An Inverse Method for Drop Size Distribution Retrieval from Polarimetric Radar at Attenuating Frequency

Matias Alcoba,Marielle Gosset,Hervé Andrieu

doi:10.3390/rs14051116

Abstract

A method that formulates the retrieval of drop size distribution (DSD) parameters from polarimetric radar variables at attenuating frequency as the solution of an inverse problem is presented. The DSD in each radar bin is represented by a normalized Gamma distribution defined by three parameters (Dm,N0*,μ). The direct problem that describes polarimetric radar observables—scattering and propagation terms—and their dependency on DSD parameters is analyzed based on T-matrix scattering simulations. The inverse algorithm and its application to the DSD retrieval are then presented. The inverse method is applied to an African Monsoon Multidisciplinary Analysis (AMMA) field campaign that deployed an X-band dual-polarization Doppler radar and optical disdrometers in Benin, West Africa, in 2006 and 2007. The dataset is composed of X-band polarimetric radar PPIs and disdrometer data for 15 organized convective systems observed in 2006. A priori information on DSD parameters (benchmark method) is derived from the polarimetric radar observables by applying power law relationships. The proposed retrieval method of DSD parameters leads to the following results as compared to the benchmark: (i) we found a better spatial consistency of the retrieved parameters, (ii) the reconstructed polarimetric radar observables are closer to the observations, (iii) The validation with disdrometer data confirms an improved estimation of the DSD parameters.

Highlights

Received: 20 January 2022Rainfall estimation has greatly benefitted from the progress of weather radar and the development of dual-polarization methods
It is commonly accepted that rainfall drop size distributions (DSD) can be represented by a Gamma law governed by three parameters characterizing: the number of drops, the characteristic diameter, and the distribution shape [14]; other laws such as lognormal or four-parameters extended gamma have been proposed, but are less commonly used
One of many African Monsoon Multidisciplinary Analysis (AMMA) objectives was a better characterization of the meso-scale convective systems (MCS) which bring most of the rainfall during the West

Summary

Introduction

Received: 20 January 2022Rainfall estimation has greatly benefitted from the progress of weather radar and the development of dual-polarization methods. A whole branch of weather radar research has been devoted to rain or cloud drop size distributions (DSD), with two purposes:. It is commonly accepted that rainfall DSD can be represented by a Gamma law governed by three parameters characterizing: the number of drops, the characteristic diameter, and the distribution shape [14]; other laws such as lognormal or four-parameters extended gamma have been proposed, but are less commonly used. Many studies have been devoted to analyzing how the DSD parameters vary with rain bulk variables (rain rate, radar reflectivity factor, liquid water content, median-volume diameter) and to finding expressions for the DSD function and parameters that reduce the variability [14,15].

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Conclusion