CORRELATIONS BETWEEN ALTIMETRIC SEA-SURFACE HEIGHT AND RADIOMETRIC SEA-SURFACE TEMPERATURE IN THE SOUTH ATLANTIC

Citation
Ms. Jones et al., CORRELATIONS BETWEEN ALTIMETRIC SEA-SURFACE HEIGHT AND RADIOMETRIC SEA-SURFACE TEMPERATURE IN THE SOUTH ATLANTIC, J GEO RES-O, 103(C4), 1998, pp. 8073-8087
Citations number
43
Categorie Soggetti
Oceanografhy,"Geosciences, Interdisciplinary","Astronomy & Astrophysics","Geochemitry & Geophysics","Metereology & Atmospheric Sciences
Journal title
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
ISSN journal
21699275 → ACNP
Volume
103
Issue
C4
Year of publication
1998
Pages
8073 - 8087
Database
ISI
SICI code
2169-9275(1998)103:C4<8073:CBASHA>2.0.ZU;2-2
Abstract
In the last decade, satellite altimetric measurements of sea surface h eight (SSH) and infrared radiometric measurements of sea surface tempe rature (SST) have provided a wealth of information about ocean circula tion and atmosphere-ocean interactions. SSH is a depth-integrated quan tity dependent upon the temperature and salinity structure of the wate r column and on the depth independent barotropic contribution. SST fro m infrared radiometers is a surface parameter representing the tempera ture of the top few microns of the ocean surface. Hence any relationsh ip between SST and SSH provides dynamical information about the coupli ng between the ocean surface and subsurface. It also offers a promise of new techniques such as interpolating SSH data using SST and of impr oved calculations of eddy kinetic energy. We use SST data from the alo ng-track scanning radiometer on ERS-1 and SSH data from the TOPEX/POSE IDON instrument to examine the relationship between SST and SSH anomal ies within the South Atlantic region for 1993 and 1994. We find that p ositive (approximate to 0.2-0.6) spatial cross correlations between SS T and SSH anomalies at zero lag are present throughout the region at l arge scales (wavelengths >1000 km). Small-scale correlations, however, are high (approximate to 0.7) only in areas associated with fronts an d mesoscale variability. These small-scale correlations are seasonal, being strongest in winter and weakest in summer. We discuss the applic ation of these correlations to various techniques requiring the synerg istic use of SSH and SST data.