Comparison of a Spectral Bin and Two Multi-Moment Bulk Microphysics Schemes for Supercell Simulation:Investigation into Key Processes Responsible for Hydrometeor Distributions and Precipitation

There are more uncertainties with ice hydrometeor representations and related processes than liquid hydrometeors within microphysics parameterization(MP)schemes because of their complicated geometries and physical properties.Idealized supercell simulations are produced using the WRF model coupled with“full”Hebrew University spectral bin MP(HU-SBM),and NSSL and Thompson bulk MP(BMP)schemes.HU-SBM downdrafts are typically weaker than those of the NSSL and Thompson simulations,accompanied by less rain evaporation.HU-SBM produces more cloud ice(plates),graupel,and hail than the BMPs,yet precipitates less at the surface.The limiting mass bins(and subsequently,particle size)of rimed ice in HU-SBM and slower rimed ice fall speeds lead to smaller melting-level net rimed ice fluxes than those of the BMPs.Aggregation from plates in HU-SBM,together with snow–graupel collisions,leads to a greater snow contribution to rain than those of the BMPs.Replacing HU-SBM’s fall speeds using the formulations of the BMPs after aggregating the discrete bin values to mass mixing ratios and total number concentrations increases net rain and rimed ice fluxes.Still,they are smaller in magnitude than bulk rain,NSSL hail,and Thompson graupel net fluxes near the surface.Conversely,the melting-layer net rimed ice fluxes are reduced when the fall speeds for the NSSL and Thompson simulations are calculated using HU-SBM fall speed formulations after discretizing the bulk particle size distributions(PSDs)into spectral bins.The results highlight precipitation sensitivity to storm dynamics,fall speed,hydrometeor evolution governed by process rates,and MP PSD design.

Analysis of Three Supercell Storms with Doppler Weather Radar Data

Three supercell storms on 24 June 2004（0624）,28 June 2003（0628）,and 27 September 2002（0927） induced different damages in Shandong Province.Storm 0927 was inferior in size and intensity to storms 0628 and 0624.The structure and evolvement of the three storms were analyzed in detail based on the WSR98D radar data in combination with weather charts.The results show that mesoscale surface convergence triggered release of instable energy,which resulted in severe convection.During the development stage,storms 0927,0628,and 0624 displayed multi-cell propagation,single-cell evolution,and multi-cell mergence,respectively.The storm tracks were similar：they were all right-moving supercell storms,i.e.,moving at an angle of 30°-70° to the right of the mean wind and at a speed of about 45%-70% of the mean wind speed.In the mature stage,the maximum reflectivity appeared at the low level in storm 0927,mid level in storm 0628,and mid-upper level in storm 0624.These storms possessed almost all typical features of supercell storms：weak echo region（WER）,bounded weak echo region（BWER）,and mesocyclone.An organized mesocyclone formed at the middle height of an updraft,deepened gradually downward and upward,and became a typical mid-level mesocyclone with strong updrafts.The vertical structures of airflows in the three storms were similar,i.e.,significant convergence at low level,nearly pure rotation at mid level,and divergent rotation at upper level.However,signatures of mid-level horizontal airflows in the three storms were different：at mid level,there was a single vortex in storm 0628,but a double-vortex flow pattern was seen in storms 0927 and 0624.The horizontal structure of the double-vortex flow was hard to be blown away by the environmental airflow,and thus the storms could persist for a longer period of time than the single vortex storm.

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.

Analyses and Forecasts of a Tornadic Supercell Outbreak Using a 3DVAR System Ensemble

As part of NOAA＇s ＂Warn-On-Forecast＂ initiative, a convective-scale data assimilation and prediction system was developed using the WRF-ARW model and ARPS 3DVAR data assimilation technique. The system was then evaluated using retrospective short-range ensemble analyses and probabilistic forecasts of the tornadic supercell outbreak event that occurred on 24 May 2011 in Oklahoma, USA. A 36-member multi-physics ensemble system provided the initial and boundary conditions for a 3-km convective-scale ensemble system. Radial velocity and reflectivity observations from four WSR-88 Ds were assimilated into the ensemble using the ARPS 3DVAR technique. Five data assimilation and forecast experiments were conducted to evaluate the sensitivity of the system to data assimilation frequencies, in-cloud temperature adjustment schemes, and fixed- and mixed-microphysics ensembles. The results indicated that the experiment with 5-min assimilation frequency quickly built up the storm and produced a more accurate analysis compared with the 10-min assimilation frequency experiment. The predicted vertical vorticity from the moist-adiabatic in-cloud temperature adjustment scheme was larger in magnitude than that from the latent heat scheme. Cycled data assimilation yielded good forecasts, where the ensemble probability of high vertical vorticity matched reasonably well with the observed tornado damage path. Overall, the results of the study suggest that the 3DVAR analysis and forecast system can provide reasonable forecasts of tornadic supercell storms.

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.