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Darrel M. Kingfield and Joseph C. Picca

Abstract

Raindrop size sorting is a ubiquitous microphysical occurrence in precipitating systems. Owing to the greater terminal fall speed of larger particles, a raindrop’s fall trajectory can be sensitive to its size, and strong air currents (e.g., a convective updraft) can enhance this sensitivity. Indeed, observational and numerical model simulation studies have confirmed these effects on raindrop size distributions near convective updrafts. One striking example is the lofting of liquid drops and partially frozen hydrometeors above the environmental 0°C level, resulting in a small columnar region of positive differential reflectivity Z DR in polarimetric radar data, known as the Z DR column. This signature can serve as a proxy for updraft location and strength, offering operational forecasters a tool for monitoring convective trends. Beneath the 0°C level, where WSR-88D spatiotemporal resolution is highest, anomalously high Z DR collocated with lower reflectivity factor at horizontal polarization Z H is often observed within and beneath convective updrafts. Here, size sorting creates a deficit in small drops, while relatively large drops and melting hydrometeors are present in low concentrations. As such, this unique raindrop size distribution and its related polarimetric signature can indicate updraft location sooner and more frequently than the detection of a Z DR column. This paper introduces a novel algorithm that capitalizes on the improved radar coverage at lower levels and automates the detection of this size sorting signature. At the algorithm core, unique Z HZ DR relationships are created for each radar elevation scan, and positive Z DR outliers (often indicative of size sorting) are identified. Algorithm design, examples, performance, strengths and limitations, and future development are discussed.

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Jeffrey C. Snyder, Alexander V. Ryzhkov, Matthew R. Kumjian, Alexander P. Khain, and Joseph Picca

Abstract

Observations and recent high-resolution numerical model simulations indicate that liquid water and partially frozen hydrometeors can be lofted considerably above the environmental 0°C level in the updrafts of convective storms owing to the warm thermal perturbation from latent heating within the updraft and to the noninstantaneous nature of drop freezing. Consequently, upward extensions of positive differential reflectivity (i.e., Z DR ≥ 1 dB)—called Z DR columns—may be a useful proxy for detecting the initiation of new convective storms and examining the evolution of convective storm updrafts. High-resolution numerical simulations with spectral bin microphysics and a polarimetric forward operator reveal a strong spatial association between updrafts and Z DR columns and show the utility of examining the structure and evolution of Z DR columns for assessing updraft evolution. This paper introduces an automated Z DR column algorithm designed to provide additional diagnostic and prognostic information pertinent to convective storm nowcasting. Although suboptimal vertical resolution above the 0°C level and limitations imposed by commonly used scanning strategies in the operational WSR-88D network can complicate Z DR column detection, examples provided herein show that the algorithm can provide operational and research-focused meteorologists with valuable information about the evolution of convective storms.

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Erica M. Griffin, Terry J. Schuur, Alexander V. Ryzhkov, Heather D. Reeves, and Joseph C. Picca

Abstract

On 8–9 February 2013, the northeastern United States experienced a historic winter weather event ranking among the top five worst blizzards in the region. Heavy snowfall and blizzard conditions occurred from northern New Jersey, inland to New York, and northward through Maine. Storm-total snow accumulations of 30–61 cm were common, with maximum accumulations up to 102 cm and snowfall rates exceeding 15 cm h−1. Dual-polarization radar measurements collected for this winter event provide valuable insights into storm microphysical processes. In this study, polarimetric data from the Weather Surveillance Radar-1988 Doppler (WSR-88D) in Upton, New York (KOKX), are investigated alongside thermodynamic analyses from the 13-km Rapid Refresh model and surface precipitation type observations from both Meteorological Phenomena Identification Near the Ground (mPING) and the National Weather Service (NWS) Forecast Office in Upton, New York, for interpretation of polarimetric signatures. The storm exhibited unique polarimetric signatures, some of which have never before been documented for a winter system. Reflectivity values were unusually large, reaching magnitudes >50 dBZ in shallow regions of heavy wet snow near the surface. The 0°C transition line was exceptionally distinct in the polarimetric imagery, providing detail that was often unmatched by the numerical model output. Other features include differential attenuation of magnitudes typical of melting hail, depolarization streaks that provide evidence of electrification, nonuniform beamfilling, a “snow flare” signature, and localized downward excursions of the melting-layer bright band collocated with observed transitions in surface precipitation types. In agreement with previous studies, widespread elevated depositional growth layers, located at temperatures near the model-predicted −15°C isotherm, appear to be correlated with increased snowfall and large reflectivity factors Z H near the surface.

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Joseph C. Picca, David M. Schultz, Brian A. Colle, Sara Ganetis, David R. Novak, and Matthew J. Sienkiewicz

The northeast U.S. extratropical cyclone of 8–9 February 2013 produced blizzard conditions and more than 0.6–0.9 m (2–3 ft) of snow from Long Island through eastern New England. A surprising aspect of this blizzard was the development and rapid weakening of a snowband to the northwest of the cyclone center with radar ref lectivity factor exceeding 55 dBZ. Because the radar reflectivity within snowbands in winter storms rarely exceeds 40 dBZ, this event warranted further investigation. The high radar reflectivity was due to mixed-phase microphysics in the snowband, characterized by high differential reflectivity (Z DR > 2 dB) and low correlation coefficient (CC < 0.9), as measured by the operational dual-polarization radar in Upton, New York (KOKX). Consistent with these radar observations, heavy snow and ice pellets (both sleet and graupel) were observed. Later, as the reflectivity decreased to less than 40 dBZ, surface observations indicated a transition to primarily high-intensity dry snow, consistent with lower-tropospheric cold advection. Therefore, the rapid decrease of the 50+ dBZ reflectivity resulted from the transition from higher-density, mixed-phase precipitation to lower-density, dry-snow crystals and aggregates. This case study indicates the value that dual-polarization radar can have in an operational forecast environment for determining the variability of frozen precipitation (e.g., ice pellets, dry snow aggregates) on relatively small spatial scales.

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Richard L. Thompson, Bryan T. Smith, Jeremy S. Grams, Andrew R. Dean, Joseph C. Picca, Ariel E. Cohen, Elizabeth M. Leitman, Aaron M. Gleason, and Patrick T. Marsh

Abstract

Previous work with observations from the NEXRAD (WSR-88D) network in the United States has shown that the probability of damage from a tornado, as represented by EF-scale ratings, increases as low-level rotational velocity increases. This work expands on previous studies by including reported tornadoes from 2014 to 2015, as well as a robust sample of nontornadic severe thunderstorms [≥1-in.- (2.54 cm) diameter hail, thunderstorm wind gusts ≥ 50 kt (25 m s−1), or reported wind damage] with low-level cyclonic rotation. The addition of the nontornadic sample allows the computation of tornado damage rating probabilities across a spectrum of organized severe thunderstorms represented by right-moving supercells and quasi-linear convective systems. Dual-polarization variables are used to ensure proper use of velocity data in the identification of tornadic and nontornadic cases. Tornado damage rating probabilities increase as low-level rotational velocity V rot increases and circulation diameter decreases. The influence of height above radar level (or range from radar) is less obvious, with a muted tendency for tornado damage rating probabilities to increase as rotation (of the same V rot magnitude) is observed closer to the ground. Consistent with previous work on gate-to-gate shear signatures such as the tornadic vortex signature, easily identifiable rotation poses a greater tornado risk compared to more nebulous areas of cyclonic azimuthal shear. Additionally, tornado probability distributions vary substantially (for similar sample sizes) when comparing the southeast United States, which has a high density of damage indicators, to the Great Plains, where damage indicators are more sparse.

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Hongli Jiang, Steve Albers, Yuanfu Xie, Zoltan Toth, Isidora Jankov, Michael Scotten, Joseph Picca, Greg Stumpf, Darrel Kingfield, Daniel Birkenheuer, and Brian Motta

Abstract

The accurate and timely depiction of the state of the atmosphere on multiple scales is critical to enhance forecaster situational awareness and to initialize very short-range numerical forecasts in support of nowcasting activities. The Local Analysis and Prediction System (LAPS) of the Earth System Research Laboratory (ESRL)/Global Systems Division (GSD) is a numerical data assimilation and forecast system designed to serve such very finescale applications. LAPS is used operationally by more than 20 national and international agencies, including the NWS, where it has been operational in the Advanced Weather Interactive Processing System (AWIPS) since 1995.

Using computationally efficient and scientifically advanced methods such as a multigrid technique that adds observational information on progressively finer scales in successive iterations, GSD recently introduced a new, variational version of LAPS (vLAPS). Surface and 3D analyses generated by vLAPS were tested in the Hazardous Weather Testbed (HWT) to gauge their utility in both situational awareness and nowcasting applications. On a number of occasions, forecasters found that the vLAPS analyses and ensuing very short-range forecasts provided useful guidance for the development of severe weather events, including tornadic storms, while in some other cases the guidance was less sufficient.

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