Geoscience Reference
In-Depth Information
key land-ocean and atmosphere-ocean interaction processes that occur within the marine
hydrological cycle. In particular, SMOS with its ocean mapping capability provides
observations across the world's largest tropical ocean fresh pool regions, and we discuss
from intraseasonal to interannual precipitation impacts as well as large-scale river runoff
from the Amazon-Orinoco and Congo rivers and its offshore advection. Synergistic multi-
satellite analyses of these new surface salinity data sets combined with sea surface tem-
perature, dynamical height and currents from altimetry, surface wind, ocean color, rainfall
estimates, and in situ observations are shown to yield new freshwater budget insight.
Finally, SSS observations from the SMOS and Aquarius/SAC-D sensors are combined to
examine the response of the upper ocean to tropical cyclone passage including the potential
role that a freshwater-induced upper ocean barrier layer may play in modulating surface
cooling and enthalpy flux in tropical cyclone track regions.
Keywords Sea surface salinity
SMOS satellite
Passive microwave remote
sensing
Oceanic freshwater cycle
1 Introduction
Salinity is known to play an important role in the dynamics of the ocean's thermohaline
overturning circulation and in large-scale atmosphere-ocean climate signals such as the El Nino
Southern Oscillation (ENSO), and is the key freshwater tracer within the oceanic component of
the global hydrologic cycle, a branch that comprises most of the global precipitation and
evaporation as well as the river runoff (Schmitt
2008
). Multi-decadal sea surface salinity (SSS)
trends have been documented in tropical and high latitudes and associated with signatures of
evaporation or precipitation variation that are consistent with global warming scenarios (e.g.,
Dickson et al.
2002
; Gordon and Guilivi
2008
;Morrowetal.
2008
; Cravatte et al.
2009
;Yu
2011
;Duracketal.
2012
;Terrayetal.
2011
). These studies highlight the need for well-sampled
SSS time series both for monitoring the change and to improve the basic understanding of the
respective roles of the atmosphere and ocean dynamics, thermodynamics, air-sea interaction,
and land-ocean interaction in the global water cycle context.
Our basic knowledge of the global SSS distribution is derived from the compilations of
all available oceanographic data collected over time (e.g., Boyer and Levitus
2002
). The
SSS in situ observing system has expanded significantly during the last decade due mostly
to the full deployment of the Argo profiling float array and now provides a monthly SSS
estimate on a grid of roughly 300-400 km
2
. Notwithstanding these recent gains, this
sampling density is still too sparse to resolve climatologically important intraseasonal,
seasonal, and interannual to decadal signals at the 300-km spatial scale within which SSS
is known to vary significantly (Lagerloef et al.
2010
). The recent launches of the ESA/Soil
Moisture and Ocean Salinity (SMOS, see Kerr et al.
2010
; Font et al.
2010
) and NASA/
Aquarius SAC-D (Lagerloef et al.
2008
; Lagerloef
2012
) mission satellites represent
contributions toward filling this gap using passive microwave remote sensing.
Salinity remote sensing is based on the measurement of sea surface microwave emission at
the lower end of the microwave spectrum and from a surface skin layer having a thickness of
O(1 cm). This emission depends partly on the dielectric constant of sea water, which in turn
can be related to salinity and temperature. Thus, given sea surface temperature (SST), theory
predicts some ability to invert SSS information. In practice, however, numerous additional
external factors (extra-terrestrial sources, atmosphere, ionosphere, and surface roughness)
also contribute to the satellite-observed emission, and these must be corrected to allow
