TRENDS AND PERIODIC VARIABILITY IN TROPICAL WAVE CLOUDS
Date
2017
Authors
Burgwardt, Lester Charles
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Abstract
This dissertation describes the acquisition and analysis of tropical wave cloudiness. Tropical wave positions for the years 2003 through 2013 were extracted via text mining, from the National Hurricane Center’s Tropical Weather Discussion, a bulletin released every six hours and published on-line. Tropical wave tracks were developed from these positions using the Multiple Hypothesis Tracking algorithm. Satellite data from the Atmospheric Infrared Sounder (AIRS) was downloaded from the NASA Mirador website based on time and position of tracked tropical waves. The AIRS data was mosaicked to provide complete coverage between satellite swaths. The AIRS Level 2 Cloud Fraction Standard product was used exclusively in the analysis. Cloud fraction data was divided into upper and lower levels as provided in the AIRS product. A cloud fraction ratio was also developed to provide some indication of the insulating quality of clouds. The analysis discovered secular trends of varying degrees and direction depending on location of tropical waves. The analysis also found significant periodic variability within cloud fraction values, much of which correlated to known global oscillations such as El Nino and the Madden-Julian Oscillation. However a number of periodic signals found within tropical wave cloudiness could not be correlated with any of the known global and non-earth oscillations tested against. Future research ideas in the conclusions include an examination of those uncorrelated periodic signals. Also included in the conclusions are theories about differences in correlations to periodic signals within a tropical wave core versus correlations that are seen in surrounding cloud patterns.
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Keywords
Remote sensing, Geography, Meteorology, AIRS, Easterly wave, Multiple hypothesis tracker, Periodic variability, Text mining, Tropical wave