Measuring Global Ocean Wave Skewness by Retracking RA-2 Envisat Waveforms

J. Gómez-Enri Laboratory for Satellite Oceanography, National Oceanography Centre, Southampton, United Kingdom

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C. P. Gommenginger Laboratory for Satellite Oceanography, National Oceanography Centre, Southampton, United Kingdom

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M. A. Srokosz Laboratory for Satellite Oceanography, National Oceanography Centre, Southampton, United Kingdom

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P. G. Challenor Laboratory for Satellite Oceanography, National Oceanography Centre, Southampton, United Kingdom

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J. Benveniste ESRIN, European Space Agency, Frascati, Italy

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Abstract

For early satellite altimeters, the retrieval of geophysical information (e.g., range, significant wave height) from altimeter ocean waveforms was performed on board the satellite, but this was restricted by computational constraints that limited how much processing could be performed. Today, ground-based retracking of averaged waveforms transmitted to the earth is less restrictive, especially with respect to assumptions about the statistics of ocean waves. In this paper, a theoretical maximum likelihood estimation (MLE) ocean waveform retracker is applied tothe Envisat Radar Altimeter system (RA-2) 18-Hz averaged waveforms under both linear (Gaussian) and nonlinear ocean wave statistics assumptions, to determine whether ocean wave skewness can be sensibly retrieved from Envisat RA-2 waveforms. Results from the MLE retracker used in nonlinear mode provide the first estimates of global ocean wave skewness based on RA-2 Envisat averaged waveforms. These results show for the first time geographically coherent skewness fields and confirm the notion that large values of skewness occur primarily in regions of large significant wave height. Results from the MLE retracker run in linear and nonlinear modes are compared with each other and with the RA-2 Level 2 Sensor Geophysical Data Records (SGDR) products to evaluate the impact of retrieving skewness on other geophysical parameters. Good agreement is obtained between the linear and nonlinear MLE results for both significant wave height and epoch (range), except in areas of high-wave-height conditions.

Corresponding author address: J. Gómez-Enri, Laboratory for Satellite Oceanography, National Oceanography Centre, Southampton, European Way, Southampton SO14 3ZH, United Kingdom. Email: jxge@noc.soton.ac.uk

Abstract

For early satellite altimeters, the retrieval of geophysical information (e.g., range, significant wave height) from altimeter ocean waveforms was performed on board the satellite, but this was restricted by computational constraints that limited how much processing could be performed. Today, ground-based retracking of averaged waveforms transmitted to the earth is less restrictive, especially with respect to assumptions about the statistics of ocean waves. In this paper, a theoretical maximum likelihood estimation (MLE) ocean waveform retracker is applied tothe Envisat Radar Altimeter system (RA-2) 18-Hz averaged waveforms under both linear (Gaussian) and nonlinear ocean wave statistics assumptions, to determine whether ocean wave skewness can be sensibly retrieved from Envisat RA-2 waveforms. Results from the MLE retracker used in nonlinear mode provide the first estimates of global ocean wave skewness based on RA-2 Envisat averaged waveforms. These results show for the first time geographically coherent skewness fields and confirm the notion that large values of skewness occur primarily in regions of large significant wave height. Results from the MLE retracker run in linear and nonlinear modes are compared with each other and with the RA-2 Level 2 Sensor Geophysical Data Records (SGDR) products to evaluate the impact of retrieving skewness on other geophysical parameters. Good agreement is obtained between the linear and nonlinear MLE results for both significant wave height and epoch (range), except in areas of high-wave-height conditions.

Corresponding author address: J. Gómez-Enri, Laboratory for Satellite Oceanography, National Oceanography Centre, Southampton, European Way, Southampton SO14 3ZH, United Kingdom. Email: jxge@noc.soton.ac.uk

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  • Abramowitz, M., and Stegun I. A. , 1968: Bessel functions of integer order. Handbook of Mathematical Functions, M. Abramowitz and I. A. Stegun, Eds., Dover, 374 pp.

    • Search Google Scholar
    • Export Citation
  • Amarouche, L., Thibaut P. , Zanife O. Z. , Dumont J. P. , Vincent P. , and Steunou N. , 2004: Improving the Jason-1 ground retracking to better account for attitude effects. Mar. Geodesy, 27 , 171197.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Barrick, D. E., and Lipa B. J. , 1985: Analysis and interpretation of altimeter sea echo. Advances in Geophysics, Vol. 27, Academic Press, 61–100.

    • Search Google Scholar
    • Export Citation
  • Brown, G. S., 1977: The average impulse response of a rough surface and its applications. IEEE J. Oceanic Eng., 2 , 6774.

  • Callahan, P. S., and Rodríguez E. , 2004: Retracking Jason-1 data. Mar. Geodesy, 27 , 391407.

  • Carter, D. J. T., and Tucker M. J. , 1986: Uncertainties in environmental design criteria. Underwater Technol., 12 , 2833.

  • Challenor, P. G., and Srokosz M. A. , 1989: The extraction of geophysical parameters from radar altimeter return from a non-linear sea surface. Mathematics in Remote Sensing, S. R. Brooks, Ed., Clarendon Press, 257–268.

    • Search Google Scholar
    • Export Citation
  • Cox, D. R., and Hinkley D. V. , 1974: Theoretical Statistics. Chapman and Hall, 511 pp.

  • ESA, 2004: ENVISAT RA2/MWR product handbook. Issue 1.2. [Available online at http://envisat.esa.int/dataproducts/ra2-mwr/.].

  • Gomez-Enri, J., Gommenginger C. , Srokosz M. , Challenor P. , and Drinkwater M. , 2006: Envisat radar altimeter tracker bias. Mar. Geodesy, 29 , 1938.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gomez-Enri, J., Srokosz M. , Gommenginger C. , Challenor P. , and Milagro-Perez M. , 2007: On the impact of mispointing error and Hamming filtering on altimeter waveform retracking and skewness retrieval. Mar. Geodesy,, in press.

    • Search Google Scholar
    • Export Citation
  • Griffiths, H. D., Wingham D. J. , Challenor P. G. , Guymer T. H. , and Srokosz M. A. , 1987: A study of mode switching and fast-delivery product algorithms for the ERS-1 altimeter. ESA Contract Rep. 6375/85/NL/BI, 250 pp.

  • Hayne, G. S., 1980: Radar altimeter mean return waveform from near-normal incidence ocean surface scattering. IEEE Trans. Antennas Propag., 28 , 687692.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Longuet-Higgins, M. S., 1963: The effect of nonlinearities on statistical distributions in the theory of sea waves. J. Fluid Mech., 17 , 459480.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Losquadro, G., 1983: Relationship between engineering and geophysical parameters. ERS-1 Selenia Spazio Doc., Selenia Spazio, 350 pp.

  • Press, W. H., Flannery B. P. , Teukolsky S. A. , and Vetterling W. T. , 1988: Numerical Recipes in C: The Art of Scientific Computing. Cambridge University Press, 768 pp.

    • Search Google Scholar
    • Export Citation
  • Rodríguez, E., 1988: Altimetry for non-Gaussian oceans: Height biases and estimation parameters. J. Geophys. Res., 93 , 1410714120.

  • Rodríguez, E., and Chapman B. , 1989: Extracting ocean surface information from altimeter returns: The deconvolution method. J. Geophys. Res., 94 , 97619778.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Srokosz, M. A., 1986: On the joint distribution of surface elevation and slopes for a nonlinear random sea, with an application to radar altimetry. J. Geophys. Res., 91 , 9951006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thibaut, P., Amarouche L. , Zanife O. Z. , Steunou N. , Vincent P. , and Raizonville P. , 2004a: Jason-1 altimeter ground processing look-up correction tables. Mar. Geodesy, 27 , 409431.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thibaut, P., Amarouche L. , Zanife O. Z. , and Vincent P. , 2004b: Estimation of the skewness coefficient in Jason-1 altimeter data. Proc. Ocean Surface Topography Science Team Meeting, St. Petersburg, FL, CNES/NASA, CD-ROM.

  • Tokmakian, R. T., Challenor P. G. , Guymer H. , and Srokosz M. A. , 1994: The U.K. EODC ERS-1 altimeter oceans processing scheme. Int. J. Remote Sens., 15 , 939962.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ulaby, F. T., Moore R. K. , and Fung A. K. , 1982: :Radar Remote Sensing and Surface Scattering and Emission Theory. Vol. II, Microwave Remote Sensing: Active and Passive, Addison-Wesley, 608 pp.

  • Zanife, O. Z., Vincent P. , Amarouche L. , Dumont J. P. , Thibaut P. , and Labroue S. , 2003: Comparison of the Ku-band range noise and the relative sea state bias of the Jason-1, TOPEX and POSEIDON-1 radar altimeters. Mar. Geodesy, 26 , 201238.

    • Crossref
    • Search Google Scholar
    • Export Citation
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