Finescale Vertical Structure of a Cold Front as Revealed by an Airborne Doppler Radar

Abstract In the afternoon of 24 May 2002, a well-defined and frontogenetic cold front moved through the Texas panhandle. Detailed observations from a series of platforms were collected near the triple point between this cold front and a dryline boundary. This paper primarily uses reflectivity and Doppler velocity data from an airborne 95-GHz radar, as well as flight-level thermodynamic data, to describe the vertical structure of the cold front as it intersected with the dryline. The prefrontal convective boundary layer was weakly capped, weakly sheared, and about 2.5 times deeper than the cold-frontal density current. The radar data depict the cold front as a fine example of an atmospheric density current at unprecedented detail (∼40 m). The echo structure and dual-Doppler-inferred airflow in the vertical plane reveal typical features such as a nose, a head, a rear-inflow current, and a broad current of rising prefrontal air that feeds the accelerating front-to-rear current over the head. The 2D cross-frontal structure, including the frontal slope, is highly variable in time or alongfront distance. Along this slope horizontal vorticity, averaging ∼0.05 s−1, is generated baroclinically, and the associated strong cross-front shear triggers Kelvin–Helmholtz (KH) billows at the density interface. Some KH billows occupy much of the depth of the density current, possibly even temporarily cutting off the head from its trailing body.

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Procedures to Improve the Accuracy of Airborne Doppler Radar Data

Journal of Atmospheric and Oceanic Technology ◽

10.1175/1520-0426-19.3.322 ◽

2002 ◽

Vol 19 (3) ◽

pp. 322-339 ◽

Cited By ~ 37

Author(s):

Brian L. Bosart ◽

Wen-Chau Lee ◽

Roger M. Wakimoto

Keyword(s):

Doppler Radar ◽

Radar Data ◽

Correction Method ◽

Fine Tuning ◽

Earth Surface ◽

Doppler Radar Data ◽

Tilt Error ◽

Corrected Data ◽

Flight Level ◽

Airborne Doppler Radar

Abstract The navigation correction method proposed in Testud et al. (referred to as the THL method) systematically identifies uncertainties in the aircraft Inertial Navigation System and errors in the radar-pointing angles by analyzing the radar returns from a flat and stationary earth surface. This paper extends the THL study to address 1) error characteristics on the radar display, 2) sensitivity of the dual-Doppler analyses to navigation errors, 3) fine-tuning the navigation corrections for individual flight legs, and 4) identifying navigation corrections over a flat and nonstationary earth surface (e.g., ocean). The results show that the errors in each of the parameters affect the dual-Doppler wind analyses and the first-order derivatives in different manners. The tilt error is the most difficult parameter to determine and has the greatest impact on the dual-Doppler analysis. The extended THL method can further reduce the drift, ground speed, and tilt errors in all flight legs over land by analyzing the residual velocities of the earth surface using the corrections obtained in the calibration legs. When reliable dual-Doppler winds can be deduced at flight level, the Bosart–Lee–Wakimoto method presented here can identify all eight errors by satisfying three criteria: 1) the flight-level dual-Doppler winds near the aircraft are statistically consistent with the in situ winds, 2) the flight-level dual-Doppler winds are continuous across the flight track, and 3) the surface velocities of the left (right) fore radar have the same magnitude but opposite sign as their counterparts of right (left) aft radar. This procedure is able to correct airborne Doppler radar data over the ocean and has been evaluated using datasets collected during past experiments. Consistent calibration factors are obtained in multiple legs. The dual-Doppler analyses using the corrected data are statistically superior to those using uncorrected data.

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Detailed Dual-Doppler Structure of Kelvin–Helmholtz Waves from an Airborne Profiling Radar over Complex Terrain. Part I: Dynamic Structure

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-19-0108.1 ◽

2020 ◽

Vol 77 (5) ◽

pp. 1761-1782 ◽

Cited By ~ 1

Author(s):

Coltin Grasmick ◽

Bart Geerts

Keyword(s):

Complex Terrain ◽

Doppler Radar ◽

Vertical Plane ◽

Dynamic Structure ◽

Radar Data ◽

Range Resolution ◽

Small Complex ◽

Steep Terrain ◽

Airborne Doppler Radar ◽

The Waves

Abstract Kelvin–Helmholtz (KH) waves are remarkably common in deep stratiform precipitation systems associated with frontal disturbances, at least in the vicinity of complex terrain, as is evident from transects of vertical velocity and 2D circulation, obtained from a 3-mm airborne Doppler radar, the Wyoming Cloud Radar. The high range resolution of this radar (~40 m) allows detection and depiction of KH waves in fine detail. These waves are observed in a variety of wavelengths, depths, amplitudes, and turbulence intensities. Proximity rawinsonde data confirm that they are triggered in layers where the Richardson number is very small. Complex terrain may locally enhance wind shear, leading to KH instability. In some KH waves, the flow remains mostly laminar, while in other cases it breaks down into turbulence. KH waves are frequently locked to the terrain, and occur at various heights, including within the free troposphere, at the boundary layer top, and close to the surface. They are observed not only upwind of terrain barriers, as has been documented before, but also in the wake of steep terrain, where the waves can be highly turbulent. Vertical-plane dual-Doppler analyses of KH waves reveal the mixing of layers of differential momentum across the high-shear zone. Doppler radar data are used to explore the dynamics of KH waves, including the response of thermodynamic and kinematic variables above, below, and within the instability layer.

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A Generalized Navigation Correction Method for Airborne Doppler Radar Data

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-18-0028.1 ◽

2018 ◽

Vol 35 (10) ◽

pp. 1999-2017 ◽

Cited By ~ 3

Author(s):

Huaqing Cai ◽

Wen-Chau Lee ◽

Michael M. Bell ◽

Cory A. Wolff ◽

Xiaowen Tang ◽

...

Keyword(s):

Doppler Radar ◽

Radar Data ◽

Correction Method ◽

Ground Speed ◽

Flat Surfaces ◽

Doppler Radar Data ◽

Flight Level ◽

The Cost ◽

Navigation Errors ◽

Airborne Doppler Radar

AbstractUncertainties in aircraft inertial navigation system and radar-pointing angles can have a large impact on the accuracy of airborne dual-Doppler analyses. The Testud et al. (THL) method has been routinely applied to data collected by airborne tail Doppler radars over flat and nonmoving terrain. The navigation correction method proposed in Georgis et al. (GRH) extended the THL method over complex terrain and moving ocean surfaces by using a variational formulation but its capability over ocean has yet to be tested. Recognizing the limitations of the THL method, Bosart et al. (BLW) proposed to derive ground speed, tilt, and drift errors by statistically comparing aircraft in situ wind with dual-Doppler wind at the flight level. When combined with the THL method, the BLW method can retrieve all navigation errors accurately; however, it can be applied only to flat surfaces, and it is rather difficult to automate. This paper presents a generalized navigation correction method (GNCM) based on the GRH method that will serve as a single algorithm for airborne tail Doppler radar navigation correction for all possible surface conditions. The GNCM includes all possible corrections in the cost function and implements a new closure assumption by taking advantage of an accurate aircraft ground speed derived from GPS technology. The GNCM is tested extensively using synthetic airborne Doppler radar data with known navigation errors and published datasets from previous field campaigns. Both tests show the GNCM is able to correct the navigation errors associated with airborne tail Doppler radar data with adequate accuracy.

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Variational Pseudo-Multiple-Doppler Wind Retrieval in the Vertical Plane for Ground-Based Mobile Radar Data

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech2028.1 ◽

2007 ◽

Vol 24 (7) ◽

pp. 1165-1185 ◽

Cited By ~ 2

Author(s):

Christopher C. Weiss ◽

Howard B. Bluestein ◽

Robert Conzemius ◽

Evgeni Fedorovich

Keyword(s):

Doppler Radar ◽

Vertical Plane ◽

Radar Data ◽

Radial Component ◽

Processing Technique ◽

Observation System ◽

Observation Error ◽

Convective Boundary ◽

Wind Retrieval ◽

The Difference

Abstract A variational procedure is developed that utilizes mobile ground-based range–height indicator (RHI) Doppler radar velocity data for the synthesis of two-dimensional, RHI plane wind vectors. The radial component winds are obtained with the radar platform in motion, a data collection strategy referred to as the rolling RHI technique. Using the assumption of stationarity—standard to any pseudo-multiple-Doppler processing technique—individual radial velocity values at a given point in space will contribute a varying amount of independent information to the two components of wind velocity in the RHI plane, depending strongly on the difference in radar viewing angles amongst the looks. The variational technique is tested successfully with observation system simulation experiments, using both a homogeneous flow field and large eddy simulation (LES) output from a highly sheared convective boundary layer simulation. Pseudoradar data are collected in these tests in a manner consistent with the specifications of the University of Massachusetts mobile W-band radar, which was used in a separate study to resolve the finescale structure of a dryline during the International H2O Project (IHOP_2002). The results of these tests indicate clearly that the technique performs well in regions of adequate “look” angle separation. Observation error contributes significantly to the analysis when the radar looks become more collinear.

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Finescale Vertical Structure and Evolution of a Preconvective Dryline on 19 June 2002

Monthly Weather Review ◽

10.1175/mwr3354.1 ◽

2007 ◽

Vol 135 (6) ◽

pp. 2111-2134 ◽

Cited By ~ 13

Author(s):

Benjamin D. Sipprell ◽

Bart Geerts

Keyword(s):

Vertical Structure ◽

Radar Data ◽

Doppler Velocity ◽

Convective Boundary ◽

Convective Initiation ◽

Depth Difference ◽

Cloud Radar ◽

Later Phase ◽

Total Elimination ◽

Vertical Transect

Abstract High-resolution airborne cloud radar data and other International H2O Project datasets are used to describe the vertical structure of an unusual prefrontal dryline. This dryline, observed in northwestern Kansas on 19 June 2002, first progressed eastward and tilted toward the west, and later became more stationary and reversed its tilt, toward the moist side. The convective boundary layer (CBL) depth difference also reversed: only in the later phase did the dry-side CBL become deeper than on the moist side. Echo and single/dual-Doppler velocity data in a vertical transect across the dryline suggest a solenoidal circulation dynamically consistent with the observed horizontal buoyancy gradient. Both this gradient and the solenoidal circulation reversed in the later phase. Simultaneously, confluence toward the dryline increased, resulting in an increasing moisture gradient as well as a deepening CBL in the dryline convergence zone. It is speculated that the baroclinically generated horizontal vorticity contributed to this CBL deepening, as the sign of this vorticity was opposite to that of the low-level wind shear on the opposite side of the dryline in both phases. Deep-convective initiation appears to have resulted from this local CBL deepening, leading to a total elimination of convective inhibition near the dryline.

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Assimilation of High-Resolution Tropical Cyclone Observations with an Ensemble Kalman Filter Using HEDAS: Evaluation of 2008–11 HWRF Forecasts

Monthly Weather Review ◽

10.1175/mwr-d-14-00138.1 ◽

2015 ◽

Vol 143 (2) ◽

pp. 511-523 ◽

Cited By ~ 25

Author(s):

Sim D. Aberson ◽

Altuğ Aksoy ◽

Kathryn J. Sellwood ◽

Tomislava Vukicevic ◽

Xuejin Zhang

Keyword(s):

Kalman Filter ◽

High Resolution ◽

Tropical Cyclone ◽

Ensemble Kalman Filter ◽

Doppler Radar ◽

Radar Data ◽

Doppler Radar Data ◽

Flight Level ◽

Airborne Doppler Radar ◽

Aircraft Data

Abstract NOAA has been gathering high-resolution, flight-level dropwindsonde and airborne Doppler radar data in tropical cyclones for almost three decades; the U.S. Air Force routinely obtained the same type and quality of data, excepting Doppler radar, for most of that time. The data have been used for operational diagnosis and for research, and, starting in 2013, have been assimilated into operational regional tropical cyclone models. This study is an effort to quantify the impact of assimilating these data into a version of the operational Hurricane Weather Research and Forecasting model using an ensemble Kalman filter. A total of 83 cases during 2008–11 were investigated. The aircraft whose data were used in the study all provide high-density flight-level wind and thermodynamic observations as well as surface wind speed data. Forecasts initialized with these data assimilated are compared to those using the model standard initialization. Since only NOAA aircraft provide airborne Doppler radar data, these data are also tested to see their impact above the standard aircraft data. The aircraft data alone are shown to provide some statistically significant improvement to track and intensity forecasts during the critical watch and warning period before projected landfall (through 60 h), with the Doppler radar data providing some further improvement. This study shows the potential for improved forecasts with regular tropical cyclone aircraft reconnaissance and the assimilation of data obtained from them, especially airborne Doppler radar data, into the numerical guidance.

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Constant Raindrop Fall Speed Profiles Derived from Doppler Radar Data Analyses for Steady Nonconvective Precipitation

Journal of the Atmospheric Sciences ◽

10.1175/jas-3369.1 ◽

2005 ◽

Vol 62 (1) ◽

pp. 220-230 ◽

Cited By ~ 7

Author(s):

Robert Nissen ◽

Roland List ◽

David Hudak ◽

Greg M. McFarquhar ◽

R. Paul Lawson ◽

...

Keyword(s):

Doppler Radar ◽

Free Fall ◽

Radar Data ◽

Measuring System ◽

Doppler Velocity ◽

Light Rain ◽

Fall Speed ◽

Air Speed ◽

Velocity Moments ◽

Rain Rates

Abstract For nonconvective, steady light rain with rain rates <5 mm h−1 the mean Doppler velocity of raindrop spectra was found to be constant below the melting band, when the drop-free fall speed was adjusted for pressure. The Doppler radar–weighted raindrop diameters varied from case to case from 1.5 to 2.5 mm while rain rates changed from 1.2 to 2.9 mm h−1. Significant changes of advected velocity moments were observed over periods of 4 min. These findings were corroborated by three independent systems: a Doppler radar for establishing vertical air speed and mean terminal drop speeds [using extended Velocity Azimuth Display (EVAD) analyses], a Joss–Waldvogel disdrometer at the ground, and a Particle Measuring System (PMS) 2-DP probe flown on an aircraft. These measurements were supported by data from upper-air soundings. The reason why inferred raindrop spectra do not change with height is the negligible interaction rate between raindrops at low rain rates. At low rain rates, numerical box models of drop collisions strongly support this interpretation. It was found that increasing characteristic drop diameters are correlated with increasing rain rates.

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A Variational Method for Filling in Missing Data in Doppler Velocity Fields

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-20-0151.1 ◽

2021 ◽

Author(s):

VINCENT T. WOOD ◽

ROBERT P. DAVIES-JONES ◽

ALAN SHAPIRO

Keyword(s):

Missing Data ◽

Doppler Radar ◽

Signal To Noise Ratio ◽

Original Data ◽

Radar Data ◽

Velocity Fields ◽

Doppler Velocity ◽

Doppler Radar Data ◽

Ground Clutter ◽

Tornado Warnings

AbstractSingle-Doppler radar data are often missing in important regions of a severe storm due to low return power, low signal-to-noise ratio, ground clutter associated with normal and anomalous propagation, and missing radials associated with partial or total beam blockage. Missing data impact the ability of WSR-88D algorithms to detect severe weather. To aid the algorithms, we develop a variational technique that fills in Doppler velocity data voids smoothly by minimizing Doppler velocity gradients while not modifying good data. This method provides estimates of the analysed variable in data voids without creating extrema.Actual single-Doppler radar data of four tornadoes are used to demonstrate the variational algorithm. In two cases, data are missing in the original data, and in the other two, data are voided artificially. The filled-in data match the voided data well in smoothly varying Doppler velocity fields. Near singularities such as tornadic vortex signatures, the match is poor as anticipated. The algorithm does not create any velocity peaks in the former data voids, thus preventing false triggering of tornado warnings. Doppler circulation is used herein as a far-field tornado detection and advance-warning parameter. In almost all cases, the measured circulation is quite insensitive to the data that have been voided and then filled. The tornado threat is still apparent.

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