Global Ocean Heat Content Anomalies from Argo Floats, 2005-2020 Baseline

Monthly and yearly time series of Ocean Heat Content Anomalies (OHCA) calculated by subtracting the 2005-2020 mean from Argo float observations. The dataset, created by Mikael Kuusela of Carnegie Mellon University, maps OHC fields using locally stationary Gaussian processes and provides global estimates for different vertical ocean sections. It includes OHC in Joules per square meter and Zettajoules, as well as volume-averaged temperature anomalies in degrees Celsius.

Use Cases

• Modeling long-term ocean warming trends based on the global OHC time series.
• Analyzing spatial patterns of heat uptake based on the mapped OHC fields.
• Studying vertical heat distribution in the ocean based on data from different depth sections.
• Validating climate models using the volume-averaged temperature anomaly time series.

Strengths

• Data is derived from the Argo array, a major international ocean observation program.
• Provides both energy (J/m2, ZJ) and temperature (degC) anomaly metrics for analysis.
• Mapping methodology uses data-driven decorrelation scales as described in a cited 2018 paper.

Limitations

• Row count, file size, and specific column definitions are unknown from the provided metadata.
• Regions shallower than 300 meters or insufficiently sampled by Argo are excluded, creating spatial gaps.
• The last update date for the dataset is unknown, which may affect freshness assessment.

Provenance

Source

Argo float data, processed by Mikael Kuusela (Carnegie Mellon University).

Collection Method

OHC anomalies calculated by subtracting a 2005-2020 mean; fields mapped using locally stationary Gaussian processes.

Time Range

Time series relative to a 2005-2020 baseline; specific start and end dates of the underlying data are not stated.

Geography

Global ocean, excluding regions shallower than 300m or poorly sampled by the Argo array.