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Changes over the years in tornado-warning performance in the United States can be modeled from the perspective of signal detection theory. From this view, it can be seen that there have been distinct periods of change in performance, most likely associated with deployment of radars, and changes in scientific understanding and training. The model also makes it clear that improvements in the false alarm ratio can only occur at the cost of large decreases in the probability of detection, or with large improvements in the overall quality of the warning system.
Changes over the years in tornado-warning performance in the United States can be modeled from the perspective of signal detection theory. From this view, it can be seen that there have been distinct periods of change in performance, most likely associated with deployment of radars, and changes in scientific understanding and training. The model also makes it clear that improvements in the false alarm ratio can only occur at the cost of large decreases in the probability of detection, or with large improvements in the overall quality of the warning system.
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No abstract available.
Abstract
The term “tornado outbreak” appeared in the meteorological literature in the 1950s and was used to highlight severe weather events with multiple tornadoes. The exact meaning of “tornado outbreak,” however, evolved over the years. Depending on the availability of scientific data, technological advancements, and the intended purpose of these definitions, authors offered a diverse set of approaches to shape the perception and applications of the term “tornado outbreak.” This paper reviews over 200 peer-reviewed publications—by decade—to outline the evolving nature of the “tornado outbreak” definition and to examine the changes in the “tornado outbreak” definition or its perception. A final discussion highlights the importance, limitations, and potential future evolution of what defines a “tornado outbreak.”
Abstract
The term “tornado outbreak” appeared in the meteorological literature in the 1950s and was used to highlight severe weather events with multiple tornadoes. The exact meaning of “tornado outbreak,” however, evolved over the years. Depending on the availability of scientific data, technological advancements, and the intended purpose of these definitions, authors offered a diverse set of approaches to shape the perception and applications of the term “tornado outbreak.” This paper reviews over 200 peer-reviewed publications—by decade—to outline the evolving nature of the “tornado outbreak” definition and to examine the changes in the “tornado outbreak” definition or its perception. A final discussion highlights the importance, limitations, and potential future evolution of what defines a “tornado outbreak.”
The question of who is the “best” forecaster in a particular media market is one that the public frequently asks. The authors have collected approximately one year's forecasts from the National Weather Service and major media presentations for Oklahoma City. Diagnostic verification procedures indicate that the question of best does not have a clear answer. All of the forecast sources have strengths and weaknesses, and it is possible that a user could take information from a variety of sources to come up with a forecast that has more value than any one individual source provides. The analysis provides numerous examples of the utility of a distributions-oriented approach to verification while also providing insight into the problems the public faces in evaluating the array of forecasts presented to them.
The question of who is the “best” forecaster in a particular media market is one that the public frequently asks. The authors have collected approximately one year's forecasts from the National Weather Service and major media presentations for Oklahoma City. Diagnostic verification procedures indicate that the question of best does not have a clear answer. All of the forecast sources have strengths and weaknesses, and it is possible that a user could take information from a variety of sources to come up with a forecast that has more value than any one individual source provides. The analysis provides numerous examples of the utility of a distributions-oriented approach to verification while also providing insight into the problems the public faces in evaluating the array of forecasts presented to them.
Abstract
Long-term trends in the historical frequency of environments supportive of atmospheric convection are unclear, and only partially follow the expectations of a warming climate. This uncertainty is driven by the lack of unequivocal changes in the ingredients for severe thunderstorms (i.e., conditional instability, sufficient low-level moisture, initiation mechanism, and vertical wind shear). ERA5 hybrid-sigma data allow for superior characterization of thermodynamic parameters including convective inhibition, which is very sensitive to the number of levels in the lower troposphere. Using hourly data we demonstrate that long-term decreases in instability and stronger convective inhibition cause a decline in the frequency of thunderstorm environments over the southern United States, particularly during summer. Conversely, increasingly favorable conditions for tornadoes are observed during winter across the Southeast. Over Europe, a pronounced multidecadal increase in low-level moisture has provided positive trends in thunderstorm environments over the south, central, and north, with decreases over the east due to strengthening convective inhibition. Modest increases in vertical wind shear and storm-relative helicity have been observed over northwestern Europe and the Great Plains. Both continents exhibit negative trends in the fraction of environments with likely convective initiation. This suggests that despite increasing instability, thunderstorms in a warming climate may be less likely to develop due to stronger convective inhibition and lower relative humidity. Decreases in convective initiation and resulting precipitation may have long-term implications for agriculture, water availability, and the frequency of severe weather such as large hail and tornadoes. Our results also indicate that trends observed over the United States cannot be assumed to be representative of other continents.
Abstract
Long-term trends in the historical frequency of environments supportive of atmospheric convection are unclear, and only partially follow the expectations of a warming climate. This uncertainty is driven by the lack of unequivocal changes in the ingredients for severe thunderstorms (i.e., conditional instability, sufficient low-level moisture, initiation mechanism, and vertical wind shear). ERA5 hybrid-sigma data allow for superior characterization of thermodynamic parameters including convective inhibition, which is very sensitive to the number of levels in the lower troposphere. Using hourly data we demonstrate that long-term decreases in instability and stronger convective inhibition cause a decline in the frequency of thunderstorm environments over the southern United States, particularly during summer. Conversely, increasingly favorable conditions for tornadoes are observed during winter across the Southeast. Over Europe, a pronounced multidecadal increase in low-level moisture has provided positive trends in thunderstorm environments over the south, central, and north, with decreases over the east due to strengthening convective inhibition. Modest increases in vertical wind shear and storm-relative helicity have been observed over northwestern Europe and the Great Plains. Both continents exhibit negative trends in the fraction of environments with likely convective initiation. This suggests that despite increasing instability, thunderstorms in a warming climate may be less likely to develop due to stronger convective inhibition and lower relative humidity. Decreases in convective initiation and resulting precipitation may have long-term implications for agriculture, water availability, and the frequency of severe weather such as large hail and tornadoes. Our results also indicate that trends observed over the United States cannot be assumed to be representative of other continents.
Abstract
Two novel approaches to extending the range of prediction for environments conducive to severe thunderstorm events are described. One approach charts Climate Forecast System, version 2 (CFSv2), run-to-run consistency of the areal extent of severe thunderstorm environments using grid counts of the supercell composite parameter (SCP). Visualization of these environments is charted for each 45-day CFSv2 run initialized at 0000 UTC. CFSv2 ensemble-mean forecast maps of SCP coverage over the contiguous United States are also produced for those forecasts meeting certain criteria for high-impact weather. The applicability of this approach to the severe weather prediction challenge is illustrated using CFSv2 output for a series of severe weather episodes occurring in March and April 2014. Another approach, possibly extending severe weather predictability from CFSv2, utilizes a run-cumulative time-averaging technique of SCP grid counts. This process is described and subjectively verified with severe weather events from early 2014.
Abstract
Two novel approaches to extending the range of prediction for environments conducive to severe thunderstorm events are described. One approach charts Climate Forecast System, version 2 (CFSv2), run-to-run consistency of the areal extent of severe thunderstorm environments using grid counts of the supercell composite parameter (SCP). Visualization of these environments is charted for each 45-day CFSv2 run initialized at 0000 UTC. CFSv2 ensemble-mean forecast maps of SCP coverage over the contiguous United States are also produced for those forecasts meeting certain criteria for high-impact weather. The applicability of this approach to the severe weather prediction challenge is illustrated using CFSv2 output for a series of severe weather episodes occurring in March and April 2014. Another approach, possibly extending severe weather predictability from CFSv2, utilizes a run-cumulative time-averaging technique of SCP grid counts. This process is described and subjectively verified with severe weather events from early 2014.
Abstract
In this work, we use 8 years (2014–21) of Operational Programme for the Exchange of Weather Radar Information (OPERA) radar data, ESWD severe weather reports, and arrival time difference (ATD) lightning detection network (ATDnet) data to create a climatology of quasi-linear convective systems (QLCSs) across Europe. In the first step, 15-min radar scans were used to identify 1475 QLCS polygons. Severe weather reports, lightning data, and morphological properties were used to classify QLCSs according to their intensity into 1151 marginal (78.0%), 272 moderate (18.5%), and 52 derecho (3.5%) events. The manual evaluation led to the recognition of QLCS morphological and precipitation archetypes, areal extent, duration, speed, forward motion, width, length, accompanying hazards, injuries, and fatalities. Results indicate that QLCSs are the most frequent during summer in central Europe, while in southern Europe, their occurrence is extended to late autumn. A bow echo feature occurred in around 29% of QLCS cases, while a mesoscale convective vortex occurred in almost 9%. Among precipitation modes, trailing and embedded stratiform types accounted for around 50% of QLCSs. The most frequent hazard accompanying QLCSs was lightning (taking up on average 94.4% of the area impacted by QLCS), followed by severe wind gusts (7.9%), excessive precipitation (6.1%), large hail (2.9%), and tornadoes (0.5%). Derechos had the largest coverage of severe wind reports (49.8%), while back-building QLCSs were the most prone to excessive precipitation events (13.5%). QLCSs caused 104 fatalities and 886 injuries. Severe wind gusts were responsible for 87.6% of fatalities and 73.6% of injuries. Nearly half of all fatalities and injuries were associated with only the 10 most impactful QLCS events, mostly warm-season derechos.
Abstract
In this work, we use 8 years (2014–21) of Operational Programme for the Exchange of Weather Radar Information (OPERA) radar data, ESWD severe weather reports, and arrival time difference (ATD) lightning detection network (ATDnet) data to create a climatology of quasi-linear convective systems (QLCSs) across Europe. In the first step, 15-min radar scans were used to identify 1475 QLCS polygons. Severe weather reports, lightning data, and morphological properties were used to classify QLCSs according to their intensity into 1151 marginal (78.0%), 272 moderate (18.5%), and 52 derecho (3.5%) events. The manual evaluation led to the recognition of QLCS morphological and precipitation archetypes, areal extent, duration, speed, forward motion, width, length, accompanying hazards, injuries, and fatalities. Results indicate that QLCSs are the most frequent during summer in central Europe, while in southern Europe, their occurrence is extended to late autumn. A bow echo feature occurred in around 29% of QLCS cases, while a mesoscale convective vortex occurred in almost 9%. Among precipitation modes, trailing and embedded stratiform types accounted for around 50% of QLCSs. The most frequent hazard accompanying QLCSs was lightning (taking up on average 94.4% of the area impacted by QLCS), followed by severe wind gusts (7.9%), excessive precipitation (6.1%), large hail (2.9%), and tornadoes (0.5%). Derechos had the largest coverage of severe wind reports (49.8%), while back-building QLCSs were the most prone to excessive precipitation events (13.5%). QLCSs caused 104 fatalities and 886 injuries. Severe wind gusts were responsible for 87.6% of fatalities and 73.6% of injuries. Nearly half of all fatalities and injuries were associated with only the 10 most impactful QLCS events, mostly warm-season derechos.
Despite the meteorological community's long-term interest in weather-society interactions, efforts to understand socioeconomic aspects of weather prediction and to incorporate this knowledge into the weather prediction system have yet to reach critical mass. This article aims to reinvigorate interest in societal and economic research and applications (SERA) activities within the meteorological and social science communities by exploring key SERA issues and proposing SERA priorities for the next decade.
The priorities were developed by the authors, building on previous work, with input from a diverse group of social scientists and meteorologists who participated in a SERA workshop in August 2006. The workshop was organized to provide input to the North American regional component of THORPEX: A Global Atmospheric Research Programme, but the priorities identified are broadly applicable to all weather forecast research and applications.
To motivate and frame SERA activities, we first discuss the concept of high-impact weather forecasts and the chain from forecast creation to value realization. Next, we present five interconnected SERA priority themes—use of forecast information in decision making, communication of forecast uncertainty, user-relevant verification, economic value of forecasts, and decision support— and propose research integrated across the themes.
SERA activities can significantly improve understanding of weather-society interactions to the benefit of the meteorological community and society. However, reaching this potential will require dedicated effort to bring together and maintain a sustainable interdisciplinary community.
Despite the meteorological community's long-term interest in weather-society interactions, efforts to understand socioeconomic aspects of weather prediction and to incorporate this knowledge into the weather prediction system have yet to reach critical mass. This article aims to reinvigorate interest in societal and economic research and applications (SERA) activities within the meteorological and social science communities by exploring key SERA issues and proposing SERA priorities for the next decade.
The priorities were developed by the authors, building on previous work, with input from a diverse group of social scientists and meteorologists who participated in a SERA workshop in August 2006. The workshop was organized to provide input to the North American regional component of THORPEX: A Global Atmospheric Research Programme, but the priorities identified are broadly applicable to all weather forecast research and applications.
To motivate and frame SERA activities, we first discuss the concept of high-impact weather forecasts and the chain from forecast creation to value realization. Next, we present five interconnected SERA priority themes—use of forecast information in decision making, communication of forecast uncertainty, user-relevant verification, economic value of forecasts, and decision support— and propose research integrated across the themes.
SERA activities can significantly improve understanding of weather-society interactions to the benefit of the meteorological community and society. However, reaching this potential will require dedicated effort to bring together and maintain a sustainable interdisciplinary community.
Collaborative activities between operational forecasters and meteorological research scientists have the potential to provide significant benefits to both groups and to society as a whole, yet such collaboration is rare. An exception to this state of affairs is occurring at the National Severe Storms Laboratory (NSSL) and Storm Prediction Center (SPC). Since the SPC moved from Kansas City to the NSSL facility in Norman, Oklahoma in 1997, collaborative efforts between researchers and forecasters at this facility have begun to flourish. This article presents a historical background for this interaction and discusses some of the factors that have helped this collaboration gain momentum. It focuses on the 2001 Spring Program, a collaborative effort focusing on experimental forecasting techniques and numerical model evaluation, as a prototype for organized interactions between researchers and forecasters. In addition, the many tangible and intangible benefits of this unusual working relationship are discussed.
Collaborative activities between operational forecasters and meteorological research scientists have the potential to provide significant benefits to both groups and to society as a whole, yet such collaboration is rare. An exception to this state of affairs is occurring at the National Severe Storms Laboratory (NSSL) and Storm Prediction Center (SPC). Since the SPC moved from Kansas City to the NSSL facility in Norman, Oklahoma in 1997, collaborative efforts between researchers and forecasters at this facility have begun to flourish. This article presents a historical background for this interaction and discusses some of the factors that have helped this collaboration gain momentum. It focuses on the 2001 Spring Program, a collaborative effort focusing on experimental forecasting techniques and numerical model evaluation, as a prototype for organized interactions between researchers and forecasters. In addition, the many tangible and intangible benefits of this unusual working relationship are discussed.
