Climate studies need long-term data sets of homogeneous quality, in order to discern trends from other physical signals present in the data and to minimise the contamination of these trends by errors in the source data. Satellite data have proved as very valuable, and we count now on more than 25 years of data for variables like sea surface temperature (SST). In order to obtain data sets valid for climate research, it is necessary to develop or improve techniques to homogenise data coming from different satellites, as biases exist between them due to their technical characteristics and the changing physical properties of the measured environments.

The GHER of the University of Liège (Belgium) coordinates the project BESST (inter-sensor Bias Estimation in Sea Surface Temperature fields) that will start on January 2012. We seek a person at the post-doc level that will study the biases between multiple SST satellite sensors.

Statistical techniques, based on the principal mode decomposition approach, will be used to reconstruct missing data in SST bias fields.

The spatio-temporal variability of the inter-sensor bias fields will be analysed to better understand the nature of these biases.

Candidates must have a PhD in Oceanography, Remote Sensing (applied to the environment), Physics, or related field. Programming skills are required (such as Matlab/Octave or Fortran), as well as a good level of English (oral and written). This full-time position has an initial duration of 1 year, starting as soon as possible, and is potentially renewable 1 additional year.

Interested persons are invited to send an application dossier consisting of an application letter, a curriculum vitae with full contact information, copy of PhD diploma, and full contact information of 3 professional references to Aida Alvera-Azcarate (a.alvera@ulg.ac.be).

The review of applications will start immediately until the position is filled.

More information about our group is available at:
http://modb.oce.ulg.ac.be/
http://modb.oce.ulg.ac.be/wiki