3B.4 Investigating the Relation between Polarimetric Radar Signatures and Downburst Forcing Mechanisms using Spectral Bin Modeling

Monday, 28 August 2023: 2:15 PM
Great Lakes A (Hyatt Regency Minneapolis)
Jacob Carlin, Cooperative Institute for Severe and High-Impact Weather Research and Operations (CIWRO), Norman, OK; and A. V. Ryzhkov

The short-term prediction and detection of downbursts remains a difficult operational forecasting challenge. In addition to environmental cues, numerous radar-based precursor signatures (e.g., descending Z cores) have been proposed over many decades. However, these signatures are not always apparent, may evolve on very short timescales within the volumetric update time of operational radars, and offer little utility for predicting the intensity of impending downburst. Recent work revisiting this subject through the lens of radar polarimetry has identified new potential precursor signatures, such as descending Kdp cores. However, the ability to discern any relationship between these new signatures and downburst intensity remains tenuous, and validation of such predictions remains challenging due to observability constraints.

This work revisits the seminal downburst modeling studies of Srivastava (1985, 1987) with updated microphysical parameterizations of hail melting and added parameterizations of meltwater shedding and drop breakup. In addition, an advanced polarimetric radar forward operator is coupled to the model output. This setup allows us to conduct sensitivity tests and study the relationship between observed polarimetric radar variables and simulated downburst characteristics in an idealized framework. Results will compare the vertical profiles, gradients, and time derivatives of the simulated polarimetric variables with the resultant downburst intensity and magnitude of the driving forces across a range of initial conditions and particle size distributions to identify any prognostic associations that may exist, as well as examine the sensitivities of these results to microphysical parameterization assumptions. The implications of these findings for operational usage will also be discussed.
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