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- Author or Editor: Cameron R. Homeyer x
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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.
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.
Abstract
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.
Abstract
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.
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.
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.
Abstract
A new method that combines radar reflectivities from individual Next Generation Weather Radars (NEXRAD) into a three-dimensional composite with high horizontal and vertical resolution is used to estimate storm-top altitudes for the continental United States east of the Rocky Mountains. Echo-top altitudes are compared with the altitude of the lapse-rate tropopause calculated from the ERA-Interim reanalysis and radiosondes. To sample the diurnal and annual cycles, tropopause-penetrating convection is analyzed at 3-h intervals throughout 2004. Overshooting convection is most common in the north-central part of the United States (the high plains). There is a pronounced seasonal cycle; the majority of overshooting systems occur during the warm season (March–August). There is also a strong diurnal cycle, with maximum overshooting occurring near 0000 UTC. The overshooting volume decreases rapidly with height above the tropopause. Radiosonde observations are used to evaluate the quality of the reanalysis tropopause altitudes and the dependence of overshooting depth on environmental characteristics. The radar–radiosonde comparison reveals that overshooting is deeper in double-tropopause environments and increases as the stability of the lower stratosphere decreases.
Abstract
A new method that combines radar reflectivities from individual Next Generation Weather Radars (NEXRAD) into a three-dimensional composite with high horizontal and vertical resolution is used to estimate storm-top altitudes for the continental United States east of the Rocky Mountains. Echo-top altitudes are compared with the altitude of the lapse-rate tropopause calculated from the ERA-Interim reanalysis and radiosondes. To sample the diurnal and annual cycles, tropopause-penetrating convection is analyzed at 3-h intervals throughout 2004. Overshooting convection is most common in the north-central part of the United States (the high plains). There is a pronounced seasonal cycle; the majority of overshooting systems occur during the warm season (March–August). There is also a strong diurnal cycle, with maximum overshooting occurring near 0000 UTC. The overshooting volume decreases rapidly with height above the tropopause. Radiosonde observations are used to evaluate the quality of the reanalysis tropopause altitudes and the dependence of overshooting depth on environmental characteristics. The radar–radiosonde comparison reveals that overshooting is deeper in double-tropopause environments and increases as the stability of the lower stratosphere decreases.
Abstract
Expansive cirrus clouds present above the anvils of extratropical convection have been observed in satellite and aircraft-based imagery for several decades. Despite knowledge of their occurrence, the precise mechanisms and atmospheric conditions leading to their formation and maintenance are not entirely known. Here, the formation of these cirrus “plumes” is examined using a combination of satellite imagery, four-dimensional ground-based radar observations, assimilated atmospheric states from a state-of-the-art reanalysis, and idealized numerical simulations with explicitly resolved convection. Using data from 20 recent events (2013–present), it is found that convective cores of storms with above-anvil cirrus plumes reach altitudes 1–6 km above the tropopause. Thus, it is likely that these clouds represent the injection of cloud material into the lower stratosphere. Comparison of storms with above-anvil cirrus plumes and observed tropopause-penetrating convection without plumes reveals an association with large vector differences between the motion of a storm and the environmental wind in the upper troposphere and lower stratosphere (UTLS), suggesting that gravity wave breaking and/or stretching of the tropopause-penetrating cloud are/is more prevalent in plume-producing storms. A weak relationship is found between plume occurrence and the stability of the lower stratosphere (or tropopause structure), and no relationship is found with the duration of stratospheric penetration or stratospheric humidity. Idealized model simulations of tropopause-penetrating convection with small and large magnitudes of storm-relative wind in the UTLS are found to reproduce the observationally established storm-relative wind relationship and show that frequent gravity wave breaking is the primary mechanism responsible for plume formation.
Abstract
Expansive cirrus clouds present above the anvils of extratropical convection have been observed in satellite and aircraft-based imagery for several decades. Despite knowledge of their occurrence, the precise mechanisms and atmospheric conditions leading to their formation and maintenance are not entirely known. Here, the formation of these cirrus “plumes” is examined using a combination of satellite imagery, four-dimensional ground-based radar observations, assimilated atmospheric states from a state-of-the-art reanalysis, and idealized numerical simulations with explicitly resolved convection. Using data from 20 recent events (2013–present), it is found that convective cores of storms with above-anvil cirrus plumes reach altitudes 1–6 km above the tropopause. Thus, it is likely that these clouds represent the injection of cloud material into the lower stratosphere. Comparison of storms with above-anvil cirrus plumes and observed tropopause-penetrating convection without plumes reveals an association with large vector differences between the motion of a storm and the environmental wind in the upper troposphere and lower stratosphere (UTLS), suggesting that gravity wave breaking and/or stretching of the tropopause-penetrating cloud are/is more prevalent in plume-producing storms. A weak relationship is found between plume occurrence and the stability of the lower stratosphere (or tropopause structure), and no relationship is found with the duration of stratospheric penetration or stratospheric humidity. Idealized model simulations of tropopause-penetrating convection with small and large magnitudes of storm-relative wind in the UTLS are found to reproduce the observationally established storm-relative wind relationship and show that frequent gravity wave breaking is the primary mechanism responsible for plume formation.
Abstract
Assessments of spatiotemporal severe hailfall characteristics using hail reports are plagued by serious limitations in report databases, including biases in reported sizes, occurrence time, and location. Multiple studies have used Next Generation Weather Radar (NEXRAD) network observations or environmental hail proxies from reanalyses. Previous work has specifically utilized the single-polarization radar parameter maximum expected size of hail (MESH). In addition to previous work being temporally limited, updates are needed to include recent improvements that have been made to MESH. This study aims to quantify severe hailfall characteristics during a 23-yr period, markedly longer than previous studies, using both radar observations and reanalysis data. First, the improved MESH configuration is applied to the full archive of gridded hourly radar observations known as GridRad (1995–2017). Next, environmental constraints from the Modern-Era Retrospective Analysis for Research and Applications, version 2, are applied to the MESH distributions to produce a corrected hailfall climatology that accounts for the reduced likelihood of hail reaching the ground. Spatial, diurnal, and seasonal patterns show that in contrast to the report climatology indicating one high-frequency hail maximum centered on the Great Plains, the MESH-only method characterizes two regions: the Great Plains and the Gulf Coast. The environmentally filtered MESH climatology reveals improved agreement between report characteristics (frequency, location, and timing) and the recently improved MESH calculation methods, and it reveals an overall increase in diagnosed hail days and westward broadening in the spatial maximum in the Great Plains than that seen in reports.
Abstract
Assessments of spatiotemporal severe hailfall characteristics using hail reports are plagued by serious limitations in report databases, including biases in reported sizes, occurrence time, and location. Multiple studies have used Next Generation Weather Radar (NEXRAD) network observations or environmental hail proxies from reanalyses. Previous work has specifically utilized the single-polarization radar parameter maximum expected size of hail (MESH). In addition to previous work being temporally limited, updates are needed to include recent improvements that have been made to MESH. This study aims to quantify severe hailfall characteristics during a 23-yr period, markedly longer than previous studies, using both radar observations and reanalysis data. First, the improved MESH configuration is applied to the full archive of gridded hourly radar observations known as GridRad (1995–2017). Next, environmental constraints from the Modern-Era Retrospective Analysis for Research and Applications, version 2, are applied to the MESH distributions to produce a corrected hailfall climatology that accounts for the reduced likelihood of hail reaching the ground. Spatial, diurnal, and seasonal patterns show that in contrast to the report climatology indicating one high-frequency hail maximum centered on the Great Plains, the MESH-only method characterizes two regions: the Great Plains and the Gulf Coast. The environmentally filtered MESH climatology reveals improved agreement between report characteristics (frequency, location, and timing) and the recently improved MESH calculation methods, and it reveals an overall increase in diagnosed hail days and westward broadening in the spatial maximum in the Great Plains than that seen in reports.
Abstract
This study presents a new storm classification method for objectively stratifying three-dimensional radar echo into five categories: convection, convective updraft, precipitating stratiform, nonprecipitating stratiform, and ice-only anvil. The Storm Labeling in Three Dimensions (SL3D) algorithm utilizes volumetric radar data to classify radar echo based on storm height, depth, and intensity in order to provide a new method for updraft classification and improve upon the limitations of traditional storm classification algorithms. Convective updrafts are identified by searching for three known polarimetric radar signatures: weak-echo regions (bounded and unbounded) in the radar reflectivity factor at horizontal polarization (
Abstract
This study presents a new storm classification method for objectively stratifying three-dimensional radar echo into five categories: convection, convective updraft, precipitating stratiform, nonprecipitating stratiform, and ice-only anvil. The Storm Labeling in Three Dimensions (SL3D) algorithm utilizes volumetric radar data to classify radar echo based on storm height, depth, and intensity in order to provide a new method for updraft classification and improve upon the limitations of traditional storm classification algorithms. Convective updrafts are identified by searching for three known polarimetric radar signatures: weak-echo regions (bounded and unbounded) in the radar reflectivity factor at horizontal polarization (
Abstract
Many studies have aimed to identify novel storm characteristics that are indicative of current or future severe weather potential using a combination of ground-based radar observations and severe reports. However, this is often done on a small scale using limited case studies on the order of tens to hundreds of storms due to how time-intensive this process is. Herein, we introduce the GridRad-Severe dataset, a database including ∼100 severe weather days per year and upward of 1.3 million objectively tracked storms from 2010 to 2019. Composite radar volumes spanning objectively determined, report-centered domains are created for each selected day using the GridRad compositing technique, with dates objectively determined using report thresholds defined to capture the highest-end severe weather days from each year, evenly distributed across all severe report types (tornadoes, severe hail, and severe wind). Spatiotemporal domain bounds for each event are objectively determined to encompass both the majority of reports and the time of convection initiation. Severe weather reports are matched to storms that are objectively tracked using the radar data, so the evolution of the storm cells and their severe weather production can be evaluated. Herein, we apply storm mode (single-cell, multicell, or mesoscale convective system storms) and right-moving supercell classification techniques to the dataset, and revisit various questions about severe storms and their bulk characteristics posed and evaluated in past work. Additional applications of this dataset are reviewed for possible future studies.
Abstract
Many studies have aimed to identify novel storm characteristics that are indicative of current or future severe weather potential using a combination of ground-based radar observations and severe reports. However, this is often done on a small scale using limited case studies on the order of tens to hundreds of storms due to how time-intensive this process is. Herein, we introduce the GridRad-Severe dataset, a database including ∼100 severe weather days per year and upward of 1.3 million objectively tracked storms from 2010 to 2019. Composite radar volumes spanning objectively determined, report-centered domains are created for each selected day using the GridRad compositing technique, with dates objectively determined using report thresholds defined to capture the highest-end severe weather days from each year, evenly distributed across all severe report types (tornadoes, severe hail, and severe wind). Spatiotemporal domain bounds for each event are objectively determined to encompass both the majority of reports and the time of convection initiation. Severe weather reports are matched to storms that are objectively tracked using the radar data, so the evolution of the storm cells and their severe weather production can be evaluated. Herein, we apply storm mode (single-cell, multicell, or mesoscale convective system storms) and right-moving supercell classification techniques to the dataset, and revisit various questions about severe storms and their bulk characteristics posed and evaluated in past work. Additional applications of this dataset are reviewed for possible future studies.
Abstract
Changes in tropical width can have important consequences in sectors including ecosystems, agriculture, and health. Observations suggest tropical expansion over the past 30 years although studies have not agreed on the magnitude of this change. Climate model projections have also indicated an expansion and show similar uncertainty in its magnitude. This study utilizes an objective, longitudinally varying, tropopause break method to define the extent of the tropics at upper levels. The location of the tropopause break is associated with enhanced stratosphere–troposphere exchange and thus its structure influences the chemical composition of the stratosphere. The method shows regional variations in the width of the upper-level tropics in the past and future. Four modern reanalyses show significant contraction of the tropics over the eastern Pacific between 1981 and 2015, and slight but significant expansion in other regions. The east Pacific narrowing contributes to zonal mean narrowing, contradicting prior work, and is attributed to the use of monthly and zonal mean data in prior studies. Six global climate models perform well in representing the climatological location of the tropical boundary. Future projections show a spread in the width trend (from ~0.5° decade−1 of narrowing to ~0.4° decade−1 of widening), with a narrowing projected across the east Pacific and Northern Hemisphere Americas. This study illustrates that this objective tropopause break method that uses instantaneous data and does not require zonal averaging is appropriate for identifying upper-level tropical width trends and the break location is connected with local and regional changes in precipitation.
Abstract
Changes in tropical width can have important consequences in sectors including ecosystems, agriculture, and health. Observations suggest tropical expansion over the past 30 years although studies have not agreed on the magnitude of this change. Climate model projections have also indicated an expansion and show similar uncertainty in its magnitude. This study utilizes an objective, longitudinally varying, tropopause break method to define the extent of the tropics at upper levels. The location of the tropopause break is associated with enhanced stratosphere–troposphere exchange and thus its structure influences the chemical composition of the stratosphere. The method shows regional variations in the width of the upper-level tropics in the past and future. Four modern reanalyses show significant contraction of the tropics over the eastern Pacific between 1981 and 2015, and slight but significant expansion in other regions. The east Pacific narrowing contributes to zonal mean narrowing, contradicting prior work, and is attributed to the use of monthly and zonal mean data in prior studies. Six global climate models perform well in representing the climatological location of the tropical boundary. Future projections show a spread in the width trend (from ~0.5° decade−1 of narrowing to ~0.4° decade−1 of widening), with a narrowing projected across the east Pacific and Northern Hemisphere Americas. This study illustrates that this objective tropopause break method that uses instantaneous data and does not require zonal averaging is appropriate for identifying upper-level tropical width trends and the break location is connected with local and regional changes in precipitation.
Abstract
Recent field campaigns, observational studies, and modeling work have demonstrated that extratropical tropopause-overshooting convection has a substantial, and previously underestimated impact on stratospheric water vapor concentrations. This necessitates improved understanding of how tropopause-overshooting convection will respond to a warming climate. A growing body of research indicates that environments conducive to severe thunderstorms will occur more often and be increasingly unstable in the future, but no study has examined how this may be related to increased overshooting. To rectify this, this study leverages an existing pseudo-global warming (PGW) experiment to evaluate potential future changes in tropopause-overshooting convection over North America. We examine two 10-year simulations consisting of (1) a retrospective period (2003 – 2012) forced by ERA-interim initial and boundary conditions (the control simulation), and (2) the same retrospective period with CMIP5 ensemble-mean high-end emission scenario climate changes added to the initial and boundary conditions (the PGW simulation). Tropopause-overshooting convection in the control simulation is validated against observed overshoots from both ground-based radar observations in the United States and GOES satellite observations over North America. The model is shown to effectively simulate the observed regional distribution, annual cycle, and diurnal cycle of tropopause-overshooting convection. The projected response of tropopause-overshooting convection in the PGW simulation is found to increase more than 250% across the model domain, and the projected seasonal period of frequent tropopause-overshooting convection is shown to extend into late-summer. Additionally, tropopause-overshooting convection with extreme tropopause-relative heights (> 4 km) are more frequent in a warmed climate scenario.
Abstract
Recent field campaigns, observational studies, and modeling work have demonstrated that extratropical tropopause-overshooting convection has a substantial, and previously underestimated impact on stratospheric water vapor concentrations. This necessitates improved understanding of how tropopause-overshooting convection will respond to a warming climate. A growing body of research indicates that environments conducive to severe thunderstorms will occur more often and be increasingly unstable in the future, but no study has examined how this may be related to increased overshooting. To rectify this, this study leverages an existing pseudo-global warming (PGW) experiment to evaluate potential future changes in tropopause-overshooting convection over North America. We examine two 10-year simulations consisting of (1) a retrospective period (2003 – 2012) forced by ERA-interim initial and boundary conditions (the control simulation), and (2) the same retrospective period with CMIP5 ensemble-mean high-end emission scenario climate changes added to the initial and boundary conditions (the PGW simulation). Tropopause-overshooting convection in the control simulation is validated against observed overshoots from both ground-based radar observations in the United States and GOES satellite observations over North America. The model is shown to effectively simulate the observed regional distribution, annual cycle, and diurnal cycle of tropopause-overshooting convection. The projected response of tropopause-overshooting convection in the PGW simulation is found to increase more than 250% across the model domain, and the projected seasonal period of frequent tropopause-overshooting convection is shown to extend into late-summer. Additionally, tropopause-overshooting convection with extreme tropopause-relative heights (> 4 km) are more frequent in a warmed climate scenario.
