**2. Data and methodology**

124 Remote Sensing of Biomass – Principles and Applications

The merging of ocean color datasets with other satellite measurements providing information of ocean dynamics has potential benefits to the understanding of some aspects of the coupling between fluid driven processes and plankton dynamics. In this regard, altimetry satellite data allows the characterization of sea level anomaly (SLA), containing information on the geostrophic current fields, mesoscale eddy variability and changes in the thermocline depth (Le Traon et al., 1998; Stammer, 1997). Lehahn et al. (2007) and Leterme & Pingree (2008) investigated the effect of the geostrophic velocity derived from satellite SLA on the redistribution of satellite CHL. Also, the impact of mesoscale eddies on the spatial

Further insight into the basin-scale dynamics affecting CHL and SLA, as an indicator of changes in the thermocline depth, in the equatorial Pacific was provided by Wilson & Adamec (2001). Correlations between CHL and SLA data using empirical orthogonal function (EOF) analysis show different responses associated with El Niño-Southern Oscillation phases. In the global ocean, direct correlations between CHL and SLA are predominately negative as lower SLA implies thermocline weakening and consequent mixing of the water column, which results in increased nutrient flux to the surface layer and phytoplankton biomass enhancement (Wilson & Adamec, 2002). However, there are areas in all ocean basins where positive correlations suggest that CHL is affected by processes other than thermocline variations. For example, Uz et al. (2001) found positive correlations between satellite CHL and SLA associated with the propagation of Rossby waves. These studies exemplify how multiple satellite observations are used to understand basin-scale dynamics and their impacts on the ocean phytoplankton biomass variability. Following these works, Jordi et al. (2009) used the singular value decomposition (SVD) analysis of the cross-covariance matrix between satellite CHL and SLA to analyze the regional scale dynamics in the northwestern Mediterranean Sea. Their results highlight the role of the water mass transported by the regional circulation on the variability of the phytoplankton biomass. The SVD analysis may be superior to EOF analysis in identifying correlated spatial

In the Mediterranean Sea, a semi-enclosed marginal sea with limited geographical dimensions (Fig. 1), ocean color data reveals that oligotrophic conditions prevail for most of the year (D'Ortenzio et al., 2002). Biological production is mainly regulated by physical processes enhancing nutrient supply to surface layers and by allochtonous inputs from the continents and the atmosphere (Barale et al., 2008). Satellite ocean color data in the Mediterranean Sea has demonstrated dominance of the seasonal cycle in phytoplankton biomass (Bosc et al., 2004). With some regional variations, the typical temperate-latitude cycle with maximum biomass in late winter-spring and minimum during summer stratified conditions occurs throughout most of the basin (Bricaud et al., 2002). Inter-annual variations in CHL concentrations are also noticeable both at a local scale and over the whole basin, and

Complementarily, altimetry satellite data shows that the sea level variability in the Mediterranean is a complex combination of a wide range of spatial and temporal scales (Cazenave et al., 2001; Larnicol et al., 2002). Besides the marked seasonal cycle in SLA caused by the steric effect, important intra- and inter-annual signals are observed associated with permanent or transitory oceanographic structures such as frontal currents and mesoscale eddies (Jordi & Wang, 2009; Pujol & Larnicol, 2005). The multiple driving forces including the ocean–atmosphere interaction, the phenomenology of the deep water

patterns of CHL has been analyzed by Siegel et al. (1999, 2008).

patterns between pairs of spatial time series (Bretherton et al., 1992).

have been related to climatic fluctuations (D'Ortenzio et al., 2003).
