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Peter S. Ray

Abstract

Tornadic storms passed between the two NSSL Doppler radars on 20 April and 8 June, 1974. Both radars simultaneously collected Dopplar data throughout these storms. From the derived velocity fields, vorticity and divergence calculations were made. Strongest convergence is noted in the weak echo region and between opposing vorticity centers.

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Terence Given
and
Peter S. Ray

Abstract

The wind field resulting from a two-dimensional dual-Doppler synthesis algorithms is spectrally modified from the true wind field. The effects of spatial filtering on wind fields from the processes of interpolation, the averaging of pulses, and the effect of the finite radar pulse dimension were assessed. The effect resulting from the use of different interpolation techniques was also evaluated. Of those techniques tested, the best are the Cressman distance-weighted averaging and linear distance-weighted averaging, with the closest neighbor and uniform weighting having more undesirable characteristics.

The optimum influence radius is defined as the influence radius at which the ratio of the rms difference between the Fourier and least-squares responses (a measure of the aliasing) and the variance of the filtered wind field is minimized. This seeks to minimize the effect of energy aliased into scales other than the input wavelength. For the Cressman interpolation technique, the optimum influence radius is between 1.85 and 2.25 times the maximum data spacing. The range of acceptable influence radii includes consideration of the filtering by the radar of the data as it is collected, as well as the resolution of the final dataset. The optimum influence radius is dependent upon the largest data separation in the analysis domain. The absolute optimum influence radius is not significantly affected by inclusion of the radar-beam filtering effects.

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Peter S. Ray
and
Mary Stephenson

Abstract

On 20 April 1984, the NOAA WP-3D aircraft, equipped with a Doppler radar in its tail, flew around a growing thunderstorm new Norman, Oklahoma. Doppler wind data was collected as the airplane flew six legs around the storm. During this time, the National Severe Storms laboratory (NSSL) dual-Doppler network collected data on the same storm. Different combinations of synthesis techniques were examined employing direct and pseudo-dual-Doppler observations from aircraft alone, and combinations of aircraft and ground-based Doppler radar. The effect of temporal resolution errors was assessed and related to uncertainties caused by geometric configuration. For this system, it was found that although the aircraft did provide useful data by extending the analysis to the region between the ground-based radars, the contribution was limited by the rapid evolution of the storm. Greater utility may generally be found for storms that evolve less rapidly.

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Paul Bieringer
and
Peter S. Ray

Abstract

The installation of the network of NEXRAD (Next Generation Weather Radar) WSR-88D (Weather Surveillance Radar—1988 Doppler) radars has been an ongoing process for more than three years. An assessment is made on how these radars and related changes at National Weather Service Offices have impacted the warning of tornadoes. Tornado warning statistics were employed to evaluate the improvements in warning lead times and detection after the installation of the WSR-88D. In an effort to remove a bias from the warning dataset, the statistics based on the first tornado event of each day were also considered. This early evaluation of the warning capability of these radars indicates an improvement at selected sites over the previous five years.

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Tina J. Cartwright
and
Peter S. Ray

Abstract

Atmospheric warming from cloud heating has a major affect on worldwide atmospheric circulations and climate. Studies have shown that the dominant source for cloud heating is the phase change of water. The location and magnitude of cloud heating has a substantial impact on atmospheric circulations. Therefore, identifying the location of phase changes provides information necessary for accurate modeling of atmospheric circulations and climate.

Radar reflectivity is a signature predominantly produced from rain formed from condensation, the primary process that produces heating. Through the application of principal component analysis on a nonhydrostatic cloud model, heating, and derived reflectivity data, a technique to illustrate a future heating algorithm capable of estimating cloud heating from reflectivity data is examined. Formative, intensifying, and mature stages of a Convection and Precipitation Electrification Experiment squall-type convective system were used to demonstrate these results. The accuracy of the technique’s estimates for the mean convective and stratiform profiles to within 1.0 K h−1 on average throughout the vertical column shows the merit of this statistical technique. The use of this type of technique in conjunction with the network of NEXRAD and spaceborne radars could provide valuable data for applications ranging from cumulus parameterization to 4D data assimilation and model initialization.

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Peter S. Ray
and
Karen L. Sangren

Abstract

Observing programs utilizing Doppler radar must have them deployed in optimum locations to best satisfy experimental objectives and maximize economies. One wishes to determine the coordinate triples (xi , yi , zi ), where i equals the number of radars, which maximize the value of the data to be collected. The optimum location is governed by a value or objective function. Here, possible networks of two to nine radars are given for two different error specifications. The objective functions with both error distributions maximize the quantity (AREAL COVERAGE/ERROR). The procedure is to search the finite number of local maxima for the global maximum in the value of the objective function. This is done by employing a searching algorithm at each of a number of starting vectors which are close enough to the local maxima to converge to the desired local maxima. In all cases, the network obtained by considering all radars simultaneously is superior to that obtained by combining optimum smaller sub-networks. Our results suggest the expected benefits for networks with additional constraints, reflecting the more complex experimental objectives particular to some individual field program. For example, the number of radars needed and their optimal configuration can be determined for a field program requiring a specified areal coverage (probability that a desired event will occur) and resolution (to retrieve a specified scale of motion).

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Peter S. Ray
,
Alan Robinson
, and
Ying Lin

Abstract

During the Taiwan Area Mesoscale Experiment (TAMEX), three Doppler radars complemented enhanced surface and upper-air observations. The focus of the experiment was to better understand the interaction of the terrain with precipitation systems in the production of the important heavy rainfall. The intensive operational period (IOP) number 8 extended from 1400 IST (local standard time) 7 June 1987 until 0800 LST 9 June 1987. During this time, a mesoscale convective system (MCS) formed in the Straits of Taiwan and moved inland. It was interrogated by many observing instruments, including three Doppler radars, over a 6-h period. During this time the front moved through the radar network. The front was shallow and the precipitation widespread, both ahead of and behind the front. The front was only 1.6-km deep over a distance of 100 km.

Using velocity-azimuth display (VAD) data, a portion of the frontogenetic function was computed during the times the front was in the vicinity of the radar. The increase in both convergence and deformation contributed to large values of the frontogenetic function.

Dynamic retrieval was also attempted on the data during the time when the front was most favorably located for analysis. The results are very similar to what has been observed both for tropical squall lines and for midlatitude squall lines.

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Carl E. Hane
and
Peter S. Ray

Abstract

A method for retrieval of pressure and buoyancy distributions in deep convection is applied to Doppler radar data collected at two analysis times during the tornadic Del City (Oklahoma) thunderstorm of 20 May 1977. Change of a previous version of the technique, necessitated by application to real data, include procedures for handling irregularly-bounded volumes and missing data and new assumptions to include reflectivity data and turbulent effects in the equations. Internal consistency cheeks on the quality of retrieved pressure fields imply that the input data are generally of good quality and point out times and heights within the storm at which greater confidence can be placed in the derived fields.

In the pretornadic stage the pressure distribution includes at each level a high–low couplet across the updraft with the maximum pressure gradient generally oriented along the environmental shear vector at that altitude. These results are in agreement with predictions of linear theory. Locations of vorticity maxima and areas of updraft development are also discussed in relation to pressure distributions. The buoyancy distribution includes a good correspondence between positive buoyancy and updraft areas. An analysis of the individual terms in the buoyancy equation reveals the importance of advective and vertical pressure gradient terms over water-related and turbulence terms.

In the tornadic stage the pressure field includes a pronounced minimum at low levels coincident with the mesocyclone. An analysis of the factors influencing the pressure distribution reveals that strong low-level vertical vorticity produces this minimum. Vorticity, vertical motion, and pressure relationships in the low-level mesocyclone region tend to agree quite well with results of recent fine-scale numerical simulations as well as with the observationally-based finding of others. The low-level buoyancy field, although noisier at this stage, tends to support the line of reasoning which stress the production of horizontal vorticity as a major factor in low-level mesocyclone development.

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Peter S. Ray
and
David P. Jorgensen

Abstract

Observations with airborne Doppler radar can expand the area of coverage and extend the time a moving weather system can remain under observation. Also, additional analysis methods are possible with the increase in independent estimates of the wind field that can be provided by an airborne sampling system. However, the advantages of airborne Doppler sensing are constrained by the geometry in which the data are collected, as well as errors introduced by uncertainties in the sampling platform location and orientation. Finally, a longer time required to sample a region than is typical for ground-based radar results in increased uncertainties due to the field's evolution and advection during the sampling interval. Uncertainties related to geometry are examined for flight patterns which are for aircraft alone and for those which also utilize data from one and two ground-based radars. These illustrate the distribution and relative magnitude of uncertainty expected for each type of flight pattern and data analysis method. Both the NOAA P−3, and the NCAR ELDORA scanning methodologies are examined.

To evaluate the different flight patterns, a relative quality index is used. It is defined as the reciprocal of the vertical velocity error variance integrated over the analysis domain. This normalized relative quality index is a mean value over the sampled volume. Flight patterns that utilize a single ground-based radar provide coverage over ∼ ten times the area in about one-half the time, and with relative quality about ten times better than that by aircraft alone.

Data collection, particularly aircraft data collection, often involves real-time decision making, and storms frequently are not in an ideal location relative to fixed ground-based radars. The best operational decisions require knowledge of eventual synthesis capabilities and the location of the volume to be interrogated relative to those facilities. These concepts are illustrated in a case example. Airborne Doppler and ground-based radar synthesis results are compared and discussed.

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J. Marshall Shepherd
,
Brad S. Ferrier
, and
Peter S. Ray

Abstract

Central Florida is the ideal test laboratory for studying convergence zone–induced convection. The region regularly experiences sea-breeze fronts and rainfall-induced outflow boundaries. The focus of this study is convection associated with the commonly occurring convergence zone established by the interaction of the sea-breeze front and an outflow boundary. Previous studies have investigated mechanisms primarily affecting storm initiation by such convergence zones. Few have focused on rainfall morphology, yet these storms contribute a significant amount of precipitation to the annual rainfall budget. Low-level convergence and midtropospheric moisture have been shown to be correlated with rainfall amounts in Florida. Using 2D and 3D numerical simulations, the roles of low-level convergence and midtropospheric moisture in rainfall evolution are examined.

The results indicate that area- and time-averaged, vertical moisture flux (VMF) at the sea-breeze front–outflow convergence zone is directly and linearly proportional to initial condensation rates. A similar relationship exists between VMF and initial rainfall. The VMF, which encompasses depth and magnitude of convergence, is better correlated to initial rainfall production than surface moisture convergence. This extends early observational studies that linked rainfall in Florida to surface moisture convergence. The amount and distribution of midtropospheric moisture affects how much rainfall associated with secondary cells develop. Rainfall amount and efficiency varied significantly over an observable range of relative humidities in the 850–500-mb layer even though rainfall evolution was similar during the initial or “first cell” period. Rainfall variability was attributed to drier midtropospheric environments inhibiting secondary cell development through entrainment effects. Observationally, a 850–500-mb moisture structure exhibits wider variability than lower-level moisture, which is virtually always present in Florida. A likely consequence of the variability in 850–500-mb moisture is a stronger statistical correlation to rainfall as noted in previous observational studies.

The VMF at convergence zones is critical in determining rainfall in the initial stage of development but plays a decreasing role in rainfall evolution as the system matures. The midtropospheric moisture (e.g., environment) plays an increasing role in rainfall evolution as the system matures. This suggests the need to improve measurements of depth and magnitude of convergence and midtropospheric moisture distribution. It also highlights that the influence of the environment needs to be better represented in convective parameterizations of larger-scale models to account for entrainment effects.

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