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David M. Schultz and Charles A. Doswell III

Abstract

Since numerical forecast models often err in predicting the timing and location of lee cyclogenesis, a physically based method to diagnose such errors is sought. A case of Rocky Mountain lee cyclogenesis associated with strong winds is examined to explore the transformation from a stationary lee trough to a mobile midlatitude cyclone (hereafter, departure). Up to 12 h before departure, a pronounced surface pressure trough travels eastward across western North America at an average speed of 22 m s−1. Several methods are employed to examine the structure and evolution of the pressure field: total sea level pressure, time series at individual stations, isallobars, and bandpass filtering. Bandpass filtering of the observed sea level pressure data is useful for clarifying the movement of the mobile trough through the complex terrain. Quasigeostrophic height-tendency diagnostics show that the mobile pressure trough is related to the traveling mid- to upper-tropospheric vorticity maximum that is responsible for departure. At many stations, surface temperature changes associated with this pressure trough are not consistent with those commonly associated with surface frontal passages. To test the hypothesis that mobile pressure troughs are associated with departure, a five-winter climatology of 111 southern Alberta lee cyclones is constructed. Sixty-two percent of these events feature an upstream pressure minimum 3–9 h prior to departure, in a manner resembling the case study. Seventy-six percent of these 111 events are associated with reports listed in Storm Data, indicating the potential severity of these storms.

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Robert H. Johns and Charles A. Doswell III

Abstract

Knowledge of severe local storms has been increasing rapidly in recent years as a result of both observational studies and numerical modeling experiments. This paper reviews that knowledge as it relates to development of new applications for forecasting of severe local storms. Many of these new applications are based on physical understanding of processes taking place on the storm scale and thus allow forecasters to become less dependent on empirical relationships. Refinements in pattern recognition and severe weather climatology continue to be of value to the operational severe local storms forecasters, however.

Current methodology for forecasting severe local storms at the National Severe Storms Forecast Center is described. Operational uses of new forecast applications, new “real-time” data sources (such as wind profilers and Doppler radars), and improved numerical model products are discussed.

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Leslie R. Lemon and Charles A. Doswell III

Abstract

Severe thunderstorm evolution is synthesized, using published and unpublished studies of radar, instrumented aircraft, visual and surface observations. These observations reveal the existence of a downdraft (originating at 7–10 km AGL) on the relative upwind side of the updraft. Air decelerates at the upwind stagnation point, is forced downward and mixes with air below which then reaches the surface through evaporative cooling and precipitation drag. The initially rotating updraft is then transformed into a new mesocyclone with a divided structure, in which the circulation center lies along the zone separating the rear blank downdraft from the updraft. This process appears to result, in part, from tilting of horizontal vorticity into the vertical. It is proposed that the zone of strong vertical velocity gradient across which the mesocyclone comes to be positioned is also characterized by a strong temperature gradient and is the genesis region of strong tornadoes. Although no direct observations are available yet, we further propose that the strong temperature contrast plays a potential modulating role in tornadogenesis by solenoidal generation of vorticity, in analogy with the extratropical cyclone, to which the transformed mesocyclone bears a striking resemblance.

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Charles A. Doswell III and Fernando Caracena

Abstract

Several aspects of the problem of estimating derivatives from an irregular, discrete sample of vector observations are considered. It is shown that one must properly account for transformations from one vector representation to another. if one is to preserve the original properties of a vector point function during such a transformation (e.g., from u and v wind components to speed and direction). A simple technique for calculating the linear kinematic properties of a vector point function (translation, cud, divergence, and deformation) is derived for any noncolinear triad of points. This technique is equivalent to a calculation done using line integrals, but is much more efficient.

It is shown that estimating derivatives by mapping the vector components onto a grid and taking finite differences is not equivalent to estimating the derivatives and mapping those estimates onto a grid, whenever the original observations are taken on a discrete, irregular network. This problem is particularly important whenever the data network is sparse relative to the wavelength of the phenomena. It is shown that conventional mapping/differencing fail to use all the information in the data, as well. Some suggesstions for minimizing the errors in derivative estimation for general (nonlinear) vector point functions are discussed.

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Frederick Sanders and Charles A. Doswell III

Detailed analysis of the temperature and moisture fields based on routine hourly surface observations in North America can provide a rational basis for surface feature analysis, thus clarifying the present confusion. Recognition of surface features is an important part of weather forecasting and is especially needed in a careful diagnosis for the prospects of deep convection.

Surface temperature gradients are advocated as the primary basis for identifying fronts; examples are given of gross discrepancies in current operational practice between the surface temperature fields and the associated frontal analyses. Surface potential temperature, selected as a means of compensating for elevation differences, is analyzed in the western United States for a period in which a strong, damaging cold front develops and dissipates over a period of less than 24 h. Frontogenesis-related calculations, based on detailed surface temperature analyses, help to explain a case of focusing of heavy precipitation in northern Kentucky that produced a flash flood.

Conditions for the initiation of intense convection are illustrated by detailed analyses of the surface moisture and temperature fields. These are used to estimate the buoyancy of surface air lifted to midtroposphere and show the relationship of this buoyancy to ensuing convection. The analyses aid in recognition of the surface dryline (a feature commonly misanalyzed as a cold front) and those convectively produced pools of cold air at the surface that often play a major role in the subsequent redevelopment of convection.

The proposed analyses might be difficult to achieve manually in operational practice during busy weather situations, but this could be facilitated by using objective methods with present and prospective workstations. Once surface features are identified, their temporal and spatial evolution must be followed carefully since they can change rapidly.

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Douglas A. Speheger, Charles A. Doswell III, and Gregory J. Stumpf

Abstract

The tornado events of 3 May 1999 within the county warning area of the Norman, Oklahoma, office of the National Weather Service are reviewed, emphasizing the challenges associated with obtaining accurate information about the existence, timing, location, and intensity of individual tornadoes. Accurate documentation of tornado and other hazardous weather events is critical to research, is needed for operational assessments, and is important for developing hazard mitigation strategies. The situation following this major event was unusual because of the high concentration of meteorologists in the area, relative to most parts of the United States. As a result of this relative abundance of resources, it is likely that these tornadoes were reasonably well documented. Despite this unique situation in central Oklahoma, it is argued that this event also provides evidence of a national need for a rapid-response scientific and engineering survey team to provide documentation of major hazardous weather events before cleanup destroys important evidence.

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Charles A. Doswell III, Donald V. Baker, and Charlie A. Liles

Abstract

The case of 7–8 June 1998 in eastern New Mexico and western Texas is used to illustrate the challenge of recognizing possible negative effects created by mesoscale processes. In this case, a region of cloud-covered cool air (which was associated with early thunderstorms) may have limited the tornadic potential of severe convection. Although the tornado potential in the synoptic situation was not highly portentous, supercell storms did eventually form, one of which was persistent for many hours. There were only relatively brief and weak tornadoes reported from this storm early in its life, despite its persistence as a long-lived supercell that produced a long swath of large hail. In this case, the development of thunderstorms east of the threat area early in the day maintained cloudiness that apparently inhibited the destabilization of the surface-based air mass over which the afternoon thunderstorms eventually moved. The persistent supercell formed on the dryline but overrode this mesoscale cool air mass relatively soon after it developed. It was able to persist as an elevated supercell despite the relatively stable near-surface air mass, but its tornadic production may have been limited by its interaction with this mesoscale feature. Implications for operational forecasting and warnings are discussed.

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Charles A. Doswell III, Harold E. Brooks, and Robert A. Maddox

Abstract

An approach to forecasting the potential for flash flood-producing storms is developed, using the notion of basic ingredients. Heavy precipitation is the result of sustained high rainfall rates. In turn, high rainfall rates involve the rapid ascent of air containing substantial water vapor and also depend on the precipitation efficiency. The duration of an event is associated with its speed of movement and the size of the system causing the event along the direction of system movement.

This leads naturally to a consideration of the meteorological processes by which these basic ingredients are brought together. A description of those processes and of the types of heavy precipitation-producing storms suggests some of the variety of ways in which heavy precipitation occurs. Since the right mixture of these ingredients can be found in a wide variety of synoptic and mesoscale situations, it is necessary to know which of the ingredients is critical in any given case. By knowing which of the ingredients is most important in any given case, forecasters can concentrate on recognition of the developing heavy precipitation potential as meteorological processes operate. This also helps with the recognition of heavy rain events as they occur, a challenging problem if the potential for such events has not been anticipated.

Three brief case examples are presented to illustrate the procedure as it might be applied in operations. The cases are geographically diverse and even illustrate how a nonconvective heavy precipitation event fits within this methodology. The concept of ingredients-based forecasting is discussed as it might apply to a broader spectrum of forecast events than just flash flood forecasting.

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Phillip L. Spencer, Mark A. Askelson, and Charles A. Doswell III

Abstract

Various combinations of smoothing parameters within a two-pass Barnes objective analysis scheme are applied to analytic observations obtained by regular and irregular sampling of a one-dimensional sinusoidal analytic wave to obtain gridded fields. Each of these various combinations of smoothing parameters would produce equivalent analyses if the observations were continuous and infinite (unbounded). The authors demonstrate that owing to the discreteness of the analytic observations, the actual analyses resulting from these various combinations of smoothing parameters are different. When derivatives are computed and as stations become more irregularly distributed, these differences increase. An awareness of these potentially significant analysis differences should prompt the analyst to consider carefully the choice of smoothing parameters when applying an objective analysis scheme to real observations.

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Harold E. Brooks, Charles A. Doswell III, and Robert A. Maddox

Abstract

In the near future, the technological capability will be available to use mesoscale and cloud-scale numerical models for forecasting convective weather in operational meteorology. We address some of the issues concerning effective utilization of this capability. The challenges that must be overcome are formidable. We argue that explicit prediction on the cloud scale, even if these challenges can be met, does not obviate the need for human interpretation of the forecasts. In the case that humans remain directly involved in the forecasting process, another set of issues is concerned with the constraints imposed by human involvement. As an alternative to direct explicit prediction of convective events by computers, we propose that mesoscale models be used to produce initial conditions for cloud-scale models. Cloud-scale models then can be run in a Monte Carlo–like mode, in order to provide an estimate of the probable types of convective weather for a forecast period. In our proposal, human forecasters fill the critical role as an interface between various stages of the forecasting and warning process. In particular, they are essential in providing input to the numerical models from the observational data and in interpreting the model output. This interpretative step is important both in helping the forecaster anticipate and interpret new observations and in providing information to the public.

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