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Abstract Reanalysis proximity vertical profile attributes associated with long-track tornadoes [LTTs; pathlength ≥ 48 km (30 mi)] and short-track tornadoes [STTs; pathlengths < 48 km (30 mi)] for a total of 48 212 tornadoes with pathlengths ≥ 0.016 km (0.01 mi) from 1979 to 2022 in the United States were examined. Both longer- and shorter-track tornadoes were associated with vast ranges of mixed-layer convective available potential energy, together with relatively low mixed-layer lifted condensation level heights and minimal convective inhibition. A large range of 500–9000-m wind speeds and bulk wind differences, 500–3000-m streamwise vorticities, storm-relative helicities, and storm-relative wind speeds were found for STTs. In stark contrast, LTTs only occurred when these kinematic attributes were larger in amplitude through the troposphere, supporting previously documented associations between observed longer-track tornado pathlengths and faster-propagating parent storms. A novel parameter, heavily weighted by kinematic parameters and lightly weighted by thermodynamic parameters, outperformed the significant tornado parameter in differentiating environments that were more supportive of both LTTs and tornadoes rated R²= 0.79 between tornado pathlength and Bunkers’ approximate tornado duration (pathlength/V_Bunkers) call for improved understanding of mesocyclone periodicities, which impact tornado longevity, to improve tornado pathlength diagnoses and forecasts. Pragmatically, diagnosing LTT environments using vertical profile attributes, perhaps, is not so much a problem of determining when there might be higher expectations for LTTs, but rather a problem of when there might be lower expectations for LTTs, e.g., weaker kinematic attributes in the lower troposphere. Significance StatementThe majority of tornadoes have pathlengths less than a few kilometers. As tornado pathlengths increase, their probability of causing impacts to society also increases. We study >40 years of modeled atmospheric vertical profiles to better understand the environmental conditions that support long-track tornadoes (pathlength ≥ 48 km or ≥30 mi). Consistent with previous studies, long-track tornadoes occurred with substantially stronger vertical wind shear profiles and low-level winds compared to short-track tornadoes; however, most tornadoes did not form in environments with exceedingly large vertical instability, regardless of pathlength or intensity. A proposed composite long-track tornado parameter (LTTP) provided better discrimination between longer and shorter pathlength events compared to preexisting parameters. 

Abstract Tornado risk, as determined by the occurrence of atmospheric conditions that support tornado incidence, has exhibited robust spatial trends in the United States Southern Plains and Mid-South during recent decades. The consequences of these risk changes have not been fully explored, especially in conjunction with growing societal vulnerability. Herein, we assess how changes in risk and vulnerability over the last 40 years have collectively and individually altered tornado-housing impact potential. Results indicate that escalating vulnerability and exposure have outweighed the effects of spatially changing risk. However, the combination of increasing risk and exposure has led to a threefold increase in Mid-South housing exposure since 1980. Though Southern Plains tornado risk has decreased since 1980, amplifying exposure has led to more than a 50% increase in mean annual tornado-housing impact potential across the region. Stakeholders should use these findings to develop more holistic mitigation and resilience-building strategies that consider a dynamically changing tornado disaster landscape. 

Abstract Tornadoes in Chile seem to develop in what are called “high-shear, low-CAPE” (HSLC) environments. An analysis of convective parameters from the ERA5 reanalysis during 16 notable tornadoes in Chile showed that several increased markedly before the time of the reports. The significant tornado parameter (STP) was able to discriminate the timing and location of the tornadoes, even though it was not created with that goal. We established thresholds for the severe hazards in environments with reduced buoyancy (SHERBE) parameter (≥1) and the STP (≤−0.3) to further identify days favorable for tornado activity in Chile. The SHERBE and STP parameters were then used to conduct a climatological analysis from 1959 to 2021 of the seasonal, interannual, and latitudinal variations of the environments that might favor tornadoes. Both parameters were found to have a strong annual cycle. The largest magnitudes of STP were found to be generally confined to south-central Chile, in agreement with the (sparse) tornado record. The probability of a day with both SHERBE and STP values beyond their thresholds was greatest between May and August, which aligns with the months with the most tornado reports. The number of days with both SHERBE and STP beyond their respective thresholds was found to fluctuate interannually. This result warrants further study given the known interannual variability of synoptic and mesoscale weather in Chile. The results of this study extend our understanding of tornado environments in Chile and provide insight into their spatiotemporal variability. 

Abstract Elevated mixed layers (EMLs) influence the severe convective storm climatology in the contiguous United States (CONUS), playing an important role in the initiation, sustenance, and suppression of storms. This study creates a high-resolution climatology of the EML to analyze variability and potential changes in EML frequency and characteristics for the first time. An objective algorithm is applied to ERA5 to detect EMLs, defined in part as layers of steep lapse rates (≥8.0°C km⁻¹) at least 200 hPa thick, in the CONUS and northern Mexico from 1979 to 2021. EMLs are most frequent over the Great Plains in spring and summer, with a standard deviation of 4–10 EML days per year highlighting sizable interannual variability. Mean convective inhibition associated with the EML’s capping inversion suggests many EMLs prohibit convection, although—like nearly all EML characteristics—there is considerable spread and notable seasonal variability. In the High Plains, statistically significant increases in EML days (4–5 more days per decade) coincide with warmer EML bases and steeper EML lapse rates, driven by warming and drying in the low levels of the western CONUS during the study period. Additionally, increases in EML base temperatures result in significantly more EML-related convective inhibition over the Great Plains, which may continue to have implications for convective storm frequency, intensity, severe perils, and precipitation if this trend persists. Significance StatementElevated mixed layers (EMLs) play a role in the spatiotemporal frequency of severe convective storms and precipitation across the contiguous United States and northern Mexico. This research creates a detailed EML climatology from a modern reanalysis dataset to uncover patterns and potential changes in EML frequency and associated meteorological characteristics. EMLs are most common over the Great Plains in spring and summer, but show significant variability year-to-year. Robust increases in the number of days with EMLs have occurred since 1979 across the High Plains. Lapse rates associated with EMLs have trended steeper, in part due to warmer EML base temperatures. This has resulted in increasing EML convective inhibition, which has important implications for regional climate. 

Abstract Atmospheric angular momentum (AAM) is used to study the variability of Earth’s atmospheric circulation during the past 45 years, a time of considerable climate change. Using global AAM, two interdecadal states are defined covering the periods 1977–98 (hereinafter P1) and 1999–2022 (P2). Global AAM decreased from P1 to P2 and was accompanied by weakened subtropical jet streams in both hemispheres, strong convection around the northern Maritime Continent, and a strengthened sea surface temperature (SST) gradient across the tropical Pacific Ocean. The period differences project onto 1) internal interdecadal Pacific variability (IPV), 2) a postulated transient ocean thermostat response to greenhouse gas and aerosol emissions, and 3) circulation anomalies related to the ozone hole. During 1977–2023, the first two processes are forcing the climate toward larger Pacific Ocean SST gradients and a poleward expansion of the Indo-Pacific warm pool (IPWP), especially into the Northern Hemisphere. The ozone hole produces its own distinct pattern of anomalies in the Southern Hemisphere that tend to become persistent in the early 1990s. The zonal and vertical mean AAM variations during P1 have frequent westerly wind anomalies between 40°N and 40°S with poleward propagation on interannual time scales. During P2, the circulation is dominated by subtropical easterly wind anomalies, poleward-shifted jets, and weaker propagation. Locally, the zonal mean anomalies manifest as midlatitude ridges that lead to continental droughts. Case studies illustrate the weakened subtropical jet streams of P2 and examine the factors behind a transition to La Niña in early 2020 that maintains the P2 pattern. 

Abstract The Madden–Julian Oscillation (MJO) is the dominant mode of intraseasonal variability in the tropics and has a documented influence on extratropical extreme weather through modulation of synoptic atmospheric conditions. MJO phase has been correlated with anomalous tornado and severe hail frequency in the United States (US). However, the robustness of this relationship is unsettled, and the variability of physical pathways to modulation is poorly understood, despite the socioeconomic impacts that tornadoes and hail evoke. We approached this problem using pentad MJO indices and practically perfect severe weather hindcasts. MJO lifecycles were cataloged and clustered to document variability and potential pathways to enhanced subseasonal tornado and hail predictability. Statistically significant increases in US tornado and hail probabilities were documented 3–4 weeks following the period of the strongest upper-level divergence for the 53 active MJO events that propagated past the Maritime continent, contrasting with the 47 MJO events that experienced the barrier effect, during boreal spring 1979–2019. The 53 MJO events that propagated past the Maritime continent revealed three prevailing MJO evolutions—each containing unique pathways and modulation of US tornado and hail frequency—advancing our knowledge and capability to anticipate these hazards at extended lead times. 

On average, modern numerical weather prediction forecasts for daily tornado frequency exhibit no skill beyond day 10. However, in this extended-range lead window, there are particular model cycles that have exceptionally high forecast skill for tornadoes because of their ability to correctly simulate the future synoptic pattern. Here, model initial conditions that produced a more skillful forecast for tornadoes over the United States were exploited while also highlighting potential causes for low-skill cycles within the Global Ensemble Forecasting System, version 12 (GEFSv12). There were 88 high-skill and 91 low-skill forecasts in which the verifying day-10 synoptic pattern for tornado conditions revealed a western U.S. thermal trough and an eastern U.S. thermal ridge, a favorable configuration for tornadic storm occurrence. Initial conditions for high skill forecasts tended to exhibit warmer sea surface temperatures throughout the tropical Pacific Ocean and Gulf of Mexico, an active Madden–Julian oscillation, and significant modulation of Earth-relative atmospheric angular momentum. Low-skill forecasts were often initialized during La Niña and negative Pacific decadal oscillation conditions. Significant atmospheric blocking over eastern Russia—in which the GEFSv12 overforecast the duration and characteristics of the downstream flow—was a common physical process associated with low-skill forecasts. This work helps to increase our understanding of the common causes of high- or low-skill extended-range tornado forecasts and could serve as a helpful tool for operational forecasters. 

Abstract Previous studies have identified environmental characteristics that skillfully discriminate between severe and significant-severe weather events, but they have largely been limited by sample size and/or population of predictor variables. Given the heightened societal impacts of significant-severe weather, this topic was revisited using over 150 000 ERA5 reanalysis-derived vertical profiles extracted at the grid-point nearest—and just prior to—tornado and hail reports during the period 1996–2019. Profiles were quality-controlled and used to calculate 84 variables. Several machine learning classification algorithms were trained, tested, and cross-validated on these data to assess skill in predicting severe or significant-severe reports for tornadoes and hail. Random forest classification outperformed all tested methods as measured by cross-validated critical success index scores and area under the receiver operating characteristic curve values. In addition, random forest classification was found to be more reliable than other methods and exhibited negligible frequency bias. The top three most important random forest classification variables for tornadoes were wind speed at 500 hPa, wind speed at 850 hPa, and 0–500-m storm-relative helicity. For hail, storm-relative helicity in the 3–6 km and -10 to -30 °C layers, along with 0–6-km bulk wind shear, were found to be most important. A game theoretic approach was used to help explain the output of the random forest classifiers and establish critical feature thresholds for operational nowcasting and forecasting. A use case of spatial applicability of the random forest model is also presented, demonstrating the potential utility for operational forecasting. Overall, this research supports a growing number of weather and climate studies finding admirable skill in random forest classification applications.