The conditions which reign over the surface of the oceans are crucial for the climate, even for that which reigns at the other end of the planet. They are also an open door onto the physics of the oceans. But the majority of observations in physical oceanography are carried out by satellite. Thus what is to be done when clouds come between the satellites and the oceans? Aida Alvera-Azcárate has validated a statistical method which allows this cloud cover to be pierced.

Are we always aware of the influence the conditions which reign at the surface of the oceans at the other end of the planet can have on our climate? In particular the temperature of the oceans’ surfaces is one of the most important hydrodynamic parameters: it influences the atmosphere and the climate. It is for example the surface temperature at the Tropics which conditions the Gulf Stream current, and through it the climate in Europe. It is because the Gulf Stream has its source in the Tropics that the Winters in Europe are milder than those of the United States, which is on the same latitude.

Scientists have an interest in the oceans’ surface in multiple ways. It is the most variable section of the oceans and thus contains much more information than a layer situated at depths of 1000m. It also has more influence on the climate than the oceans’ interiors. Finally, and in a more practical manner, satellites only have access to the surface of the oceans. Nevertheless measurements taken at the surface allow deeper layers to be scanned, thanks to hydrodynamic models of the oceans built on the basis of the laws of physics.

The continuous observation of the oceans’ surface by different satellites generates a quantity of data whose management is a heavy task, even when dynamic models are used. Models, empirical ones in this case, can be used beforehand in the process to reduce the quantity of data. The principal components (EOF) methodology has for example been much used for a hundred years or so in every scientific field. It offers the advantage of being able to reduce a large quantity of data to several very simplified functions.

To understand its principle let us consider a basin filled with water whose surface is oscillating. To describe this surface wave we can note the position of every point at every moment, which rapidly generates a colossal amount of data. On the basis of this it is possible to find simple and empirical functions which allow the system to be described simply: a spatial function which gives the form of the wave at a given moment and a temporal function which characterises the variation of the wave over time. The determining of these functions then allows one to bypass an accumulation of data.