Extended Reconstructed Sea Surface Temperature Version 6 (ERSSTv6): Part I. An Artificial Neural Network Approach

Huang, Boyin; Yin, Xungang; Boyer, Tim; Liu, Chunying; Menne, Matthew; Rao, Yuhan Douglas; Smith, Thomas; Vose, Russell; Zhang, Huai-Min

doi:10.1175/JCLI-D-23-0707.1

Advanced Search

Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

Advanced Search
Custom Query

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Clear All

Query Builder

Query box

Clear All

For additional assistance using the Custom Query please check out our Help Page

The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners. As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.

Extended Reconstructed Sea Surface Temperature Version 6 (ERSSTv6): Part I. An Artificial Neural Network Approach

2025
By Huang, Boyin ; Yin, Xungang ; Boyer, Tim ; ...
Source: Journal of Climate (2025)

Public Access Version Available on: July 02, 2025, 12:00 AM

Please check back on the date listed above.

Details You May Also Like

Details:

Journal Title:

Journal of Climate
Personal Author:

Huang, Boyin ; Yin, Xungang ; Boyer, Tim ; Liu, Chunying ; Menne, Matthew ; ... More +

Huang, Boyin ; Yin, Xungang ; Boyer, Tim ; Liu, Chunying ; Menne, Matthew ; Rao, Yuhan Douglas ; Smith, Thomas ; Vose, Russell ; Zhang, Huai-Min Less -
NOAA Program & Office:

NESDIS (National Environmental Satellite, Data, and Information Service) ; NCEI (National Centers for Environmental Information) ; NCICS (North Carolina Institute for Climate Studies) ; STAR (Center for Satellite Applications and Research)

NESDIS (National Environmental Satellite, Data, and Information Service) ; NCEI (National Centers for Environmental Information) ; NCICS (North Carolina Institute for Climate Studies) ; STAR (Center for Satellite Applications and Research) Less -
Description:

NOAA’s Extended Reconstructed Sea Surface Temperature (SST; ERSST) is operational global SST product based on in situ observations, which has been widely used monitoring and assessing global ocean climate particularly El Niño and Southern Oscillation (ENSO) events. ERSSTv5 and its predecessors, however, encountered two shortcomings: (1) low SST spatial-variabilities in the data sparse regions before the 1950s and (2) low performance scores against in situ observations after the 1970s. The first problem has been mitigated in this Part study of ERSSTv6 by removing a 3-month running average and applying an interpolation method using an artificial neural network (ANN). The improvements of ANN method over an empirical orthogonal teleconnection (EOT) method used in previous versions were assessed against validation, testing, and observation datasets. In comparison with ERSSTv5, the spatial correlation coefficient (SCC) with reference to observations increases by 5%, and root-mean-square-difference (RMSD) with reference to observations decreases by 0.03°C in ERSSTv6. The improvements of SCC and RMSD are more pronounced in the tropical Pacific and the Southern Hemisphere oceans between 60°S and 30°S. The second problem has been addressed separately in our Part II study.
Source:

Journal of Climate (2025)
DOI:

https://doi.org/10.1175/JCLI-D-23-0707.1
ISSN:

0894-8755;1520-0442;
Format:

PDF
Publisher:

American Meteorological Society
Document Type:

Journal Article
Rights Information:

Other
Compliance:

Submitted
Main Document Checksum:

[+]

urn:sha-512:fb8c142402bcefa36c9b0e917bbc1f0d6c1edfc369e8bdafbf14368682cf17c04dbfc1025f37f67a6773f1ab783d36da69614f5308af40b8cfb3931daacf796c
File Type:

Supporting Files:

No Additional Files

More +