Estimates of sea surface nitrate concentrations from sea surface temperature and chlorophyll concentration in upwelling areas: A case study for the Benguela system

• Published in: Remote sensing of environment 2008-06, Vol.112 (6), p.3173-3180
• Main Authors: Silió-Calzada, Ana, Bricaud, Annick, Gentili, Bernard
• Format: Article
• Language: English
• Subjects: Animal, plant and microbial ecology; Applied geophysics; Benguela; Biological and medical sciences; Earth sciences; Earth, ocean, space; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Internal geophysics; Marine; Nitrate; Satellite; Sea surface temperature; Teledetection and vegetation maps; Upwelling
• ISSN: 0034-4257; 1879-0704
• DOI: 10.1016/j.rse.2008.03.014

The knowledge of nitrate fields at global or regional scales in the ocean is fundamental for the study of oceanic biogeochemical processes, particularly those linked to new primary production. The estimate of nitrate concentrations from space is generally based on empirical inverse relationships between sea surface temperature (SST) and nitrate concentrations. These relationships, however, are often highly variable spatially and temporally, and hardly applicable to large areas ( i.e., larger than a few degrees in latitude). In this paper we propose a new approach specifically developed for areas influenced by upwelling processes. It relates the nitrate concentration to the difference between SST and the estimated temperature of the upwelled water (variable with latitude and season), δ T, which is an indicator of the time elapsed since upwelling. This approach is tested for the Benguela upwelling system, and algorithms are developed using in situ data provided by the World Ocean Database 2005 of the NOAA-NESDIS-National Oceanographic Data Center. The results reveal a significant improvement compared to the NO 3–SST relationships, and a single algorithm can be applied to the whole upwelling area (15 to 35°S). Further improvement is gained by coupling this approach with a method that derives sea surface nitrate concentrations from SST and surface chlorophyll a concentration using multiple regression analyses, as proposed by Goes et al. [Goes, Saino, Oaku, Jiang, (1999). Method for estimating sea surface nitrate concentrations from remotely sensed SST and chlorophyll a: A case study for the North Pacific Ocean using OCTS/ADEOS data. IEEE Transactions on Geoscience and Remote Sensing, 37, no. 3 II, 1633–1644].