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Study of Ardmore, Oklahoma storm clouds. I - Convective storm cloud initiation and development based on the remote sensing gravity-wave-induced convection. II - Satellite infrared remote sensing and numerical simulation

The role of gravity waves is discussed with respect to the vertical velocity of convection. Specific attention is given to wave-induced convection which contributes to the fractions of formation and the development of severe convective storms. Large-amplitude gravity waves and convective instability were investigated in storm clouds above Ardmore, Oklahoma. Rapid-scan satellite imagery and radar summaries provide evidence of water-vapor condensation related to convection which is introduced by gravity waves. Gravity wave periods of 35 minutes are found to initiate weak convection, which can be intensified by gravity waves with periods of 20 minutes. The convective motion reaches a maximum about one hour before funnel clouds develop. Other mechanisms which contribute to convective motion are considered, but gravity waves are the major contributor to the initiation, formation, and development of mesoscale storm clouds. Cloud modeling based on satellite imagery and sounding data showed that by overshooting cloud tops that penetrated the tropopause, storm clouds mature; that these clouds collapse about 9 minutes before the touchdown of tornadoes; and that cloud tops collapse at a high rate about 6 minutes before tornadoes lift off.

Hung, R. J.↗

Comparing Tropopause-Penetrating Convection Identifications Derived from NEXRAD and GOES over the Contiguous United States

Overshooting cloud tops (OTs) are a result of powerful updrafts that rapidly transport air from the troposphere to the lower stratosphere. Aside from the well-known relationships between strong updrafts and severe weather, the boundaries of updrafts, including the OT, are turbulent, which leads to irreversible mixing of air between the stratosphere and troposphere, altering the composition of both layers. In order to better understand the impact of OTs, knowing precisely when and where they occur is vital. Within the last decade remote-sensing observations from satellites and radars have been used to identify OTs, but the results thus far have not been entirely consistent due to challenges with accurately identifying OTs with these sensor datasets. This study compares OTs identified using NEXRAD reflectivity data from the GridRad dataset with an approach that uses GOES infrared (IR) data. The GridRad method estimates the altitude of echo tops directly from the radar pointing geometry, merging a combination of radars that enables products every 5 mins, with 2 km spatial and 1 km vertical grid spacing. The GOES satellite method uses spatial patterns in tropopause-relative IR brightness temperature to derive an OT likelihood. The study region covers a large part of the contiguous United States during selected active convection dates in 2017 and includes data from GOES-13/16. A large sample of OTs observed by NEXRAD and GOES-13/16 satellites are analyzed to better understand NEXRAD and IR observations of OTs, quantify agreement between the OT detection methods, and demonstrate how the 4x increase in spatial resolution from GOES-13 to GOES-16 impacts OT algorithm detection performance. The results show that for nearly time-matched scenes, with many severe storms, GOES-13 and -16 detection accuracy is quite comparable; however, some missed detections are attributed to poorer GOES-13 image resolution. It was found that GOES-13 OT regions are ~2 K warmer than GOES-16 on average, but such differences exceed 5 K for the most intense OT regions. It is found that false GOES IR-based detections are unavoidable, given that cold cloud pixels significantly colder than the tropopause from nearby or recently decayed OTs can persist within anvils for 15 minutes or more.

John W. Cooney↗

Spaceborne Passive-Microwave and Visible/IR Observations of Severe Weather: Leveraging Multiple Perspectives for Detection, Validation, and Climatologies

Severe weather phenomena not only are responsible for damages to property, infrastructure, and agriculture, they are also difficult to measure in-situ and have been associated with large errors and uncertainties in precipitation estimation that pose challenges to establishing the current climatology of severe storms and their future trend in a changing Earth system. Severe convection exhibits distinct signatures in remote-sensing datasets, where it is manifested as textured or overshooting cloud tops in visible/IR imagery, or resulting a prominent brightness temperature depression in passive-microwave imagery. These distinct deep convective signatures in spaceborne datasets have been leveraged to analyze severe thunderstorms, create climatologies, improve prediction, and provide a method of detection around the globe where traditional ground-based data may be inconsistent or unavailable. Visible/IR and passive-microwave instruments are powerful tools for detecting severe thunderstorms, however, these datasets exhibit key limitations when examined individually: passive-microwave channels have large footprint and exhibit non-uniform beam filling. The visible/IR instruments have fine horizontal resolution but are limited by their insensitivity to processes occurring below cloud top. We investigate the nearly simultaneous and colocated MODIS (visible/IR) and AMSR-E (passive-microwave) onboard the Aqua satellite to leverage both datasets together and assess the extent to which these datasets can be combined to improve severe thunderstorm detection. We pair passive microwave, IR, and visible signatures of severe convection with ground-based weather radar, severe weather reports, and environmental parameters defined by the MERRA-2 reanalysis to characterize potentially severe convective storms observed by Aqua MODIS and AMSR-E. We will discuss how MODIS and AMSR-E signatures may be used together to diagnose storm properties and processes, and how the interrelationships between the signatures varies seasonally and geographically.

Sarah D. Bang↗

A Census of Severe Weather as Observed From Aqua: Visible/IR and Passive-Microwave Perspectives of Severe Convection

Severe weather phenomena represent the extreme upper end of the spectrum of convection and precipitation and tend to be highly localized and relatively rare compared to the rest of the distribution, but they can cause damage and loss disproportionate to their scale and frequency. Fortunately, severe convection exhibits distinct signatures in spaceborne remote-sensing datasets (e.g. overshooting cloud tops in visible/IR, or brightness temperature depressions in passive-microwave imagery). Leveraging these signatures individually has become a long-established practice to detect, analyze and establish climatologies of severe thunderstorms, especially in instances where traditional ground-based data may be unavailable. Spaceborne visible/IR and passive-microwave approaches are not without their pitfalls, however: passive-microwave channels have large footprints and exhibit non-uniform beam filling. Visible/IR instruments have fine horizontal resolution but are limited by their insensitivity to processes occurring below cloud top. To address this, we investigate the nearly simultaneous and colocated MODIS (visible/IR) and AMSR-E (passive-microwave) onboard the Aqua satellite to leverage both datasets together and assess the extent to which these datasets can be combined to improve severe thunderstorm detection. We pair AMSR-E and MODIS signatures of severe convection with ground-based weather radar, severe weather reports, and environmental parameters defined by the MERRA-2 reanalysis in six different geographical regimes throughout the Aqua domain. We present a census of potentially severe convective storms and their environments as seen by multiple instruments simultaneously, investigating how MODIS and AMSR-E signatures may be used together to diagnose storm properties and processes, and how the interrelationships between the signatures varies seasonally and geographically. Using statistical machine learning analysis, we aim to quantify the optimal MODIS and AMSR-E parameter sets for discriminating severe from non-severe storm cells and assess what improvement (if any) in detection results from combining the IR, visible, and microwave datasets.

Sarah Bang↗

Challenges in Remote-Sensing of Hail: Examining the Performance and Biases of Satellite Hail Retrievals Using Aqua MODIS Visible/IR and AMSR-E Passive-Microwave Observations

Hail poses threats to myriad aspects of human life and society, infrastructure, and agriculture. Scientifically, hail can often cause large errors in precipitation retrieval and estimation, posing challenges to establishing the current climatology of severe storms and their future trend in a changing Earth system. Fortunately, hailstorms exhibit distinct signatures in spaceborne remote-sensing datasets (e.g. overshooting cloud tops in visible/IR, or brightness temperature depressions in passive-microwave imagery). Approaches that leverage these signatures, however, are not without their pitfalls,: passive-microwave channels have large footprints and exhibit non-uniform beam filling. Visible/IR instruments have fine horizontal resolution but are limited by their insensitivity to processes occurring below cloud top. Large horizontal areas of smaller scatterers may also meaningfully lower the brightness temperatures, especially if they are able to occupy large portions of the footprint. Radiative transfer simulations show that low frequencies such as 19- and 37-GHz can be scattered to extremely low brightness temperatures by high concentrations of smaller (graupel-sized) ice scatterers, especially in larger features that are more likely to occupy the footprint, which may cause climatologies to overestimate the frequency severe hail. To address this, we investigate the nearly simultaneous and colocated MODIS (visible/IR) and AMSR-E (passive-microwave) onboard the Aqua satellite to leverage both datasets together, pairing AMSR-E and MODIS signatures of severe convection with ground-based weather radar, severe weather reports, and environmental parameters defined by the MERRA-2 reanalysis over CONUS, and then explore the performance and challenges of the algorithm when we expand outside the United States into six different geographical regimes throughout the Aqua domain.

Sarah D Bang↗

TPSAS-NF1676L-21193-DND

Researchers at NASA Langley Research Center have been developing an automated pattern recognition algorithm to identify overshooting convective cloud tops (OTs) in support of the GOES-R satellite program. This algorithm identify regions of overshooting at the individual 1-4 km geostationary satellite pixel scale using visible (during daytime only) and infrared channel imagery and numerical weather analysis data. The algorithm has been developed based upon analysis of 0.25-1 km spatial resolution Aqua MODIS imagery, using a database of over 2000 manually identified OT features throughout the world in storms with varying intensity and morphology. The OT database includes storms ranging from small, warm topped cells in Alaska and Mongolia, tornadic supercells over the U.S. Central Plains and Europe, large tropical mesoscale convective systems, and overshooting in the eyewalls and spiral bands of category 5 tropical cyclones. This database is available for use by the research community. The algorithm is designed to operate on data from any current and historical satellite imager, allowing for development of a highly accurate global OT detection climatology that extends back into the 1990's at up to a 15-30 min temporal resolution throughout the diurnal cycle. As members of the McIDAS Users Group, NASA LaRC has immediate access to the full global archive of geostationary imager data which would allows rapid development of OT climatologies and short-term databases. This type of capability has never been available within the weather and climate research community. Regional geostationary OT databases have been already developed over CONUS during SEAC4RS, for 18-years over the Eastern U.S., and for 5-10 years over Australia, Europe, Southeast Asia, and East Africa among many other regions. Some of these datasets are being used by climate researchers and private industry to examine UTLS-penetrating storm spatial distributions and their temporal variability, in addition to weather hazards associated with these storms at unprecedented spatial detail. This presentation will describe the OT pattern recognition algorithm and highlight recent product applications.

Kristopher Bedka↗

Spearhead echo and downburst in the crash of an airliner

Meteorological conditions leading to the crash of an airliner short of the runway of a New York airport were studied. Thunderstorm downdrafts much stronger than those measured on the 1946-47 Thunderstorm Project were found. These exceptional downdrafts have been designated as 'downbursts'. The violent cloud systems that produce downburst cells can be identified in the form of forward extensions of radar echoes designed as 'spearhead echoes' which move with unusual speed. The development of downburst cells appears to be tied in with overshooting tops of clouds at the anvil level.

Fujita, T. T.↗

Detection of severe storms by satellites

Ideas are presented for severe storm identification based on satellite data. The tops of huge thunderstorms in satellite pictures often appear as vast areas of extensive cirrus cloud; they consist of clusters of anvil clouds, each generated by vigorous thunderstorm circulation. The overshooting tops observed in satellite pictures are located where the subanvil updrafts are the strongest. Learjet experiment results show that an overshooting top varies either quickly or slowly, depending on the characteristics of individual clouds. When an overshooting top collapses, a small segment of the anvil cirrus jumps upward in the wake of the overshooting top. Also discussed is the monitoring of vertical motions from satellites and tornado-producing thunderstorms from geostationary altitude. A very high-resolution imagery of both infrared and visual spectral bands makes it possible to infer vertical motions beneath the anvil top. A combination of cloud velocity and anvil expansion rate will permit, in the future, determining the location of severe storms within the vast areas of anvil clouds.

Fujita, T. T.↗

Effects of stratospheric lapse rate on numerically simulated thunderstorm cloud top structure

The study of overshooting midlatitude severe thunderstorm tops has led to the detection of some intriguing patterns. This paper provides a summary of an investigation of the effects of stratospheric stability on thunderstorm cloud top structure, taking into account the utilization of a fully three-dimensional (3D) anelastic model discussed by Schlesinger (1975, 1978, 1984). The layout of model experiments is discussed, giving attention to initial environmental soundings, and initial forcing. The time variation of the vertical velocity extreme is examined, and a description of the mature storm structure is presented. Constant-altitude plane views throughout storm depth are considered along with cloud top height fields. With the stratospheric lapse, the warm region is small and breaks down into separate spots with secondary cold spots downshear of them.

Schlesinger, R. E.↗

BIRDIE beryllium-10 and -7 measurements from 2022 summer deep convection rain at ARM SGP

Water samples were manually collected from 11 SGP ARM sites in the early summer of 2022 to measure cosmogenic isotopes of beryllium. The water samples were brought back to the Center for Accelerator Mass Spectrometry (CAMS) at LLNL and analysed for beryllium-10 and beryllium-7 as well as for chlorine-37, chlorine-36, and tritium. A total of six storm events were measured over three weeks. At least five of those storms included overshooting cloud events. Available data include precipitation amount, beryllium-10 concentration, beryllium-7 concentration, and 10/7Be ratio. Spatial and temporal variability in the cosmogenic isotopes was relatively high but could not directly be linked to precipitation amount. Analysis is on-going to explain the measured variability and to see if it can be linked to cloud top height and overshooting depth.

54 ENVIRONMENTAL SCIENCES↗

Thunderstorm top structure observed by aircraft overflights with an infrared radiometer

Thunderstorm top structure is examined with high spatial resolution radiometric data (visible and infrared) from aircraft overflights together with other storm views, including geosynchronous satellite observations. Results show that overshooting cumuliform towers appear as distinct cold areas in the high resolution, 11-micron IR aircraft images, but that the geosynchronous satellite observations significantly overestimate the thunderstorm-top IR brightness temperature, T(B), due to field of view effects. Profiles of cloud top height and T(B) across overshooting features indicate an adiabatic cloud surface lapse rate. However, one-dimensional cloud model results indicate that when comparing thunderstorm top temperature and height at different times or different storms, a temperature-to-height conversion of about 7 K/km is appropriate. Examination of mature storm evolution indicates that, during periods when the updraft is relatively intense, the satellite IR 'cold point' is aligned with the low-level radar reflectivity maximum, but during periods of updraft weakening and lowering cloud top heights, the satellite T(B) minimum occurs downwind with cirrus anvil debris. The growth period of a relatively weak cumulonimbus cluster is also examined with aircraft and satellite data.

Adler, R. F.↗

Observations of Overshooting Convective Tops and Dynamical Implications

Convective tops overshooting the tropopause have been suggested in the literature to play an important role in modifying the tropical tropopause. The structure of thunderstorm tops overshooting the tropopause have been difficult to measure due to the intensity of the convection and aircraft safety. This paper presents remote observations of overshooting convective tops with the high-altitude ER-2 aircraft during several of the Tropical Rain Measuring Mission (TRMM) and (Convection and Moisture Experiment) CAMEX campaigns. The ER-2 was instrumented with the down-looking ER-2 Doppler Radar (EDOP), a new dropsonde system (ER-2 High Altitude Dropsonde, EHAD), and an IR radiometer (Modis Airborne Simulator, MAS). Measurements were collected in Florida and Amazonia (Brazil). In this study, we utilize the radar cloud top information and cloud top infrared temperatures to document the amount of overshoot and temperature difference relative to the soundings provided by dropsondes and conventional upsondes. The radar measurements provide the details of the updraft structure near cloud top, and it is found that tops of stronger convective cells can overshoot by 1-2 km and with temperatures 5C colder than the tropopause minimum temperature. The negatively buoyant cloud tops are also evidenced in the Doppler measurements by strong subsiding flow along the sides of the convective tops . These findings support some of the conceptual and modeling studies of deep convection penetrating the tropopause.

Heymsfield, Gerald M.↗

Thunderstorm cloud top dynamics as inferred from satellite observations and a cloud top parcel model

Thunderstorm top temperature-height structure and temperature-height conversion relations in the convective overshooting top region are examined using data from GOES IR, AVHRR, and aircraft overflights, and GOES stereoscopic observations. Using a Lagrangian one-dimensional cloud parcel model applied in the overshooting region, three classes of storm tops are described and the causes of their unique temperature-height structures are explored. Although the parcel model used does not fully reproduce the three-dimensional structure and dynamics of an evolving thunderstorm top, it is shown to crudely reproduce the parcel dynamics of updraft core parcels. The locations of cold points, high points, warm points, and the magnitude of cold-high offsets compare favorably between the model and the satellite observations.

Adler, Robert F.↗

An Integrated 0-1 Hour First-Flash Lightning Nowcasting, Lightning Amount and Lightning Jump Warning Capability

Lightning one of the most dangerous weather-related phenomena, especially as many jobs and activities occur outdoors, presenting risk from a lightning strike. Cloud-to-ground (CG) lightning represents a considerable safety threat to people at airfields, marinas, and outdoor facilities-from airfield personnel, to people attending outdoor stadium events, on beaches and golf courses, to mariners, as well as emergency personnel. Holle et al. (2005) show that 90% of lightning deaths occurred outdoors, while 10% occurred indoors despite the perception of safety when inside buildings. Curran et al. (2000) found that nearly half of fatalities due to weather were related to convective weather in the 1992-1994 timeframe, with lightning causing a large component of the fatalities, in addition to tornadoes and flash flooding. Related to the aviation industry, CG lightning represents a considerable hazard to baggage-handlers, aircraft refuelers, food caterers, and emergency personnel, who all become exposed to the risk of being struck within short time periods while convective storm clouds develop. Airport safety protocols require that ramp operations be modified or discontinued when lightning is in the vicinity (typically 16 km), which becomes very costly and disruptive to flight operations. Therefore, much focus has been paid to nowcasting the first-time initiation and extent of lightning, both of CG and of any lightning (e.g, in-cloud, cloud-to-cloud). For this project three lightning nowcasting methodologies will be combined: (1) a GOESbased 0-1 hour lightning initiation (LI) product (Harris et al. 2010; Iskenderian et al. 2012), (2) a High Resolution Rapid Refresh (HRRR) lightning probability and forecasted lightning flash density product, such that a quantitative amount of lightning (QL) can be assigned to a location of expected LI, and (3) an algorithm that relates Pseudo-GLM data (Stano et al. 2012, 2014) to the so-called "lightning jump" (LJ) methodology (Shultz et al. 2011) to monitor lightning trends and to anticipate/forecast severe weather (hail > or =2.5 cm, winds > or =25 m/s, tornadoes). The result will be a time-continuous algorithm that uses GOES satellite, radar fields, and HRRR model fields to nowcast first-flash LI and QL, and subsequently monitors lightning trends on a perstorm basis within the LJ algorithm for possible severe weather occurrence out to > or =3 hours. The LI-QL-LJ product will also help prepare the operational forecast community for Geostationary Lightning Mapper (GLM) data expected in late 2015, as these data are monitored for ongoing convective storms. The LI-QL-LJ product will first predict where new lightning is highly probable using GOES imagery of developing cumulus clouds, followed by n analysis of NWS (dual-polarization) radar indicators (reflectivity at the -10 C altitude) of lightning occurrence, to increase confidence that LI is immanent. Once lightning is observed, time-continuous lightning mapping array and Pseudo-GLM observations will be analyzed to assess trends and the severe weather threat as identified by trends in lightning (i.e. LJs). Additionally, 5- and 15-min GOES imagery will then be evaluated on a per-storm basis for overshooting and other cloud-top features known to be associated with severe storms. For the processing framework, the GOES-R 0-1 hour convective initiation algorithm's output will be developed within the Warning Decision Support System - Integrated Information (WDSS-II) tracking tool, and merged with radar and lightning (LMA/Psuedo-GLM) datasets for active storms. The initial focus of system development will be over North Alabama for select lightning-active days in summer 2014, yet will be formed in an expandable manner. The lightning alert tool will also be developed in concert with National Weather Service (NWS) forecasters to meet their needs for real-time, accurate first-flash LI and timing, as well as anticipated lightning trends, amounts, continuation and cessation, so to provide key situational awareness and decision support information. The NASA Short-term Prediction Research and Transition (SPoRT) Center will provide important logistical and collaborative support and training, involving interactions with the NWS and broader user community.

Mecikalski, John↗

Downward Convective Moisture Transport Dominated by a Few Overshooting Clouds in Marine and Continental Shallow Convection

Abstract In a previous study (Xiao et al., 2023, https://doi.org/10.1029/2022ms003526 ), we found that ignoring the moist convective downdrafts associated with overshooting clouds in parameterizations can lead to significant biases in the simulated depth and liquid water content of a shallow cloud layer. In this study, we seek to better quantify the properties of the clouds responsible for these moist downdrafts to help improve shallow convection parameterizations. We apply a 3‐D cloud‐tracking algorithm to large‐eddy simulations (LESs) of marine and continental shallow convection. We find that top 1% and 2% of the tracked cloud population ranked by lifetime‐mean cloud‐base mass flux can explain 90%–95% of the total downward moisture transport in the upper cloud layer whereas top 10%–20% is required to explain 90%–95% of the total upward moisture transport near mean cloud base. The vertical structure of the clouds in the top 1% and 2% (the overshooting “deep mode”) is also distinctively different from that of the rest of the cloud population (the “shallow mode”). Shallow convection parameterizations need to capture accurately the properties and convective transports of the clouds in both the deep and shallow modes. To do that, our results suggest that mass‐flux parameterizations need to (a) accurately predict the size and number of the deep‐mode clouds and (b) explicitly represent overshooting cloud updrafts and associated moist downdrafts.

54 ENVIRONMENTAL SCIENCES↗

The 1980 stratospheric-tropospheric exchange experiment

Data are presented from the Stratospheric-Tropospheric Water Vapor Exchange Experiment. Measurements were made during 11 flights of the NASA U-2 aircraft which provided data from horizontal traverser and samplings in and about the tops of extensive cirrus-anvil clouds produced by overshooting cumulus turrets. Aircraft measurements were made of water vapor, ozone, ambient and cloud top temperature, fluorocarbons, nitrous oxide, nitric acid, aerosols, and ice crystal populations. Balloonsondes were flown about twice daily providing data on ozone, wind fields, pressure and temperature to altitudes near 30 km. Satellite photography provided detailed cloud and cloud top temperature information. Descriptions of individual experiments and detailed compilations of all results are provided.

Margozzi, A. P.↗

Lightning Rings and Gravity Waves: Insights Into the Giant Eruption Plume From Tonga's Hunga Volcano on 15 January 2022

Abstract On 15 January 2022, Hunga Volcano in Tonga produced the most violent eruption in the modern satellite era, sending a water‐rich plume at least 58 km high. Using a combination of satellite‐ and ground‐based sensors, we investigate the astonishing rate of volcanic lightning (>2,600 flashes min −1 ) and what it reveals about the dynamics of the submarine eruption. In map view, lightning locations form radially expanding rings. We show that the initial lightning ring is co‐located with an internal gravity wave traveling >80 m s −1 in the stratospheric umbrella cloud. Buoyant oscillations of the plume's overshooting top generated the gravity waves, which enhanced turbulent particle interactions and triggered high‐current electrical discharges at unusually high altitudes. Our analysis attributes the intense lightning activity to an exceptional mass eruption rate (>5 × 10 9 kg s −1 ), rapidly expanding umbrella cloud, and entrainment of abundant seawater vaporized from magma‐water interaction at the submarine vent.

58 GEOSCIENCES↗

Overshooting top behavior of three tornado-producing thunderstorms

The behavior of overshooting tops and jumping cirrus observed in three tornado-producing thunderstorms during the 1974 Learjet Cloud-Truth experiment is discussed. An investigation of temporal changes in the heights of overshooting domes (conglomerations of overshooting tops with diameters less than 1 km) reveals several distinctive features associated with tornadic events. There is a gradual decrease in dome height prior to tornado touchdown. Minimum dome activity occurred 5 min after, 5.5 min before, and at approximately the same time as the tornadic event in the storms observed. In all cases, dramatic dome growth at a rate of 17 to 23 m/sec immediately followed the occurrence of the minimum dome heights. There is evidence that tornado production is insensitive to the pre-touchdown maximum dome heights between 1 and 3 km.

Umenhofer, T. A.↗