PHiDP Unfolding and Conditioning

When computed for each range bin, PhiDP is inherently noisy, especially in volume samples not having meteorological scatterers present.

PhiDP can typically have values greater than 360° of phase difference, causing folding in the valid data ranges used in IRIS/RDA. Therefore, the first processing steps are to smooth and unfold the PhiDP data.

The following methodologies are available for unfolding and conditioning PhiDP data:

  • Least squares fit (LSQ). 1
  • Cubic spline fit. 2

The cubic spline fit is the recommended process. The methodology to be executed is a user-selectable option in IRIS and RDA processing.

1 Panov,S., R. Keranen, and V. Chandrasekar, 2008: Assessment of the Polarimetric Attenuation Correction Implementation in the RVP8 Signal Processor. 5th European Conference on Radar in Meteorology and Hydrology, Helsinki, Finland.
2 Chandrasekar,V., and Y. Wang, 2009: Adaptive Specific Differential Phase at Dual-Polarization Radar International Application Published under the Patent Cooperation Treaty. WO 2009/114868 A1.