NOAAGlobalTemp Version 6: An AI-Based Global Surface Temperature Dataset

Abstract The National Oceanic and Atmospheric Administration Global Surface Temperature (NOAAGlobalTemp) dataset is widely used for scientific research, operational monitoring, and climate assessment activities. Aligning with NOAA’s mission values, NOAAGlobalTemp has been updated to version 6 (i.e., NGTv6), which includes two enhancements over its predecessor (NGTv5). The first enhancement is the expansion of the spatial coverage to encompass the entire globe and the extension of temporal coverage back to 1850 (an interim version of NOAAGlobalTemp with these features was released in February 2023). The expansion of spatial coverage is accomplished by utilizing surface air temperatures over the Arctic Ocean and by eliminating the data reconstruction mask used in NGTv5 that had suppressed interpolation in data-sparse regions. This change has important implications for global temperature trends since the Arctic region has been warming at a much faster pace, more than 4 times the global average, in the twenty-first century to date. The second enhancement is the implementation of a methodology based on artificial intelligence (AI) for reconstructing surface air temperature over the global land surface and the Arctic Ocean. The AI model employs an artificial neural network to fill data gaps and is demonstrated to be more robust, stable, and accurate than the previous gap-filling method, particularly in observation-sparse areas such as the polar regions. The model outperforms the previous approach across all evaluated statistical metrics, and the output reaches a stable state more quickly as observations are received, which facilitates climate monitoring. NGTv6 was released in February 2024.

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Publication Details

Journal
Bulletin of the American Meteorological Society
Published
2024-09-30
DOI
https://doi.org/10.1175/bams-d-24-0012.1
Citations
6
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
2.26
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article

NOAAGlobalTemp Version 6: An AI-Based Global Surface Temperature Dataset

Karin Gleason, Chun‐Ying Liu, Huai‐Min Zhang, Adedoja Adeyeye et al.
6 citations
Bulletin of the American Meteorological Society
Meteorological Phenomena and Simulations
2.26
article

NOAAGlobalTemp Version 6: An AI-Based Global Surface Temperature Dataset

Karin Gleason, Chun‐Ying Liu, Huai‐Min Zhang, Adedoja Adeyeye, Matthew J. Menne, Scott Applequist, Ahira Sánchez-Lugo, Russell S. Vose, Boyin Huang, Xungang Yin
article en
6 citations

Abstract

Abstract The National Oceanic and Atmospheric Administration Global Surface Temperature (NOAAGlobalTemp) dataset is widely used for scientific research, operational monitoring, and climate assessment activities. Aligning with NOAA’s mission values, NOAAGlobalTemp has been updated to version 6 (i.e., NGTv6), which includes two enhancements over its predecessor (NGTv5). The first enhancement is the expansion of the spatial coverage to encompass the entire globe and the extension of temporal coverage back to 1850 (an interim version of NOAAGlobalTemp with these features was released in February 2023). The expansion of spatial coverage is accomplished by utilizing surface air temperatures over the Arctic Ocean and by eliminating the data reconstruction mask used in NGTv5 that had suppressed interpolation in data-sparse regions. This change has important implications for global temperature trends since the Arctic region has been warming at a much faster pace, more than 4 times the global average, in the twenty-first century to date. The second enhancement is the implementation of a methodology based on artificial intelligence (AI) for reconstructing surface air temperature over the global land surface and the Arctic Ocean. The AI model employs an artificial neural network to fill data gaps and is demonstrated to be more robust, stable, and accurate than the previous gap-filling method, particularly in observation-sparse areas such as the polar regions. The model outperforms the previous approach across all evaluated statistical metrics, and the output reaches a stable state more quickly as observations are received, which facilitates climate monitoring. NGTv6 was released in February 2024.

Bulletin of the American Meteorological SocietyVol. 105(11)
Riverside Technology (United States) (US), NOAA National Centers for Environmental Information (US)
Openalex Percentile: Top 13%
Meteorological Phenomena and Simulations
2.26
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