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A climatological study of downbursts in Arkansas, Louisiana, Tennessee, Mississippi, Alabama, and Georgia was carried out, as well as studies of the Huntsville area microbursts on July 7, 1984, and a Decatur microburst on August 1984.
Storm electricity data, radar data, and visual observations were used both to present a case study for a supercell thunderstorm that occurred in the Texas Panhandle on 19 June 1980 and to search for insight into how lightning to ground might be related to storm dynamics in the updraft/downdraft couplet in supercell storms. It was observed that two-thirds of the lightning ground-strike points in the developing and maturing stages of a supercell thunderstorm occurred within the region surrounding the wall cloud (a cloud feature often characteristic of a supercell updraft) and on the southern flank of the precipitation. Electrical activity in the 19 June 1980 storm was atypical in that it was a right-mover. Lightning to ground reached a peak rate of 18/min and intracloud flashes were as frequent as 176/min in the final stages of the storm's life.
The follow-on agreement will implement needed systems enhancements of the satellite ground station installed under the previous SPSSD/WS project. These enhancements include the purchase and installation of an Uninterruptible Power Supply (UPS) and lightning protection unit, hardware modifications to provide system redundancy and increased data storage capacity, software modifications for the new Japanese GMS digital data, upgrades of the image processing software, and both hardware maintenance and tropical cyclone analysis training, and a non-renewable grant to provide emergency field repairs and replacement/spare parts. In March 1988, the UPS and lightning protection unit was installed at the Fiji Meteorological Service by NASA personnel. A tape recorder and demodulator was shipped to Fiji to record the new digital GMS data. Data tapes are not yet available from the Japanese Meteorological Service of the new digital format. This data is required to test the GMS digital software being developed for the Fiji SPSSD/WS facility.
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Several characteristics of a major dust storm on 20 February 1976 are presented. Four primary areas of discussion are considered: dust storm characteristics; comparisons between the cell detection capabilities of the geosynchronous satellite and radar; the use of the NASA Atmospheric and Oceanographic Information Processing System (an interactive image processing system) for interactive display of visual and IR digital data to obtain qualitative and quantitative results on specific dust cloud and cloud top characteristics; and evidence that the intersection downwind of dust clouds (streaks) with the dryline can be used to forecast the initial storm development on the dryline and that the dust clouds detected on 20 February 1976 are a reflection of upper tropospheric speed maxima, which according to McNulty (1978) and others, are associated with rapid severe convective local storm development.
Abstract Severe convection occurring in high-shear, low-CAPE (HSLC) environments is a common cool-season threat in the southeastern United States. Previous studies of HSLC convection document the increased operational challenges that these environments present compared to their high-CAPE counterparts, corresponding to higher false-alarm ratios and lower probability of detection for severe watches and warnings. These environments can exhibit rapid destabilization in the hours prior to convection, sometimes associated with the release of potential instability. Here, we use self-organizing maps (SOMs) to objectively identify environmental patterns accompanying HSLC cool-season severe events and associate them with variations in severe weather frequency and distribution. Large-scale patterns exhibit modest variation within the HSLC subclass, featuring strong surface cyclones accompanied by vigorous upper-tropospheric troughs and northward-extending regions of instability, consistent with prior studies. In most patterns, severe weather occurs immediately ahead of a cold front. Other convective ingredients, such as lower-tropospheric vertical wind shear, near-surface equivalent potential temperature (θ e ) advection, and the release of potential instability, varied more significantly across patterns. No single variable used to train SOMs consistently demonstrated differences in the distribution of severe weather occurrence across patterns. Comparison of SOMs based on upper and lower quartiles of severe occurrence demonstrated that the release of potential instability was most consistently associated with higher-impact events in comparison to other convective ingredients. Overall, we find that previously developed HSLC composite parameters reasonably identify high-impact HSLC events. Significance Statement Even when atmospheric instability is not optimal for severe convective storms, in some situations they can still occur, presenting increased challenges to forecasters. These marginal environments may occur at night or during the cool season, when people are less attuned to severe weather threats. Here, we use a sorting algorithm to classify different weather patterns accompanying such storms, and we distinguish which specific patterns and weather system features are most strongly associated with severe storms. Our goals are to increase situational awareness for forecasters and to improve understanding of the processes leading to severe convection in marginal environments.
Severe weather is an awe-inspiring phenomenon that affects the entire globe. Lightning, hail, damaging wind and tornadoes pose threats to society and challenges to the scientific community. Severe weather is annually responsible for tens of billions of dollars in insured losses to property, infrastructure, and agriculture. Satellite platforms offer a globally uniform approach to observing weather phenomena in remote or data-sparse regions and over the oceans. Severe convection exhibits distinct signatures in spaceborne datasets that we use to analyze severe storms. We leverage these signatures create climatologies, improve prediction, and provide a method of detection around the globe where traditional ground-based data (such as ground-based radar or human-spotter reports) are inconsistent or unavailable. Satellites in low-earth, sun-synchronous, and geostationary orbit provide a consistent, global view of severe weather from which we can examine the current global distribution, frequency, and severity of severe storms and establish a baseline to assess their future trend in a changing Earth system.
Severe weather is an awe-inspiring phenomenon that affects the entire globe. Lightning, hail, damaging wind and tornadoes pose threats to society and challenges to the scientific community. Severe weather is annually responsible for tens of billions of dollars in insured losses to property, infrastructure, and agriculture. Satellite platforms offer a globally uniform approach to observing weather phenomena in remote or data-sparse regions and over the oceans. Severe convection exhibits distinct signatures in spaceborne datasets that we use to analyze severe storms. We leverage these signatures create climatologies, improve prediction, and provide a method of detection around the globe where traditional ground-based data (such as ground-based radar or human-spotter reports) are inconsistent or unavailable. Satellites in low-earth, sun-synchronous, and geostationary orbit provide a consistent, global view of severe weather from which we can examine the current global distribution, frequency, and severity of severe storms and establish a baseline to assess their future trend in a changing Earth system.
A documentation of eight National Severe Storm Laboratory severe storm cases, which serve as a basis for a simulated VISSR Atmospheric Sounder retrieval study, is presented in this paper. Six of the selected cases provide a control data set to complete the statistical information needed for retrieval techniques based upon the use of regression matrices. The other two cases are to be used in the actual retrieval experiments. The selection was based upon the presence of moisture gradients in the analysis region, the availability of satellite images at the selected time periods, and the extent of cloud cover within the observing network.
The Tibet Plateau significantly affects the initiation and development of heavy rainfall and severe storms in China, just as the Rocky Mountains influence local severe storms in the United States. The study shows that the heavy rainfall in the Plateau area is usually preceded by a high growth rate of the convective clouds, followed by a rapid collapse of the cloud top. The study also shows that the tops of the convective clouds associated with heavy rainfall over the Plateau usually lie between the altitude of the two tropopauses which exist over the Plateau. There is good agreement between the collapsing of the cloud as observed from the satellite imagery, and the beginning of the rainfall observed by the ground stations and also between the dissipation of the cloud observed from the satellite infrared imagery, and the ending of the rainfall, observed by the ground stations. Comparison of the volumetric dissipation of clouds per unit area over the location of the ground station with the rainfall recorded at that station shows a linear relationship for rainfall mounts exceeding 8 mm. The ratio of observed rainfall at the ground station over the satellite observed cloud volume dissipation per unit area was also computed. The result shows that the ratio is almost constant with the value of 9.55 mm/(pixel . km/pixel) for rainfall amounts exceeding 15 mm; and the variation is less then 10 percent for rainfall mounts between 8 and 15 mm. Needless to say, further investigation is required to verify this ratio.
The American satellite, GOES-1 was moved to the Indian Ocean at 58 deg E during the First GARP Global Experiment (FGGE). The Qinghai-Xizang Plateau significantly affects the initiation and development of heavy rainfall and severe storms in China, just as the Rocky Mountains influence the local storms in the United States. Satelite remote sensing of short-lived, meso-scale convective storms is particularly important for covering a huge area of a high elevation with a low population density, such as the Qinghai-Xizang Plateau. Results of this study show that a high growth rate of the convective clouds, followed by a rapid collapse of the cloud top, is associated with heavy rainfall in the area. The tops of the convective clouds developed over the Plateau lie between the altitudes of the two tropopauses, while the tops of convective clouds associated with severe storms in the United States usually extend much above the tropopause.
The progress and problems associated with the dynamical forecast system which was developed to predict severe storms are examined. The meteorological problem of severe convective storm forecasting is reviewed. The cascade hypothesis which forms the theoretical core of the nested grid dynamical numerical modelling system is described. The dynamical and numerical structure of the model used during the 1978 test period is presented and a preliminary description of a proposed multigrid system for future experiments and tests is provided. Six cases from the spring of 1978 are discussed to illustrate the model's performance and its problems. Potential solutions to the problems are examined.
Several cases of GOES digital infrared data and Doppler Sounder array data during the three-hour time period immediately preceding the touchdown of the tornado were analyzed. Tornado-associated clouds are compared with non-tornado-associated clouds using satellite infrared data, ray tracing of gravity waves detected by the Doppler Sounder array and rawinsonde data. The satellite observations are at 15-minute intervals. Our study shows that tornado-associated clouds are always accompanied by overshooting turrets penetrating above the tropopause. The growth rate of the overshooting turret above the tropopause for severe storm-associated clouds is much greater than that for non-severe storm-associated clouds.
Changes in upper ionosphere during severe magnetic storms
GOES digital infrared data during the time period between two hours before the touchdown of tornado and the tornado touchdown time were used in this study. Comparison between tornado-associated clouds and non-tornado-associated clouds indicates that the difference between overshooting cloud top temperature and the tropopause temperature, or how much the cloud has penetrated above the tropopause, rather than either the absolute temperature of penetrative cloud top or the height of the top of overshooting turret is significant for the possible formation of severe storms. The penetrative overshooting cloud top collapses about 15 to 30 minutes before the touchdown of tornado. Gravity waves were detected from the severe convective storms.
Wind fields derived from cloud-tracking on the visible digital data of the Synchronous Meteorological Satellite-2 are used to study the onset of local severe storms. The study is based on an assessment of several dynamic parameters of lower tropospheric wind fields, including the divergence, relative vorticity, and deformation. The automated cloud-tracking proves capable of detecting a preferred area of flow convergence located ahead of a dry line; the detection of this convergence aids in monitoring the onset of a hail-producing thunderstorm.