Quantifying relationships between environmental factors and power dissipation on the most prolific days in the largest tornado “outbreaks”

Schroder, Zoe; Elsner, James B.

doi:10.1002/joc.6388

Cited by 12 publications

(20 citation statements)

References 36 publications

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“…Then, we divide the space-time difference by 15 m s −1 to account for the average speed of tornado-producing storms, which is commensurate with the magnitude of the steeringlevel wind field. Additional detail about the clustering procedure, along with a comparison of the resulting clusters to well-known outbreaks, is available in [43].…”

Section: Tornado Clustersmentioning

confidence: 99%

“…Tornado outbreaks are getting more expansive and more destructive on average. Although research indicates that tornado days are declining annually, tornado counts and accumulated tornado power (ATP) are increasing on these days [15,17,36,38,39,43,44,55,56]. Research shows that convective available potential energy (CAPE), shallow-layer bulk shear (SLBS), and deep-layer bulk shear (DLBS) directly influence tornado and casualty counts and ATP in outbreaks with at least ten tornadoes [17,20,43,44].…”

Section: Introductionmentioning

confidence: 99%

“…Although research indicates that tornado days are declining annually, tornado counts and accumulated tornado power (ATP) are increasing on these days [15,17,36,38,39,43,44,55,56]. Research shows that convective available potential energy (CAPE), shallow-layer bulk shear (SLBS), and deep-layer bulk shear (DLBS) directly influence tornado and casualty counts and ATP in outbreaks with at least ten tornadoes [17,20,43,44]. However, it is challenging to attribute these changes in outbreak characteristics to climate change, although the environmental factors will likely change in the future [6,11,12,14,17,31,45,46,58].…”

Section: Introductionmentioning

confidence: 99%

“…First, we assign each global climate variable to its respective cluster. Next, we fit a series of regression models to cluster-level environmental data and climate variables on convective days (24-hour period; 12 UTC to 12 UTC) when the number of tornadoes is at least ten [see [43]]. These models quantify the relationships that exist between climate variables and environmental conditions associated with tornado outbreaks.…”

Section: Introductionmentioning

confidence: 99%

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Regional SST and SLP conditions related to tornado 'outbreak' environments 15 days later

Schroder¹

2021

Preprint

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Global climate features are known to influence tornado frequency in the U.S., but more work needs to focus on understanding the extent to which climate variables contribute to increases in CAPE and shear on days with an outbreak of at least ten tornadoes. Here the authors quantify the conditional relationships between precursor SST and SLP variables and localized extremes of CAPE and shear associated with large outbreaks. They do this by fitting linear regressions to global climate variables averaged over the fifteen days before the outbreak to estimate the changes in CAPE and shear on days with at least ten tornadoes. Results show that for every 1° increase in the SST gradient between the Gulf of Alaska and the Caribbean, DLBS increases by 0.88 m s¯¹, SLBS increases by 0.62 m s¯¹, and CAPE decreases by 50.6 J kg¯¹, conditional on at least ten tornadoes, and holding the other variables constant. Further, results show that for every 1° E increase in longitude, DLBS increases by 0.15 m s¯¹, SLBS increases by 0.38 m s¯¹, and CAPE decreases by 39.3 J kg¯¹, conditional on at least ten tornadoes, and holding the other variables constant. Additionally, SLBS is the only environmental factor that has a significant upward annual trend.

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Section: Tornado Clustersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Regional SST and SLP conditions related to tornado 'outbreak' environments 15 days later

Schroder¹

2021

Preprint

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“…Such multi-day clusters of hail days can cause substantial damage in a short time. Multi-day clusters of severe weather and associated high impacts have also been reported from North America (Shafer, C., Doswell III, 2012;Trapp, 2014;Schroder and Elsner, 2020;Gensini et al, 2019). Although the atmospheric conditions associated with hail in Switzerland and central Europe are well studied (e.g., Huntrieser et al, 1997;Madonna et al, 2018;Taszarek et al, 2017;Púčik et al, 2015;Brooks, 2009;Púčik et al, 01 Nov. 2019;Kunz et al, 2020), little is known about the large-scale weather conditions that lead to multi-day clusters of hail days.…”

Section: Introductionmentioning

confidence: 98%

Multi-day hail clusters and isolated hail days in Switzerland – large-scale flow conditions and precursors

Barras

Martius

Nisi

et al. 2021

Preprint

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Abstract. In Switzerland, hail regularly occurs in multi-day hail clusters. The atmospheric conditions prior to and during multi-day hail clusters are described and contrasted to the conditions prior to and during isolated hail days. The analysis focuses on hail days that occurred between April and September 2002–2019 within 140 km of the Swiss radar network. Hail days north and south of the Alps are defined using a minimum area threshold of a radar-based hail product. Multi-day clusters are defined as 5-day windows containing 4 or 5 hail days and isolated hail days as 5-day windows containing a single hail day. The reanalysis ERA-5 is used to study the large-scale flow in combination with objectively identified cold fronts, atmospheric blocking events, and a weather type classification. Both north and south of the Alps, isolated hail days have frequency maxima in May and August-September whereas clustered hail days occur mostly in July and August. Composites of atmospheric variables indicate a more stationary and meridionally amplified atmospheric flow both north and south of the Alps during multi-day hail clusters. On clustered hail days north of the Alps, blocks are more frequent over the North Sea, and surface fronts are located farther from Switzerland than on isolated hail days. Clustered hail days north of the Alps are also characterized by significantly higher convective available potential energy (CAPE) values, warmer daily maximum surface temperatures, and higher atmospheric moisture content than isolated hail days. Hence, both stationary flow conditions and anomalous amounts of moisture are necessary for multi-day hail clusters on the north side. In contrast, differences in CAPE on the south side between clustered hail days and isolated hail days are small. The mean sea level pressure south of the Alps is significantly deeper, the maximum temperature is colder, and local moisture is significantly lower on isolated hail days. Both north and south of the Alps, the upper-level atmospheric flow over the eastern Atlantic is meridionally more amplified three days prior to clustered hail days than prior to isolated days. Moreover, Moreover blocking occurs prior to more than 10 % of clustered hail days over Scandinavia, but no blocks occur prior to isolated hail days. Half of the clustered hail days south of the Alps are also clustered north of the Alps. On hail days clustering only south of the Alps, fronts are more frequently located on the Alpine ridge, and local low- level winds are stronger. The temporal clustering of hail days is coupled to specific synoptic- and local- scale flow conditions, this information may be exploited for short to medium-range forecasts of hail in Switzerland.

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Climatology of 500‐hPa geopotential height anomalies associated with May tornado outbreaks in the United States

Ćwik

McPherson

Richman

et al. 2022

Intl Journal of Climatology

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This study supports efforts directed toward research on large-scale atmospheric patterns and on the variability of tornado outbreaks. Specifically, we applied rotated principal component analysis to identify synoptic-scale patterns of 500-hPa geopotential height associated with tornado outbreaks in the United States. We created a database of historic tornado outbreaks using kernel density estimation on events composed of at least seven tornadoes of magnitude (E)F2 or higher (major tornado outbreaks) that occurred in May from 1950 to 2019 (91 events). Results of the analysis show that the first three principal components explained the majority, that is, 74% of the total variation. Based on the analysis of congruence coefficients, the Promax oblique transformation was chosen as the most representative rotation in portraying physically meaningful modes and resulted in three main atmospheric patterns. Two of these, to the best of our knowledge, have not been yet identified as the most representative of tornado outbreaks in any previous studies. Additionally, results suggest that although synoptic patterns associated with major May tornado outbreaks remain the same over time, partial variability in their geographic location exhibits some cyclical behaviour, especially on decadal and multidecadal scales. Identifying these patterns can serve as a first step in determining how they may change under anthropogenic climate change in the future. K E Y W O R D S 500-hPa geopotential height, climate change, climatology, large-scale atmospheric patterns, principal component analysis, tornado outbreaks, United States

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Quantifying relationships between environmental factors and power dissipation on the most prolific days in the largest tornado “outbreaks”

Cited by 12 publications

References 36 publications

Regional SST and SLP conditions related to tornado 'outbreak' environments 15 days later

Regional SST and SLP conditions related to tornado 'outbreak' environments 15 days later

Multi-day hail clusters and isolated hail days in Switzerland – large-scale flow conditions and precursors

Climatology of 500‐hPa geopotential height anomalies associated with May tornado outbreaks in the United States

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