Watch and Outlook Scale Forecasting

How Much Does “Backing Aloft” Actually Impact a Supercell?

Matthew D. Parker


Among forecasters and storm chasers, there is a common perception that hodographs with counterclockwise curvature or kinking in the midlevels (sometimes called backing aloft or veer–back–veer profiles) are unfavorable for long-lived supercells and tornadoes. This study reviews and then evaluates several possible explanations for the purported negative effect of backing aloft. As a controlled hypothesis test, simulated supercells are initiated within a range of idealized wind profiles, many of which include representative counterclockwise kinks or bends in their hodographs. In these experiments, the short-term, direct impacts of backing aloft upon supercell maintenance are generally small. Backing aloft does modify the component of vertical accelerations linked to updraft–shear interactions, but these changes generally occur well above the level of free convection (LFC), and they are generally offset by substantial upward accelerations attributable to other processes (e.g., within-storm rotation and positive buoyancy). In these simulations, the longevity of isolated supercells seems to be most directly hindered in environments with very low storm-relative helicity (SRH) or else (for a line of supercells) substantial along-line flow in the upper troposphere. Although these two disrupting properties can accompany backing aloft, they are neither universally nor exclusively associated with it. From the perspective of storm dynamics, it seems advisable to focus on SRH and along-line flow in the environment, rather than the presence (or absence) of backing aloft in the wind profile.

Cold-season tornadoes: Climatological and meteorological insights

Samuel Childs, Russ Schumacher, John Allen


Tornadoes that occur during the cold season, defined here as November–February (NDJF), pose many societal risks, yet less attention has been given to their climatological trends and variability than their warm-season counterparts, and their meteorological environments have been studied relatively recently. This study aims to advance the current state of knowledge of cold-season tornadoes through analysis of these components. A climatology of all (E)F1–(E)F5 NDJF tornadoes from 1953 to 2015 across a domain of 25°–42.5°N, 75°–100°W was developed. An increasing trend in cold-season tornado occurrence was found across much of the southeastern United States, with a bull’s-eye in western Tennessee, while a decreasing trend was found across eastern Oklahoma. Spectral analysis reveals a cyclic pattern of enhanced NDJF counts every 3–7 years, coincident with the period of ENSO. La Niña episodes favor enhanced NDJF counts, but a stronger relationship was found with the Arctic Oscillation (AO). From a meteorological standpoint, the most-tornadic and least-tornadic NDJF seasons were compared using NCEP–NCAR reanalysis data of various severe weather and tornado parameters. The most-tornadic cold seasons are characterized by warm and moist conditions across the Southeast, with an anomalous mean trough across the western United States. In addition, analysis of the convective mode reveals that NDJF tornadoes are common in both discrete and linear storm modes, yet those associated with discrete supercells are more deadly. Taken together, the perspectives presented here provide a deeper understanding of NDJF tornadoes and their societal impacts, an understanding that serves to increase public awareness and reduce human casualty.

Probabilistic Verification of Storm Prediction Center Convective Outlooks

Gregory Herman, Erik Nielsen, Russ Schumacher


Eight years’ worth of day 1 and 4.5 years’ worth of day 2–3 probabilistic convective outlooks from the Storm Prediction Center (SPC) are converted to probability grids spanning the continental United States (CONUS). These results are then evaluated using standard probabilistic forecast metrics including the Brier skill score and reliability diagrams. Forecasts are gridded in two different ways: one with a high-resolution grid and interpolation between probability contours and another on an 80-km-spaced grid without interpolation. Overall, the highest skill is found for severe wind forecasts and the lowest skill is observed for tornadoes; for significant severe criteria, the opposite discrepancy is observed, with highest forecast skill for significant tornadoes and approximately no overall forecast skill for significant severe winds. Highest climatology-relative skill is generally observed over the central and northern Great Plains and Midwest, with the lowest—and often negative—skill seen in the West, southern Texas, and the Atlantic Southeast. No discernible year-to-year trend in skill was identified; seasonally, forecasts verified the best in the spring and late autumn and worst in the summer and early autumn. Forecasts are also evaluated in CAPE-versus-shear parameter space; forecasts struggle most in very low shear but also in high-shear, low-CAPE environments. In aggregate, forecasts for all variables verified more skillfully using interpolated probability grids, suggesting utility in interpreting forecasts as a continuous field. Forecast reliability results depend substantially on the interpretation of the forecast fields, but day 1 and day 2–3 tornado outlooks consistently exhibit an underforecast bias.