KDP estimation

The LROSE procedure to estimating KDP from PHIDP

Basics

KDP is estimated from the range derivative of PHIDP. PHIDP accumulates along a radar beam as it passes through a precipitating medium and estimating KDP can identify regions of large phase shifts, which can then identify regions of increased liquid water content.

The LROSE method for estimating KDP is based on an updated version of the technique developed by Hubbert and Bringi (1995).

Hubbert, J. and V.N. Bringi, 1995: An Iterative Filtering Technique for the Analysis of Copolar Differential Phase and Dual-Frequency Radar Measurements. J. Atmos. Oceanic Technol., 12, 643–648. Link .

Main Objectives

As a radar beam propagates through a precipitating medium, the electromagnetic wave slows down resulting in a phase shift. In radar volumes where the hydrometeors are not spherical, the phase shifts of the horizontal and vertical pulses are different. PHIDP measures the difference between these phase shifts. However, PHIDP accumulates along the beam, which makes the field difficult to interpret. Calculating the range derivative of PHIDP produces the KDP field, which highlights areas of strong changes in PHIDP.

In order to ensure the KDP field is useful, pre-processing of the PHIDP field is necessary. First, PHIDP is a noisy field. We want to ensure the KDP algorithm identifies regions of substantial change in PHIDP. Second, although phase shifts in Rayleigh-scattering regimes are dominated by changes in the wave propagation speed, Mie-scattering regimes will induce a additional phase shift component related to backscatter differential phase. That is, where nonspherical hydrometeors are large compared to the radar wavelength, constructive and destructive interference in the backscattered signal due to resonance can produce local phase shifts that aren't directly related to the liquid water content slowing down the radar beam. Before KDP is calculated, these two issues need to be accounted for.

Thus, the two main objectives of the LROSE KDP computation are as follows:

• smooth the PHIDP profile
• remove local increases in PHIDP caused by backscatter differential phase

Algorithm

(1) unfold PHIDP.

(2) apply a finite impulse response filter to unfolded PHIDP, a specified number of times, to create 'smoothed PHIDP'. This step is similar to Hubbert and Bringi (1995), but uses fewer iterations.

(3) for increasing range, identify peaks in 'smoothed PHIDP' which are followed by a minimum. Remove these peaks, by trimming them down to the minimum that follows. We call the result the 'conditioned PHIDP'. (this is the revised method to remove the bumps).

(4) apply FIR filter to 'conditioned PHIDP' a number of times, to provide further smoothing.

(5) Compute KDP as the (slope of conditioned PHIDP in range) / 2.0.