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Development of a Satellite SAR Image Spectra and Altimeter Wave Height Data Assimilation System for ERS-1


Hasselmann,  Klaus
MPI for Meteorology, Max Planck Society;

Hasselmann,  Susanne
MPI for Meteorology, Max Planck Society;

Bauer,  Eva
MPI for Meteorology, Max Planck Society;

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Hasselmann, K., Hasselmann, S., Bauer, E., Brüning, C., Lehner, S., Graber, H., et al. (1988). Development of a Satellite SAR Image Spectra and Altimeter Wave Height Data Assimilation System for ERS-1. Report / Max-Planck-Institut für Meteorologie, 019. doi:10.17617/2.2578369.

Cite as: https://hdl.handle.net/21.11116/0000-0001-2999-5
A study on the applicability of ERS—l wind and wave data for wave models is
carried out using the WAM third generation wave model and SEASAT altimeter,
scatterometer and SAR data.
A series of global wave hindcasts is made for the surface stress and surface
Wind fields derived by Atlas et al. (1987) by assimilation of scatterometer
data for the full 96—day SEASAT and also for two wind field analyses for
shorter periods produced by Anderson et al. (1987) (by assimilation with the
higher resolution ECMWF T63 model) and by Woiceshyn et al. (1987) (by sub—
jective analysis methods). It is found that wave models respond very sensi—
tively to inconsistencies in wind field analyses and therefore provide a
valuable data validation tool.
Comparisons between SEASAT SAR image spectra and theoretical SAR spectra
derived from the hindcast wave spectra by Monte Carlo simulations yielded
good eyerall agreement for 32 cases representing a wide variety of wave
conditions. It is concluded that SAR wave imaging is sufficiently Well under—
stood to apply SAR image spectra with confidence for wave studies if supported
by realistic wave models and theoretical computations of the strongly non—
linear mapping of the wave spectrum into the SAR image spectrum. A new,
closed nonlinear integral expression for this spectral mapping relation is
derived which avoids the inherent statistical errors of Monte Carlo compu—
tations and may prove to be more efficient numerically.
A theoretical frameWOrk is developed for the assimilation of arbitrary wave
data in models in which the wind and wave fields are modified simultaneouely
in accordance with the constraints imposed by the wave model. As a first
step, a simplified wave data assimilation exercise is carried out in which
only the wave field is modified.