Extended triple collocation: Estimating errors and correlation coefficients with respect to an unknown target

By K. McColl, Jur Vogelzang, A. Konings, Dara Entekhabi, M. Piles, Ad Stoffelen. 2014

364 citations recorded by the source corpus.

Calibration and validation of geophysical measurement systems typically require knowledge of the “true” value of the target variable. However, the data considered to represent the “true” values often include their own measurement errors, biasing calibration, and validation results. Triple collocation (TC) can be used to estimate the root‐mean‐square‐error (RMSE), using observations from three mutually independent, error‐prone measurement systems. Here, we introduce Extended Triple Collocation (ETC): using exactly the same assumptions as TC, we derive an additional performance metric, the correlation coefficient of the measurement system with respect to the unknown target, ρt,Xi . We demonstrate that ρt,Xi2 is the scaled, unbiased signal‐to‐noise ratio and provides a complementary perspective compared to the RMSE. We apply it to three collocated wind data sets. Since ETC is as easy to implement as TC, requires no additional assumptions, and provides an extra performance metric, it may be of interest in a wide range of geophysical disciplines.

Subfields: Atmospheric Science, Environmental Engineering, Geophysics

View Paper: https://www.semanticscholar.org/paper/b554e7ed107cc49016dd97b0fcda993c368e7c6d

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In Atmospheric Science

  1. Wade T. Crow
  2. Thomas J. Jackson
  3. Marek Zreda
  4. Dara Entekhabi
  5. Eni G. Njoku
  6. Ad Stoffelen
  7. Hoshin V. Gupta

In Environmental Engineering

  1. Wade T. Crow
  2. Thomas J. Jackson
  3. Marek Zreda
  4. Todd G. Caldwell
  5. Dara Entekhabi
  6. Eni G. Njoku
  7. Hoshin V. Gupta

In Geophysics

  1. Marek Zreda
  2. Todd G. Caldwell

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