Classification of optical water groups in the subarctic pacific and adjacent seas using satellite-derived light absorption spectra of chromophoric dissolved organic matter

Abstract

The characteristics of the water masses that contribute to high biological production in the subarctic Pacific and adjacent seas (SPA) could change because of recent climate change. This study reports on a method to classify water in the SPA into distinct optical water groups using the light absorption coefficient of chromophoric dissolved organic matter (CDOM), a_CDOM(λ), captured using an ocean color satellite. In situ samples obtained from ship surveys between 2006 and 2021 were classified into five optical group numbers (OGN1–OGN5) based on a_CDOM parameters in the ultraviolet (UV) region: a_CDOM(λ) at 350 nm (a_CDOM(350)) and the spectral slopes at 275–295 nm (S_275–295) and at 350–400 nm (S_350–400). We were also able to identify OGN with a new method using machine learning technique developed in this study that adopted satellite-derived a_CDOM(λ) in the visible (VIS) region. The distribution and characteristics of OGN classified using the in situ a_CDOM parameters in the UV region supplement the interpretation of the origin and mixing of the water masses classified by temperature and salinity. Relative to in situ samples, the accuracy of the OGN estimation from the ocean color satellites was 83.3%. The satellite-derived OGN were able to distinguish high chlorophyll-a areas where high phytoplankton productivity is expected. In addition, identifying the distribution of OGN from satellites supports improved understanding of the bloom process. This method has potential to help to understand the impact of phenomena from accelerating ocean warming (e.g., sea ice decline, enhancement of stratification and increase in riverine input) on water masses structure and the consequent changes in the phytoplankton productivity in the SPA.