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Extended Reconstructed Sea Surface Temperature Version 6 (ERSSTv6): Part II. Upgrades on Quality Control and Large-scale Filter
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2025
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Source: Journal of Climate (2025)
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Journal Title:Journal of Climate
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Description:NOAA’s Extended Reconstructed Sea Surface Temperature (SST; ERSST) is a monthly 2° SST product starting from 1850. Our Part I study indicated that the performance scores of spatial correlation coefficient (SCC) and root-mean-square-difference (RMSD) dropped clearly after the mid-1970s in the analysis of ERSST with an artificial neural network (ANN) method. In this Part II study, we demonstrate that ERSST with the ANN method can further be improved progressively in the final ERSSTv6 by the following steps: 1) applying a nearest neighbor check (NNC) quality control algorithm on ship observations, 2) applying a large-scale (>200km) filter (LS200) on SST super-observations, and 3) upgrading algorithms in proxy SST from ice concentration. These progressive improvements were assessed against validation and observation datasets. In comparison with ERSST with the ANN method alone, the quality of ERSSTv6 improves in the statistical metrics of SCC and RMSD by 2–11% and 0.01°–0.24°C, respectively, in the global oceans. In the ice-covered regions, SST bias and RMSD decrease by 0.67°C and 0.29°C, respectively.
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Source:Journal of Climate (2025)
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DOI:
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ISSN:0894-8755;1520-0442;
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Rights Information:Other
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Compliance:Submitted
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Supporting Files:No Additional Files
