Monthly Global Sea Surface Temperature Reconstruction Since 1854

ERSST v5 provides a historical reconstruction of monthly global ocean surface temperatures and anomalies on a 2-degree spatial grid since 1854. The dataset is produced by POCLOUD using in-situ observations from ICOADS R3.0 and GTS data, with anomalies calculated relative to a 1971-2000 climatology. Version 5 incorporates new data sources like Argo floats and improved statistical methodologies for better representation of El Niño and La Niña events.

Use Cases

• Analyze long-term SST trends and temperature anomalies across the 2-degree global grid to study climate change impacts.
• Model El Niño and La Niña event magnitudes and spatial structures using the improved SST reconstruction fields.
• Validate coupled climate models by comparing simulated SSTs against the reconstructed historical SST and associated error standard deviation fields.
• Study regional ocean heat content changes by integrating the spatially-complete SST anomaly data over specific basins.

Strengths

• Provides a continuous, spatially-complete monthly record since 1854, covering over 160 years.
• Implements improved statistical methodologies, including Empirical Orthogonal Teleconnection analysis with better tuning for sparse data regions.
• Version 5 incorporates new and updated input datasets like Argo floats, ICOADS R3.0, and HadISST2 sea ice concentration.

Limitations

• Spatial resolution is coarse at a 2-degree grid, limiting analysis of small-scale oceanographic features.
• Reconstruction accuracy is lower for early periods (pre-1900) and sparsely sampled regions due to data scarcity.
• The dataset is a statistical reconstruction from in-situ observations, not a direct measurement product, introducing methodological uncertainty.

Provenance

Source

POCLOUD, utilizing the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) and Global Telecommunications System (GTS) data.

Collection Method

Statistical reconstruction from in-situ ship, buoy, and float observations, employing bias correction and gap-filling techniques to create a spatially-complete grid.

Time Range

1854 to present (monthly)

Geography

Global ocean surface on a 2-degree latitude-longitude grid