Researcher(s):
Laurel Garrett
ENVS course(s): 400, 499 Initiated: December 2015 Completed: May 2016 Go to project site
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This thesis examines the production process behind cloud identification and the network of tools, algorithms, and instruments that shape our understanding. Clouds are an integral component of our atmosphere and are involved in complex interactions that regulate the climate of our Earth. It is necessary to have a comprehensive observational record of both cloud type and cloud cover in order to document temporal changes, better understand atmospheric processes, and to validate with model’s predictions. Constructing an automated cloud classification algorithm for sky images confronts problems of observational subjectivity and examines the validity of technological solutions. Confronting this problem by examining the production process within a specific cloud observing technology and method of automatic cloud identification leads to the conclusion that we can not objectively measure reality, but rather construct representations that further our knowledge.