Coastal Waveform Retracking in the Slick-Rich Sulawesi Sea of Indonesia, Based on Variable Footprint Size with Homogeneous Sea Surface Roughness

• Wang, Xifeng

  School of Marine Science and Environment Engineering, Dalian Ocean University

• Ichikawa, Kaoru

  Research Institute for Applied Mechanics, Kyushu University

• Wei, Dongni

  Dalian Marine Environmental Monitoring Station of Chinese State Oceanic Administration

Abstract

Waveforms of radar altimeters are often corrupted due to heterogeneous sea surface roughness within footprints, such as slicks. In past studies, subwaveform retrackers such as the adaptive leading edge subwaveform retracker (ALES) which use only a section of the waveform have been proposed. However, it is difficult to choose a reasonable estimation window from an individual waveform. In the present study, a post-processed subwaveform retracker is proposed which identifies the waveforms of surrounding along-track points. The size of the estimation window is variable and is determined to keep the sea surface roughness within the corresponding footprint homogeneous. The method was applied to seven years of 20 Hz Jason-2 altimeter data over the slick-rich Sulawesi Sea of Indonesia and compared with ALES and sensor geophysical data record (SGDR) products. The standard deviation of the sea surface dynamic heights was around 0.13 m, even without spatial smoothing or some geophysical corrections. This is only 75% and 25% of the ALES and SGDR results, respectively. Moreover, all retrievals of the range, SWH, and sigma0 include less outliers than the other products. These results indicate that the variable estimation windows determined in the present study can adapt well to the variation of sea surface roughness.

Journal

• Remote Sensing

  Remote Sensing 11 (11), 1274-1-1274-17, 2019-05-29

  MDPI

Keywords

• radar altimeter
• sea slick
• subwaveform retracker
• echogram
• ALES
• Sulawesi Sea of Indonesia

Details

• CRID: 1050017057727871872
• NII Article ID: 120006643521
• DOI: 10.3390/rs11111274
• ISSN: 20724292
• HANDLE: 2324/2244490
• Web Site: https://www.mdpi.com/2072-4292/11/11/1274/pdf
• Text Lang: en
• Article Type: journal article
• Data Source:
  • IRDB
  • Crossref
  • CiNii Articles
  • KAKEN