Assessment of Tornado Alerting Performance for Canada

The Northern Tornadoes Project (NTP) completed a first independent assessment of national tornado warning alerting (watches and warnings) in Canada covering the 2019–2021 period. The NTP undertook this study in the spirit of open data, understanding tornado warning issues unique to this country, and improving tornado warning performance. Utilizing the NTP tornado event database for verification, tornado alerts were reviewed for accuracy and timeliness. For the 250 tornadoes that occurred during the study period–and using a definition of what constitutes a warning ‘hit’ developed for the study–the standard 2 × 2 contingency table scores were Probability of Detection = 0.23, FAR = 0.78, and CSI = 0.13. Over 70% of tornadoes had no tornado warning, including 35 EF2 tornadoes. The tornado warning results were compared with US National Weather Service tornado warning scores for the US and US states along the southern Canadian border to provide context. NTP also developed a ‘report card’ aimed at public and media consumption that took into consideration Environment and Climate Change Canada’s national performance targets for tornado warning Probability of Detection (POD) and lead time as well as tornado watch issuance. Using weighted scores for these criteria, NTP assigned a total score of 33.3/100, indicating significant room for improvement. A follow-up assessment was conducted for the 2022 tornado season in Canada following the same established procedures. It was found that the number of both tornado watches and tornado warnings had roughly doubled, resulting in a significant increase in the POD for tornado warnings to 0.35. The report card score also improved to a passing grade of 56.6/100. Further exploration of the results showed enhanced performance for tornadoes that occurred within Doppler radar range, when the parent thunderstorm involved supercell processes, and for tornadoes rated EF2 or higher. A number of recommendations are made aimed at further improvements to tornado alerting performance

Assessment of wind speeds along the damage path of the Alonsa, Manitoba EF4 tornado on 3 August 2018

Given the impracticality of attempting to directly measure wind speeds in tornadoes, wind speed estimation typically relies on the assessment of damage to structures and vegetation using classifications described in the Enhanced Fujita (EF) Scale. The advent of technology enabling the collection of large amounts of data, including detailed ground, drone, and aerial imagery, has led to a growth in research on non-conventional approaches for estimating tornado wind speeds. Research methods focused on defining the tornadic wind field based on forensic analysis of damage observations have shown promise for improving tornado assessments in a quantitative manner. In this study, novel methods for collecting forensic data following tornadoes are presented. Data from the Alonsa, MB tornado are applied to estimating the wind field along the damage path using treefall pattern analysis and threshold debris flight speed calculations. Comparison of the resulting wind speed estimates show reasonable agreement, with maximum speeds from both methods in the EF5 range. These research methods yield higher wind speeds than the maximum value obtained from the conventional EF-Scale assessment, which is in the low-end of the EF4 range based on a wood-frame house with sub-standard construction that was swept entirely from its foundation. Further work is still needed to make these methods operational for routine tornado intensity estimates

Retrieval of Peak Thunderstorm Wind Velocities Using WSR-88D Weather Radars

The current study develops a variant of the VAD method to retrieve thunderstorm peak event velocities using low-elevation WSR-88D radar scans. The main challenge pertains to the localized nature of thunderstorm winds, which complicates single-Doppler retrievals as it dictates the use of a limited spatial scale. Since VAD methods assume constant velocity in the fitted section, it is important that retrieved sections do not contain background flow. Accordingly, the current study proposes an image processing method to partition scans into regions, representing events and the background flows, that can be retrieved independently. The study compares the retrieved peak velocities to retrievals using another VAD method. The proposed technique is found to estimate peak event velocities that are closer to measured ASOS readings, making it more suitable for historical analysis. The study also compares the results of retrievals from over 2600 thunderstorm events from 19 radar–ASOS station combinations that are less than 10 km away from the radar. Comparisons of probability distributions of peak event velocities for ASOS readings and radar retrievals showed good agreement for stations within 4 km from the radar while more distant stations had a higher bias toward retrieved velocities compared to ASOS velocities. The mean absolute error for velocity magnitude increases with height ranging between 1.5 and 4.5 m s21. A proposed correction based on the exponential trend of mean errors was shown to improve the probability distribution comparisons, especially for higher velocity magnitudes