The Influence of Assimilated Targeted Observations Upon Ensemble Forecasts of Convection Initiation

The influence of assimilating targeted meso-α- to synoptic-scale observations collected in the upstream, pre-convective environment upon subsequent short-range ensemble forecasts of convection initiation (CI) across the central United States for the fifteen aircraft missions conducted by the Mesoscale Predictability Experiment (MPEX) in May and June 2013 is evaluated in this study. Utilizing the ensemble Kalman filter implementation within the Data Assimilation Research Testbed software package as coupled to version 3.4.1 of the Advanced Research version of the Weather Research and Forecasting model, two nearly-identical thirty- member ensembles of short-range forecasts are conducted for each mission. Initial conditions for one ensemble are generated through a cycled data assimilation process that incorporates the targeted MPEX dropsonde observations from that day\u27s mission, and initial conditions for the other ensemble are generated through a cycled data assimilation process that excludes the targeted MPEX dropsonde observations. All forecasts for a given mission begin at 1500 UTC, extend forward 15 h, and are conducted on a domain encompassing the conterminous United States with 3 km horizontal grid spacing and 40 vertical levels. Verification is conducted over spatiotemporal thresholds of 50 km/0.5 h, 100 km/1 h, and 200 km/2 h of an observed CI event to assess the skill of probabilistic forecasts and quantify the influence that assimilating targeted observations has upon forecast skill for the events considered. Forecasts without the targeted observations have high probabilities of detection but also greatly overproduce CI, and the inclusion of targeted observations minimally improves some forecasts and minimally degrades other forecasts. Within the 100 km/1 h threshold, the targeted observations on average reduce distance errors between matched modeled and observed objects by 0.22 km while adding a time bias of 0.24 minutes. The forecast performance of specific cases as well as implications for CI predictability are discussed

Radar-Detected Mesocyclone Tilt in Tornadic and Nontornadic Supercells

While supercell thunderstorms are the storms with the greatest potential of producing tornadoes, the majority of supercells do not produce tornadoes. Recent work has demonstrated that low-level (LL) vertical wind shear and lifting condensation level (LCL) height in the storm inflow region are the most promising discriminators between tornadic and nontornadic supercells. It is anticipated that as the horizontal distance between the LL and mid-level (ML) mesocyclones (mesocyclone tilt) decreases, the likelihood and intensity of a tornado increase. It is expected that there is an orientation of both LL vertical shear and lower LCL height that results in a smaller mesocyclone tilt. This study builds a climatology of radar data to distinguish between tornadic and nontornadic supercells. Level-II and -III Weather Surveillance Radar-1988 Doppler data were collected and processed for a subset of isolated supercells in the contiguous United States from 2009 to 2015. From this initial climatology, LL and ML azimuthal wind shear maxima are located, representing the LL and ML mesocyclones, and the horizontal distance between each maximum is calculated during the evolution of each supercell. Results connecting the mesocyclone tilt to aspects of the near-storm environment, including LL shear magnitude and orientation and LCL height, will be discussed. Characteristics of the storm environment are obtained from proximity soundings derived from the Rapid Update Cycle and Rapid Refresh model analyses. Statistical and observational analyses of the climatology and of individual case studies will be presented Significantly tornadic supercells are associated with low LCL heights, strong southwesterly LL vertical wind shear, and critical angles below 100°. While smaller mesocyclone tilts are often associated with significant tornadoes, there is considerable overlap between distributions, suggesting that nontornadic and weakly tornadic storms may also have small tilts. There may be also a balance of shear orientation that moderates the position of outflow to result in a small positive or negative mesocyclone tilt. Further consideration should be given to the LL kinematic storm environment when discriminating between tornadic and nontornadic supercells

The Influence of PBL Parameterization on the Practical Predictability of Convection Initiation During the Mesoscale Predictability Experiment (MPEX)

This study evaluates the influence of planetary boundary layer (PBL) parameterizations on short-range (0-15 h) forecasts of convection initiation (CI) within convection-allowing ensembles that utilize sub-synoptic-scale observations collected during the Mesoscale Predictability Experiment (MPEX). Running five thirty-member ensembles with the Advanced Research Weather Research and Forecasting Model (WRF-ARW) with each differing only in the chosen PBL parameterization, forecast skill, PBL sensitivity on the environment in which CI occurred, and the variability within are examined. Three MPEX cases, 19-20 May 2013, 31 May-1 June 2013, and 8-9 June 2013 are considered, each characterized by a different large-scale flow pattern to analyze a wider spectrum of events. Using an object-based method to verify and analyze the forecasts of CI, it was found that none of the Five PBL schemes analyzed significantly improved the forecast skill. The non-local mixing PBL schemes, MYJ and QNSE, had in all cases higher probability of detection (POD) but consequently had a higher false alarm ratio (FAR) resulting from the models overproducing the number of CI objects, with all PBLs, and thus resulting in relative high bias scores as well. The CSI showed only subtle changes between PBL schemes suggesting no one PBL scheme drastically outperforms the other. The temporal distribution of errors associated with the “hits” in the CI object matching showed an approximate normal distribution around a mean of 0-s suggesting little systematic timing bias. While the spatial distribution of errors yielded skewed distributions with on average a mean (median) distance error of just over 44-km (28-km). Analysis of cumulative distribution functions (CDFs) of the “hits” highlighted limits to increased forecast skill beyond temporal and spatial thresholds of 60-min and 100-km. Mean error (ME) plots computed for surface features as well as vertical profiles in pre-convective environments highlighted biases in both the initial conditions as well as between ensembles. In agreement with previous studies, it was found that non-local mixing PBL schemes tend to produce PBLs that are too shallow, cool, and moist while local mixing schemes tend to be deeper, warmer, and drier as a function of the stronger (weaker) vertical mixing within the local (non-local) PBL schemes. Relative to the analysis of the vertical profiles, it was seen that the model has an inherent inability to accurately represent strong capping inversions in models across all PBL schemes suggesting an issue with the handling of vertical diffusion within the PBL and the implicit damping associated with the discretization schemes used within WRF

Radar-Detected Mesocyclone Tilt in Tornadic and Nontornadic Supercells

While supercell thunderstorms are the storms with the greatest potential of producing tornadoes, the majority of supercells do not produce tornadoes. Recent work has demonstrated that low-level (LL) vertical wind shear and lifting condensation level (LCL) height in the storm inflow region are the most promising discriminators between tornadic and nontornadic supercells. It is anticipated that as the horizontal distance between the LL and mid-level (ML) mesocyclones (mesocyclone tilt) decreases, the likelihood and intensity of a tornado increase. It is expected that there is an orientation of both LL vertical shear and lower LCL height that results in a smaller mesocyclone tilt. This study builds a climatology of radar data to distinguish between tornadic and nontornadic supercells. Level-II and -III Weather Surveillance Radar-1988 Doppler data were collected and processed for a subset of isolated supercells in the contiguous United States from 2009 to 2015. From this initial climatology, LL and ML azimuthal wind shear maxima are located, representing the LL and ML mesocyclones, and the horizontal distance between each maximum is calculated during the evolution of each supercell. Results connecting the mesocyclone tilt to aspects of the near-storm environment, including LL shear magnitude and orientation and LCL height, will be discussed. Characteristics of the storm environment are obtained from proximity soundings derived from the Rapid Update Cycle and Rapid Refresh model analyses. Statistical and observational analyses of the climatology and of individual case studies will be presented Significantly tornadic supercells are associated with low LCL heights, strong southwesterly LL vertical wind shear, and critical angles below 100°. While smaller mesocyclone tilts are often associated with significant tornadoes, there is considerable overlap between distributions, suggesting that nontornadic and weakly tornadic storms may also have small tilts. There may be also a balance of shear orientation that moderates the position of outflow to result in a small positive or negative mesocyclone tilt. Further consideration should be given to the LL kinematic storm environment when discriminating between tornadic and nontornadic supercells