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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.
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.
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.
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.
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).
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).
Abstract
A technique to remove the ambiguity in Doppler mean velocity estimates is described. The technique assumes that along a radial, or portion of a radial, the velocity estimates are quasi-uniformly distributed about the mean. If the data do not meet this criterion, the velocities are adjusted such that they are distributed about the mean.
Abstract
A technique to remove the ambiguity in Doppler mean velocity estimates is described. The technique assumes that along a radial, or portion of a radial, the velocity estimates are quasi-uniformly distributed about the mean. If the data do not meet this criterion, the velocities are adjusted such that they are distributed about the mean.
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.
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.
Abstract
A vertically looking, multiple-wavelength Doppler radar technique to estimate vertical velocity, drop size distribution and turbulence is presented. The ratio of the Doppler spectra, corresponding to the drop fall velocities at two different wavelengths, is uniquely related to the ratio of the radar scattering cross sections at the appropriate temperature. These ratios are used to estimate drop fall velocities and therefore drop size distributions and vertical wind. Turbulence, which broadens the velocity power spectrum, can be estimated by deconvolution and the drop size distribution subsequently derived.
Abstract
A vertically looking, multiple-wavelength Doppler radar technique to estimate vertical velocity, drop size distribution and turbulence is presented. The ratio of the Doppler spectra, corresponding to the drop fall velocities at two different wavelengths, is uniquely related to the ratio of the radar scattering cross sections at the appropriate temperature. These ratios are used to estimate drop fall velocities and therefore drop size distributions and vertical wind. Turbulence, which broadens the velocity power spectrum, can be estimated by deconvolution and the drop size distribution subsequently derived.
