Retrieving Rain Drop Size Distribution Moments from GPM Dual-Frequency Precipitation Radar

Merhala Thurai,David Wolff,Matthew T Wingo,Patrick N Gatlin,Viswanathan Bringi,David A Marks

doi:10.3390/rs13224690

Abstract

A novel method for retrieving the moments of rain drop size distribution (DSD) from the dual-frequency precipitation radar (DPR) onboard the global precipitation mission satellite (GPM) is presented. The method involves the estimation of two chosen reference moments from two specific DPR products, namely the attenuation-corrected Ku-band radar reflectivity and (if made available) the specific attenuation at Ka-band. The reference moments are then combined with a function representing the underlying shape of the DSD based on the generalized gamma model. Simulations are performed to quantify the algorithm errors. The performance of methodology is assessed with two GPM-DPR overpass cases over disdrometer sites, one in Huntsville, Alabama and one in Delmarva peninsula, Virginia, both in the US. Results are promising and indicate that it is feasible to estimate DSD moments directly from DPR-based quantities.

Highlights

The global precipitation measurement (GPM) core satellite hosts the dual-frequency precipitation radar (DPR), which is the first spaceborne radar operating at Ku- and Kabands for precipitation mapping [1]
In remote sensing applications at microwave frequencies, M3 will be related to specific attenuation, and M6 will be related to the radar reflectivity, but in the non-Rayleigh scattering region, the relationships will show more scatter depending on the frequency-band
Our results have shown that it is feasible to retrieve drop size distribution (DSD) moments directly from Our results have shown that it is feasible to retrieve DSD moments directly from

Summary

Introduction

The global precipitation measurement (GPM) core satellite hosts the dual-frequency precipitation radar (DPR), which is the first spaceborne radar operating at Ku- and Kabands for precipitation mapping [1]. The. DPR facilitates better estimates of the two main parameters governing the drop size distributions (DSDs), namely the mass-weighted mean diameter (Dm ) and the normalized intercept parameter (NW ) [5,6]. The DPR precipitation retrieval algorithm [7] employs the normalized representation of the drop size distribution based on the gamma distribution with shape parameter fixed (μ = 3) and uses a rather complex adjustment parameter to estimate the DSD and precipitation rate [8]. A number of recent studies have analyzed the statistics of [Dm , NW ] from the DPR and compared these with similar statistics from a diverse network of ground-based polarimetric radars [9] and surface disdrometers on a seasonal or global scale [10,11]. Such statistical comparisons have to encompass many years of data to overcome the “snapshot” view from DPR over a footprint of 5 km × 5 km versus nearly continuous

Methods

Results

Conclusion