Model Applications

Initially, most model applications were targeted toward understanding what physics drives the ocean circulation. While this remains a topic of interest, much of the more recent development effort has focused on areas of model application and coupling.

Although the use of atmospheric models for forecasting weather conditions has been around for many years, the development of ocean forecasts has lagged behind. This is in part due to the small number of observations available for initializing and validating ocean models. While many industries such as shipping and ocean oil production, as well as the military depend on information about ocean currents, they require forecasts that include information about mesoscale, or small eddy structures that can have large effects on local currents. These types of forecasts require accurate initial model conditions that include current features that may be less than 5-10 km in size. As a result, ocean forecasting has grown in tandem with the fields of satellite oceanography and methods to blend data into model simulation, 'data assimilation'. Satellites provide frequent information such as sea-surface temperature and surface elevation over broad and also high-resolution spatial scales that can be used to constrain an ocean model simulation through data assimilation techniques. Essentially, these techniques consist of forcing the ocean model to mimic the real world through pushing the ocean model toward the satellite or in situ data despite errors in the forcing information and simulated physics.

An example of the Cyprus Coastal Ocean Model Real Time Ocean Forecast (CYCOFOS) (http://www.oceano-graphy.ucy.ac.cy) is given in Figure 3. This model is based on the POM, and is initialized from a larger domain ocean model that assimilates both satellite and in-water data and also provides lateral boundary conditions. Output is used for predicting oil and other pollutant spill trajectories, as well as for managing marine resources.

Models used for seasonal to interannual (such as El Nino) or climate timescale forecasting share many features common to short-term ocean prediction, including a dependence on data from water platforms such as drifters or temperature and current meter moorings as well as from satellites. However, they have a much greater dependence on effective integration between the atmospheric and radiative models used to force the ocean surface, ice models, and the land surface models that provide a lower boundary condition for the atmosphere over land. Each of these components is a complex system alone. When they interact, the results can be unexpected and difficult to ascribe to any single process. One example of the many processes linked together in a coupled climate model is shown in Figure 4 from the Coupled Climate System Model (CCSM). Here, the ocean is just one of many nonlinear systems interacting to modulate the climate of the earth system.

Increasing recognition of the importance of pelagic ecosystem dynamics in regulating climate processes, combined with the need for coupled models that can be used to help guide management decisions in coastal waters, has also led to a growing emphasis on integrating ecosystem models into existing hydrodynamic model codes. Each of the major open source modeling systems discussed above (POM, ROMS, HYCOM, MOM) now comes with integrated tracer advection algorithms and a simple coupled NPZD-type ecosystem model (see Marine Models and Lake Models), at a minimum. Some of these modeling packages even offer multiple ecosystem model options. Some studies suggest that ecological models, and particularly the absorption of light by phytoplankton populations, can affect the model circulation particularly in the tropical oceans. The ecosystem also affects the ocean carbon system, influencing the rate at which the ocean absorbs carbon dioxide from the atmosphere, and feeds back to the global climate.

Recent studies suggest that the underlying circulation or hydrodynamic model that provides an environment for biology is the greatest factor differentiating different models (see Marine Models). Thus, an emphasis on improving the underlying physics will continue to be

Surface temperature on date: 04/02/2007 00:00

Surface temperature on date: 04/02/2007 00:00

18.21

17.75 17.28 16.82 16.35 15.89 15.42 14.96 14.49 14.03 13.56

LONGITUDE 35° 0'

18.21

17.75 17.28 16.82 16.35 15.89 15.42 14.96 14.49 14.03 13.56

Figure 3 A 4-day forecast from (CYCOFOS), showing surface ocean temperature (°C) around Cyprus in the Mediterranean Sea.

Incoming solar energy

Outgoing heat

... , energy Transition from

Cirrus clouds

Precipitation and evaporation

Incoming solar energy

Outgoing heat

... , energy Transition from

Cirrus clouds

Precipitation and evaporation

Figure 4 A schematic illustrating the different components of the CCSM model system, one of several earth system models.

critical to improving the success ofcoupled model studies. The increasing trend in interdisciplinary modeling approaches seems likely to continue as the demand for assessments of the impacts of anthropogenic effects in estuarine, coastal, and open ocean systems becomes more acute.

10 Ways To Fight Off Cancer

10 Ways To Fight Off Cancer

Learning About 10 Ways Fight Off Cancer Can Have Amazing Benefits For Your Life The Best Tips On How To Keep This Killer At Bay Discovering that you or a loved one has cancer can be utterly terrifying. All the same, once you comprehend the causes of cancer and learn how to reverse those causes, you or your loved one may have more than a fighting chance of beating out cancer.

Get My Free Ebook


Post a comment