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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