Ocean surface salinity in the tropical
oceans using satellite derived OLR
Subrahmanyam
Bulusu
University of South
Carolina
Abstract:
The
objective of this research work is to develop algorithms and estimate
sea surface salinity (SSS) from satellite measurements of Outgoing
Longwave Radiation (OLR) over the tropical oceans. This new technique
was applied to the tropical Indian Ocean, with a set of algorithms
based on the inter-relationships between OLR, the Effective Oceanic
Layer (EOL), climatological SSS (World Ocean Atlas 2001; WOA01) and
freshwater flux (P-E). The results for the tropical Indian Ocean showed
higher correlation coefficients for the relationships between OLR vs.
EOL, EOL vs. WOA98 SSS and OLR vs. P-E. The former relationship couples
the atmospheric convection (OLR) and the geopotential thickness of the
near-surface stratified layer (EOL). The estimated SSS at 2.5x2.5°
grid on monthly scale was close to the WOA98 SSS with lesser
differences (within ±0.5 psu) away from the coastal region. The
estimated SSS also agrees reasonably with the observed SSS along the
transindian zonal sections occupied during World Ocean Circulation
Experiment (WOCE) and also other sections. The SSS differences brought
out clearly the impact of the strong 1997-98 El Niño on the
rainfall in the southeastern Indian Ocean and the eastern equatorial
region, wherein the salinity anomalies (estimated SSS minus WOA98 SSS)
were large and positive. Using 25 years (1979-present) of daily OLR
data at 2.5x2.5° grid and the algorithms, the SSS was estimated in
the tropical Indian Ocean. It was found that consideration of the
mixing and advection processes using the Hybrid Coordinate Ocean Model
(HYCOM) was necessary for the refinement of estimated SSS. This new
technique of obtaining SSS from OLR would further be applied to the
time series upper ocean temperature and salinity measurements in the
tropical oceans, and the results would be discussed. This information
would be useful for further studies in the other tropical Oceans aiming
on coupled models, El Niño-Southern Oscillation forecast models
and Ocean Global Circulation Models or regional scale circulation
models.