Daily NeurOST: Sea Surface Height and Geostrophic Currents from Neural Network Analysis

NeurOST Level 4 analysis products map daily sea surface height and surface geostrophic currents using a neural network trained on sparse satellite altimetry and sea surface temperature data. This dataset is produced by the University of Washington and NASA's Jet Propulsion Laboratory. The data was last updated on March 13, 2026.

Use Cases

• Modeling ocean circulation dynamics based on daily sea surface height and geostrophic current data
• Analyzing mesoscale eddies based on high-resolution surface topography data
• Training or validating machine learning models for ocean state estimation based on the neural network mapping method
• Studying sea surface topography variability based on the combined altimetry and sea surface temperature inputs

Strengths

• Data is produced by authoritative institutions: the University of Washington and NASA's Jet Propulsion Laboratory
• Analysis product is at Level 4, indicating it is a gap-filled, gridded, and interpolated dataset
• Last updated on 2026-03-13, suggesting ongoing maintenance

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• Description metadata is limited; actual data quality requires manual inspection after download

Provenance

Source

National Aeronautics and Space Administration, University of Washington, Jet Propulsion Laboratory

Collection Method

Mapped by a neural network trained with sparse Level 3 nadir altimetry observations (CMEMS) and the MUR Level 4 gridded sea surface temperature product (PO.DAAC)

Time Range

Daily

Freshness

Last updated 2026-03-13 03:23:30.479161

Geography

Global oceans