Amit Dutta

and 3 more

This paper presents microphysical inference retrievals obtained from spectral polarimetry during the Relampago (Remote sensing of Electrification, Lightning, And Mesoscale/Microscale Processes with Adaptive Ground Observations) campaign. Spectral processing has been an essential part of weather radar moments estimation for a long period of time. Various processing can be performed in the spectral domain including precipitation detection in presence of strong clutter and noise, clutter & interference mitigation by algorithms such as GMAP, object-oriented filters and many more. However spectral applications to polarimetry have been rare. The C band CSU-CHIVO radar that was deployed in Cordoba region in Argentina between June 2018 and April 2019 during the Relampago campaign, recorded some of the tallest storms in the world characterized by strong wind shear, updrifts, turbulence and occurrence of severe hail and rain. The polarimetric spectrum in precipitation with rain and hail mixtures were characterized. This Spectral polarimetry revealed different spectral characteristics including multi-modal spectrum, spectral broadening, slopes in spectral differential reflectivity and lowering of coherency spectrum. These results characterized occurrence of mixed hydrometeor types in a radar resolution volume such as presence of rain and hail mixture, large drops formation and size sorting. Spectral displays are inherently noisy, and the paper also presented methodology to obtain clean quality spectrum implementing spectral quality index, that is used to process the observations and the results are presented.