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Barry N. Hanstrum, Graham A. Mills, Andrew Watson, John P. Monteverdi, and Charles A. Doswell III

Abstract

Examples of cool-season tornadic thunderstorms in California and southern Australia are examined. Almost one-half of the reported Australian tornadoes and the majority of those in California occur in the cool season. It is shown that in both areas the typical synoptic pattern shows an active midlatitude trough just upstream, with a strong jet streak aloft. In both areas the tornadic thunderstorms occur with weak to moderate levels of thermodynamic instability in the lower troposphere but with extremely high values of low-level positive and bulk shear. Statistical tests on null cases (nontornadic thunderstorms) in the Central Valley of California indicate that large values of 0–1-km shear provide a discriminator for more damaging (F1–F3) tornadoes, whereas bulk measures of buoyancy, such as CAPE, do not. Australian case studies and tornado proximity soundings show similar characteristics. A “cool-season tornadic thunderstorm potential” diagnostic for Australian conditions, based on regional NWP analyses and forecasts, is described. It identifies those locations at which negative 700-hPa surface lifted index, near-surface convergence, and surface–850 hPa shear >11 m s−1 are forecast to occur simultaneously, and it shows considerable potential as an objective alert for forecasters. During the winter of 1996, all nine occasions on which tornadoes were reported were successfully identified in 24-h forecasts. After a variety of assessments suggested the value of this diagnostic, and following positive forecaster feedback during preoperational trials, it became an operational forecast product in May of 2000.

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James A. Smith, Mary Lynn Baeck, Yu Zhang, and Charles A. Doswell III

Abstract

Supercell thunderstorms, the storm systems responsible for most tornadoes, have often been dismissed as flood hazards. The role of supercell thunderstorms as flood agents is examined through analyses of storm systems that occurred in Texas (5–6 May 1995), Florida (26 March 1992), Nebraska (20–21 June 1996), and Pennsylvania (18–19 July 1996). Particular attention is given to the “Dallas Supercell,” which resulted in 16 deaths from flash flooding and more than $1 billion in property damage during the evening of 5 May 1995. Rainfall analyses using Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity observations and special mesonet rain gauge observations from Dallas, Texas, show that catastrophic flash flooding resulted from exceptional rainfall rates at 5–60-min timescales. The spatial structure of extreme rainfall was linked to supercell structure and motion. The “Orlando Supercell” produced extreme rainfall rates (greater than 300 mm h−1) at 1–5-min timescales over a dense rain gauge network. The Nebraska and Pennsylvania storm systems produced record flooding over larger spatial scales than the Texas and Florida storms, by virtue of organization and motion of multiple storms over the same region. For both the Nebraska and Pennsylvania storms, extreme rainfall and tornadoes occurred in tandem. Severe rainfall measurement problems arise for supercell thunderstorms, both from conventional gauge networks and weather radar. It is hypothesized that supercell storms play a significant role in the “climatology” of extreme rainfall rates (100-yr return interval and greater) at short time intervals (1–60 min) in much of the central and eastern United States.

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Ding Jincai, Charles A. Doswell III, Donald W. Burgess, Michael P. Foster, and Michael L. Branick

Abstract

Two experimental forecasting projects, each called Mesoscale Applications Project (MAP), were conducted jointly by the National Severe Storms Laboratory and the National Weather Service Forecast Office at Norman, Oklahoma, during 1988 and 1989. This paper focuses primarily on the verification of the MAP'88 and MAP'89 experimental forecasts, and combines the results with those from a similar experiment run in 1987, to examine the evolution of forecast skill over that three-year period.

Results suggest that the severe-weather outlooks issued on a given experiment day exhibited good skill, with the skill being fairly stable over the three-year period studied. For outlooks issued the day before, the skill was notably higher in 1987 than in the subsequent years. Convective-mode forecasts ranged from poor to moderate skill levels, and did not change significantly from results obtained in 1987. Areal lightning forecasts were attempted in 1988 and 1989, with skill increasing more or less as the valid area increased, that area being defined as a circle ranging from 10 to 40 km of Norman. Advance outlooks for lightning, issued the day before the anticipated event, showed little or no skill. Some discussion of the possible reasons for the observed forecasting skill and its trends is presented. Several aspects of forecasting experiments in general are discussed also, based on experience during the MAP experiments.

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Romualdo Romero, Clemente Ramis, Sergio Alonso, Charles A. Doswell III, and David J. Stensrud

Abstract

A mesoscale numerical model with parameterized moist convection is applied to three cases involving heavy rainfall in the western Mediterranean region. Forecast precipitation fields, although not perfect when compared to the observations of rainfall, appear to have sufficient information to be considered useful forecasting guidance. The results illustrate that a good simulation for this type of event in a region with complex topography is strongly dependent on a good initialization and prediction of the low-level flow and water vapor distribution.

For two of the cases that have a marked synoptic-scale contribution, the simulations give reasonably accurate predictions of the precipitation distribution, although the amounts are generally underestimated. The third case exhibits relatively subtle synoptic-scale forcing and is dominated by isolated convective storms (mostly over the sea) that also produced severe thunderstorms (including tornadoes), and the prediction of precipitation is not as promising. Overall, the results are encouraging in terms of potential application of mesoscale models operationally in the western Mediterranean region. Additional experiments beyond the “control” simulations have been performed to isolate the influence of orography and water vapor flux from the Mediterranean Sea on the model simulations. This factor separation indicates that both effects can be important contributors to a successful forecast. Suggestions are offered for future efforts in pursuing the application of mesoscale models to this forecast problem.

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Frederick H. Carr, Phillip L. Spencer, Charles A. Doswell III, and Jeffrey D. Powell

Abstract

Two methods for objective analysis of wind profiler data in time-height space are proposed and compared. One is a straightforward adaptation of a procedure developed by Doswell for introducing time continuity into a sequence of spatial analyses. The second technique, named the correlation method, introduces a new rationale for selection of the Barnes filter parameter that is based on knowledge of the statistical structure of wind profiler data. The advantages and disadvantages of each method are discussed. It is noted that the correlation method, in principle, allows the deduction of consistent sampling intervals in time and space for the most dominant phenomena resolved by the data provided by a given atmospheric observing system. It is recommended that an objective analysis of wind profiler data be performed before single- or multiprofiler kinematic calculations are made.

In addition, it is shown that the positions of extrema in kinematic quantities computed from profiler triangles are relatively insensitive to the number of passes used in the analysis procedures. In fact, it is demonstrated that multipass Barnes-type schemes can overfit the original data, suggesting that a one-pass method may be preferable provided that the filter parameter is selected properly.

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David M. Schultz, Yvette P. Richardson, Paul M. Markowski, and Charles A. Doswell III

After tornado outbreaks or individual violent tornadoes occur in the central United States, media stories often attribute the location, number, or intensity of tornadoes to the “clash of air masses” between warm tropical air and cold polar air. This article argues that such a characterization of tornadogenesis is oversimplified, outdated, and incorrect. Airmass boundaries and associated temperature gradients can be important in tornadogenesis, but not in the ways envisioned on the synoptic scale with the clash-of-air-masses conceptual model. In fact, excessively strong horizontal temperature gradients (either on the synoptic scale or associated with a storm's own cool outflow) may be detrimental to tornadogenesis. Where adjacent air masses are relevant is through their vertical distribution that produces the requisite instability for the convective storm, but that instability is not directly related to the formation of tornadoes. Therefore, this article recommends that a greater effort be made to communicate accurately to the public the current scientific understanding of the conditions under which tornadoes are formed.

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Jonathan M. Davies, Charles A. Doswell III, Donald W. Burgess, and John F. Weaver

This paper considers a tornadic storm that struck south-central and eastern Kansas on 13 March 1990. Most of the devastation was associated with the first tornado from the storm as it passed through Hesston, Kansas. From the synoptic-scale and mesoscale viewpoints, the event was part of an outbreak of tornadoes on a day when the tornado threat was synoptically evident. Satellite imagery, combined with conventional data, suggest that the Hesston storm was affected by a preexisting, mesoscale outflow boundary laid down by morning storms. Radar and satellite data give clear indication of the supercellular character of the storm, despite limited radar data coverage.

Because of the considerable photographic coverage, several interesting features of the storm were recorded and are analyzed here. These include the following: 1) the movement and dissipation of a cloud band associated with an apparent rear-flank downdraft; 2) a transition from a rather large funnel through an apparent dissipation to the formation of a narrow funnel, during which the damage on the ground was continuous; and 3) a period of interaction between the first and second tornadoes.

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Andrew E. Mercer, Chad M. Shafer, Charles A. Doswell III, Lance M. Leslie, and Michael B. Richman

Abstract

Tornadic and nontornadic outbreaks occur within the United States and elsewhere around the world each year with devastating effect. However, few studies have considered the physical differences between these two outbreak types. To address this issue, synoptic-scale pattern composites of tornadic and nontornadic outbreaks are formulated over North America using a rotated principal component analysis (RPCA). A cluster analysis of the RPC loadings group similar outbreak events, and the resulting map types represent an idealized composite of the constituent cases in each cluster. These composites are used to initialize a Weather Research and Forecasting Model (WRF) simulation of each hypothetical composite outbreak type in an effort to determine the WRF’s capability to distinguish the outbreak type each composite represents.

Synoptic-scale pattern analyses of the composites reveal strikingly different characteristics within each outbreak type, particularly in the wind fields. The tornado outbreak composites reveal a strong low- and midlevel cyclone over the eastern Rockies, which is likely responsible for the observed surface low pressure system in the plains. Composite soundings from the hypothetical outbreak centroids reveal significantly greater bulk shear and storm-relative environmental helicity values in the tornado outbreak environment, whereas instability fields are similar between the two outbreak types. The WRF simulations of the map types confirm results observed in the composite soundings.

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Chad M. Shafer, Andrew E. Mercer, Lance M. Leslie, Michael B. Richman, and Charles A. Doswell III

Abstract

Recent studies, investigating the ability to use the Weather Research and Forecasting (WRF) model to distinguish tornado outbreaks from primarily nontornadic outbreaks when initialized with synoptic-scale data, have suggested that accurate discrimination of outbreak type is possible up to three days in advance of the outbreaks. However, these studies have focused on the most meteorologically significant events without regard to the season in which the outbreaks occurred. Because tornado outbreaks usually occur during the spring and fall seasons, whereas the primarily nontornadic outbreaks develop predominantly during the summer, the results of these studies may have been influenced by climatological conditions (e.g., reduced shear, in the mean, in the summer months), in addition to synoptic-scale processes.

This study focuses on the impacts of choosing outbreaks of severe weather during the same time of year. Specifically, primarily nontornadic outbreaks that occurred during the summer have been replaced with outbreaks that do not occur in the summer. Subjective and objective analyses of the outbreak simulations indicate that the WRF’s capability of distinguishing outbreak type correctly is reduced when the seasonal constraints are included. However, accuracy scores exceeding 0.7 and skill scores exceeding 0.5 using 1-day simulation fields of individual meteorological parameters, show that precursor synoptic-scale processes play an important role in the occurrence or absence of tornadoes in severe weather outbreaks. Low-level storm-relative helicity parameters and synoptic parameters, such as geopotential heights and mean sea level pressure, appear to be most helpful in distinguishing outbreak type, whereas thermodynamic instability parameters are noticeably both less accurate and less skillful.

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Chad M. Shafer, Andrew E. Mercer, Michael B. Richman, Lance M. Leslie, and Charles A. Doswell III

Abstract

The areal extent of severe weather parameters favorable for significant severe weather is evaluated as a means of identifying major severe weather outbreaks. The first areal coverage method uses kernel density estimation (KDE) to identify severe weather outbreak locations. A selected severe weather parameter value is computed at each grid point within the region identified by KDE. The average, median, or sum value is used to diagnose the event’s severity. The second areal coverage method finds the largest contiguous region where a severe weather parameter exceeds a specified threshold that intersects the KDE region. The severe weather parameter values at grid points within the parameter exceedance region are computed, with the average, median, or sum value used to diagnose the event’s severity. A total of 4057 severe weather outbreaks from 1979 to 2008 are analyzed. An event is considered a major outbreak if it exceeds a selected ranking index score (developed in previous work), and is a minor event otherwise. The areal coverage method is also compared to Storm Prediction Center (SPC) day-1 convective outlooks from 2003 to 2008. Comparisons of the SPC forecasts and areal coverage diagnoses indicate the areal coverage methods have similar skill to SPC convective outlooks in discriminating major and minor severe weather outbreaks. Despite a seemingly large sample size, the rare-events nature of the dataset leads to sample size sensitivities. Nevertheless, the findings of this study suggest that areal coverage should be tested in a forecasting environment as a means of providing guidance in future outbreak scenarios.

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