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Cloud Screening and Classification in Satellite Imagery
Shona MackiePhD student, University of Edinburgh
CASE studentship: Met Office, U.K.
Supervisor: Chris Merchant
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Clouds are important! Weather and climate
– Energy budget
– Temperature
– Precipitation
www.larc.nasa.gov/SCOOL/cloudeffects.jpg
– Height
– Optical thickness
– Diurnal variation
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Numerical Forecast– Cloud treatment not
perfect
» Spatial and temporal
» Sub-grid parameterisation
Satellite Imagery– Visual inspection
» amendments
– Automated assimilation
Weather Forecasting
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Overall Aim Bayesian Cloud
Classification (Chris Old)
– Physically based
– Flexible
– Expand
» To land
» To cloud types
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Current state of project
Problems– Ocean fronts
– Coastline
– Land
Clustering
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General Method
Small area of one image scene
– Cloud detection on clusters
» Classification?
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Clustering to aid detection
Expand technique to land
Expand to cloud types
(low, medium, high)
Expand to refined cloud types
Implement method at the MET Office
PLAN
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The End