OMCLDRR: Satellite Cloud Pressure and Fraction from Raman Scattering

OMI/Aura OMCLDRR is a Level-2 satellite data product providing global measurements of cloud properties. It supplies effective cloud pressure and cloud fraction derived from Rotational Raman Scattering analysis of spectra between 392 and 398 nm. The dataset includes ancillary parameters, geolocation, viewing angles, and quality flags for each 13x24 km pixel.

Use Cases

• Analyzing global cloud fraction distribution based on the Raman scattering retrieval algorithm.
• Studying cloud top pressure for climate and weather model validation using the pixel-level geospatial data.
• Investigating satellite viewing angle effects on cloud retrievals using the ancillary solar and viewing angles.
• Assessing data quality for atmospheric composition studies using the included quality flags.

Strengths

• Provides two primary cloud parameters (effective cloud pressure and fraction) from a specific, physics-based algorithm (Rotational Raman Scattering).
• Offers high spatial resolution data at approximately 13x24 km at nadir, with global coverage from multiple daily orbits.
• Contains extensive ancillary data including terrain information, geolocation, and quality flags to support analysis.

Limitations

• Column names and a complete data schema are not provided in the available metadata, limiting understanding of the full data structure.
• Key metadata such as row count, file size, and specific license terms conflict or are missing across sources.
• Data is stored in the HDF-EOS5 format, which may require specialized software or libraries for access and analysis.

Provenance

Source

National Aeronautics and Space Administration (NASA), Aura Ozone Monitoring Instrument (OMI). Algorithm lead: Dr. Joanna Joinner.

Collection Method

Satellite remote sensing via the OMI instrument, using the Rotational Raman Scattering method for retrieval.

Freshness

2026-04-09 (from datagov platform, but this appears to be a future date which may indicate a metadata error)

Geography

Global