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Abstract Downbursts present a major operational forecasting challenge. Numerous radar-based signatures have been proposed for nowcasting downburst development, including recent research on polarimetric signatures associated with downbursts. However, the reliability of these signatures, and their relationship to downburst intensity, are not well established. In this work, we develop an idealized one-dimensional model of downburst development with bin microphysics and a coupled polarimetric radar forward operator to study the relationships, if any, between proposed downburst radar signatures (viz., descendingZandK_dpcores) and forcing mechanisms (i.e., precipitation loading and diabatic cooling). The model is able to realistically reproduce observed downburst radar signatures and evolution, with precipitation loading being the dominant forcing mechanism close to the 0°C level and diabatic cooling becoming dominant closer to the surface. Environmental sensitivity runs show that for a given initial particle size distribution, the diabatic cooling forcing/downdraft magnitude andK_dpexhibit opposite responses to variations in temperature lapse rate and RH, whileZand total precipitation loading forcing are mostly insensitive to the environment. However, ensemble simulations show that although neitherZorK_dpare well correlated with the instantaneous forcing magnitudes at most heights,K_dpbelow the 0°C level is well correlated with the resultant downburst intensity at the surface within a given thermodynamic environment, with higherK_dpaloft corresponding to stronger downbursts. These findings support the use and further exploration ofK_dpcores near the melting level as downburst radar precursors. Significance StatementDownbursts present a major nowcasting challenge due to their rapid evolution. While various weather radar signatures have been proposed to be indicative of the existence of developing downbursts, the purpose of this study is to better understand what these signatures may be able to tell us about their intensity. Using a detailed model of downburst generation, we found that, together with knowledge of how favorable the environment is for downbursts, the maximum magnitude of a specific differential phase core beneath the melting layer is associated with how strong a downburst will be when it eventually reaches the surface. This supports the potential use of this radar signature aloft to predict the severity of impending downbursts. 

Abstract Downbursts pose a threat to life, property, and aviation, yet they remain challenging to predict. Prior studies have found radar-based downburst signatures such as divergent and convergent velocity signatures at the surface and midlevels, respectively; descending radar reflectivity (Z) cores (DRCs); present or descending specific differential phase (K_DP) cores; and troughs of decreased differential reflectivity (Z_DR) collocated with decreased copolar correlation coefficient (ρ_hv) below the melting layer. This research expands on those studies using the multicell identification and tracking (MCIT) algorithm to automate storm detection and analyze 53 downburst cases spanning most regions of the CONUS. Individual case analysis revealed that DRCs appeared in 83% of cases, descendingK_DPcores appeared in 85% of cases, andZ_DRtroughs and collocatedρ_hvdrops appeared in 89% of cases. The magnitude of low-level divergence and midlevel convergence reached a threshold of 0.0025 s⁻¹in 68% and 83% of cases, respectively. Composite time series revealed that divergence displayed the most prominent signature near the surface; aloft,K_DPat and 1 km below the freezing level, midlevel convergence,Z_DRcolumn area and volume, and VIL displayed the most prominent signatures. Differences were observed between geographic regions and thermodynamic environments, with lower velocity-related and higherK_DP-related values most common in the eastern United States and environments with wind index (WINDEX) < 60; conversely, higher velocity-related and lowerK_DP-related values were most common in the western United States and environments with WINDEX > 60. These findings may help inform future polarimetric downburst detection and algorithm development efforts.