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Statistical Considerations for ABFM Radar Parameters

Statistical Considerations for ABFM Radar Parameters. Francis J. Merceret 2d ABFM/LAP Joint Workshop 16 May 2003. Overview. Core Issues Relevant Results to Date Things Planned for Near Term. Core Issues. Peak or average? What kind of average? dBZ, Z, or Z-derived LWC?

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Statistical Considerations for ABFM Radar Parameters

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  1. Statistical Considerations for ABFM Radar Parameters Francis J. Merceret 2d ABFM/LAP Joint Workshop 16 May 2003

  2. Overview • Core Issues • Relevant Results to Date • Things Planned for Near Term

  3. Core Issues • Peak or average? • What kind of average? • dBZ, Z, or Z-derived LWC? • Truncated (where)? • How big a box?

  4. Peak or Average? • Peak values are extremely sensitive to statistical sampling fluctuation. • See Reflectivity Averaging: A Monte Carlo Study under the reports link at ABFM Home Page for details • Use of average is strongly recommended.

  5. What Kind of Average? - 1 • Averages of Z are extremely sensitive to peaks and share disadvantages of peak values. • Averages of Zn such as LWC (n ~ 0.5) behave much like averages of Z • Averages of dBZ seem more consistent and repeatable as shown in Monte Carlo report.

  6. What Kind of Average? - 2 • Averages of data truncated at a lower bound are biased upward. Bias is severe if actual mean is within one std. dev. of boundary • Without truncation, how handle • Clear air (dBZ <<< 0) ? • Radar noise floor (range dependent) ? • Recommendation: Truncate at highest noise floor in the range of interest but no higher than two standard deviations below LLCC trigger threshold • See Monte Carlo report for quantitative analysis

  7. How Big a Box? • Box should be much bigger than radar beam position uncertainties. These are of order 1 Km. See Radar Beam Geometry Effects for ABFM under report link for details. • Box should be of same order as correlation length of phenomena being averaged. This is of order 10 – 20 Km. See Autocorrelation Presentation under report link for details.

  8. Things Planned for Near Term • Spectral analysis to determine scales of features most contributing to variance and covariance of radar and electric fields • Improved correlation analysis to determine degree of independence of the data • Correct QC error in preliminary work • Process entire data set • Include new averaged variables

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