The focus of this research effort is directed toward identifying
new methods of forecasting the cessation of lightning along the
Central Atlantic Coast of Florida. Cloud-to-ground lightning
flashes place Air Force (AF) personnel and assets at risk almost
daily at this location. Providing a more accurate method of
forecasting the cessation of lightning would allow for safer and
more efficient execution of AF operations. A data set consisting of
40 thunderstorm cases was identified within a 90 nautical miles
(nmi) region surrounding the Melbourne, Florida WSR-88D (KMLB)
site. Each case falls between the months of May and September and
the years of 1995 through 1997. Simple and multiple linear
regression models are built using this dataset. Variables included
max Vertically Integrated Liquid water (VIL), max reflectivity, max
peak current, peak cumulative flash rate, peak negative flash rate,
and peak positive flash rate. Results indicate that three of the
simple linear regression models to some extent accurately represent
the data. Additionally, when the data set is separated by
thunderstorm cell type (multi or single) and cell specific
regressions are built, results indicate that the regressions based
on the single-cell data set produce a substantial increase in
forecast skill compared to that of climatology. In fact, some
regressions are shown to improve forecast accuracy by 90 % over
that of climatology. Moreover, multiple linear regression models
are shown to produce similar results and further reinforce the
notion that each thunderstorm cell type (multi or single) behaves
substantially different from the other with respect to forecasting
the cessation of lightning.
General
Imprint: |
Biblioscholar
|
Country of origin: |
United States |
Release date: |
November 2012 |
First published: |
November 2012 |
Authors: |
Michael W. Holmes
|
Dimensions: |
246 x 189 x 5mm (L x W x T) |
Format: |
Paperback - Trade
|
Pages: |
94 |
ISBN-13: |
978-1-288-29185-4 |
Categories: |
Books >
Social sciences >
Education >
General
Promotions
|
LSN: |
1-288-29185-X |
Barcode: |
9781288291854 |
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