2026-10-10T14:20:07Z https://www.scidb.cn/oai

10.11922/sciencedb.01058 2023-07-31T15:26:21Z

2023-07-31 OPEN: A Global 1º×1º Monthly Ocean Heat Content Dataset from Remote Sensing Data via a Neural Network Approach (1993-2022) doi:10.11922/sciencedb.01058 en 2023-07-07 v1.1.1 updates: We have updated the OPEN OHC data to the end of 2022. See OPEN-OHCv1.1.1_1993-2022.nc. Ensemble mean across six ensembles and associated standard deviation are provided for four depth integrals (0-300m, 0-700m, 0-1500m, and 0-2000m).The OPEN dataset estimates OHC anomalies over four different depths down to 2000 m covering the near-global ocean, with a neural network method, from remote sensing-based products (SSH, SST, and Winds) to Argo-gridded OHC as training data. The resolution is monthly and a quarter degree, while the time span is from 1993 to 2018. The work was published in Remote Sensing (https://www.mdpi.com/2072-4292/12/14/2294). It was cited by IPCC's Sixth Assessment Report (AR6), among the direct estimations of global OHC. Ocean Heat Content; Multi-source Remote Sensing; Machine Learning; Global Ocean; Climate Change; artificial neural network Wenfang Lu Hua Su Haojie Zhang Xupu Geng Xiao-Hai Yan PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/https://doi.org/10.3390/rs12142294 Science Data Bank