Introduction

Measuring ocean surface winds

This product provides the scientific community with easy-to-use synoptic gridded fields of surface wind over the ocean, as observed from space. The surface wind is a key parameter for the determination of many ocean-atmosphere interaction parameters such as air-sea latent and sensible heat fluxes, air-sea transfer rate of carbon dioxide, momentum flux and wind stress on the surface layer of the ocean. The wind vectors (speed and direction) can be retrieved from space using a scatterometer. This active microwave instrument measure the radar backscatter of the ocean surface, from which the wind vectors can then be estimated using semi-empirical models and inversion/dealiasing algorithms. The observation pattern of these sensors corresponds to a band, or swath, relative to the satellite track (the virtual line on the Earth's surface followed by the satellite nadir). The duration necessary to cover the whole Earth's surface is related to the orbital characteristics of the satellite and the swath width of the sensor.

The CERSAT has been archiving and distributing the swath data from all scatterometers for more than 10 years, starting with ESA's AMI-Wind, onboard ERS-1 and ERS-2, and then - as a mirror site of JPL/PO.DAAC - with NASA's NSCAT and QuikSCAT, onboard respectively ADEOS-1 and QuikSCAT.

Computing global mean fields

Surface winds averaged and mapped over a regular grid with a given space resolution are much more easier and practical to handle than swath raw products, since they avoid the user to cope with the sensor's sampling pattern. Therefore a great deal of effort has been devoted to develop a method enabling to produce gridded wind fields.

Because of the observation pattern of satellite sensors (sequential acquisition along the sensor swath), averaging where overlap occurs and interpolating over the gaps is necessary when mapping the sample data on a grid within a given time range (as short as possible to obtain the finest temporal resolution). In order to reconstruct gap-filled and averaged synoptic fields from discrete observations over each time period, a statistical interpolation is performed; this statistical interpolation is a minimum variance method related to the Kriging technique widely used in geophysical studies. The analysis scheme is based on the determination of the spatial and temporal structure functions of estimated variables (magnitude, zonal and meridional components). The estimators of each variable are then determined and analyzed by the objective method. The standard errors of the parameters estimated by this method are also computed.

This work resulted in the mean wind fields product, generated for each scatterometer on their complete lifetime at different time and space resolution, and thus making available long-term homogeneous and consistent temporal series of wind-related parameters (e.g. 10 year long in the case of the ERS mission).

Go to the content section for more details on the data provided within this product. Much more details on scatterometers, objective analyse and validation work can be obtained in the documents section.