Jason-1 will carry an altimeter and a microwave radiometer, like its predecessors TOPEX/POSEIDON and ERS-1/2.
We propose to participate in data processing and in-flight calibration/validation activities, on the basis of
our previous work on ERS-1/2 [Bernard et al., 1993, Eymard et al., 1994] extended to the altimeter. Our study
is therefore divided into two main parts: improvements in geophysical parameter retrieval algorithms and calibration
/validation/long-term survey of the JMR radiometer.
Retrieval algorithms for integrated water vapor content (equivalent to wet tropospheric correction),
integrated liquid water Content and sea surface wind speed will be improved. "Statistical" retrieval
algorithms are formulated using a large data set at latitudes lower than 60° North and South over
the oceans [Bourras, 1999], containing surface parameters and atmospheric profiles, and corresponding
simulated brightness temperatures and backscattering cross-sections. The source of meteorological
data is 12-hour predictions derived from the meteorological model developed by the European Center
for Medium-range Weather Forecasts (ECMWF). Relationships between satellite measurements and
geophysical parameters are formulated using a classical multilinear regression. Improvement in
retrieval algorithms depends therefore on the representativity of the database, the accuracy of
the radiative transfer model, and finally on the quality of the inversion model. First, the database
will be built using the latest version of the ECMWF forecast model, which has been operational since
November, 2000. The 60 levels in the model enable a complete description of the
troposphere/stratosphere profiles and the horizontal resolution is now one-half a degree.
Second, we will study the impact of a better sea surface model (at long and short scales),
using assessed parameterizations of the atmospheric forcing (surface fluxes) [Smith, 1980,
and Dupuis et al., 1997], then of a consistent description of the sea surface spectrum and
the foam coverage. We use the emissivity model from the Université Catholique de Louvain
[Lemaire, 1998], coupled with an atmospheric model [Liebe et al., 1993] for gazeous absorption.
A systematic comparison between measurements and simulations (active and passive) will be
performed over coincident meteorological fields in Jason configuration and also in TMR,
ERS-2/MWR, Envisat/MWR, SSM/I and TMI configurations, allowing a direct comparison between
different measurements. Finally, for the inversion, we will compare performance of neural
network inversion with the classical regression.
In-flight calibration will consist first of all in evaluating the calibration by comparison
of measurements with simulations, using the same radiative transfer model and ECMWF global
meteorological fields at coincident locations with the satellite. Although such a method
only provides the relative discrepancy with respect to the simulation chain, the results,
obtained simultaneously for several radiometers, can be used to detect significant calibration
problems (more than 2-3 K). Before applying the inversion algorithms, the calibration will
be fitted to the model used for inversion, leading to no significant bias in the retrieval.
The validation of retrieved products will be performed by comparison with in situ measurements
from shipborne radiosoundings for water vapor and ship or buoy measurements for surface wind
speed. Finally, for the long-term drift control, we will compare the method used for the
long-term survey of the TMR [Keihm et al., 2000], which consists in surveying the colder
sea points of the brightness temperature distribution, and continental areas where the
atmosphere variability is much less than over open oceans. Using this last method, the
stability of brightness temperatures can be checked using hot targets (Amazonian forest and
Sahara desert) or cold targets (Greenland glacier).
Bernard R., A. Le Cornec, L. Eymard, L. Tabary, 1993: The microwave radiometer on board ERS-1. Part 1: Characteristics and performances. IEEE Trans. Geosc. Remote Sensing, 31, 1186-1198.
Eymard L., L. Tabary, E. Gérard, A. Le Cornec, S.A. Boukabara, 1996: The microwave radiometer aboard ERS-1. Part 2: Validation of the geophysical products. IEEE Trans. Geosc. Remote Sensing, 34, 291-303.
Bourras D., 1999: Estimation par satellite du flux de chaleur latente à la surface des océans, Thèse de l'Université Paris 6.
Dupuis H., P.K. Taylor, A. Weill, K.B. Katsaros, 1997: The inertial dissipation method applied to derive momentum fluxes over the ocean during the SOFIA/ASTEX and SEMAPHORE experiments with low to moderate wind speeds. J. Geophys. Res., 102, C9, 21,115-21,129.
Smith S.D., 1980: Wind stress and heat flux over the ocean in gale force winds. J. Phys. Oceanogr., 10, 709-726.
Lemaire D., 1998: Non-fully developed sea state characteristics from real aperture radar remote sensing. Thèse de l'Universite Catholique de Louvain, Faculté des sciences appliquees.
Liebe H., G. Hufford, M. Cotton, 1993: Propagation modeling of moist air and suspended water/ice particles at frequencies below 1000 GHz. Reprints of the Agard 52nd specialists' meeting of the electromagnetic wave propagation panel, Palma de Mallorca, Spain, 17-21 May 1993.