TROPICS06: Satellite-Based Tropical Cyclone Intensity Estimates

TROPICS06 L2B D-MINT183 data provides estimates of tropical cyclone intensity from a constellation of five small satellites. The dataset contains estimates for Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW), derived from passive microwave spectrometer observations. The estimates are generated by a convolutional neural network trained on brightness temperature imagery from multiple satellite sensors.

Use Cases

• Estimating tropical cyclone intensity based on passive microwave brightness temperatures.
• Analyzing storm structure using observations from a constellation of five small satellites.
• Comparing neural-network-derived intensity estimates with other physical algorithms.
• Monitoring tropical cyclone development with high temporal resolution satellite data.

Strengths

• Data originates from a dedicated constellation of five identical satellite vehicles.
• Algorithm uses a convolutional neural network trained on imagery from four established satellite sensors (SSMIS, ATMS, MHS, AMSU-B).

Limitations

• Specific column names and dataset size (rows, file size) are unknown across all sources.
• The neural network algorithm has no inherent physical understanding of intensity relationships.
• The 'last updated' metadata is inconsistent, with one source showing a 2026 date and others showing 'None'.

Provenance

Source

NASA GES_DISC and University of Wisconsin/CIMSS

Collection Method

Observations from the TROPICS satellite constellation's Millimeter-wave Sounder (TMS) payload.

Freshness

2026-04-09 21:20:11.118245

Geography

Global, focusing on tropical cyclone regions.