Equilibrium Energy and Entropy of Vortex Filaments in the Context of Tornadogenesis and Tornadic Flows

In this work, we study approximations of supercritical or suction vortices in tornadic flows and their contribution to tornadogenesis and tornado maintenance using self-avoiding walks on a cubic lattice. We extend the previous work on turbulence by A. Chorin and collaborators to approximate the statistical equilibrium quantities of vortex filaments on a cubic lattice when both an energy and a statistical temperature are involved. Our results confirm that supercritical (smooth, “straight”) vortices have the highest average energy and correspond to negative temperatures in this model. The lowest-energy configurations are folded up and “balled up” to a great extent. The results support A. Chorin’s findings that, in the context of supercritical vortices in a tornadic flow, when such high-energy vortices stretch, they need to fold and transfer energy to the surrounding flow, contributing to tornado maintenance or leading to its genesis. The computations are performed using a Markov Chain Monte Carlo approach with a simple sampling algorithm using local transformations that allow the results to be reliable over a wide range of statistical temperatures, unlike the originally used pivot algorithm that only performs well near infinite temperatures. Efficient ways to compute entropy are discussed and show that a system with supercritical vortices will increase entropy by having these vortices fold and transfer their energy to the surrounding flow.

Sensitivities of Tornadogenesis to Drop Size Distribution in a Simulated Subtropical Supercell over Eastern China

ABSTRACT Numerical simulations with the Advanced Regional Prediction System （ARPS） model were performed to investigate the impact of microphysical drop size distribution （DSD） on tornadogenesis in a subtropical supercell thunderstorm over Anhui Province, eastern China. Sensitivity experiments with different intercept parameters of rain, hail and snow DSDs in a Lin-type microphysics scheme were conducted. Results showed that rain and hail DSDs have a significant impact on the simulated storm both microphysically and dynamically. DSDs characterized by larger （smaller） intercepts have a smaller （larger） particle size and a lower （higher） mass-weighted mean fall velocity, and produce relatively stronger （weaker） and wider （narrower） cold pools through enhanced （reduced） rain evaporation and hail melting processes, which are then less favorable （favorable） for tornadogenesis. However, tornadogenesis will also be suppressed by the weakened mid-level mesocyclone when the cold pool is too weak. When compared to a U.S. Great Plain case, the two microphysical processes are more sensitive to DSD variations in the present case with a higher melting level and deeper warm layer. This suggests that DSD-related cloud microphysics has a stronger influence on tornadogenesis in supercells over the subtropics than the U.S. Great Plains.

Applications of Vortex Gas Models to Tornadogenesis and Maintenance

Processes related to the production of vorticity in the forward and rear flank downdrafts and their interaction with the boundary layer are thought to play a role in tornadogenesis. We argue that an inverse energy cascade is a plausible mechanism for tornadogenesis and tornado maintenance and provides supporting evidence which is both numerical and observational. We apply a three-dimensional vortex gas model to supercritical vortices produced at the surface boundary layer possibly due to interactions of vortices brought to the surface by the rear flank downdraft and also to those related to the forward flank downdraft. Two-dimensional and three-dimensional vortex gas models are discussed, and the three-dimensional vortex gas model of Chorin, developed further by Flandoli and Gubinelli, is proposed as a model for intense small-scale subvortices found in tornadoes and in recent numerical studies by Orf et al. In this paper, the smaller scales are represented by intense, supercritical vortices, which transfer energy to the larger-scale tornadic flows (inverse energy cascade). We address the formation of these vortices as a result of the interaction of the flow with the surface and a boundary layer.

Advanced Method for Forecasting and Warning of Severe Convective Weather and Local-scale Hazards

Hurricane Ida ferociously affected many south-eastern and eastern parts of the United States,making it one of the strongest hurricanes in recent years.Advanced forecast and warning tool has been used to track the path of the ex-Hurricane,Ida,as it left New Orleans on its way towards the northeast,accurately predicting significant supercell development above New York City on September 01,2021.This advanced method accurately detected the area with the highest possible level of convective instability with 24-h lead time and even Level 5,devised in the categorical outlooks legend of the system.Therefore,an extreme level implied a very high probability of the local-scale hazard occurring above the NYC.Cloud model output fields(updrafts and downdrafts,wind shear,near-surface convergence,the vertical component of relative vorticity)show the rapid development of a strong supercell storm with rotating updrafts and a mesocyclone.The characteristic hook-shaped echo signature visible in the reflectivity patterns indicates a signal for a highly precipitable(HP)supercell with the possibility of tornado initiation.Open boundary conditions represent a good basis for simulating a tornado that evolved from a supercell storm,initialized with initial data obtained from a real-time simulation in the period when the bow echo and tornado-like signature occurred.Тhe modeled results agree well with the observations.