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Lightning and precipitation interrelated for a stormy dayLo, Cheuk-Wai January 1977 (has links)
No description available.
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Z-M in lightning forecastingMachina, Alexia J. January 2009 (has links) (PDF)
Thesis (M.S. in Meteorology)--Naval Postgraduate School, March 2009. / Thesis Advisor(s): Nuss, Wendell A. "March 2009." Description based on title screen as viewed on May 6, 2009. Author(s) subject terms: Lightning, Ice content, Florida Includes bibliographical references (p. 43-44). Also available in print.
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Climate analysis of lightning launch commit criteria for Kennedy Space Center and Cape Canaveral Air Force StationMuller, Eric C. January 2010 (has links) (PDF)
Thesis (M.S. in Meteorology)--Naval Postgraduate School, March 2010. / Thesis Advisor(s): Murphree, Tom ; Jordan, Mary S. "March 2010." Description based on title screen as viewed on April 23, 2010. Author(s) subject terms: Cape Canaveral Air Force Station, Climate Analysis, Climate Variations, Climatology, Kennedy Space Center, Lightning Launch Commit Criteria, Lightning Probability, Long-range Forecasting, National Lightning Detection Network, Reanalysis, Space Vehicle Launch, Teleconnections, Triggered Lightning Includes bibliographical references (p. 103-109). Also available in print.
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Lightning and precipitation interrelated for a stormy dayLo, Cheuk-Wai January 1977 (has links)
No description available.
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Using Cloud to Ground Lightning as a Forecast Tool for Severe HailReagan, Matthew 12 May 2012 (has links)
Ten years of lightning data was used to examine the lightning climatology in the Mid-South and to create a model capable of predicting severe hail storms using CG lightning. Cloud to ground lightning peaked reached a maximum in July and a minimum in January. Positive CG accounted for 5.3% of all strikes. The percentage of positive strikes reached a maximum in December and a minimum in August. Artificial intelligence along with logistic regression models were used for hail prediction. The 95% confidence intervals of the contingency statistics were used to determine the performance of the models. The linear cost 100 model and logistic regression had the highest performance and were tested with an independent data set. The logistic regression model outperformed the linear cost 100 model. The performance by both models was under the median statistics but within the 95% confidence interval.
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Analysing lightning data from two spatially separate magnetic direction findersRice, David Andrew 23 March 2009 (has links)
Two lightning detectors, of the magnetic direction finder type, form part of a two station
system for determining the position of lightning strikes. The detectors are on a baseline
of approximately 600 m, and the ultimate aim of the system is to accurately detect and
map lightning within a radius of 30 km. Although no real time capability is present, the
archive data collected from each separate station is used to find the offset errors in the
azimuthal orientation, as well as in time (using processes described in Appendix A). The
relative offset errors are determined by shifting the time and azimuthal information for one
station’s data and calculating the maximum possible matching records (within certain time
and azimuth criteria) for each incremental shift. An analysis of the peaks in total matching
records, when plotted against the relevant shift increments, is performed in order to obtain
the values of the offset errors. Between the two individual stations, the relative offset in
orientation is found to be 24.5 degrees, and in time to be 0.001305 days (112.75 seconds). The
individual stations, as well as the triangulated data calculated from matching records, can
also be calibrated using data from the South African Weather Service Lightning Detection
Network (SAWSLDN). Individual station calibration indicated an offset of +6.4 degrees and
0.00575 days (496.8 seconds) for Station 1, with the offsets for Station 2 determined as +29.4
degrees and −0.000105 days (9.07 seconds). Comparison of triangulated data to SAWSLDN
data yields unexpected results with regard to resultant shifts, which may point to an error or
anomaly in the triangulation calculations. A detailed analysis of the storm data is contained
in Appendix B of the dissertation.
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Houston LDAR II network: design, operation, and performance analysisEly, Brandon Lee 10 October 2008 (has links)
The Houston LDAR II network is an array of twelve VHF time-of-arrival (TOA)
sensors operated by Texas A&M University. The goals of the network are to conduct indepth
studies of thunderstorm electrification and provide timely lightning threats to the
Houston area. Before analyses are conducted using data from the Houston LDAR
network, it is necessary to understand the LDAR networkâ s performance and limitations,
such as the LDAR source detection efficiency, network range, and location accuracy.
Initial results from the 31 October 2005 Mesoscale Convective System (MCS)
timing error analysis revealed an RMS timing error for the Houston LDAR network of
90 ns for 6 sensor solutions. This gives a three-dimensional location accuracy of 1 km at
a distance of 150 km and 100 m over the center of the network. Reanalysis with updated
sensor positions decreased the RMS timing error to 75 ns. This decrease in RMS timing
error increased the median three-dimensional location accuracy by ~100 m at a 100 km
range. The network has been operated at both 70 MHz and 40 MHz. Model results of
detection efficiency suggest that the change to 40 MHz yields an increase of 9 - 10 dB in
network sensitivity. Analysis of VHF source power distributions shows a similar shift
from that expected from the model. These results show that the 40 MHz LDAR network
detects ~3.3 times more VHF sources than the 70 MHz network.
The analysis of the usable network range for research purposes is currently set by
rough guidelines of location accuracy and detection efficiency. For location accuracy, a
1 km limit allows storm analysis out to a range of more than 150 km. For the detection
efficiency analysis, results based on source power distributions suggest a gradual fall off
with range. Examining the change in VHF source density by range reveals different
results. VHF source density remained fairly constant out to a range of 100 km at which
point a significant fall off was observed. Based on these results the usable network
range for the Houston network is 100 km.
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The Houston Lightning Mapping Array: Network Installation and Preliminary AnalysisCullen, Matthew Ryan 16 December 2013 (has links)
The Houston Lightning Mapping Array (LMA) is a lightning detection network providing total lightning mapping for the Houston metropolitan area and southeast Texas. The network is comprised of twelve Very High Frequency (VHF) time-of-arrival total lightning mapping sensors built by New Mexico Institute of Mining and Technology and purchased by Texas A&M University. The sensors, installed in April 2012, are of the latest, modular design and built to be independent stations that utilize a solar panel for electricity and cellular data modems for communication. Each sensor detects the time of arrival of a VHF impulse emitted as part of the electrical breakdown and lightning propagation process. Data from each sensor are processed on a central LMA server to provide three-dimensional mapping of these impulses, also called LMA sources. This processing facilitates the analysis of variations in thunderstorm structure and the associated changes in both space and time.
The primary objectives for the installation of the Houston LMA network are twofold: first, to provide a dataset enabling research into thunderstorm electrification in the context of a coastal, urban, polluted environment; and second, to enable improvements in operational forecasting and public safety by providing total lightning data to partners including the National Weather Service (NWS). A workflow was established to create and share real-time data to these partners, while simultaneously maintaining a full, research-quality dataset. Data are retrieved from the field sensors and backed up to a central LMA server for processing and storage. Archived network data are available from July 2012 through the present. The network measures 150 km from north to south, with stations in College Station and Galveston complementing the ten sites surrounding downtown Houston. This extends the region constrained by the network beyond the immediate metropolitan Houston area, resulting in increased accuracy in locating sources further from the network center. Based on initial analyses, the effective range of the Houston LMA is 75 km for three-dimensional mapping and approximately 250 km for two-dimension mapping.
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Determination of lightning characteristics through the use of electromagnetic field dataTeschan, Paul Erhard January 1990 (has links)
In this thesis we determine the electromagnetic fields of a current distribution located, in free space, above a perfectly conducting plane earth. Then we consider the inverse problem of determining the source distribution from the fields. Formulae are obtained for the volume integral (dipole moment) of the current density of a small current source in terms of the fields and known functions. If field data are measured (from lightning over sea water for example) the dipole moment of the current density producing the fields may be found. The validity of the small source approximation used in this work is also established. Finally, a method is developed for determining the average current at points on a vertical line current source, a common model for a lightning return stroke. We treat the source as a string of dipoles and apply a method of constrained inversion.
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Simulation, analysis, assessment and diagnosis of high frequency power system transientsProbert, Sarah Ann January 2002 (has links)
No description available.
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