Search Results

You are looking at 1 - 10 of 17 items for

  • Author or Editor: Samuel Haimov x
  • Refine by Access: All Content x
Clear All Modify Search
Samuel Haimov
and
Alfred Rodi

Abstract

Doppler velocity measurements from airborne meteorological Doppler radars require removal of the aircraft motion contribution in order to provide radial velocity of hydrometeor targets. This is a critical step for hydrometeor motion and wind retrievals. The aircraft motion contribution is defined as the scalar product between the radar antenna beam-pointing vector and the aircraft velocity vector at the antenna phase center. The accuracy in the removal of the aircraft velocity contribution is determined by the accuracy of the beam-pointing vector, the rigidity of the antenna mount, and the accuracy of the aircraft attitude and velocity measurements. In this paper an optimization technique is proposed to determine the antenna beam-pointing vector and to analyze its uncertainties using aircraft attitude and velocity data from a GPS-aided inertial measurement unit and radar observations of the earth surface. The technique is applied to Wyoming Cloud Radar (WCR) on the University of Wyoming King Air (UWKA) aircraft. The beam-pointing vectors of the two fixed downward-pointing WCR antennas are calibrated using data selected from several calibration flights. The maximum root-mean-square error in the calibrated beam-pointing angles is smaller than 0.03°, resulting in less than 0.1 m s−1 aircraft motion residual error in the Doppler velocities after removing the aircraft motion contribution. Some applicability and limitations to other airborne Doppler radars with fixed antennas are discussed.

Full access
Samuel Haimov
and
Alfred Rodi
Full access
Bart Geerts
,
Rick Damiani
, and
Samuel Haimov

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.

Full access
Andrew L. Pazmany
and
Samuel J. Haimov

Abstract

Coherent power is an alternative to the conventional noise-subtracted power technique for measuring weather radar signal power. The inherent noise-canceling feature of coherent power eliminates the need for estimating and subtracting the noise component, which is required when performing conventional signal power estimation at low signal-to-noise ratio. The coherent power technique is particularly useful when averaging a high number of samples to improve sensitivity to weak signals. In such cases, the signal power is small compared to the noise power and the required accuracy of the estimated noise power may be difficult to achieve. This paper compares conventional signal power estimation with the coherent power measurement technique by investigating bias, standard deviation, and probability of false alarm and detection rates as a function of signal-to-noise ratio and threshold level. This comparison is performed using analytical expressions, numerical simulations, and analysis of cloud and precipitation data collected with the airborne solid-state Ka-band precipitation radar (KPR) operated by the University of Wyoming.

Full access
Rick Damiani
,
Gabor Vali
, and
Samuel Haimov

Abstract

A newly developed technique for airborne dual-Doppler observations with the Wyoming Cloud Radar is used to characterize the velocity fields in vertical planes across cumulus turrets. The clouds sampled were continental in nature, with high bases (near 0°C) and with depths of 2–3 km. Clear evidence was found that the clouds evolved through sequences of bubbles, or thermals, with well-defined toroidal circulations, or vortex rings. The ring core and tube diameters were about 200–600 m, leading to turret sizes of 1–2 km in the horizontal. The largest updraft speeds were observed in the ring centers, but regions of turbulent, ascending air extended behind the thermals to distances comparable with the toroid sizes. Vertical shear of ambient winds, when present, led to a tilting of the updrafts and toroids. Patterns in the reflectivity and velocity fields indicated regions of major intrusions into the thermals, accompanied by entrainment of ambient air, or recycling of larger hydrometeors, depending on their location. In addition, at the upper cloud/environment interface, instability nodes contributed to further entrapment of cloud-free air. The observations presented in this paper constitute clear demonstrations and quantitative characterization of vortical circulations in growing cumulus turrets; they should provide a more reliable basis for the assessment of simulations and of model parameterizations.

Full access
Adam Majewski
,
Jeffrey R. French
, and
Samuel Haimov

Abstract

High-resolution airborne cloud Doppler radars such as the W-band Wyoming Cloud Radar (WCR) have, since the 1990s, investigated cloud microphysical, kinematic, and precipitation structures down to 30-m resolution. These measurements revolutionized our understanding of fine-scale cloud structure and the scales at which cloud processes occur. Airborne cloud Doppler radars may also resolve cloud turbulent eddy structure directly at 10-m scales. To date, cloud turbulence has been examined as variances and dissipation rates at coarser resolution than individual pulse volumes. The present work advances the potential of near-vertical pulse-pair Doppler spectrum width as a metric for turbulent air motion. Doppler spectrum width has long been used to investigate turbulent motions from ground-based remote sensors. However, complexities of airborne Doppler radar and spectral broadening resulting from platform and hydrometeor motions have limited airborne radar spectrum width measurements to qualitative interpretation only. Here we present the first quantitative validation of spectrum width from an airborne cloud radar. Echoes with signal-to-noise ratio greater than 10 dB yield spectrum width values that strongly correlate with retrieved mean Doppler variance for a range of nonconvective cloud conditions. Further, Doppler spectrum width within turbulent regions of cloud also shows good agreement with in situ eddy dissipation rate (EDR) and gust probe variance. However, the use of pulse-pair estimated spectrum width as a metric for turbulent air motion intensity is only suitable for turbulent air motions more energetic than the magnitude of spectral broadening, estimated to be <0.4 m s−1 for the WCR in these cases.

Significance Statement

Doppler spectrum width is a widely available airborne radar measurement previously considered too uncertain to attribute to atmospheric turbulence. We validate, for the first time, the response of spectrum width to turbulence at and away from research aircraft flight level and demonstrate that under certain conditions, spectrum width can be used to diagnose atmospheric turbulence down to scales of tens of meters. These high-resolution turbulent air motion intensity measurements may better connect to cloud hydrometeor process and growth response seen in coincident radar reflectivity structures proximate to turbulent eddies.

Open access
Bart Geerts
,
Yang Yang
,
Roy Rasmussen
,
Samuel Haimov
, and
Binod Pokharel

Abstract

Airborne vertical-plane dual-Doppler cloud radar data, collected on wind-parallel flight legs over a mountain in Wyoming during 16 winter storms, are used to analyze the growth, transport, and sedimentation of snow. In all storms the wind is rather strong, such that the flow is unblocked. The sampled clouds are mixed phase, shallow, and generally produce snowfall over the mountain only. The 2D scatterers’ mean motion in the vertical along-track plane below flight level is synthesized using one radar antenna pointing to nadir, and one 30° forward of nadir. This yields instantaneous cross-mountain hydrometeor streamlines.

The dynamics of the orographic flow dominate the precipitation patterns across the mountain. Three patterns are distinguished: the first two contain small convective cells, either boundary layer (BL) convection or elevated convection, the latter likely due to the release of potential instability in orographically lifted air. In these patterns the cross-mountain flow is relatively undisturbed. Precipitation from BL convection falls mostly on the windward side but precipitation from elevated convection may fall mostly in the lee. The third pattern is marked by more stratified flow, often with vertically propagating mountain waves, and with strong, plunging flow in the lee, resulting in rapid clearing of the storm across the crest and occasionally a hydraulic jump. In this case, most snow tends to fall upwind of the crest, although a shallow, sublimating snow “foot” is often seen over the leeward slopes.

Full access
Coltin Grasmick
,
Bart Geerts
,
Jeffrey R. French
,
Samuel Haimov
, and
Robert M. Rauber

Abstract

Properties of frozen hydrometeors in clouds remain difficult to sense remotely. Estimates of number concentration, distribution shape, ice particle density, and ice water content are essential for connecting cloud processes to surface precipitation. Progress has been made with dual-frequency radars, but validation has been difficult because of lack of particle imaging and sizing observations collocated with the radar measurements. Here, data are used from two airborne profiling (up and down) radars, the W-band Wyoming Cloud Radar and the Ka-band Profiling Radar, allowing for Ka–W-band dual-wavelength ratio (DWR) profiles. The aircraft (the University of Wyoming King Air) also carried a suite of in situ cloud and precipitation probes. This arrangement is optimal for relating the “flight-level” DWR (an average from radar gates below and above flight level) to ice particle size distributions measured by in situ optical array probes, as well as bulk properties such as minimum snow particle density and ice water content. This comparison reveals a strong relationship between DWR and the ice particle median-volume diameter. An optimal range of DWR values ensures the highest retrieval confidence, bounded by the radars’ relative calibration and DWR saturation, found here to be about 2.5–7.5 dB. The DWR-defined size distribution shape is used with a Mie scattering model and an experimental mass–diameter relationship to test retrievals of ice particle concentration and ice water content. Comparison with flight-level cloud-probe data indicate good performance, allowing microphysical interpretations for the rest of the vertical radar transects.

Free access
Min Deng
,
Jeffrey French
,
Bart Geerts
,
Samuel Haimov
,
Larry Oolman
,
Dave Plummer
, and
Zhien Wang

Abstract

As part of the analysis following the Seeded and Natural Orographic Wintertime Storms (SNOWIE) project, the ice water content (IWC) in ice and mixed-phase clouds is retrieved from airborne Wyoming Cloud Radar (WCR) measurements aboard the University of Wyoming King Air (UWKA), which has a suite of integrated in situ IWC, optical array probes, and remote sensing measurements, and it provides a unique dataset for this algorithm development and evaluation. A sensitivity study with different idealized ice particle habits shows that the retrieved IWC with aggregate ice particle habit agrees the best with the in situ measurement, especially in ice or ice-dominated mixed-phase clouds with a correlation coefficient (rr) of 0.91 and a bias of close to 0. For mixed-phase clouds with ice fraction ratio less than 0.8, the variances of IWC estimates increase (rr = 0.76) and the retrieved mean IWC is larger than in situ IWC by a factor of 2. This is found to be related to the uncertainty of in situ measurements, the large cloud inhomogeneity, and the retrieval assumption uncertainty. The simulated reflectivity Ze and IWC relationships assuming three idealized ice particle habits and measured particle size distributions show that hexagonal columns with the same Ze have a lower IWC than aggregates, whose Ze–IWC relation is more consistent with the observed WCR Ze and in situ IWC relation in those clouds. The 2D stereo probe (2DS) images also indicate that ice particle habit transition occurs in orographic mixed-phase clouds; hence, the retrieved IWC assuming modified gamma particle size distribution (PSD) of aggregate particles tends to have a greater bias in this kind of clouds.

Open access
Jeffrey R. French
,
Samuel J. Haimov
,
Larry D. Oolman
,
Vanda Grubišić
,
Stefano Serafin
, and
Lukas Strauss

Abstract

Two cases of mountain waves, rotors, and the associated turbulence in the lee of the Medicine Bow Mountains in southeastern Wyoming are investigated in a two-part study using aircraft observations and numerical simulations. In Part I, observations from in situ instruments and high-resolution cloud radar on board the University of Wyoming King Air aircraft are presented and analyzed. Measurements from the radar compose the first direct observations of wave-induced boundary layer separation.

The data from these two events show some striking similarities but also significant differences. In both cases, rotors were observed; yet one looks like a classical lee-wave rotor, while the other resembles an atmospheric hydraulic jump with midtropospheric gravity wave breaking aloft. High-resolution (30 × 30 m2) dual-Doppler syntheses of the two-dimensional velocity fields in the vertical plane beneath the aircraft reveal the boundary layer separation, the scale and structure of the attendant rotors, and downslope windstorms. In the stronger of the two events, near-surface winds upwind of the boundary layer separation reached 35 m s−1, and vertical winds were in excess of 10 m s−1. Moderate to strong turbulence was observed within and downstream of these regions. In both cases, the rotor extended horizontally 5–10 km and vertically 2–2.5 km. Horizontal vorticity within the rotor zone reached 0.2 s−1. Several subrotors from 500 to 1000 m in diameter were identified inside the main rotor in one of the cases.

Part II presents a modeling study and investigates the kinematic structure and the dynamic evolution of these two events.

Full access