40
G. Lagerloef and J. Font
Other sources of error in the SSS retrieval include numerous effects that change
the brightness temperatures from the idealized flat surface emmission in Equations
(3.1) and (3.2) to what is actually measured by a satellite radiometer in orbit. These
include surface reflections of astronomical L-band radiation sources such as the
cosmic background, galactic core, sun and moon. Attenuation in the atmosphere and
ionosphere, including Faraday rotation (Yueh, 2000) must also be corrected. Clouds
are transparent at L-band and pose not problem, but attenuation during very heavy
rain can be significant and those data will need to be flagged. The T B variation with
respect to temperature falls generally between ±0.15 K ◦ C –1 and near zero over a
broad S and T range. Knowledge of the surface temperature to within a few tenths ◦ C
will be adequate to correct T B for temperature effects and can be obtained using
data from other satellite systems. In general these terms are well understood and
will be corrected with appropriate models and ancillary data. See Lagerloef et al.
(2008) for these terms tabulated for the Aquarius error analysis. The optical depth
for this microwave frequency in seawater is about 1–2 cm, and the remotely sensed
measurement depends on the T and S in that surface layer thickness, which poses a
potential problem when comparing satellite data to in-situ measurements within a
few meters of the surface.
The error source posing the most significant problem, however, is the change in
emissivity from surface roughness due to wind, including sea state, wave breaking
and foam. The change in T B due to wind is much smaller at L-band than at higher
frequencies (Hollinger, 1971), but nevertheless it is still the largest error source
for salinity remote sensing. The Wind and Salinity Experiment (WISE) field study
early in the decade (Camps et al., 2004; Gabarró et al., 2004) measured the L-band
response wind, wave height and foam at a range of incidence angles and developed empirical formulas relative to those variables. These results show that the T BH
response is much larger than T BV for incidence angles from 25 to 65 ◦ and is typically 0.2–0.4 K/m/s of wind. This implies large corrections for even moderate winds
of a few m/s. Recent airborne measurements show that the T BV response is larger
than indicated by the WISE data, and that there is a detectable modulation due to
the wind direction in both polarizations (S. Yueh, 2009, personal communication).
Clearly there remains considerable uncertainty in correcting the wind and roughness
effect, and this will be addressed once the satellites are on orbit through the calibration and validation activities. The Aquarius instrument will use radar backscatter to
help make this correction, where as SMOS will derive a wind correction through a
complex inversion algorithm that will rely on a model such as WISE that covers the
full range of SMOS incidence angles.
3.4 Soil Moisture Ocean Salinity (SMOS) Mission
3.4.1 Early Configuration and Evolution of Design
ESA organized in 1995 a consultative meeting on “Soil Moisture and Ocean Salinity,
Measurement Requirements and Radiometer Techniques” to analyze the feasibility
G. Lagerloef and J. Font
Other sources of error in the SSS retrieval include numerous effects that change
the brightness temperatures from the idealized flat surface emmission in Equations
(3.1) and (3.2) to what is actually measured by a satellite radiometer in orbit. These
include surface reflections of astronomical L-band radiation sources such as the
cosmic background, galactic core, sun and moon. Attenuation in the atmosphere and
ionosphere, including Faraday rotation (Yueh, 2000) must also be corrected. Clouds
are transparent at L-band and pose not problem, but attenuation during very heavy
rain can be significant and those data will need to be flagged. The T B variation with
respect to temperature falls generally between ±0.15 K ◦ C –1 and near zero over a
broad S and T range. Knowledge of the surface temperature to within a few tenths ◦ C
will be adequate to correct T B for temperature effects and can be obtained using
data from other satellite systems. In general these terms are well understood and
will be corrected with appropriate models and ancillary data. See Lagerloef et al.
(2008) for these terms tabulated for the Aquarius error analysis. The optical depth
for this microwave frequency in seawater is about 1–2 cm, and the remotely sensed
measurement depends on the T and S in that surface layer thickness, which poses a
potential problem when comparing satellite data to in-situ measurements within a
few meters of the surface.
The error source posing the most significant problem, however, is the change in
emissivity from surface roughness due to wind, including sea state, wave breaking
and foam. The change in T B due to wind is much smaller at L-band than at higher
frequencies (Hollinger, 1971), but nevertheless it is still the largest error source
for salinity remote sensing. The Wind and Salinity Experiment (WISE) field study
early in the decade (Camps et al., 2004; Gabarró et al., 2004) measured the L-band
response wind, wave height and foam at a range of incidence angles and developed empirical formulas relative to those variables. These results show that the T BH
response is much larger than T BV for incidence angles from 25 to 65 ◦ and is typically 0.2–0.4 K/m/s of wind. This implies large corrections for even moderate winds
of a few m/s. Recent airborne measurements show that the T BV response is larger
than indicated by the WISE data, and that there is a detectable modulation due to
the wind direction in both polarizations (S. Yueh, 2009, personal communication).
Clearly there remains considerable uncertainty in correcting the wind and roughness
effect, and this will be addressed once the satellites are on orbit through the calibration and validation activities. The Aquarius instrument will use radar backscatter to
help make this correction, where as SMOS will derive a wind correction through a
complex inversion algorithm that will rely on a model such as WISE that covers the
full range of SMOS incidence angles.
3.4 Soil Moisture Ocean Salinity (SMOS) Mission
3.4.1 Early Configuration and Evolution of Design
ESA organized in 1995 a consultative meeting on “Soil Moisture and Ocean Salinity,
Measurement Requirements and Radiometer Techniques” to analyze the feasibility