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Detecting small seamounts in AltiKa repeat cycle data

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  • Journal Title:
    Marine Geophysical Research
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    We present a technique of stacking repeat cycles of satellite altimeter sea surface height profiles that lowers the noise and improves the resolution of small seamounts. Our approach differs from other studies because it uses the median (not the mean) of the stacks, which suppresses outliers. Seamounts as small as 720 m tall are easily detected in stacked 40 Hz AltiKa data profiles, and a 500 m tall seamount is perceptible. Noise variance decreases with an increase in the number of cycles stacked, and RMS noise dips below 2 cm when 11 or more cycles are stacked. Coherence analyses between geoid height and bathymetry show that full wavelengths down to about 10 km can be resolved. Comparisons of study areas with and without seamounts find that signal from small seamounts lies in the ~10–28 km waveband. A simple Gaussian band-pass filter based on the seamount waveband passes signals that can be used in seamount detection studies. Such studies may find seamounts <2 km tall that are predicted to be abundant on the ocean floor.
  • Source:
    Marine Geophysical Research, 37(4), 349-359
  • DOI:
  • ISSN:
    0025-3235 ; 1573-0581
  • Format:
    PDF
  • Publisher:
    Springer Science and Business Media LLC
  • Document Type:
    Journal Article
  • Rights Information:
    Accepted Manuscript
  • Rights Statement:
    The NOAA IR provides access to this content under the authority of the government's retained license to distribute publications and data resulting from federal funding. While users may legally access this content, the copyright owners retain rights that govern the reproduction, redistribution, and re-use of this work. The user is solely responsible for complying with applicable copyright law.
  • Compliance:
    Submitted
  • Main Document Checksum:
    urn:sha-512:edf44806060f59a8a1dcd269c19ffccf7c9b59b92b7e110942ff631f61941158f830e26c4a49f32d0782246d1d8a9a29053150b0096748635a27855f79427b17
  • Download URL:
  • File Type:
    Filetype[PDF - 1.04 MB ]

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