Abstract's details

Coastal improvements for tidal models: the benefit of ALES retracker

Gaia Piccioni (DGFI-TUM, Germany)

Denise Dettmering (DGFI-TUM, Germany); Wolfgang Bosch (DGFI-TUM, Germany); Marcello Passaro (DGFI-TUM, Germany); Florian Seitz (DGFI-TUM, Germany)

Event: 2017 Ocean Surface Topography Science Team Meeting

Session: Tides, internal tides and high-frequency processes

Presentation type: Oral

The performance of altimetry at coastal areas has always been challenging. During the last years a major focus on this subject brought to a significant progress in sea level determination and geophysical corrections. However, the scientific community still highlights the need of improvements in wet tropospheric and tidal corrections.
A new version of the Empirical Ocean Tide (EOT) model is currently under development at DGFI-TUM, and takes advantage of the most recent altimetric products. The model scheme follows the former EOT11a: residual tidal constituents are derived on a least-squares-based harmonic analysis applied to Sea Level Anomalies (SLA) corrected for the newly-released FES2014 model. In order to improve the solutions at the coast, the range used for SLAs is computed exploiting the Adaptive Leading Edge Slope (ALES) retracker. The whole process is implemented on a grid with spacing of 1/8 by 1/8 degree, and a variable data weighting is applied at each node in proximity of the shore. This flexible weighting is bathymetry-dependent, so that shorter tidal wavelengths at shallow waters are accounted.
This work presents the features of the EOT model at its early stage and provides a first overview on its performance at coastal areas. For this purpose, the effects of ALES on the tidal model will be shown and compared with an ordinary retracker at regional scales. This evaluation represents a crucial point for further improvements in EOT as well as possible benefits in altimetry for coastal monitoring.

Contribution: TID_01_tides_ales_piccioni.pdf (pdf, 948 ko)

Corresponding author:

Gaia Piccioni

DGFI-TUM

Germany

gaia.piccioni@tum.de

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