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K. R. Thompson
,
R. F. Marsden
, and
D. G. Wright

Abstract

A simple, approximate formula for mean wind stress is given in terms of the mean and variance of the wind fluctuations over the averaging period. The formula is nonlinear with respect to the mean wind speed.

The formula is tested using 3 h wind observations from eight North Atlantic Ocean Weather Ships. Mean wind stress is calculated 1) by vector averaging the 3 h wind stresses and 2) by applying the approximate formula. For an averaging period of 4 months the two methods agree to within ±0.025 Pa, 95% of the time. For an averaging period of 1 month the approximate formula slightly overestimates the stress. This is due to skewness in the probability density function of the observed 3 h wind fluctuations. An expression for the modification of the mean stress due to skewness is given.

A straightforward method is described for the estimation of vector mean wind and variance fields, and thus mean stress fields, over the open ocean. To cheek the method, the long-term stress field of the North Atlantic, and the seasonal Sverdrup transport across 31°N, are computed and compared with the values given by Willebrand, and Bunker and Leetma. Good agreement is obtained. The zonally integrated Sverdrup transport across 45°N is also calculated and shown to exhibit significant interannual fluctuations.

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Owen E. Thompson
,
Jae K. Eom
, and
Joseph R. Wagenhofer

Abstract

Preliminary results of a study to assess the vertical resolving power of NOAA satellite VTPR radiation measurements used to estimate temperature profiles are presented. A brief analysis of the trade-off between vertical resolution and noise effects is given, patterned after the approach of Backus and Gilbert and of Conrath. Also given are results of a more direct assessment of the resolution of fine-scale structure in the temperature profile carried out in a computer simulation study. The simulation scheme allows the direct examination of the mapping of well-defined flnestructure in the temperature profile into the retrieved estimates of that finestructure. The results indicate that temperature anomalies are drastically smoothed and spread over deep layers by the radiative transfer integral and the temperature retrieval algorithm. Simulation results are presented for a minimum information retrieval scheme and a scheme designed to optimize vertical resolving power, and both are compared with the theoretical measures of resolution.

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C. A. Doswell III
,
R. Edwards
,
R. L. Thompson
,
J. A. Hart
, and
K. C. Crosbie

Abstract

The notion of an “outbreak” of severe weather has been used for decades, but has never been formally defined. There are many different criteria by which outbreaks can be defined based on severe weather occurrence data, and there is not likely to be any compelling logic to choose any single criterion as ideal for all purposes. Therefore, a method has been developed that uses multiple variables and allows for considerable flexibility. The technique can be adapted easily to any project that needs to establish a ranking of weather events. The intended use involves isolating the most important tornado outbreak days, as well as important outbreak days of primarily nontornadic severe convective weather, during a period when the number of reports has been growing rapidly from nonmeteorological factors. The method is illustrated for both tornadic and primarily nontornadic severe weather event day cases. The impact of the secular trends in the data has been reduced by a simple detrending scheme. The effect of detrending is less important for the tornado outbreak cases and is illustrated by comparing rankings with and without detrending. It is shown that the resulting rankings are relatively resistant to secular trends in the data, as intended, and not strongly sensitive to the choices made in applying the method. The rankings are also consistent with subjective judgments of the relative importance of historical tornado outbreak cases.

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Alexandra K. Anderson-Frey
,
Yvette P. Richardson
,
Andrew R. Dean
,
Richard L. Thompson
, and
Bryan T. Smith
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Alexandra K. Anderson-Frey
,
Yvette P. Richardson
,
Andrew R. Dean
,
Richard L. Thompson
, and
Bryan T. Smith

Abstract

In this study, a 13-yr climatology of tornado event and warning environments, including metrics of tornado intensity and storm morphology, is investigated with particular focus on the environments of tornadoes associated with quasi-linear convective systems and right-moving supercells. The regions of the environmental parameter space having poor warning performance in various geographical locations, as well as during different times of the day and year, are highlighted. Kernel density estimations of the tornado report and warning environments are produced for two parameter spaces: mixed-layer convective available potential energy (MLCAPE) versus 0–6-km vector shear magnitude (SHR6), and mixed-layer lifting condensation level (MLLCL) versus 0–1-km storm-relative helicity (SRH1). The warning performance is best in environments characteristic of severe convection (i.e., environments featuring large values of MLCAPE and SHR6). For tornadoes occurring during the early evening transition period, MLCAPE is maximized, MLLCL heights decrease, SHR6 and SRH1 increase, tornadoes rated as 2 or greater on the enhanced Fujita scale (EF2+) are most common, the probability of detection is relatively high, and false alarm ratios are relatively low. Overall, the parameter-space distributions of warnings and events are similar; at least in a broad sense, there is no systematic problem with forecasting that explains the high overall false alarm ratio, which instead seems to stem from the inability to know which storms in a given environment will be tornadic.

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Alexandra K. Anderson-Frey
,
Yvette P. Richardson
,
Andrew R. Dean
,
Richard L. Thompson
, and
Bryan T. Smith

Abstract

In this work, self-organizing maps (SOMs) are used to investigate patterns of favorable near-storm environmental parameters in a 13-yr climatology of 14 814 tornado events and 44 961 tornado warnings across the continental United States. Establishing nine statistically distinct clusters of spatial distributions of the significant tornado parameter (STP) in the 480 km × 480 km region surrounding each tornado event or warning allows for the examination of each cluster in isolation. For tornado events, distinct patterns are associated more with particular times of day, geographical locations, and times of year. For example, the archetypal springtime dryline setup in the Great Plains emerges readily from the data. While high values of STP tend to correspond to relatively high probabilities of detection (PODs) and relatively low false alarm ratios (FARs), the majority of tornado events occur within a pattern of uniformly lower STP, with relatively high FAR and low POD. Overall, the two-dimensional plots produced by the SOM approach provide an intuitive way of creating nuanced climatologies of tornadic near-storm environments.

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Alexandra K. Anderson-Frey
,
Yvette P. Richardson
,
Andrew R. Dean
,
Richard L. Thompson
, and
Bryan T. Smith

Abstract

Between 2003 and 2015, there were 5343 outbreak tornadoes and 9389 isolated tornadoes reported in the continental United States. Here, the near-storm environmental parameter-space distributions of these two categories are compared via kernel density estimation, and the seasonal, diurnal, and geographical features of near-storm environments of these two sets of events are compared via self-organizing maps (SOMs). Outbreak tornadoes in a given geographical region tend to be characterized by greater 0–1-km storm-relative helicity and 0–6-km vector shear magnitude than isolated tornadoes in the same geographical region and also have considerably higher tornado warning-based probability of detection (POD) than isolated tornadoes. A SOM of isolated tornadoes highlights that isolated tornadoes with higher POD also tend to feature higher values of the significant tornado parameter (STP), regardless of the specific shape of the area of STP. For a SOM of outbreak tornadoes, when two outbreak environments with similarly high magnitudes but different patterns of STP are compared, the difference is primarily geographical, with one environment dominated by Great Plains and Midwest outbreaks and another dominated by outbreaks in the southeastern United States. Two specific tornado outbreaks are featured, and the events are placed into their climatological context with more nuance than typical single proximity sounding-based approaches would allow.

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Alexandra K. Anderson-Frey
,
Yvette P. Richardson
,
Andrew R. Dean
,
Richard L. Thompson
, and
Bryan T. Smith

Abstract

The southeastern United States has become a prime area of focus in tornado-related literature due, in part, to the abundance of tornadoes occurring in high-shear low-CAPE (HSLC) environments. Through this analysis of 4133 tornado events and 16 429 tornado warnings in the southeastern United States, we find that tornadoes in the Southeast do indeed have, on average, higher shear and lower CAPE than tornadoes elsewhere in the contiguous United States (CONUS). We also examine tornado warning skill in the form of probability of detection (POD; percent of tornadoes receiving warning prior to tornado occurrence) and false alarm ratio (FAR; percent of tornado warnings for which no corresponding tornado is detected), and find that, on average, POD is better and FAR is worse for tornadoes in the Southeast than for the CONUS as a whole. These measures of warning skill remain consistent even when we consider only HSLC tornadoes. The Southeast also has nearly double the CONUS percentage of deadly tornadoes, with the highest percentage of these deadly tornadoes occurring during the spring, the winter, and around local sunset. On average, however, the tornadoes with the lowest POD also tend to be those that are weakest and least likely to be deadly; for the most part, the most dangerous storms are indeed being successfully warned.

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Bryan T. Smith
,
Richard L. Thompson
,
Douglas A. Speheger
,
Andrew R. Dean
,
Christopher D. Karstens
, and
Alexandra K. Anderson-Frey

Abstract

A sample of damage-surveyed tornadoes in the contiguous United States (2009–17), containing specific wind speed estimates from damage indicators (DIs) within the Damage Assessment Toolkit dataset, were linked to radar-observed circulations using the nearest WSR-88D data in Part I of this work. The maximum wind speed associated with the highest-rated DI for each radar scan, corresponding 0.5° tilt angle rotational velocity V rot, significant tornado parameter (STP), and National Weather Service (NWS) convective impact-based warning (IBW) type, are analyzed herein for the sample of cases in Part I and an independent case sample from parts of 2019–20. As V rot and STP both increase, peak DI-estimated wind speeds and IBW warning type also tend to increase. Different combinations of V rot, STP, and population density—related to ranges of peak DI wind speed—exhibited a strong ability to discriminate across the tornado damage intensity spectrum. Furthermore, longer duration of high V rot (i.e., ≥70 kt) in significant tornado environments (i.e., STP ≥ 6) corresponds to increasing chances that DIs will reveal the occurrence of an intense tornado (i.e., EF3+). These findings were corroborated via the independent sample from parts of 2019–20, and can be applied in a real-time operational setting to assist in determining a potential range of wind speeds. This work provides evidence-based support for creating an objective and consistent, real-time framework for assessing and differentiating tornadoes across the tornado intensity spectrum.

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Bryan T. Smith
,
Richard L. Thompson
,
Douglas A. Speheger
,
Andrew R. Dean
,
Christopher D. Karstens
, and
Alexandra K. Anderson-Frey

Abstract

The Storm Prediction Center (SPC) has developed a database of damage-surveyed tornadoes in the contiguous United States (2009–17) that relates environmental and radar-derived storm attributes to damage ratings that change during a tornado life cycle. Damage indicators (DIs), and the associated wind speed estimates from tornado damage surveys compiled in the Damage Assessment Toolkit (DAT) dataset, were linked to the nearest manual calculations of 0.5° tilt angle maximum rotational velocity V rot from single-site WSR-88D data. For each radar scan, the maximum wind speed from the highest-rated DI, V rot, and the significant tornado parameter (STP) from the SPC hourly objective mesoscale analysis archive were recorded and analyzed. Results from examining V rot and STP data indicate an increasing conditional probability for higher-rated DIs (i.e., EF-scale wind speed estimate) as both STP and V rot increase. This work suggests that tornadic wind speed exceedance probabilities can be estimated in real time, on a scan-by-scan basis, via V rot and STP for ongoing tornadoes.

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