Developing an Objective Identification Algorithm for Tropical Cloud Clusters from Geostationary Satellite Data By Chip Helms Faculty Advisor: Dr. Chris Hennon
What is a cloud cluster? An organized grouping of clouds in the tropics with the potential for forming a tropical cyclone
Cloud Cluster Requirements Clusters must be... –Independent of other systems –2 degrees in diameter –Located in a favorable area of the ocean –Persistent for at least 24 hours –Located over water The Problem Objective testing against somewhat subjective requirements
Data as used in the algorithm Infrared (IR) satellite data –Measurement of cloud temperature Known as the brightness temperature –Colder temperatures correspond to darker colors Clouds appear black Program focuses on Atlantic Basin region
Data Source Provided by the National Climatic Data Center (NCDC) HURSAT-Basin dataset, courtesy of Ken Knapp Part of the HURSAT data project Created from geostationary satellite data
How does it work?
Cloud Clusters from 1999 Season
Results for 1999 Atlantic Season 1999 Run Statistics Cluster Candidates: 1080 Clusters Found: Statistics Systems Tracked: 16 Hurricanes: 8 Tropical Storms: 4 Tropical Depressions: 4
Cloud Clusters from 2000 Season
Results for 2000 Atlantic Season 2000 Run Statistics Cluster Candidates: 1077 Clusters Found: Statistics Systems Tracked: 18 Hurricanes: 8 Tropical Storms: 6 Tropical Depressions: 4
Cloud Clusters from 2001 Season
Results for 2001 Atlantic Season 2001 Run Statistics Cluster Candidates: 1013 Clusters Found: Statistics Systems Tracked: 17 Hurricanes: 9 Tropical Storms: 6 Tropical Depressions: 2
Applications:Preferred Development Examples using data from Source: June
Applications:Preferred Development Examples using data from Source: July
Applications:Preferred Development Examples using data from Source: August
Applications:Preferred Development Examples using data from Source: September
Applications:Preferred Development Examples using data from Source: October
Applications:Preferred Development Examples using data from Source: November
Is it accurate? A tentative yes, but more analysis is still needed.
Output Statistics Text file output Information about modifications to points (Smoothed, Interpolated) Track number Latitude Longitude Statistics on the cluster
Applications Climatology Areas of preferred development Impacts of climate change on development Impacts of cycles such as El Nino Case Studies for Cyclogenesis Modeling
Future Work Run additional years Adapt algorithm for other basins Filter out developed systems (Hurricanes, Tropical Storms) Verification
Bibliography Goldenberg, S.B., C.W. Landsea, A.M. Mestas-Nuñez, and W.M. Gray, 2001: The recent increase in Atlantic hurricane activity: Causes and implications. Science, 293, Hennon, C.C., and J.S. Hobgood, 2003: Forecasting tropical cyclogenesis over the Atlantic Basin using large-scale data. Monthly Weather Review, 131, Hennon, C.C., C. Marzban, and J.S. Hobgood, 2005: Improving tropical cyclogenesis statistical model forecasts through the application of a neural network classifier. Weather and Forecasting, 20, Lee, C.S., 1989: Observational analysis of tropical cyclogenesis in the Western North Pacific. Part I: Structural evolution of cloud clusters. Journal of the Atmospheric Sciences, 46,
Questions? Hurricane Epsilon (2005) taken from the International Space Station