CASCCAD: Global Cumulus and Stratocumulus Cloud Profiles from Satellite

Global-scale spatial distributions and profiles of stratocumulus and cumulus clouds. The data was generated by applying a discrimination algorithm to active-sensor observations from the CALIPSO and CloudSat-CALIPSO combined satellite missions. The dataset, created by G Cesana of Columbia University, enables evaluation of shallow convection and boundary layer clouds in climate models.

Use Cases

• Evaluating shallow convection (Cu type) cloud representations in climate models based on cloud top height and horizontal extent.
• Assessing boundary layer (Sc type) cloud simulations based on their large area coverage and stable geometrical thickness.
• Developing or validating cloud discrimination algorithms using observable properties like cloud top height, horizontal cloud fraction, and vertical cloud fraction variability.
• Studying the global geographical distribution of fundamental cloud types for climate research.

Strengths

• Focuses on two fundamental cloud types (stratocumulus and cumulus) critical for climate modeling.
• Derived from authoritative satellite observations (CALIPSO and CloudSat-CALIPSO combined).
• Uses a defined discrimination algorithm based on three observable cloud properties.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

CALIPSO-GOCCP and CloudSat-CALIPSO combined satellite observations.

Collection Method

Processed using an original discrimination algorithm applied to instantaneous satellite profiles.

Geography

Global scale