Geoscience Reference
In-Depth Information
accurate ocean salinity estimates. The SMOS and Aquarius sensors are both ocean micro-
wave radiometers operating at a frequency of *1.4 GHz (L-band, wavelength of 21 cm), a
band chosen for the relatively strong sensitivity to change in salinity and because this is a
transmission-free, or protected, frequency. An additional and important benefit for this choice
is minimization of atmospheric signal contributions.
Based on the observed SSS variability and need to better resolve it, the satellite missions
aim to produce salinity estimates with an accuracy of 0.1-0.2 over the so-called Global
Ocean Data Assimilation Experiment scales of 100 km, 1 month or 200 km, and 10 days.
This is a challenging objective for several reasons. First, the sensitivity of L-band
brightness temperatures to variations in SSS is on average 0.5 degK per salinity scale. This
sensitivity is very weak given that spatial and temporal variability in open ocean SSS does
not exceed several units and that the instrument noise is typically 2-5 degK. Note that
salinity computations are based on the Practical Salinity Scale PSS-78 and reported with no
units (United Nations Educational, Scientific and Cultural Organization
1985
). Second,
there are many geophysical sources of brightness at L-band that corrupt the salinity signal,
and correction models for these factors have uncertain accuracy. Moreover, the technical
approach developed in order to achieve adequate radiometric accuracy and spatiotemporal
resolution for SMOS is polarimetric interferometric radiometry, the first such space-borne
system. The complex SMOS image reconstruction data processing includes contamination
by different errors and induces residual inaccuracies in SSS estimates. Finally, there is
significant radio frequency interference emanating from sources along the many coastlines
that contaminate data collected over many ocean regions. Nevertheless, much work at ESA
SMOS level 2 expert centers and the CNES/IFREMER Centre Aval de Traitement des
Donn´es SMOS (CATDS) has addressed these issues, leading to the first global satellite
SSS estimates (Font et al.
2013
; Reul et al.
2012
; Boutin et al.
2012a
).
Two examples of monthly composite SMOS SSS maps are shown in Fig.
1
. They show
salient basin scale features, including the elevated salinity in the Atlantic relative to the
other basins, and the general correspondence of lower SSS with known river runoff and
tropical precipitation regions. SMOS data validation efforts using in situ observations
reveal an overall SSS accuracy on the order of 0.3 (Boutin et al.
2012a
; Reul et al.
2012
;
Banks et al.
2012
; Font et al.
2013
), but with degraded quality at high latitudes partly
because of reduced sensitivity in colder waters. While further improvements are in pro-
gress, many interesting features of the global SSS could be already evidenced.
This paper reviews preliminary results addressing several key applications of these new
satellite SSS data. Given the reduced SMOS sensitivity in cold waters, the focus is on tropical
ocean data where SMOS measurements have proven to be the most accurate. We also attempt
to highlight combined use of other satellite and in situ observations (altimetry, SST, ocean
color, river discharge, evaporation, and precipitation). It is shown that these new data are
proving useful in the monitoring of intraseasonal to interannual variability across major
tropical freshwater pools of the world ocean. SMOS-detected SSS freshening events within
intense precipitation zones (e.g., the Inter Tropical Convergence Zone) are also shown to
provide promising new information related to the ocean surface response to rainfall. Finally,
SMOS SSS data are used to address interactions between wind-driven phenomena, such as
upwelling and tropical cyclones (TCs), and some of the world's largest fresh pools. The data
sets used in these cases are described in Sect.
2
. SMOS monitoring capabilities for the major
tropical river plumes are given in Sect.
3
. In Sects.
4
and
5
, we illustrate rain impacts detected
in SMOS SSS data; then, their application improved the understanding of freshwater pools
interaction with the atmosphere. Conclusions and perspectives are given in Sect.
6
.
