The high-incidence area was determined as 4°×4° regions where high incidence of tornadoes during 2004–2016 were located. In China, the highest frequency of tornado was labeled as JS, which was primarily located in Jiangsu Province. In the United States, the highest incidence region was located in central United States, labeled as UC. Special attention was given to the prime months for tornado occurrence in this study, and tornado season was defined as the three consecutive months when the most tornadoes struck. Tornado season was from June to August in JS, and lasted from April to June in UC. From 2004 to 2016, this yielded 875 tornadoes in UC during its tornado season, amounting to about four times that in JS.
Results showed that the difference in the total tornado counts between UC and JS was probably caused by their different abilities in generating multiple tornadoes. We defined the tornado event as the event whose tornadoes occurred within 6 hours and a 1°×1° area. The tornado event with only one tornado was defined as single-tornado event (STE), while the tornado event with more than one individual tornado was defined as the multiple-tornado event (MTE). During the tornado season, although the number of STEs in JS (168) was basically equal to that in UC (171), the number of the MTEs in JS (22) was much less than that in UC (187).
Our results showed that SRH1 could be a useful parameter for assessing the ability to produce multiple tornadoes. Based on NCEP reanalysis data, we found that during the tornado season, the 0-1 km storm-relative helicity (SRH1) and 0-6 km bulk shear (SHR6) in JS were much lower than UC, which well corresponded to the less MTEs in JS. Considering the great discrepancy in the number of MTEs between JS and UC, we selected two additional 4°×4° regions to compensate for this gap and further tested the relationship between the MTEs and the two environmental parameters. One region was the highest incidence area in the southeastern United States, labeled as USE1, whose MTEs were five times of JS. The other counterpart was USE2, which had nearly double MTEs of JS. In the four regions, the number of MTEs decreased monotonically as SRH1 decreased while SHR6 did not, which suggested that SRH1 may present a better description of the ability to generate MTEs rather than SHR6.
Our further analyses showed that the total tornado counts during peak month in a given region well corresponded with the magnitude of the significant tornado parameter (STP). JS had the peak tornado occurrence in July, while the peak month of UC was in May, and both of USE1 and USE2 faced their biggest tornado risk in April. The mean values of STP in the peak month of UC, USE1, JS and USE2 were 0.19, 0.11, 0.04, and 0.03 respectively, which were consistent with the decreasing tornado counts in peak month from UC (531), to USE1 (345), JS (114) and USE2 (83). The Spearman rank correlation coefficient between total tornado counts and the average STP in peak month from 2004 to 2016, was nearly 0.76.