Analysis of multispectral fields of satellite IR measurements: Using statistics of second spatial differential of spectral fields for measurement characterization

  • Authors:

  • Youri Plokhenko;W. Paul Menzel;Henry E. Revercomb;Eva Borbas;Paolo Antonelli;EliSabeth Weisz

  • Affiliations:

  • Cooperative Institute for Meteorological Satellite Studies (CIMSS), University of Wisconsin-Madison, Madison, WI 53706, USA;Office of Research and Applications, NOAA/NESDIS, Madison, WI 53706, USA;Space Science and Engineering Center (SSEC), University of Wisconsin-Madison, Madison, WI 53706, USA;Cooperative Institute for Meteorological Satellite Studies (CIMSS), University of Wisconsin-Madison, Madison, WI 53706, USA;Cooperative Institute for Meteorological Satellite Studies (CIMSS), University of Wisconsin-Madison, Madison, WI 53706, USA;Cooperative Institute for Meteorological Satellite Studies (CIMSS), University of Wisconsin-Madison, Madison, WI 53706, USA

  • Venue:
  • International Journal of Remote Sensing
  • Year:
  • 2008

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Abstract

An approach using spatial analysis of satellite IR spectral measurements for quality assessment is presented. The second spatial differential is used as a model of measurement noise for spatially smooth radiative fields. Spatial differentiation significantly magnifies the noise contribution and reduces the physical signal amplitude because of differences in spatial distributions of instrument noise and atmospheric thermal fields. The second spatial differential represents a convenient and effective tool for numerical analysis of satellite IR measurements. This paper demonstrates that statistics of the second spatial differential are informative predictors for data-quality characterization. Statistics of the second spatial differential are used for identifying anomalies in spectral channel data caused by detector noise, sensitivity loss to spatial shortwave thermal variations, and spatially (temporally) correlated noise.