The Full Picture

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Modelling the ocean – short-term ocean prediction

Much of the focus on ocean observing systems has been

on the modelling of the oceanic environment in order to

provide long-term predictions of change, even to the

extent of climate trends. However the ever-increasing

network of marine observing platforms, fixed and free-

drifting, is just as valuable as input to the numerical

models which predict what might be referred to as ‘ocean

weather’, which is to say, changes in the ocean environ-

ment over periods of a few hours to several days.

Obviously this data has to reach the modelling centres

as soon as possible after the observation time.

Fortunately most oceanographers recognized the benefit

of getting data in real-time mode some time ago. With

a fixed platform such a wave-measuring buoy or a tide

gauge one can at least rectify any fault before too much

valuable data has been lost. Even in the case of drifting

platforms new generation satellite data communication

is two-way, making it possible to activate backup sensors

or program transmission changes.

A lot of additional responsibilities tend to be given to

National Meteorological Services (NMS) which are not

directly related to meteorology. Indeed, some have no

relation to meteorology at all. This is simply because

NMS are often the only national service which operates

day and night, 365 days a year. An example of the former

is the prediction of ocean waves. Although surface winds

play a very important role in their generation, they are

essentially still in the realm of the oceanographer. The

provides an important platform for the deployment of buoys for the

Global Drifter Program as well as the Argo project. SAWS operates

manned weather stations on Gough and Marion Islands, where mete-

orologists record surface data and do atmospheric soundings twice

per day.

Observing the ocean from space

The value of satellite-based remote sensing of the earth cannot be

overemphasized, particularly over the ocean where in situ data may

be very sparse. Low earth orbiting satellites measuring upwelling radi-

ation in the visible, IR and far IR portions of the electromagnetic

spectrum provide information on a variety of ocean features, at an

ever-improving resolution. Particularly important however are those

sensors, active and passive, which make use of the microwave portion

of the spectrum to essentially bypass the blocking effects of cloud

cover and precipitation, and to also continue observations in the dark.

Typical examples of satellite-derived ocean surface parameters are

ocean colour (chlorophyll), sea surface temperature, wind vectors,

wave height and sea level. The synthetic aperture radar is a particu-

larly versatile satellite-borne sensor which provides very high

resolution imagery of sea ice and other ocean features, as well as

wave spectra. A good example of the value of satellite data is the

measurement of sea ice in the Arctic region, which has revealed a

marked downward trend in the residual summer coverage. This

could only have been possible with regular satellite passes (over a

period of three decades) and the use of a passive microwave sensors.

However, there is still a need for in situ data, which is used to

develop and improve the algorithms that turn the raw data from the

satellite sensor into useable information.

The Envisat satellite of the European Space Agency. This giant satellite (10x4x4 metres) boasts a multitude of EO sensors including an Advanced

Synthetic Aperture Radar (ASAR)

Image: ESA

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