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Steven J. Weiss, Charles A. Doswell III, and Frederick P. Ostby

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No abstract available.

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Phillip L. Spencer, Paul R. Janish, and Charles A. Doswell III

Abstract

A 4D Barnes objective analysis scheme for wind profiler data is developed in order to improve upon previously developed 2D analysis schemes. A significant shortcoming of the 2D schemes is their sensitivity to gaps in the profiler time–height series; they may produce unrealistic gradient information if large data-void regions are present. The 4D analysis scheme described herein, however, provides an effective means for dealing with data voids within profiler time–height series. The 4D analysis scheme differs from the 2D techniques in that data from neighboring profiler stations affect the time–height wind analysis at each site. This allows the analysis scheme to produce smooth, spatially and temporally consistent time–height wind analyses for each station of the Wind Profiler Network (WPN), even if large data gaps are present.

Gridded time–height wind fields at each profiler site resulting from the 4D analysis scheme are provided as input to a line integral-equivalent technique that is applied over many WPN triangles for the purpose of diagnosing the kinematic and thermodynamic structure of subsynoptic-scale weather systems. Time–height series of triangle-derived variables have been proven elsewhere to be an effective method for diagnosing subsynoptic-scale temporal structure of weather systems; mapping the irregularly spaced triangle information onto a regular, quasihorizontal grid provides a complementary perspective of their spatial structure and evolution.

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

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Kinematic and thermodynamic quantities derived from wind profiler triangles are used to help describe the structure of both an amplifying and decaying baroclinic wave as they traversed portions of the wind profiler demonstration network. The data provide excellent diagnoses of the cyclogenetic processes associated with the amplifying system and the cyclolytic processes associated with the decaying system. The importance of a baroclinic wave's vertical tilt and the associated profiler-derived advective patterns of the systems as they relate to surface evolution are shown to be consistent with conceptual models of baroclinic waves. These structural aspects of the observed baroclinic waves are also shown to vary substantially on short timescales. In addition, a sub-synoptic-scale feature associated with a severe convective event that developed ahead of the decaying wave trough axis was observed quite well by the profiler network. This feature's detection was dependent on the high temporal resolution of the profiler data and was not detectable with data provided by the rawinsonde network.

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Harold E. Brooks, Charles A. Doswell III, and Louis J. Wicker

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An experiment using a three-dimensional cloud-scale numerical model in an operational forecasting environment was carried out in the spring of 1991. It involved meteorologists generating forecast environmental conditions associated with anticipated strong convection. Those conditions then were used to initialize the cloud model, which was run subsequently to forecast qualitative descriptions of storm type. Verification was done on both the sounding forecast and numerical model portions of the experiment. Of the 12 experiment days, the numerical model generated six good forecasts, two of which involved significant tornadic storms. More importantly, while demonstrating the potential for cloud-scale modeling in an operational environment, the experiment highlights some of the obstacles in the path of such an implementation.

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Donald L. Kelly, Joseph T. Schaefer, and Charles A. Doswell III

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While the climatology of excessive rain and tornadoes is well-documented, little is known of storms that produce high winds or large hail. The characteristics of the approximately 75 000 severe thunderstorms which occurred in the United States from 1955 through 1983 are analyzed in an attempt to rectify this situation.

The distribution of over 29 000 storms causing hail larger than 19 mm shows marked diurnal, seasonal, and geographic preferences. These storms occur most frequently during the midafternoon hours of May and June in a zone running from central Texas to Nebraska. Spring storms tend to occur south of the Kansas-Nebraska border and summer storms north of it.

Thunderstorm winds which produce either “structural” damage or are reported as faster than 25.8 m s−1 generated about 46 000 reports. These storms typically occur during midafternoon in June and July. While the geographic distribution of violent windstorms is similar to that hailstorms, a zone of weaker severe thunderstorm gusts lies from northern Iowa to central Ohio. During May, windstorms are predominant across the plains area, but by August thew storms are indigenous only to the northern Midwest.

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Tony Hall, Harold E. Brooks, and Charles A. Doswell III

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A neural network, using input from the Eta Model and upper air soundings, has been developed for the probability of precipitation (PoP) and quantitative precipitation forecast (QPF) for the Dallas–Fort Worth, Texas, area. Forecasts from two years were verified against a network of 36 rain gauges. The resulting forecasts were remarkably sharp, with over 70% of the PoP forecasts being less than 5% or greater than 95%. Of the 436 days with forecasts of less than 5% PoP, no rain occurred on 435 days. On the 111 days with forecasts of greater than 95% PoP, rain always occurred. The linear correlation between the forecast and observed precipitation amount was 0.95. Equitable threat scores for threshold precipitation amounts from 0.05 in. (∼1 mm) to 1 in. (∼25 mm) are 0.63 or higher, with maximum values over 0.86. Combining the PoP and QPF products indicates that for very high PoPs, the correlation between the QPF and observations is higher than for lower PoPs. In addition, 61 of the 70 observed rains of at least 0.5 in. (12.7 mm) are associated with PoPs greater than 85%. As a result, the system indicates a potential for more accurate precipitation forecasting.

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Robert Davies-Jones, Charles A. Doswell III, and Harold E. Brooks

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No Abstract Available

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Harold E. Brooks, Charles A. Doswell III, and Robert B. Wilhelmson

Abstract

Using a three-dimensional numerical model, supercell simulations initialized in environments characterized by hodographs with large curvature in the lowest 3 km and a range of linear midlevel shears are investigated. For low values of the midlevel shear (0.005 s−1), the storm develops a mesocyclone at the lowest model level within the first hour of the simulation. The gust front starts to move ahead of the main updraft and cuts off the inflow to the storm by approximately 2 h, resulting in decay of the initial storm and growth of a new rotating storm on the outflow. As the midlevel shear increases to approximately 0.010 s−1, the initial development of the low-level mesocyclone is delayed, but the mesocyclone that develops is more persistent, lasting for over 2 h. Further increases of the shear to 0.015 s−1 result in the suppression of any low-level mesocyclone, despite the presence of intense rotation at midlevels of the storm.

We hypothesize that differences in the distribution of precipitation within the storms, resulting from the changes in storm-relative winds, are responsible for the changes in low-level mesocyclone development. In the weak-shear regime, storm-relative midlevel winds are weak and much of the rain is carded by the midlevel mesocyclonic flow to fall west of the updraft. As this rain evaporates, baroclinic generation of vorticity in the downdraft leads to mesocyclogenesis at low levels of the storm. The outflow from the cold air associated with the rain eventually undercuts the inflow to the storm. As the midlevel shear increases, the storm-relative winds increase and more of the rain generated by the storm falls well away from the updraft. As a result, baroclinic generation of vorticity in the downdraft immediately west of the updraft is slower. Once a low-level mesocyclone is generated, however, the weaker outflow allows the mesocyclone to persist.

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Harold E. Brooks, Charles A. Doswell III, and Michael P. Kay

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An estimate is made of the probability of an occurrence of a tornado day near any location in the contiguous 48 states for any time during the year. Gaussian smoothers in space and time have been applied to the observed record of tornado days from 1980 to 1999 to produce daily maps and annual cycles at any point on an 80 km × 80 km grid. Many aspects of this climatological estimate have been identified in previous work, but the method allows one to consider the record in several new ways. The two regions of maximum tornado days in the United States are northeastern Colorado and peninsular Florida, but there is a large region between the Appalachian and Rocky Mountains that has at least 1 day on which a tornado touches down on the grid. The annual cycle of tornado days is of particular interest. The southeastern United States, outside of Florida, faces its maximum threat in April. Farther west and north, the threat is later in the year, with the northern United States and New England facing its maximum threat in July. In addition, the repeatability of the annual cycle is much greater in the plains than farther east. By combining the region of greatest threat with the region of highest repeatability of the season, an objective definition of Tornado Alley as a region that extends from the southern Texas Panhandle through Nebraska and northeastward into eastern North Dakota and Minnesota can be provided.

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Phillip L. Spencer and Charles A. Doswell III

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For diagnostic purposes, the “traditional” approach to estimating derivatives employs objective analysis to provide a gridded field from the original observations, which are typically not uniformly distributed in space. However, there exist other methods involving derivative estimation via line integral (“triangle”) techniques that do not involve a prior mapping of the field onto a uniform grid. It has been suggested that these give improved results. Empirical testing of the differences between wind field derivative estimation using two different schemes is done with prototypical examples of the techniques. Test results verify that the triangle method indeed provides substantial improvements over the traditional scheme. The magnitude of the improvement is shown to depend on the degree of irregularity of the data distribution, as expected. Although the particular prototype methods chosen have the property that the triangle method truncates the amplitude of the input field slightly more than the traditional scheme, the pattern of the field is significantly better using the triangle technique than with the traditional method. An unexpected result is that the improvement by the triangle method over the traditional approach does not diminish as the wavelength of the input field increases. It is shown that this is a consequence of overfitting of the field to the station observations, causing local discontinuities in the field that produce errors in the gradient calculations, even in situations where the distribution of data is uniform. Overall, the test results make it abundantly clear that the traditional method is generally inferior to derivative estimates via the line integral methodology.

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