Radar and Remote Sensing

Convective-Stratiform Separation Characterized by Video Disdrometer Observations in Central Oklahoma – The Bayesian Approach

Petar Bukovcic
ARRC / SoM

01 May 2014, 1:15 PM

Radar Innovations Laboratory (RIL) Seminar Room 202
University of Oklahoma
Norman, OK

Application of 2-Dimensional Video Disdrometer (2DVD) data, collected in central Oklahoma, to the problem of convective-stratiform rain separation is presented. Primary focus of this study is the separation of the rain events into convective (CO) and stratiform (ST) periods by applying a multi-variable Bayesian classification
algorithm to the 2DVD dataset. It has been found that the CO-ST separation methods developed for one type of the disdrometric instrument may not work optimally for the different type of the disdrometric instrument. Similarly, single/dual parameter, or simple threshold separation methods may not be able to adequately separate CO and
ST rain types. The corresponding shape-slope (μ-Λ) relations of the constrained gamma distribution are derived for the CO and ST rain classes. These CO-ST constrained gamma relations are then used for rain DSD retrievals, and the results are compared with those obtained from the exponential distribution and unified μ-Λ
constraint previously used. It is demonstrated that the results based on the convective-stratiform separation yield more accurate DSD retrievals with respect to exponential and moderate improvements in comparison to unified μ-Λ constraint.

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