Abstract's details
COSTA v.1.0: DGFI-TUM Along Track Sea Level Product for ERS-2 and Envisat (1996-2010) in the Mediterranean Sea and in the North Sea
CoAuthors
Event: 2017 Ocean Surface Topography Science Team Meeting
Session: Advances in coastal altimetry: measurement techniques, science applications and synergy with in situ and models
Presentation type: Type Poster
Contribution: PDF file
Abstract:
The COastal Sea level Tailored ALES (COSTA) dataset contains dedicated coastal altimetry sea level measurements based on the Adaptive Leading Edge Subwaveform (ALES) reprocessing. In this version, the missions involved are ERS-2 (1996-2002) and Envisat (2002-2010), and the data are available in the Mediterranean Sea and in the North Sea.
The dataset is generated by the application of the ALES fitting algorithm to the radar signal provided by the official products of the missions. The ALES algorithm selects only a portion of the altimetric signal (waveform), in order to estimate the distance between the satellite and the sea surface (range) while avoiding the noise in the tail of the signal. The algorithm is based on the relation between estimated sea state, achievable precision and width of the subwaveform. The sea state bias correction, which accounts for the effects of waves and the tracking errors, is recomputed for the ALES output.
Following this pre-processing, the data are post-processed with updated geophysical corrections, tidal and mean sea surface models. Finally, the sea level measurements are averaged at 1 Hz (one measurement every ~7 km along each track) after removing the outliers. To facilitate the temporal analysis, the sea level anomalies for each track are stored in matrices in which each row corresponds to the time series at one latitude-longitude location.
The validation work, presented at the 10th Coastal Altimetry Workshop (2017-02-21 - 24, Florence, Italy), has shown a 15% decrease in the high-rate noise of the measurements if compared to the standard product, with larger improvements in the last 20 km from the coastline and a better precision also in the open ocean.
The COSTA dataset is made available to the scientific community in order to foster the application of coastal altimetry data by users, who are not necessarily trained in radar altimetry processing. Its objective is the provision of easy-to-use along-track sea level data that can be directly used for sea level and circulation studies not only in the open ocean, but also in the coastal regions.
The dataset is generated by the application of the ALES fitting algorithm to the radar signal provided by the official products of the missions. The ALES algorithm selects only a portion of the altimetric signal (waveform), in order to estimate the distance between the satellite and the sea surface (range) while avoiding the noise in the tail of the signal. The algorithm is based on the relation between estimated sea state, achievable precision and width of the subwaveform. The sea state bias correction, which accounts for the effects of waves and the tracking errors, is recomputed for the ALES output.
Following this pre-processing, the data are post-processed with updated geophysical corrections, tidal and mean sea surface models. Finally, the sea level measurements are averaged at 1 Hz (one measurement every ~7 km along each track) after removing the outliers. To facilitate the temporal analysis, the sea level anomalies for each track are stored in matrices in which each row corresponds to the time series at one latitude-longitude location.
The validation work, presented at the 10th Coastal Altimetry Workshop (2017-02-21 - 24, Florence, Italy), has shown a 15% decrease in the high-rate noise of the measurements if compared to the standard product, with larger improvements in the last 20 km from the coastline and a better precision also in the open ocean.
The COSTA dataset is made available to the scientific community in order to foster the application of coastal altimetry data by users, who are not necessarily trained in radar altimetry processing. Its objective is the provision of easy-to-use along-track sea level data that can be directly used for sea level and circulation studies not only in the open ocean, but also in the coastal regions.