NASA ATDD Project: AMSR-E and MODIS/Aqua Satellite Subsets Along CloudSat Track

NASA ATDD Project provides two subsets of satellite data from the AMSR-E and MODIS/Aqua instruments, aligned with the CloudSat satellite's field of view. The AMSR-E subset contains instantaneous rain rate and type measurements over ocean and land from June 2002 to October 2011. The MODIS subsets provide atmospheric aerosol optical properties, such as optical thickness and size distribution, globally over ocean and near-globally over land.

Use Cases

• Correlating rain type (convective vs. stratiform) with aerosol optical properties based on the co-located satellite measurements.
• Analyzing long-term trends in passive microwave-derived rain rates over a nine-year period mentioned in the description.
• Studying the spatial distribution of atmospheric aerosols in relation to CloudSat's observational track based on the 200 km wide-swath subset.
• Validating and calibrating satellite-based precipitation algorithms using the subset's preserved original HDF-EOS data format.

Strengths

• Data spans a significant time range from 18 June 2002 to October 2011.
• Subsets are precisely co-located with CloudSat's track, with cross-track widths defined at +/-100 km for AMSR-E and +/-5 km or +/-100 km for MODIS.
• Original HDF-EOS formatting is preserved, maintaining compatibility with standard Earth science tools.

Limitations

• Row count and dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data freshness is unverified as the last update date is unknown.

Provenance

Source

NASA Goddard Space Flight Center (GSFC) and the AMSR-E and MODIS/Aqua satellite missions.

Collection Method

Subsets were created by selecting data from the original Level-2B (AE_Rain) and Level-2 (MYD04_L2) swath products within specified distances from the CloudSat track.

Time Range

18 June 2002 to October 2011.

Freshness

Data collection ended in October 2011; the dataset is historical.

Geography

Global coverage, with specific algorithms for ocean and land areas.