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Cameron R. Homeyer

Abstract

The responsible mechanism for the formation of the enhanced-V infrared cloud-top feature observed above tropopause-penetrating thunderstorms is not well understood. A new method for the combination of volumetric radar reflectivity from individual radars into three-dimensional composites with high vertical resolution (1 km) is introduced and used to test various formation mechanisms proposed in the literature. For analysis, a set of 89 enhanced-V storms over the eastern continental United States are identified in the 10-yr period from 2001 to 2010 using geostationary satellite data. The background atmospheric state from each storm is determined using the Interim ECMWF Re-Analysis (ERA-Interim) and radiosonde observations. In conjunction with the infrared temperature fields, analysis of the radar data in a coordinate relative to the location of the overshooting convective top and in altitudes relative to the tropopause suggests that above-anvil (stratospheric) cirrus clouds are the most likely mechanism for the formation of the enhanced V.

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Cameron R. Homeyer and Matthew R. Kumjian

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The authors present observations of the microphysical characteristics of deep convection that overshoots the altitude of the extratropical tropopause from analysis of the polarimetric radar variables of radar reflectivity factor at horizontal polarization Z H, differential reflectivity Z DR, and specific differential phase K DP. Identified overshooting convective storms are separated by their organization and intensity into three classifications: organized convection, discrete ordinary convection, and discrete supercell convection. Composite analysis of identified storms for each classification reveals microphysical features similar to those found in previous studies of deep convection, with deep columns of highly positive Z DR and K DP representing lofting of liquid hydrometeors within the convective updraft and above the melting level. In addition, organized and discrete supercell classifications show distinct near-zero Z DR minima aligned horizontally with and at altitudes higher than the updraft column features, likely indicative of the frequent presence of large hail in each case. Composites for organized convective systems show a similar Z DR minimum throughout the portion of the convective core that is overshooting the tropopause, corresponding to Z H in the range of 15–30 dBZ and negative K DP observations, in agreement with the scattering properties of small hail and/or lump or conical graupel. Additional analyses of the evolution of overshooting storms reveals that the Z DR minima indicative of hail in the middle and upper troposphere and graupel in the overshooting top are associated with the mature and decaying stages of overshooting, respectively, supporting their inferred contributions to the observed polarimetric fields.

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Elisa M. Murillo and Cameron R. Homeyer

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Severe hail days account for the vast majority of severe weather–induced property losses in the United States each year. In the United States, real-time detection of severe storms is largely conducted using ground-based radar observations, mostly using the operational Next Generation Weather Radar network (NEXRAD), which provides three-dimensional information on the physics and dynamics of storms at ~5-min time intervals. Recent NEXRAD upgrades to higher resolution and to dual-polarization capabilities have provided improved hydrometeor discrimination in real time. New geostationary satellite platforms have also led to significant changes in observing capabilities over the United States beginning in 2016, with spatiotemporal resolution that is comparable to that of NEXRAD. Given these recent improvements, a thorough assessment of their ability to identify hailstorms and hail occurrence and to discriminate between hail sizes is needed. This study provides a comprehensive comparative analysis of existing observational radar and satellite products from more than 10 000 storms objectively identified via radar echo-top tracking and nearly 6000 hail reports during 30 recent severe weather days (2013–present). It is found that radar observations provide the most skillful discrimination between severe and nonsevere hailstorms and identification of individual hail occurrence. Single-polarization and dual-polarization radar observations perform similarly at these tasks, with the greatest skill found from combining both single- and dual-polarization metrics. In addition, revisions to the “maximum expected size of hail” (MESH) metric are proposed and are shown to improve spatiotemporal comparisons between reported hail sizes and radar-based estimates for the cases studied.

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Shawn L. Handler and Cameron R. Homeyer

Abstract

In 2013, all NEXRAD WSR-88D units in the United States were upgraded to dual polarization. Dual polarization allows for the identification of precipitation particle shape, size, orientation, and concentration. In this study, dual-polarization NEXRAD observations from 34 recent events are used to identify the bulk microphysical characteristics of a specific subset of mesoscale convective systems (MCSs), the leading-line trailing-stratiform (LLTS) MCS. NEXRAD observations are used to examine hydrometeor distributions in relative altitude to the 0°C level and as a function of storm life cycle, precipitation source (convective or stratiform), and storm environment. The analysis reveals that graupel particles are the most frequently classified hydrometeor class in a layer extending from the 0°C-level altitude to approximately 5 km above within the convective region. Below the 0°C level, rain is the most frequently classified hydrometeor, with small hail and graupel concentrations present throughout the LLTS system’s life cycle. The stratiform precipitation region contains small graupel concentrations in a shallow layer above the 0°C level, with pristine ice crystals being classified as the most frequently observed hydrometeor at higher altitudes and snow aggregates being classified as the most frequently observed hydrometeor at lower altitudes above the environmental 0°C level. Variations in most unstable convective available potential energy (MUCAPE) have the largest impact on the vertical distribution of hydrometeors, because more-unstable environments are characterized by a greater production of rimed ice.

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Elisa M. Murillo and Cameron R. Homeyer
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Cameron R. Homeyer and Kenneth P. Bowman

Abstract

Rossby wave breaking is an important mechanism for the two-way exchange of air between the tropical upper troposphere and lower stratosphere and the extratropical lower stratosphere. The authors present a 30-yr climatology (1981–2010) of anticyclonically and cyclonically sheared wave-breaking events along the boundary of the tropics in the 350–500-K potential temperature range from ECMWF Interim Re-Analysis (ERA-Interim). Lagrangian transport analyses show net equatorward transport from wave breaking near 380 K and poleward transport at altitudes below and above the 370–390-K layer. The finding of poleward transport at lower levels is in disagreement with previous studies and is shown to largely depend on the choice of tropical boundary. In addition, three distinct modes of transport for anticyclonic wave-breaking events are found near the tropical tropopause (380 K): poleward, equatorward, and symmetric. Transport associated with cyclonic wave-breaking events, however, is predominantly poleward. The three transport modes for anticyclonic wave breaking are associated with specific characteristics of the geometry of the mean flow. In particular, composite averages show that poleward transport is associated with a “split” subtropical jet where the jet on the upstream side of the breaking wave extends eastward and lies poleward and at lower altitudes of the subtropical jet on the downstream side, producing a substantial longitudinal overlap between the two jets. Equatorward transport is not associated with a split subtropical jet and is found immediately downstream of stationary anticyclones in the tropics, often associated with monsoon circulations. It is further shown that, in general, the transport direction of breaking waves is determined primarily by the relative positions of the jets.

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Jong-Hoon Jeong, Jiwen Fan, and Cameron R. Homeyer

Abstract

Following on our study of hail for the southern Great Plains (SGP), we investigated the spatial and temporal hail trends and variabilities for the northern Great Plains (NGP) and the contributing factors for summers (June–August) focusing on the period of 2004–16 using two independent hail datasets. Analysis for an extended period (1994–2016) with the hail reports was also conducted to more reliably investigate the contributing factors. Both severe hail (diameter between 1 and 2 inches) and significant severe hail (SSH; diameter > 2 inches) were examined and similar results were obtained. The occurrence of hail over the NGP demonstrated a large interannual variability, with a positive slope overall. Spatially, the increase is mainly located in the western part of Nebraska, South Dakota, and North Dakota. We find the three major dynamical factors that most likely contribute to the hail interannual variability in the NGP are El Niño–Southern Oscillation (ENSO), the North Atlantic subtropical high (NASH), and the low-level jet (LLJ). With a thermodynamical variable integrated water vapor transport that is strongly controlled by LLJ, the four factors can explain 78% of the interannual variability in the number of SSH reports. Hail occurrences in the La Niña years are higher than the El Niño years since the jet stream is stronger and NASH extends farther into the southeastern United States, thereby strengthening the LLJ and in turn water vapor transport. Interestingly, the important factors impacting hail interannual variability over the NGP are quite different from those for the SGP, except for ENSO.

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Jong-Hoon Jeong, Jiwen Fan, Cameron R. Homeyer, and Zhangshuan Hou

Abstract

Hailstones are a natural hazard that pose a significant threat to property and are responsible for significant economic losses each year in the United States. Detailed understanding of their characteristics is essential to mitigate their impact. Identifying the dynamic and physical factors contributing to hail formation and hailstone sizes is of great importance to weather and climate prediction and policymakers. In this study, we have analyzed the temporal and spatial variabilities of severe hail occurrences over the U.S. southern Great Plains (SGP) states from 2004 to 2016 using two hail datasets: hail reports from the Storm Prediction Center and the newly developed radar-retrieved maximum expected size of hail (MESH). It is found that severe and significant severe hail occurrences have a considerable year-to-year temporal variability in the SGP region. The interannual variabilities have a strong correspondence with sea surface temperature anomalies over the northern Gulf of Mexico and there is no outlier. The year 2016 is identified as an outlier for the correlations with both El Niño–Southern Oscillation (ENSO) and aerosol loading. The correlations with ENSO and aerosol loading are not statistically robust to inclusion of the outlier 2016. Statistical analysis without the outlier 2016 shows that 1) aerosols that may be mainly from northern Mexico have the largest correlation with hail interannual variability among the three factors and 2) meteorological covariation does not significantly contribute to the high correlation. These analyses warrant further investigations of aerosol impacts on hail occurrence.

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Cameron R. Homeyer, Courtney Schumacher, and Larry J. Hopper Jr.

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Long-term radar observations from a subtropical location in southeastern Texas are used to examine the impact of storm systems with tropical or extratropical characteristics on the large-scale circulation. Climatological vertical profiles of the horizontal wind divergence are analyzed for four distinct storm classifications: cold frontal (CF), warm frontal (WF), deep convective upper-level disturbance (DC-ULD), and nondeep convective upper-level disturbances (NC-ULD). DC-ULD systems are characterized by weakly baroclinic or equivalent barotropic environments that are more tropical in nature, while the remaining classifications are representative of common midlatitude systems with varying degrees of baroclinicity. DC-ULD systems are shown to have the highest levels of nondivergence (LND) and implied diabatic heating maxima near 6 km, whereas the remaining baroclinic storm classifications have LND altitudes that are about 0.5–1 km lower. Analyses of climatological mean divergence profiles are also separated by rain regions that are primarily convective, stratiform, or indeterminate. Convective–stratiform separations reveal similar divergence characteristics to those observed in the tropics in previous studies, with higher altitudes of implied heating in stratiform rain regions, suggesting that the convective–stratiform paradigm outlined in previous studies is applicable in the midlatitudes. Divergence profiles that cannot be classified as primarily convective or stratiform are typically characterized by large regions of stratiform rain with areas of embedded convection of shallow to moderate extent (i.e., echo tops <10 km). These indeterminate profiles illustrate that, despite not being very deep and accounting for a relatively small fraction of a given storm system, convection dominates the vertical divergence profile and implied heating in these cases.

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Kenneth P. Bowman, Cameron R. Homeyer, and Dalon G. Stone

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A number of Earth remote sensing satellites are currently carrying passive microwave radiometers. A variety of different retrieval algorithms are used to estimate surface rain rates over the ocean from the microwave radiances observed by the radiometers. This study compares several different satellite algorithms with each other and with independent data from rain gauges on ocean buoys. The rain gauge data are from buoys operated by the NOAA Pacific Marine Environmental Laboratory. Potential errors and biases in the gauge data are evaluated. Satellite data are from the Tropical Rainfall Measuring Mission Microwave Imager and from the Special Sensor Microwave Imager instruments on the operational Defense Meteorological Satellite Program F13, F14, and F15 satellites. These data have been processed into rain-rate estimates by the NASA Precipitation Measurement Mission and by Remote Sensing Systems, Inc. Biases between the different datasets are estimated by computing differences between long-term time averages. Most of the satellite datasets agree with each other, and with the gauge data, to within 10% or less. The biases tend to be proportional to the mean rain rate, but the geographical patterns of bias vary depending on the choice of data source and algorithm. Some datasets, however, show biases as large as about 25%, so care should be taken when using these data for climatological studies.

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