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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.
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.
Abstract
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.
Abstract
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.
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.
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.
Abstract
Forecasting tornadogenesis remains a difficult problem in meteorology, especially for short-lived, predominantly nonsupercellular tornadic storms embedded within mesoscale convective systems (MCSs). This study compares populations of tornadic nonsupercellular MCS storm cells with their nontornadic counterparts, focusing on nontornadic storms that have similar radar characteristics to tornadic storms. Comparisons of single-polarization radar variables during storm lifetimes show that median values of low-level, midlevel, and column-maximum azimuthal shear, as well as low-level radial divergence, enable the highest degree of separation between tornadic and nontornadic storms. Focusing on low-level azimuthal shear values, null storms were randomly selected such that the distribution of null low-level azimuthal shear values matched the distribution of tornadic values. After isolating the null cases from the nontornadic population, signatures emerge in single-polarization data that enable discrimination between nontornadic and tornadic storms. In comparison, dual-polarization variables show little deviation between storm types. Tornadic storms both at tornadogenesis and at a 20-min lead time show collocation of the primary storm updraft with enhanced near-surface rotation and convergence, facilitating the nonmesocyclonic tornadogenesis processes.
Abstract
Forecasting tornadogenesis remains a difficult problem in meteorology, especially for short-lived, predominantly nonsupercellular tornadic storms embedded within mesoscale convective systems (MCSs). This study compares populations of tornadic nonsupercellular MCS storm cells with their nontornadic counterparts, focusing on nontornadic storms that have similar radar characteristics to tornadic storms. Comparisons of single-polarization radar variables during storm lifetimes show that median values of low-level, midlevel, and column-maximum azimuthal shear, as well as low-level radial divergence, enable the highest degree of separation between tornadic and nontornadic storms. Focusing on low-level azimuthal shear values, null storms were randomly selected such that the distribution of null low-level azimuthal shear values matched the distribution of tornadic values. After isolating the null cases from the nontornadic population, signatures emerge in single-polarization data that enable discrimination between nontornadic and tornadic storms. In comparison, dual-polarization variables show little deviation between storm types. Tornadic storms both at tornadogenesis and at a 20-min lead time show collocation of the primary storm updraft with enhanced near-surface rotation and convergence, facilitating the nonmesocyclonic tornadogenesis processes.
Abstract
Above-anvil cirrus plumes (AACPs) in midlatitude convection are important indicators of severe storms and stratospheric hydration events. Recent studies of AACPs have shown large variability in their characteristics, although many of the causes remain unknown. Notably, some AACPs appear equally as cold (or colder) than the broader storm top when compared to the more frequently observed warm AACP feature in infrared satellite imagery. To confidently identify the presence of an AACP, trained experts utilize infrared imagery to support the primary source of AACP identification, visible imagery. Thus, nighttime AACPs are often left unidentified due to unavailable visible imagery, especially for cold AACPs. In this study, 89 warm and 89 cold AACPs from 1-min GOES-16 satellite imagery coupled with ground-based radar observations and reanalysis data are comparatively evaluated to answer the following research questions: 1) Why do some AACPs exhibit a warm feature in infrared imagery while others do not, and 2) what observable storm and environment differences exist between warm and cold AACPs? It is found that cold AACPs tend to occur in tropical environments, which feature higher, cold-point tropopauses. Conversely, warm AACPs tend to occur in midlatitude environments, with lower tropopauses accompanied by an isothermal region (or tropopause inversion layer) in the lower stratosphere. Similar storm characteristics are found for warm and cold AACP events, implying that infrared temperature variability is driven by environmental differences. Together, these results suggest that cold AACPs are predominantly tropospheric phenomena, while warm AACPs reside in the lower stratosphere.
Significance Statement
The purpose of this study is to determine why some storms with a specific cloud-top feature exhibit a broad warm spot in infrared satellite imagery while others appear cold. This is important because storms with this specific cloud-top feature, whether warm or cold, produce much more severe weather than most other storms. These cloud-top features are also potentially indicative of increased water vapor in the stratosphere, which results in warming of Earth’s climate. Our results help us better understand storms that are frequently severe and suggest that the storms with cold features are less important to understanding stratospheric water vapor and climate change.
Abstract
Above-anvil cirrus plumes (AACPs) in midlatitude convection are important indicators of severe storms and stratospheric hydration events. Recent studies of AACPs have shown large variability in their characteristics, although many of the causes remain unknown. Notably, some AACPs appear equally as cold (or colder) than the broader storm top when compared to the more frequently observed warm AACP feature in infrared satellite imagery. To confidently identify the presence of an AACP, trained experts utilize infrared imagery to support the primary source of AACP identification, visible imagery. Thus, nighttime AACPs are often left unidentified due to unavailable visible imagery, especially for cold AACPs. In this study, 89 warm and 89 cold AACPs from 1-min GOES-16 satellite imagery coupled with ground-based radar observations and reanalysis data are comparatively evaluated to answer the following research questions: 1) Why do some AACPs exhibit a warm feature in infrared imagery while others do not, and 2) what observable storm and environment differences exist between warm and cold AACPs? It is found that cold AACPs tend to occur in tropical environments, which feature higher, cold-point tropopauses. Conversely, warm AACPs tend to occur in midlatitude environments, with lower tropopauses accompanied by an isothermal region (or tropopause inversion layer) in the lower stratosphere. Similar storm characteristics are found for warm and cold AACP events, implying that infrared temperature variability is driven by environmental differences. Together, these results suggest that cold AACPs are predominantly tropospheric phenomena, while warm AACPs reside in the lower stratosphere.
Significance Statement
The purpose of this study is to determine why some storms with a specific cloud-top feature exhibit a broad warm spot in infrared satellite imagery while others appear cold. This is important because storms with this specific cloud-top feature, whether warm or cold, produce much more severe weather than most other storms. These cloud-top features are also potentially indicative of increased water vapor in the stratosphere, which results in warming of Earth’s climate. Our results help us better understand storms that are frequently severe and suggest that the storms with cold features are less important to understanding stratospheric water vapor and climate change.
Abstract
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.
Abstract
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.
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.
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.
Abstract
Supercell storms are commonly responsible for severe hail, which is the costliest severe storm hazard in the United States and elsewhere. Radar observations of such storms are common and have been leveraged to estimate hail size and severe hail occurrence. However, many established relationships between radar-observed storm characteristics and severe hail occurrence have been found using data from few storms and in isolation from other radar metrics. This study leverages a 10-yr record of polarimetric Doppler radar observations in the United States to evaluate and compare radar observations of thousands of severe hail–producing supercells based on their maximum hail size. In agreement with prior studies, it is found that increasing hail size relates to increasing volume of high (≥50 dBZ) radar reflectivity, increasing midaltitude mesocyclone rotation (azimuthal shear), increasing storm-top divergence, and decreased differential reflectivity and copolar correlation coefficient at low levels (mostly below the environmental 0°C level). New insights include increasing vertical alignment of the storm mesocyclone with increasing hail size and a Doppler velocity spectrum width minimum aloft near storm center that increases in area with increasing hail size and is argued to indicate increasing updraft width. To complement the extensive radar analysis, near-storm environments from reanalyses are compared and indicate that the greatest environmental differences exist in the middle troposphere (within the hail growth region), especially the wind speed perpendicular to storm motion. Recommendations are given for future improvements to radar-based hail-size estimation.
Abstract
Supercell storms are commonly responsible for severe hail, which is the costliest severe storm hazard in the United States and elsewhere. Radar observations of such storms are common and have been leveraged to estimate hail size and severe hail occurrence. However, many established relationships between radar-observed storm characteristics and severe hail occurrence have been found using data from few storms and in isolation from other radar metrics. This study leverages a 10-yr record of polarimetric Doppler radar observations in the United States to evaluate and compare radar observations of thousands of severe hail–producing supercells based on their maximum hail size. In agreement with prior studies, it is found that increasing hail size relates to increasing volume of high (≥50 dBZ) radar reflectivity, increasing midaltitude mesocyclone rotation (azimuthal shear), increasing storm-top divergence, and decreased differential reflectivity and copolar correlation coefficient at low levels (mostly below the environmental 0°C level). New insights include increasing vertical alignment of the storm mesocyclone with increasing hail size and a Doppler velocity spectrum width minimum aloft near storm center that increases in area with increasing hail size and is argued to indicate increasing updraft width. To complement the extensive radar analysis, near-storm environments from reanalyses are compared and indicate that the greatest environmental differences exist in the middle troposphere (within the hail growth region), especially the wind speed perpendicular to storm motion. Recommendations are given for future improvements to radar-based hail-size estimation.
Abstract
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.
Abstract
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.
