Titre de la thèse : Long-term blended analysis of SSS in the northern Indian Ocean from in situ and multi-sensor satellite data
Encadrants : Clément de Boyer Montégut , Nicolas Reul, Jean Tournadre et Jérôme Vialard (LOCEAN)
Financements : demi bourses CNES et région Bretagne
Date de début : 01/10/2019
The complex surface salinity variations in the northern Indian Ocean remain difficult to understand. This PhD aims to take advantage of the synergy between existing sea surface salinity data (satellite and in-situ) to investigate different mechanisms of inter-annual salinity variability in this zone over a long-term period. Space-borne radiometric instruments (L-band), designed to remotely monitor salinity, have only been available since the launch of SMOS in 2009. Thus, for long-term studies it is necessary to reconstruct salinity time series from data measured by older satellite which were not designed for this purpose (e.g. AMSR-E).
We will first focus on developing an algorithm to reconstruct salinity from the C and X-band products of AMSR-E. It will be based on the common period between AMSR-E data (May 2002 – October 2011) and the ESA-project Climate Change Initiative dataset (CCI, 2010-today). This will extend the existing remotely sensed SSS database by 8 years prior to SMOS. Once the database restored, a study of processes susceptible to dictate the inter-annual variability of the sea surface salinity will be performed. For this, we will focus on the Bay of Bengal over the period from 2002 to 2019.