Cloud optical thickness data is derived from the GOME-2 instruments aboard three MetOp satellites. The dataset provides global measurements of cloud properties, including cloud fraction, cloud-top pressure, and cloud-top albedo, for atmospheric composition monitoring. Products are generated by DLR under the EUMETSAT AC-SAF framework using the OCRA and ROCINN retrieval algorithms.
Use Cases
- Analyze trends in cloud optical thickness and cloud fraction to study climate feedback mechanisms.
- Validate and improve radiative transfer models using retrieved cloud-top pressure and albedo data.
- Correlate cloud property measurements with concurrent trace gas data from the same GOME-2 instrument for atmospheric chemistry studies.
- Assimilate near-real-time cloud optical thickness data into numerical weather prediction models.
- Map global distributions of cloud optical properties to assess their impact on ultraviolet radiation at the surface.
Strengths
- Data continuity from three satellites launched in 2006, 2012, and 2018 provides a multi-decade record.
- Near-real-time products are available within two hours of satellite sensing.
- Retrieval uses advanced neural network (ROCINN) and radiative transfer (libRadtran) methods.
Limitations
- Specific row count, spatial resolution, and temporal frequency are not provided in the input.
- The description does not specify potential biases or uncertainties in the neural network retrieval process.
- Data access and file format details are unknown, which may complicate initial use.
Provenance
- Source
- DLR (German Aerospace Center) under EUMETSAT's AC-SAF, using data from the GOME-2 instruments on MetOp-A, -B, and -C satellites.
- Collection Method
- Satellite remote sensing with retrieval via the OCRA cloud detection algorithm and the ROCINN neural network inversion scheme.
- Time Range
- Operational from at least 2006 (MetOp-A launch) to present.
- Freshness
- null
- Geography
- Global