<p> It has been hypothesized that some measurable properties of $Z_{DR}$ arcs in supercells may change in the minutes prior to tornadogenesis and tornadogenesis failure, and that $Z_{DR}$ arc area will change with SRH and can be used as a real-time proxy to estimate SRH. Output form the Cloud Model 1 (CM1) along with a polarimetric emulator is used to simulate $Z_{DR}$ arcs in 9 tornadic and 9 non-tornadic supercells. A random forest algorithm is used to automatically identify the $Z_{DR}$ arcs. Finally the inflow sector SRH is calculated at times when $Z_{DR}$ arcs are identified. To analyze the change in intensity and area a comparison between the average $Z_{DR}$ value inside and outside of the arc, as well as the spatial size of the arc and storm was done. Model calculated SRH is then compared to these metrics.</p> <p> </p> <p> It has also been observed that hail fallout complicates the automatic identification of $Z_{DR}$ arcs. In this study, three experiments are run where the simulated $Z_{DR}$ arcs are produced. One using all categories of hydrometeors, one where wet growth and melting of hail is excluded, and one excluding the contribution to $Z_{DR}$ from the hail hydrometeor category. The same analysis as above is repeated for all three experiments. Finally observed $Z_{DR}$ arcs are analyzed to see if these results are applicable to the real world. </p>

<p dir="ltr">It is known that tornadic storms favor environments characteristic of high values of thermal instability, adequate vertical wind shear, abundant near-surface moisture supply, and strong storm-relative helicity at the lowest 1-km boundary layer. These mesoscale environmental conditions and associated storm behaviors are strongly governed by large-scale synoptic patterns and sensitive to variabilities in near-surface characteristics, which are less known in the current research community. This study aims to advance the relatively underexplored area regarding the interaction between surface characteristics, mesoscale environmental conditions, and large-scale synoptic patterns driving tornadic storms in the U.S. </p><p dir="ltr">We first investigate the impact of surface drag on the structure and evolution of these boundaries, their associated distribution of near-surface vorticity, and tornadogenesis and maintenance. Comparisons between idealized simulations without and with drag introduced in the mature stage of the storm prior to tornadogenesis reveal that the inclusion of surface drag substantially alters the low-level structure, particularly with respect to the number, location, and intensity of surface convergence boundaries. Substantial drag-generated horizontal vorticity induces rotor structures near the surface associated with the convergence boundaries in both the forward and rear flanks of the storm. Stretching of horizontal vorticity and subsequent tilting into the vertical along the convergence boundaries lead to elongated positive vertical vorticity sheets on the ascending branch of the rotors and the opposite on the descending branch. The larger near-surface pressure deficit associated with the faster development of the near-surface cyclone when drag is active creates a downward dynamic vertical pressure gradient force that suppresses vertical growth, leading to a weaker and wider tornado detached from the surrounding convergence boundaries. A conceptual model of the low-level structure of the tornadic supercell is presented that focuses on the contribution of surface drag, with the aim of adding more insight and complexity to previous conceptual models.</p><p dir="ltr">We then examine the behaviors and dynamics of TLVs in response to a range of surface drag strengths in idealized simulations and explore their sensitivities to different storm environments. We find that the contribution of surface drag on TLV development is strongly governed by the interaction between surface rotation, surface convergence boundaries, and the low-level mesocyclone. Surface drag facilitates TLV formation by enhancing near-surface vortices and low-level lifting, mitigating the need for an intense updraft gradient developing close to the ground. As surface drag increases, a wider circulation near the surface blocks the inflow from directly reaching the rotating core, leading to a less tilted structure that allows the TLV position beneath the pressure minima aloft. Further increase in drag strength discourages TLV intensification by suppressing vertical stretching due to a negative vertical pressure perturbation gradient force, and it stops benefiting from the support of surrounding convergence boundaries and the overlying low-level updraft, instead becoming detached from them. We hence propose a favorable condition for TLV formation and duration where a TLV forms a less tilted structure directly beneath the low-level mesocyclone but also evolves near surrounding surface boundaries, which scenario strongly depends on underlying surface drag strength. </p><p dir="ltr">Beyond near-surface characteristics, we further explore how these storm-favorable environmental conditions may interact with the larger-scale synoptic patterns and how these interactions may affect the tornadic storm potential in the current warming climate. We employ hierarchical clustering analysis to classify the leading synoptic patterns driving tornadic storms across different geographic regions in the U.S. We find that the primary synoptic patterns are distinguishable across geographic regions and seasonalities. The intense upper-level jet streak described by the high values of eddy kinetic energy (EKE) associated with the dense distribution of Z500 contours dominates the tornado events in the southeast U.S. in the cold season (November-March). Late Spring and early Summer Tornado events in the central and south Great Plains are dominated by deep trough systems to the west axes of the tornado genesis position, while more summer events associated with weak synoptic forcing are positioned closer to the lee side of Rocky Mountain. Moreover, the increasing trend in tornado frequency in the southeastern U.S. is mainly driven by synoptic patterns with intense forcing, and the decreasing trends in portions of the Great Plains are associated with weak synoptic forcing. This finding indicates that the physical mechanisms driving the spatial trends of tornado occurrences differ across regions in the U.S.</p>