• DocumentCode
    1559887
  • Title

    Error estimates for a histogram in scatterometer geophysical model function estimation

  • Author

    Migliaccio, Maurizio ; Colandrea, Paolo

  • Author_Institution
    Dipt. di Ingegneria Elettrica ed Elettronica, Cagliari Univ., Italy
  • Volume
    40
  • Issue
    1
  • fYear
    2002
  • fDate
    1/1/2002 12:00:00 AM
  • Firstpage
    217
  • Lastpage
    220
  • Abstract
    The relationship between the normalized radar cross section σ° and the ocean surface wind field, i.e., the geophysical model function, is a key element in scatterometry. Due to many unsolved physical modeling problems, only a semi-empirical approach can be used to quantitatively relate the observed σ° to the wind field. Once the appropriate functional form has been selected, a model calibration procedure based on colocated σ° measurements and external wind field observations/determinations is accomplished. To this end, a σ° data grouping (binning) is performed to limit measurement uncertainties and reduce data volume. On this note, the binning procedure is revisited as an histogram estimation procedure and the relevant errors are determined. It is shown that in the best case of wind field error-free model the bias error introduced by the binning is negligible (but for low wind regimes) while the variance error is significant
  • Keywords
    atmospheric techniques; meteorological radar; oceanographic techniques; remote sensing by radar; wind; colocated measurements; data binning; data grouping; error estimate; geophysical model function; histogram; marine atmosphere; measurement technique; meteorological radar; model calibration procedure; normalized radar cross section; ocean wave; radar remote sensing; radar scatterometry; scatterometry; sea surface; semi-empirical approach; surface wind field; wind; Calibration; Geophysical measurements; Histograms; Measurement uncertainty; Oceans; Performance evaluation; Radar cross section; Radar measurements; Sea measurements; Sea surface;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/36.981364
  • Filename
    981364