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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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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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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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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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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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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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Paul E. Bieringer
,
Peter S. Ray
, and
Andrew J. Annunzio

Abstract

The concept of improving the accuracy of numerical weather forecasts by targeting additional meteorological observations in areas where the initial condition error is suspected to grow rapidly has been the topic of numerous studies and field programs. The challenge faced by this approach is that it typically requires a costly observation system that can be quickly adapted to place instrumentation where needed. The present study examines whether the underlying terrain in a mesoscale model influences model initial condition sensitivity and if knowledge of the terrain and corresponding predominant flow patterns for a region can be used to direct the placement of instrumentation. This follows the same concept on which earlier targeted observation approaches were based, but eliminates the need for an observation system that needs to be continually reconfigured. Simulations from the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) and its adjoint are used to characterize the locations, variables, and magnitudes of initial condition perturbations that have the most significant impact on the surface wind forecast. This study examines a relatively simple case where an idealized mountain surrounded by a flat plain is located upwind of the forecast verification region. The results suggest that, when elevated terrain is present upstream of the target forecast area, the largest forecast impact (defined as the difference between the simulation with perturbed initial conditions and a control simulation where the initial condition was not perturbed) occurs when the initial analysis perturbations are made in regions with complex terrain.

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Paul E. Bieringer
,
Peter S. Ray
, and
Andrew J. Annunzio

Abstract

A study by Bieringer et al., which is Part I of this two-part study, demonstrated analytically using the shallow-water equations and numerically in controlled experiments that the presence of terrain can result in an enhancement of sensitivities to initial condition adjustments. The increased impact of adjustments to initial conditions corresponds with gradients in the flow field induced by the presence of the terrain obstacle. In cross-barrier flow situations the impact of the initial condition adjustments on the final forecast increases linearly as the height of the terrain obstacle increases. While this property associated with initial condition perturbations may be present in an analytic and controlled numerical environment, it is often difficult to realize these benefits in a more operationally realistic setting. This study extends the prior work to a situation with actual terrain, Doppler radar wind observations over the terrain, and observations from a surface mesonet for model verification. The results indicate that the downstream surface wind forecast was improved more when the initial conditions adjusted through the assimilation of Doppler radar data originated from areas with terrain gradients than from regions where the terrain was relatively flat. This result is consistent with the findings presented in Part I and suggests that when varying terrain elevation is present upstream of a target forecast area, a greater benefit (in terms of forecast accuracy) can be made by targeting additional observations in the regions containing variable terrain than regions where the terrain is relatively flat.

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Ying Lin
,
Peter S. Ray
, and
Kenneth W. Johnson

Abstract

A method is developed to initialize convective storm simulations with Doppler radar-derived fields. Input fields for initialization include velocity, rainwater derived from radar reflectivity, and pressure and temperature fields obtained through thermodynamic retrieval. A procedure has been developed to fill in missing wind data, followed by a variational adjustment to the filled wind field to minimize “shocks” that would otherwise cause the simulated fields to deteriorate rapidly.

A series of experiments using data from a simulated storm establishes the feasibility of the initialization method. Multiple-Doppler radar observations from the 20 May 1977 Del City tornadic storm are used for the initialization experiments. Simulation results are shown and compared to observations taken at a later time. The simulated storm shows good agreement with the subsequent observations, though the simulated storm appears to be evolving faster than observed. Possible reasons for the discrepancies are discussed.

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Brenda C. Johnson
,
Judith Stokes
, and
Peter S. Ray

Abstract

Optimum design of a Doppler radar system for operation in a severe storm environment will depend on the maximum unambiguous velocity. Radial velocities of severe storms are examined from four Doppler radars over several hours on 20 May 1977. The probability of a radial velocity occurrence for a given pulse repetition frequency-wavelength combination is presented.

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