Global Ozone Monitoring Experiment-2 (GOME-2) instruments on three MetOp satellites provide near-real-time atmospheric sulfur dioxide (SO2) total column data. The dataset is generated operationally by DLR for EUMETSAT's AC-SAF, with products available within two hours of satellite sensing. Monitoring began with MetOp-A in 2006, followed by MetOp-B in 2012 and MetOp-C in 2018.
Use Cases
- Tracking volcanic SO2 plume dispersion and magnitude using the total column product.
- Analyzing long-term trends in anthropogenic SO2 emissions from industrial regions via time-series of column densities.
- Validating atmospheric chemistry models by comparing simulated SO2 columns against satellite-retrieved slant columns and vertical column densities.
- Studying the correlation between SO2 concentrations and cloud properties or ultraviolet radiation intensities measured by the same instrument.
Strengths
- Near-real-time data availability within two hours of satellite sensing.
- Continuous monitoring from three satellites providing long-term coverage since 2006.
- Operational products generated using a standardized algorithm (GDP 4.x) with corrections for equatorial offset and spectral interference.
Limitations
- Specific row count, spatial resolution, and data volume are unknown from the description.
- Algorithm reliance on a single wavelength for vertical column computation may introduce retrieval uncertainties under certain atmospheric conditions.
- The dataset's completeness and global coverage consistency across all three satellite lifetimes are not detailed.
Provenance
- Source
- DLR (German Aerospace Center) for EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF).
- Collection Method
- Satellite remote sensing via GOME-2 instruments on MetOp-A, -B, and -C, processed using the GDP 4.x algorithm within the UPAS processor.
- Time Range
- Operational from October 2006 (MetOp-A) to present, with additional satellites launched in 2012 and 2018.
- Freshness
- Near-real-time (available within two hours of sensing).
- Geography
- Global.