Abstract's details
Improving altimetry in the Arctic
CoAuthors
Event: 2014 Ocean Surface Topography Science Team Meeting
Session: Quantifying Errors and Uncertainties in Altimetry data
Presentation type: Type Poster
Contribution: PDF file
Abstract:
The measuring of sea surface height is now a very mature discipline in the open ocean, with great care taken to understand the altimeter responses and the accuracy of the corrections. However, the accurate recovery of sea level information in Arctic regions prone to sea-ice is still challenging on account of the effect of reflections from sea-ice on the altimeter waveforms. There are two main problems: recognising which altimeter returns come from pure ocean, which from ocean leads within the sea-ice, and which are from sea-ice alone, and , secondly, retracking the more complex returns from mixed surfaces (water + sea-ice). Within Phase 2 o f the Sea Level CCI project, we are exploring both aspects to optimise the use of ERS-1, ERS-2 and Envisat altimetry data in the Arctic.
Firstly the project makes use of the latest versions of the high-rate waveform data, and investigates various classification techniques involving the application of different thresholds on peakiness, sigma0 and the short-term variability in range. The altimeter-based classifications are compared with high-resolution imagery from thermal instruments, optical sensors or selected SAR scenes in order to assess the robustness of the methodology. Secondly, we aim to improve on the mixed-surfaces retracker originally developed within the Sea Ice CCI. We intend to use the results of this classification and retracking to facilitate greater monthly coverage of Arctic sea level, and to better understand the seasonal and long-term changes.
Firstly the project makes use of the latest versions of the high-rate waveform data, and investigates various classification techniques involving the application of different thresholds on peakiness, sigma0 and the short-term variability in range. The altimeter-based classifications are compared with high-resolution imagery from thermal instruments, optical sensors or selected SAR scenes in order to assess the robustness of the methodology. Secondly, we aim to improve on the mixed-surfaces retracker originally developed within the Sea Ice CCI. We intend to use the results of this classification and retracking to facilitate greater monthly coverage of Arctic sea level, and to better understand the seasonal and long-term changes.