TROPESS CrIS-SNPP: Global Ammonia Vertical Profiles from Satellite

NASA's TROPESS project provides a global, 15-level vertical profile of atmospheric ammonia (NH3) using an optimal estimation algorithm called MUSES. Daily data files from the Suomi-NPP satellite's CrIS instrument offer a spatial resolution of 14 km, covering over seven years from December 2015 to May 2023. This dataset is a reanalysis stream summary product designed for consistent long-term analysis of a key atmospheric pollutant.

Use Cases

• Tracking global ammonia pollution sources and transport based on daily, vertically-resolved satellite measurements.
• Validating and improving atmospheric chemistry models using the 15-level vertical profile data.
• Analyzing long-term trends in atmospheric ammonia concentrations for the 2015-2023 period.
• Studying the correlation between ammonia levels and other atmospheric parameters in reanalysis products.

Strengths

• Provides a specific 15-level vertical profile from the surface to 0.1 hPa, offering detailed atmospheric structure.
• Covers a significant and recent time range of over seven years (2015-12-01 to 2023-05-18).
• Data is produced by NASA's TROPESS project using a defined optimal estimation algorithm (MUSES), indicating a processed, research-grade product.
• Has a fine spatial resolution of 14 km at nadir, suitable for regional-scale studies.

Limitations

• Column names and a precise row/size count are not provided in the available metadata, limiting immediate understanding of data structure.
• The license is ambiguously listed as 'other-license-specified' without explicit terms.
• The dataset's update status is unclear; the 'last updated' metadata field may refer to catalog entry maintenance, not data currency beyond May 2023.

Provenance

Source

National Aeronautics and Space Administration (NASA), TROPESS project, Principal Investigator Kevin W. Bowman.

Collection Method

Retrieved via the Cross-track Infrared Sounder (CrIS) on the Suomi-NPP satellite, processed using the MUlti-SpEctra, MUlti-SpEcies, Multi-SEnsors (MUSES) optimal estimation algorithm.

Time Range

2015-12-01 to 2023-05-18

Freshness

2026-04-09 21:22:58.753484 (Catalog metadata update; data coverage ends 2023-05-18)

Geography

Global