Assessing the Impacts of Proximity Sounding Criteria on the Climatology of Significant Tornado Environments

Abstract

Proximity sounding studies typically seek to optimize several trade-offs that involve somewhat arbitrary definitions of how to define a ''proximity sounding.'' More restrictive proximity criteria, which presumably produce results that are more characteristic of the near-storm environment, typically result in smaller sample sizes that can reduce the statistical significance of the results. Conversely, the use of broad proximity criteria will typically increase the sample size and the apparent robustness of the statistical analysis, but the sounding data may not necessarily be representative of near-storm environments, given the presence of mesoscale variability in the atmosphere. Previous investigations have used a wide range of spatial and temporal proximity criteria to analyze severe storm environments. However, the sensitivity of storm environment climatologies to the proximity definition has not yet been rigorously examined.In this study, a very large set (;1200) of proximity soundings associated with significant tornado reports is used to generate distributions of several parameters typically used to characterize severe weather environments. Statistical tests are used to assess the sensitivity of the parameter distributions to the proximity criteria.The results indicate that while soundings collected too far in space and time from significant tornadoes tend to be more representative of the larger-scale environment than of the storm environment, soundings collected too close to the tornado also tend to be less representative due to the convective feedback process. The storm environment itself is thus optimally sampled at an intermediate spatiotemporal range referred to here as the Goldilocks zone. Implications of these results for future proximity sounding studies are discussed.

Soil moisture–precipitation coupling: observations from the Oklahoma Mesonet and underlying physical mechanisms

“…These events were used to quantify the relationship between the land surface and the atmosphere. The 50 km threshold was selected based on the expected representativeness of the atmospheric profile (Potvin et al, 2010) over Lamont as well as the spatial autocorrelation of soil moisture in Oklahoma. Convective events were only retained if (1) they occurred within 50 km of Lamont, (2) afternoon precipitation was also recorded in Lamont, or (3) soil moisture percentiles in the grid cell where convection occurred had the same anomaly (wet or dry) as Lamont.…”

A severe thunderstorm climatology for Australia and associated thunderstorm environments

“…A problem with this type of approach is the sparse spatial distribution of rawinsonde stations relative to the location of recorded severe thunderstorms. Upperair soundings taken more than 200 kilometres away from a thunderstorm may not be representative of that storm's environment (Ryan 1992;Brooks et al 1994;Potvin et al 2010). The Australian rawinsonde network exceeds spatial distances of 200 km between sites in most cases (Ryan 1992).…”

“…Soundings in Australia are taken at 0000 GMT (10.00 am local time on the east coast), with a few locations recording at 1200 GMT (10.00 pm), neither of which are ideal for proximity soundings. This temporal proximity of a rawinsonde is important because advection processes and localised boundary effects can result in rapid modification of sounding environments (Potvin et al 2010). The alternative to rawinsonde data is to use reanalysis or model-derived 'pseudo-proximity' soundings (Lee 2002), which use grid points in proximity to severe thunderstorm reports.…”

Future Change of Tornadogenesis-Favorable Environmental Conditions in Japan Estimated by a 20-km-Mesh Atmospheric General Circulation Model

“…However, the 32-km horizontal resolution of NARR could be adequate because favorable environmental fields for tornado occurrence and their corresponding index values are distributed over a distance of 40-80 km from the site of the tornado (Potvin et al 2010). The NARR data used in this study were available every 6 h at the same times (0000, 0600, 1200, and 1800 UTC) as the climate experiment archive.…”