Abstract's details
Round robin assessment of radar altimeter LRM and SAR retracking algorithms for significant wave height.
Event: 2019 Ocean Surface Topography Science Team Meeting
Session: Regional and Global CAL/VAL for Assembling a Climate Data Record
Presentation type: Poster
In June 2018, the Sea State Climate Change Initiative (SeaState_cci) was launched by the European Space Agency (ESA). The main goal of the project is the estimation and exploitation of consistent climate-quality time-series of significant wave height (SWH) across different missions.
The responsibility of the altimetry Algorithm Development (AD) team of the SeaState_cci project is to improve and develop novel algorithms for estimating the SWH parameters yielding increased signal-to-noise ratio (SNR) and better performance in the coastal zone. Furthermore, the new estimation techniques shall generate consistent results in terms of precision and accuracy during the past 25 years of satellite altimetry data. The process of fitting a satellite radar waveform to a modelled waveform, from which the SWH and wind speed can be extracted, is called retracking. Two novel retracking algorithms with the best retracking performance shall be selected for production, one for each of the two main operational modes of satellite altimetry, i.e. low resolution mode (LRM) and synthetic aperture radar mode (SARM).
In accordance to other ESA CCI projects, a round robin (RR) exercise for algorithm evaluation and selection is being conducted and was open to both internal and external teams. Five groups have participated in the call. The objective of this abstract is to illustrate the selection procedure and present an overview of the results of the different candidate algorithms.
The RR is focused on test datasets of the two missions Jason-3 (J3) and Sentinel-3A (S3A) covering two years of data and spanning different sea state conditions. The type of open-ocean and coastal scenarios were carefully selected, such that the overall performance of the retracker algorithms can be evaluated. In this regard, a series of criteria, which have been discussed and agreed within the consortium, have been defined. These include criteria for both internal statistics and for a comparison against in-situ (buoys) and model data. The former covers an extensive outlier and noise analysis. In the evaluation process, a differentiation is made between open-ocean and coastal scenarios and also for average and extreme sea states, in order to identify the general applicability of the individual retracking algorithms. The evaluation algorithms (written in Python or MATLAB) will be made publicly available to establish an objective evaluation process. A common code base for evaluating the performance of a retracking algorithm will be highly beneficial to the satellite altimetry community.
The improved estimation of sea state has a strong impact on the understanding and forecasting of climate and its variability, particularly in key areas of interest such as the coastal zone and in high-impact scenarios such as weather extremes. The RR exercise of the ESA SeaState_cci project is an excellent opportunity to harmonise the algorithm evaluation process for finding the best performing retracking algorithms and can be reused in other projects that involve satellite altimetry.
Back to the list of abstractThe responsibility of the altimetry Algorithm Development (AD) team of the SeaState_cci project is to improve and develop novel algorithms for estimating the SWH parameters yielding increased signal-to-noise ratio (SNR) and better performance in the coastal zone. Furthermore, the new estimation techniques shall generate consistent results in terms of precision and accuracy during the past 25 years of satellite altimetry data. The process of fitting a satellite radar waveform to a modelled waveform, from which the SWH and wind speed can be extracted, is called retracking. Two novel retracking algorithms with the best retracking performance shall be selected for production, one for each of the two main operational modes of satellite altimetry, i.e. low resolution mode (LRM) and synthetic aperture radar mode (SARM).
In accordance to other ESA CCI projects, a round robin (RR) exercise for algorithm evaluation and selection is being conducted and was open to both internal and external teams. Five groups have participated in the call. The objective of this abstract is to illustrate the selection procedure and present an overview of the results of the different candidate algorithms.
The RR is focused on test datasets of the two missions Jason-3 (J3) and Sentinel-3A (S3A) covering two years of data and spanning different sea state conditions. The type of open-ocean and coastal scenarios were carefully selected, such that the overall performance of the retracker algorithms can be evaluated. In this regard, a series of criteria, which have been discussed and agreed within the consortium, have been defined. These include criteria for both internal statistics and for a comparison against in-situ (buoys) and model data. The former covers an extensive outlier and noise analysis. In the evaluation process, a differentiation is made between open-ocean and coastal scenarios and also for average and extreme sea states, in order to identify the general applicability of the individual retracking algorithms. The evaluation algorithms (written in Python or MATLAB) will be made publicly available to establish an objective evaluation process. A common code base for evaluating the performance of a retracking algorithm will be highly beneficial to the satellite altimetry community.
The improved estimation of sea state has a strong impact on the understanding and forecasting of climate and its variability, particularly in key areas of interest such as the coastal zone and in high-impact scenarios such as weather extremes. The RR exercise of the ESA SeaState_cci project is an excellent opportunity to harmonise the algorithm evaluation process for finding the best performing retracking algorithms and can be reused in other projects that involve satellite altimetry.