Cloud Climatologies for Rocket Triggered Lightning from Launches at Cape Canaveral Air Force Station and Kennedy Space Center
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Authors
Strong, Greg J.
Subjects
Cape Canaveral Air Force Station
Climate Forecast System Reanalysis
Cloud Climatolgies
Kennedy Space Center
Lightning Launch Commit Criteria
Rocket Triggered Lightning
Thick Cloud
Climate Forecast System Reanalysis
Cloud Climatolgies
Kennedy Space Center
Lightning Launch Commit Criteria
Rocket Triggered Lightning
Thick Cloud
Advisors
Murphree, Tom
Boerlage, Andrew P.
Date of Issue
2012-03
Date
Mar-12
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
We have conducted a study on the development of detailed climatological probabilities of violating cloud related Lightning Launch Commit Criteria (LLCC) used by Cape Canaveral Air Force Station and Kennedy Space Center (CCAFS and KSC). This study was conducted to provide the 45th Weather Squadron with improved capabilities for operational forecasting for launches from CCAFS and KSC. Our focus was on developing methods to produce climatological probabilities of violating one of the LLCC, the thick cloud layer rule. We developed a hybrid process of blending data from the Climate Forecast System Reanalysis (CFSR), meteorological aerodrome reports (METARs), radiosonde observations (RAOBs), and expert meteorologist data sets to create a merged data set for determining the probability of violating the thick cloud layer rule. Using our blended hybrid process, we computed cloud thicknesses, and probabilities of violating the thick cloud LLCC for each day of the year at 00Z and 12Z. Additionally, we conducted a sensitivity analysis to identify the potential for modifying the thick cloud LLCC. A primary result from our study is a sub-daily data set of the climatological probabilities of violating the thick cloud layer rule. We conducted eight validation case studies that demonstrated our calculated violations match well with observed violations. The development of a merged data set that provides more useful information than any one of the individual data sets is a technique that is likely to be useful in solving many other climatological problems
Type
Thesis
Description
Series/Report No
Department
Meteorology