mission satellite observations of sea surface height (SSH), sea surface temperature (SST) and ocean color observations of chlorophyll-a (chl-a), as well as 1/12-deg global HYbrid Coordinate Ocean Model (HYCOM) simulations of SSH, SST and sea surface salinity (SSS) in the Indian Ocean. While the surface structure of Rossby waves can be elucidated from comparisons of the signal in different sea surface parameters, models are needed to gain direct information about how these waves affect the ocean at depth. The first three baroclinic modes of the Rossby waves are inferred from the Fast Fourier Transform (FFT), and two-dimensional Radon Transform (2D RT). At many latitudes the first and second baroclinic mode Rossby wave phase speeds from satellite observations and model parameters are identified.

SSH (SEA SURFACE HEIGHT)↗
NASA NTRS2004

Core Formation in the Earth: Constraints from Ni and Co

Due to their metal-loving nature, Ni and Co were strongly partitioned into the metallic core and were left depleted in the silicate mantle during core formation in the Earth. Based on experimental liquid metal- liquid silicate partition coefficients (D), studies have suggested that core formation in an early magma Ocean can explain the observed mantle depletions of Ni and Co [l-51. However, the conditions proposed by the magma ocean models have ranged from pressures of 24 to 59 GPa and temperatures of 2200 to < 4000 K. Furthermore, the proposed magma Ocean oxygen fugacities have differed by nearly two orders of magnitude.Chabot and Agee noted that the different models predicted contradictory behaviors for D(Ni) and D(Co) as a function of temperature. With the hope of resolving the discrepancies between the magma ocean models, we conducted a systematic experimental study to constrain the effects of temperature on D(Ni) and D(Co).

Chabot, N. L.↗
NASA NTRS1987

A model El Nino-Southern Oscillation

A coupled atmosphere-ocean model is developed and used to study the ENSO (El Nino/Southern Oscillation) phenomenon. With no anomalous external forcing, the coupled model reproduces certain key features of the observed phenomenon, including the recurrence of warm events at irregular intervals with a preference for three to four years. It is shown that the mean sea surface temperature, wind and ocean current fields determine the characteristic spatial structure of ENSO anomalies. The tendency for phase-locking of anomalies is explained in terms of a variation in coupling strength associated with the annual cycle in the mean fields. Sensitivity studies reveal that both the amplitude and the time scale of the oscillation are sensitive to several parameters that affect the strength of the atmosphere-ocean coupling. Stronger coupling implies larger oscillations with a longer timescale. A critical element of the model oscillation is the variability in the equatorial heat content of the upper ocean. Equatorial heat content increases prior to warm events and decreases sharply during the events. A theory for this variability and the associated transitions between non-El Nino and El Nino states is presented. Implications of the model results for the prediction of El Nino events are discussed.

Zebiak, Stephen E.↗
NASA NTRS1997

Applications of Data Assimilation to Analysis of the Ocean on Large Scales

It is commonplace to begin talks on this topic by noting that oceanographic data are too scarce and sparse to provide complete initial and boundary conditions for large-scale ocean models. Even considering the availability of remotely-sensed data such as radar altimetry from the TOPEX and ERS-1 satellites, a glance at a map of available subsurface data should convince most observers that this is still the case. Data are still too sparse for comprehensive treatment of interannual to interdecadal climate change through the use of models, since the new data sets have not been around for very long. In view of the dearth of data, we must note that the overall picture is changing rapidly. Recently, there have been a number of large scale ocean analysis and prediction efforts, some of which now run on an operational or at least quasi-operational basis, most notably the model based analyses of the tropical oceans. These programs are modeled on numerical weather prediction. Aside from the success of the global tide models, assimilation of data in the tropics, in support of prediction and analysis of seasonal to interannual climate change, is probably the area of large scale ocean modeling and data assimilation in which the most progress has been made. Climate change is a problem which is particularly suited to advanced data assimilation methods. Linear models are useful, and the linear theory can be exploited. For the most part, the data are sufficiently sparse that implementation of advanced methods is worthwhile. As an example of a large scale data assimilation experiment with a recent extensive data set, we present results of a tropical ocean experiment in which the Kalman filter was used to assimilate three years of altimetric data from Geosat into a coarsely resolved linearized long wave shallow water model. Since nonlinear processes dominate the local dynamic signal outside the tropics, subsurface dynamical quantities cannot be reliably inferred from surface height anomalies. Because of its potential for large scale synoptic coverage of the deep ocean, acoustic travel time data should be a natural complement to satellite altimetry. Satellite data give us vertical integrals associated with thermodynamic and dynamic processes.

Miller, Robert N.↗
NASA NTRS2009

Combined MODIS/AMSR-E SST Composites for Regional Weather Applications

Recent applications of a high resolution MODlS composite SST product have clearly shown the importance of developing high-resolution SST data sets for coastal applications and modeling. In general, coupling between the oceans and atmospheres has been closely linked to SST gradients and fronts, indicating a need for high resolution SSTs, specifically in the areas of large gradients associated with coastal regions. Thus an accurate determination of SST gradients has become critical for determining the appropriate air-sea coupling and the influence on ocean modeling. Recent research is focused on improving the accuracy and spatial coverage of the current operational MODIS SST composite product provided by the Short-term Prediction Research and Transition (SPORT) project and distributed to the community. GHRSST-PP MODlS data and microwave AMSR-E data are being combined to produce composite data sets for both the West Coast and East Coast of the United States, including the Gulf of Mexico. The use of 1 km MODIS data has explicit advantages over other SST products including its global coverage and high resolution. The AMSR-E data will reduce the latency of the composites. A strategy for utilizing the error characteristics contained in the GHRSST data has been developed. This strategy will include using the error characteristics directly to calculate weights in the SST composites, uncertainty maps based on the composite biases and RMS errors, and latency products calculated in the compositing process. Recent accomplishments include the development of an enhanced compositing approach based on the error-weighted combination of recent clear MODIS SST values, where the error contributions come from measurement error, potential cloud contamination, and data latency sources. Future plans call for the inclusion of AMSR-E SST values with appropriate weights based upon measurement accuracy, MODIS-AMSR-E SST bias, and latency.

Jedlovec, Gary↗
NASA NTRS2000

An Assessment of the Predictability of Northern Winter Seasonal Means with the NSIPP 1 AGCM

This atlas assesses the predictability of January-February-March (JFM) means using version 1 of the NASA Seasonal-to-Interannual Prediction Project Atmospheric General Circulation Model (the NSIPP 1 AGCM). The AGCM is part of the NSIPP coupled atmosphere-land-ocean model. For these results, the atmosphere was run uncoupled from the ocean, but coupled with an interactive land model. The results are based on 20 ensembles of nine JFM hindcasts for the period 1980-1999, with sea surface temperature (SST) and sea ice specified from observations. The model integrations were started from initial atmospheric conditions (taken from NCEP/NCAR reanalyses) centered on December 15. The analysis focuses on 200 mb height, precipitation, surface temperature, and sea-level pressure. The results address issues of both predictability and forecast skill. Various signal-to-noise measures are computed to demonstrate the potential for skillful prediction on seasonal time scales under the assumption of a perfect model and perfectly known oceanic boundary forcings. The results show that the model produces a realistic ENSO response in both the tropics and extratropics.

Suarez, Max J.↗
NASA NTRS2009

A USCLIVAR Project to Assess and Compare the Responses of Global Climate Models to Drought-Related SST Forcing Patterns: Overview and Results

The USCLI VAR working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land-atmosphere feedbacks on regional drought. Specific questions that the runs are designed to address include: What are the mechanisms that maintain drought across the seasonal cycle and from one year to the next? What is the role of the leading patterns of SST variability, and what are the physical mechanisms linking the remote SST forcing to regional drought, including the role of land-atmosphere coupling? The runs were carried out with five different atmospheric general circulation models (AGCM5), and one coupled atmosphere-ocean model in which the model was continuously nudged to the imposed SST forcing. This paper provides an overview of the experiments and some initial results focusing on the responses to the leading patterns of annual mean SST variability consisting of a Pacific El Nino/Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic Multi-decadal Oscillation (AMO), and a global trend pattern. One of the key findings is that all the AGCMs produce broadly similar (though different in detail) precipitation responses to the Pacific forcing pattern, with a cold Pacific leading to reduced precipitation and a warm Pacific leading to enhanced precipitation over most of the United States. While the response to the Atlantic pattern is less robust, there is general agreement among the models that the largest precipitation response over the U.S. tends to occur when the two oceans have anomalies of opposite sign. That is, a cold Pacific and warm Atlantic tend to produce the largest precipitation reductions, whereas a warm Pacific and cold Atlantic tend to produce the greatest precipitation enhancements. Further analysis of the response over the U.S. to the Pacific forcing highlights a number of noteworthy and to some extent unexpected results. These include a seasonal dependence of the precipitation response that is characterized by signal-to-noise ratios that peak in spring, and surface temperature signal-to-noise ratios that are both lower and show less agreement among the models than those found for the precipitation response. Another interesting result concerns what appears to be a substantially different character in the surface temperature response over the U.S. to the Pacific forcing by the only model examined here that was developed for use in numerical weather prediction. The response to the positive SST trend forcing pattern is an overall surface warming over the world's land areas with substantial regional variations that are in part reproduced in runs forced with a globally uniform SST trend forcing. The precipitation response to the trend forcing is weak in all the models.

Schubert, Siegfried↗
NASA NTRS2020

CMIP6 Historical Simulations (1850‐2014) with GISS‐E2.1

Simulations of the CMIP6 historical period 1850‐‐2014, characterized by the emergence of anthropogenic climate drivers like greenhouse gases, are presented for different configurations of the NASA Goddard Institute for Space Studies (GISS) Earth System ModelE2.1. The GISS‐E2.1 ensembles are more sensitive to forcing than their CMIP5 predecessors (GISS‐E2), but warm less during recent decades due to reduced total forcing. This forcing reduction is attributed to an increase in longwave opacity in pre‐industrial simulations, resulting in an atmosphere less sensitive to further increases in opacity that result from rising greenhouse gas concentrations. This demonstrates the importance of the base climatology to forcing and forced climate trends. Most model versions match observed temperature trends since 1979 from the ocean to the stratosphere. The choice of ocean model is important to the transient climate response, as found in CMIP5 GISS‐E2: the model that more efficiently exports heat to the deep ocean shows a smaller rise in tropospheric temperature. Model sea level rise over the historical period is traced to excessive drawdown of aquifers to meet irrigation demand with a smaller contribution from thermal expansion. This shows how fully coupled models can provide indirect observational constraints upon forcing, in this case, constraining irrigation rates with observed sea level changes. The overall agreement of GISS‐E2.1 with observed trends is familiar from evaluation of its predecessors, as is the conclusion that these trends are almost entirely anthropogenic in origin.

NASA Goddard Institute for Space Studies (GISS) Ea↗
NASA NTRS2020

Computationally Efficient Modeling and Data Assimilation of Near-Surface Variability

Near-surface (< 20m) ocean exhibits high variability due to coupled interactions, for e.g., with the atmosphere, sea ice, land, etc. Here we focus on atmospheric heat and momentum (wind) forcing, which are known to cause diurnal variability within the mixed layer. Only recently with a combination of sufficiently high vertical/horizontal resolution (75L, 1/4deg) and sub-daily atmospheric forcing fields, ocean models are starting to resolve this diurnal variability. However, the computation expense of such a high vertical resolution is burdensome in the context of coupled modeling and data assimilation. An alternative approach is to parameterize this diurnal variability with a prognostic model, that is embedded into the ocean model.In the first part of this presentation, we will demonstrate results with the above two approaches, by comparing them to profiles of near-surface temperature and salinity. In the context of data assimilation and reanalysis, this modeling capability opens the door to re-examine and perhaps improve specification of background (or, ensemble) error characteristics. The second half of this talk will focus on illustrating diurnally varying errors within an ensemble DA, and possible approaches to improve localization (horizontal/vertical) to extract maximum possible observational information content from in-situ and satellite observations of sea surface temperature.

Akella, Santha↗
NASA NTRS2004

Research on the Natural Variability of Climate

The scheme for ocean vertical mixing presented in Canuto, Howard, Cheng & Dubovikov and Canuto, Howard, Hogan, Cheng, Dubovikov & Montenegro [GISS mixing scheme] was extended to include the latitudinal dependence reported by Gregg, Sanford & Winkel of the input to the interior ocean turbulence field of energy from internal waves. The resulting latitude dependence was implemented in our module of code for the GISS vertical mixing scheme and tested in the global NCAR-CSM ocean model with 3 degree X 3 degree resolution and 25 levels in the vertical. With the latitude dependence, the background diffusivity decreases from approx. 0.1 sq cm/sec at midlatitudes to approx. less than 0.01 sq cm/sec at the equator. A significant improvement was seen in the tropical ocean, with tropical thermoclines being sharpened in agreement with the requirements of observational studies and the needs of ENS0 modeling. At the same time global measures nf performance such as the meridional overturning and northward heat transport were not adversely affected. Results were presented at the 2004 Layered Ocean Modeling meeting and a paper has been prepared and submitted to Geophysical Research Letters.

Source record↗
NASA NTRSDate not supplied

AMOC Stability in GISS-E2-1-G: A Case of Stochastic Bifurcation

A 10-member ensemble simulation using the NASA GISS-E2-1-G climate model shows a clear bifurcation in the Atlantic Meridional Overturning Circulation (AMOC) strength under the SSP2-4.5 future scenario, leading to 8 stable AMOC-on and 2 stable AMOC-off climate states after 400 years of integration, despite identical forcing of each ensemble member. Ocean models have previously shown a tipping point where sufficient forcing (e.g. by freshwater inputs) can shut down the AMOC. A variety of fully coupled models have demonstrated this, either through hosing experiments or increased precipitation and warming at high latitudes due to increased concentrations of greenhouse gases. In the GISS simulations, there are no external freshwater perturbations. The bifurcation arises freely in the coupled system and is the result of stochastic variability associated with sea-ice transport and melting in the Irminger Sea following a slowing of the GHG concentration increase at the end of the twenty-first century. We believe this is the first time that a CMIP-class model has shown such a bifurcation across an initial condition ensemble.

GISS ModelE2.1↗
NASA NTRS2001

The Low-Frequency Variability of the Tropical Atlantic Ocean

Upper ocean temperature variability in the tropical Atlantic is examined from the Comprehensive Ocean Atmosphere Data Set (COADS) as well as from an ocean model simulation forced by COADS anomalies appended to a monthly climatology. Our findings are as follows: Only the sea surface temperatures (SST) in the northern tropics are driven by heat fluxes, while the southern tropical variability arises from wind driven ocean circulation changes. The subsurface temperatures in the northern and southern tropics are found to have a strong linkage to buoyancy forcing changes in the northern North Atlantic. Evidence for Kelvin-like boundary wave propagation from the high latitudes is presented from the model simulation. This extratropical influence is associated with wintertime North Atlantic Oscillation (NAO) forcing and manifests itself in the northern and southern tropical temperature anomalies of the same sign at depth of 100-200 meters as result of a Rossby wave propagation away from the eastern boundary in the wake of the boundary wave passage. The most apparent association of the southern tropical sea surface temperature anomalies (STA) arises with the anomalous cross-equatorial winds which can be related to both NAO and the remote influence from the Pacific equatorial region. These teleconnections are seasonal so that the NAO impact on the tropical SST is the largest it mid-winter but in spring and early summer the Pacific remote influence competes with NAO. However, NAO appears to have a more substantial role than the Pacific influence at low frequencies during the last 50 years. The dynamic origin of STA is indirectly confirmed from the SST-heat flux relationship using ocean model experiments which remove either anomalous wind stress forcing or atmospheric forcing anomalies contributing to heat exchange.

Haekkinen, Sirpa↗
NASA NTRS2020

Decay of the Snow Cover Over Arctic Sea Ice From ICESat‐2 Acquisitions During Summer Melt in 2019

From the onset of melt in early June, corresponding declines in Ice, Cloud, and Land Elevation Satellite‐2 (ICESat‐2) freeboard and surface albedo can be seen over the entire Arctic sea ice cover. In the 2019 summer, area‐averaged freeboard decreased from 34 cm prior to melt to a minimum of 12 cm in August while the area‐averaged albedo decreased from ~0.7 to 0.38 for the same period. Calculations using ICESat‐2 freeboards and modeled ice thickness from Pan‐Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) give area‐averaged snow depths ranging from 17 cm prior to melt to 3 cm in August over seasonal ice and from 34 to 4 cm over multiyear ice. Mean rates of snow ablation (including evaporation) in mid‐June were as high as 2 cm/day, comparable to field records from other years. Increases in freeboard after mid‐August in the high latitude (>80°N) multiyear ice cover, north of the Greenland coast, are likely due to earlier freeze‐up and snow accumulation in these regions with shorter melt seasons.

R Kwok↗
NASA NTRS1999

Arctic Summer Ice Processes

The primary objective of this study is to estimate the flux of heat and freshwater resulting from sea ice melt in the polar seas. The approach taken is to examine the decay of sea ice in the summer months primarily through the use of spaceborne Synthetic Aperture Radar (SAR) imagery. The improved understanding of the dynamics of the melt process can be usefully combined with ice thermodynamic and upper ocean models to form more complete models of ice melt. Models indicate that more heat is absorbed in the upper ocean when the ice cover is composed of smaller rather than larger floes and when there is more open water. Over the course of the summer, floes disintegrate by physical forcing and heating, melting into smaller and smaller sizes. By measuring the change in distribution of floes together with open water over a summer period, we can make estimates of the amount of heating by region and time. In a climatic sense, these studies are intended to improve the understanding of the Arctic heat budget which can then be eventually incorporated into improved global climate models. This work has two focus areas. The first is examining the detailed effect of storms on floe size and open water. A strong Arctic low pressure storm has been shown to loosen up the pack ice, increase the open water concentration well into the pack ice, and change the distribution of floes toward fewer and smaller floes. This suggests episodic melting and the increased importance of horizontal (lateral) melt during storms. The second focus area is related to an extensive ship-based experiment that recently took place in the Arctic called Surface Heat Budget of the Arctic (SHEBA). An icebreaker was placed purposely into the older pack ice north of Alaska in September 1997. The ship served as the base for experimenters who deployed extensive instrumentation to measure the atmosphere, ocean, and ice during a one-year period. My experiment will be to derive similar measurements (floe size, open water, temporal change) using spaceborne SAR data obtained during the summer of 1998, and compare these results with an ocean and ice model of summer melt. Additional information is contained in the original.

Holt, Benjamin↗
NASA NTRS1999

Sensitivity of the Tropical Pacific Ocean to Precipitation Induced Freshwater Flux

We have performed a series of experiments using an ocean model to study the sensitivity of tropical Pacific Ocean to variations in precipitation induced freshwater fluxes. Variations in these fluxes arise from natural causes on all time scales. In addition, estimates of these fluxes are uncertain because of differences among measurement techniques. The model used is a quasi-isopycnal model, covering the Pacific from 40 S to 40 N. The surface forcing is constructed from observed wind stress, evaporation, precipitation, and surface temperature (SST) fields. The heat flux is produced with an iterative technique so as to maintain the model close to the observed climatology, but with only a weak damping to that climatology. Climatological estimates of evaporation are combined with various estimates of precipitation to determine the net surface freshwater flux. Results indicate that increased freshwater input decreases salinity as expected, but increases temperatures in the upper ocean. Using the freshwater flux estimated from the Microwave Sounding Unit leads to a warming of up to 0.6 C in the western Pacific over a case with zero net freshwater flux. SST is sensitive to the discrepancies among different precipitation observations, with root-mean-square differences in SST on the order of 0.2-0.3 C. The change in SST is more pronounced in the eastern Pacific, with differences of over 1 C found among the various precipitation products. Interannual variation in precipitation during El Nino events leads to increased warming. During the winter of 1982-83, freshwater flux accounts for about 0.4 C (approximately 10-15% of the maximum warming) of the surface warming in the central-eastern Pacific. Thus, the error of SST caused by the discrepancies in precipitation products is more than half of the SST anomaly produced by the interannual variability of observed precipitation. Further experiments, in which freshwater flux anomalies are imposed in the western, central, and eastern Pacific, show that the influence of net freshwater flux is also spatially dependent. The imposition of freshwater flux in the far western Pacific leads to a trapping of salinity anomaly to the surface layers near the equator. An identical flux imposed in the central Pacific produces deeper and off-equatorial salinity anomalies. The contrast between these two simulations is consistent with other simulations of the western Pacific barrier layer information.

Yang, Song↗
NASA NTRS1979

A large-scale numerical model of sea ice

The described large-scale sea ice model, which is capable of coupling with atmospheric and oceanic models of comparable resolution, simulates the yearly cycle of ice in both the Northern and Southern Hemispheres. Model results for the yearly cycle of sea ice thickness and extent in both the Arctic and the Antarctic are presented. Horizontally the model resolution is approximately 200 km, while vertically four layers - ice, snow, ocean, and atmosphere - are considered. Thermodynamic processes based on energy balances at the various interfaces and dynamic processes based on wind stress, water stress, Coriolis force, internal ice resistance, and the stress from the tilt of the sea surface are incorporated. It is assumed that the ice within a given grid square is of uniform thickness, although each square has a variable percentage of its area ice free.

Parkinson, C. L.↗
NASA NTRS2000

A Coupled Ocean General Circulation, Biogeochemical, and Radiative Model of the Global Oceans: Seasonal Distributions of Ocean Chlorophyll and Nutrients

A coupled ocean general circulation, biogeochemical, and radiative model was constructed to evaluate and understand the nature of seasonal variability of chlorophyll and nutrients in the global oceans. Biogeochemical processes in the model are determined from the influences of circulation and turbulence dynamics, irradiance availability. and the interactions among three functional phytoplankton groups (diatoms. chlorophytes, and picoplankton) and three nutrients (nitrate, ammonium, and silicate). Basin scale (greater than 1000 km) model chlorophyll results are in overall agreement with CZCS pigments in many global regions. Seasonal variability observed in the CZCS is also represented in the model. Synoptic scale (100-1000 km) comparisons of imagery are generally in conformance although occasional departures are apparent. Model nitrate distributions agree with in situ data, including seasonal dynamics, except for the equatorial Atlantic. The overall agreement of the model with satellite and in situ data sources indicates that the model dynamics offer a reasonably realistic simulation of phytoplankton and nutrient dynamics on synoptic scales. This is especially true given that initial conditions are homogenous chlorophyll fields. The success of the model in producing a reasonable representation of chlorophyll and nutrient distributions and seasonal variability in the global oceans is attributed to the application of a generalized, processes-driven approach as opposed to regional parameterization and the existence of multiple phytoplankton groups with different physiological and physical properties. These factors enable the model to simultaneously represent many aspects of the great diversity of physical, biological, chemical, and radiative environments encountered in the global oceans.

Gregg, Watson W.↗