How Does Operational Oceanography Forecast the Oceans

The oceans can be divided in a large number of small cells that interact. The laws of physics related to the dynamic of fluids govern the interactions between these cells. These cells will have tracer properties like: temperature and salinity, together with dynamical characteristics governing exchanges between cells such as the velocity of the water and many others. If it is possible to define the properties of all the cells at an initial instant, numerical models may be employed to predict the evolution in time of these properties. Based upon data acquired at frequent intervals, such models are able to predict the evolution by simulating the behavior of these cells, under constraints provided by the law of physics, by the initial ocean state characteristics provided by measurement data, and by boundary conditions like the geography of the coast and the intensity and direction of winds or currents.

One of the most important parameters to monitor and predict is how the dynamics of the ocean will evolve. This relies on characterization of the geographical distribution and strength of currents and how they will evolve. By redistributing water around the globe, ocean currents distort the ocean surface from the equilibrium position that the sea-surface would adopt in case the whole ocean would be at rest. This theoretical surface is called the 'Geoid' and it constitutes the absolute reference or equipotential surface of the Earth's gravity field. Any differences between the local water level and the reference Geoid represent geopotential heights. These so-called "anomalies" in sea-level may be mapped, and the shape contours or slope in sea-level (i.e. sea surface topography) may be used to determine the movement of the ocean at any point, and thus the ocean currents. This implies that the fundamental observations required to predict the dynamics of the ocean are precise observations of local sea-level anomalies. Today, instruments carried by satellite radar altimeters provide measurements of the local sea level height, while their difference from the local geoid allows sea-level anomalies and thus dynamic topography of the ocean to be calculated.

Radar altimeters determine the sea-surface height and sea-level anomalies by sending a radar signal to the ocean and measuring the time needed for the signal to return. This delay gives the distance from the satellite to the water level. These distances can be converted into sea-level anomalies, or 'dynamic topography' if the absolute position of the satellite with respect to the Earth ellipsoid reference frame and/or Geoid is known and if the total delay is corrected for atmospheric effects—water vapor contents—that also produce delays.

Satellites are excellent tools with which to provide a systematic, homogeneous and global data set, and provided that a sufficiently large number of radar altimeters is available it is possible to initialize all the cells of the ocean circulation models with their corresponding sea level anomaly data. If the dataset is comprehensive and sufficiently timely, and if the data are of good quality and if the physics of the model is correct, the prediction of the models will be reliable. Data on ocean temperature, salinity and biological activity also provide supplementary information that can be

Range

Orbit

Range

Altitude

^ Atmospheric Effects

^ Atmospheric Effects

Topography is directly related to ocean currents

Fig. 3 Satellite orbit, satellite sea-level range and dynamic topography. The Dynamic

Fig. 3 Satellite orbit, satellite sea-level range and dynamic topography. The Dynamic

Ellipsoid

incorporated to the models. The ocean models also require meteorological data: winds, air temperature, air pressure and others to provide the basic forces with which to drive the dynamics of the interaction between the ocean the atmosphere. Good quality atmospheric data improves the quality or skill of ocean prediction, whilst by the same token good ocean data may help to improve the quality of Atmospheric predictions. This increment on the accuracy of atmospheric predictions will be a supplementary social and economic advantage to be derived from operational oceanography.

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