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Data · dataset · 2026

Liquid phase cloud microphysical property estimates from CALIPSO measurements

Listed in National Center for Atmospheric Research

A neural-network algorithm that uses CALIPSO lidar measurements to infer droplet effective radius, extinction coefficient, liquid-water content, and droplet number concentration for water clouds is described and assessed.

Description

These results are verified against values inferred from High-Spectral-Resolution Lidar (HSRL) and Research Scanning Polarimeter (RSP) measurements made on an aircraft that flew under CALIPSO. The global cloud microphysical properties are derived from 14+ years of CALIPSO lidar measurements, and the droplet sizes are compared to corresponding values inferred from MODIS passive imagery.

This new product will provide constraints to improve modeling of Earth's water cycle and cloud-climate interactions.

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Provenance · 1 source records, 7 field assertions
SourceKeyLast seenRaw
National Center for Atmospheric Research1d5d2da7-1e6a-41e6-b3f6-ae5b64a3cf5d12 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].local:field:earth-environmentalmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[field].local:field:ocean-atmosphericmapping · data ucar educonnector:data_ucar_edu@1.0.0
created_datesource · data ucar educonnector:data_ucar_edu@1.0.0
descriptionsource · data ucar educonnector:data_ucar_edu@1.0.0/notes
publication_datesource · data ucar educonnector:data_ucar_edu@1.0.0
titlesource · data ucar educonnector:data_ucar_edu@1.0.0/title
updated_datesource · data ucar educonnector:data_ucar_edu@1.0.0