Sea surface temperature (SST) plays an important role in a number of ecological processes and can vary over a wide range of time scales, from daily to decadal changes. SST influences primary production, species migration patterns, and coral health. If temperatures are anomalously warm for extended periods of time, drastic changes in the surrounding ecosystem can result, including harmful effects such as coral bleaching. This layer represents the annual average frequency of anomalies of SST from 2000-2013, with values presented as fraction of a year.
Three SST datasets were combined to provide continuous coverage from 1985-2013. The concatenation applies bias adjustment derived from linear regression to the overlap periods of datasets, with the final representation matching the 0.05-degree (~5-km) near real-time SST product. First, a weekly composite, gap-filled SST dataset from the NOAA Pathfinder v5.2 SST 1/24-degree (~4-km), daily dataset (a NOAA Climate Data Record) for each location was produced following Heron et al. (2010) for January 1985 to December 2012. Next, weekly composite SST data from the NOAA/NESDIS/STAR Blended SST 0.1-degree (~11-km), daily dataset was produced for February 2009 to October 2013. Finally, a weekly composite SST dataset from the NOAA/NESDIS/STAR Blended SST 0.05-degree (~5-km), daily dataset was produced for March 2012 to December 2013.
The SST average annual frequency of anomalies was calculated by taking the average number of weeks that exceeded the maximum monthly climatological SST value from 2000-2013 for each pixel.
About this Dataset
Title | Sea Surface Temperature (SST) Average Annual Frequency of Anomalies, 2000-2013 - Hawaii |
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Description | Sea surface temperature (SST) plays an important role in a number of ecological processes and can vary over a wide range of time scales, from daily to decadal changes. SST influences primary production, species migration patterns, and coral health. If temperatures are anomalously warm for extended periods of time, drastic changes in the surrounding ecosystem can result, including harmful effects such as coral bleaching. This layer represents the annual average frequency of anomalies of SST from 2000-2013, with values presented as fraction of a year. Three SST datasets were combined to provide continuous coverage from 1985-2013. The concatenation applies bias adjustment derived from linear regression to the overlap periods of datasets, with the final representation matching the 0.05-degree (~5-km) near real-time SST product. First, a weekly composite, gap-filled SST dataset from the NOAA Pathfinder v5.2 SST 1/24-degree (~4-km), daily dataset (a NOAA Climate Data Record) for each location was produced following Heron et al. (2010) for January 1985 to December 2012. Next, weekly composite SST data from the NOAA/NESDIS/STAR Blended SST 0.1-degree (~11-km), daily dataset was produced for February 2009 to October 2013. Finally, a weekly composite SST dataset from the NOAA/NESDIS/STAR Blended SST 0.05-degree (~5-km), daily dataset was produced for March 2012 to December 2013. The SST average annual frequency of anomalies was calculated by taking the average number of weeks that exceeded the maximum monthly climatological SST value from 2000-2013 for each pixel. |
Modified | 2025-04-18T03:19:35.918Z |
Publisher Name | N/A |
Contact | N/A |
Keywords | Earth Science > Biosphere > Aquatic Ecosystems > Reef Habitat , Earth Science > Biosphere > Ecosystems > Marine Ecosystems > Reef > Coral Reef , Earth Science > Human Dimensions > Human Settlements > Coastal Areas , Earth Science > Oceans > Coastal Processes > Coral Reefs , Earth Science > Oceans > Ocean Temperature > Sea Surface Temperature , Continent > North America > United States Of America > Hawaii , Ocean > Pacific Ocean > Central Pacific Ocean > Hawaiian Islands , PacIOOS > Pacific Islands Ocean Observing System , PacIOOS > Pacific Islands Ocean Observing System , oceans |
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