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Three Types of Antarctic Intermediate Water Revealed by a Machine Learning Approach.
- Source :
- Geophysical Research Letters; 11/16/2022, Vol. 49 Issue 21, p1-8, 8p
- Publication Year :
- 2022
-
Abstract
- The subduction and export of Antarctic Intermediate Water (AAIW) is important for the heat, freshwater, carbon, and nutrient budgets of the world's oceans. Three types of AAIW are identified by applying an unsupervised machine learning approach to individual Argo profiles. The likely sources and pathways of these AAIWs are indicated by the locations and magnitudes of the salinity and oxygen extrema. The Southeast Pacific AAIW forms north of the Subantarctic Front (SAF) in the west corner of the Drake Passage and is exported north into the subtropical gyre. The South Pacific AAIW forms in the South Pacific along the SAF and is transported through the Drake Passage, thereby becoming a saliter and denser AAIW. The circumpolar AAIW, the coldest and freshest AAIW, has a circumpolar source and is injected into the ocean interior in the Brazil‐Malvinas confluence. The results clarify different types of AAIW have different origins. Plain Language Summary: The formation and export of Antarctic Intermediate Water (AAIW) strongly influence the global climate system by redistributing heat, freshwater, carbon, and nutrients from high latitudes to the tropics. Thanks to an increasing number of observations from autonomous instruments and Argo floats, our understanding of the sources and pathways of AAIW has deepened in recent decades. Even so, there is controversy about the formation of AAIW. Unlike previous studies using traditional property‐driven classification, we apply an unsupervised classification technique to automatically classify the Argo temperature and salinity profiles and identify three types of AAIWs from the regimes in the Southern Ocean. The classification results are consistent with previous studies. Moreover, we find that different types of AAIW form in different regions. This paper shows that the machine learning technique benefits us in dealing with a large data set and identifying AAIW classes that is hard to distinguish by the traditional property‐driven classification method. Key Points: An unsupervised learning approach, the profile classification model (PCM), is applied to classify Argo temperature and salinity profilesPCM identifies three types of Antarctic Intermediate Water (AAIW) in the Southern Ocean and reveals their locations and boundariesThe Polar Frontal Zone in the South Pacific sector is established as the source region for AAIW formation [ABSTRACT FROM AUTHOR]
- Subjects :
- MACHINE learning
FRESH water
HEATING
Subjects
Details
- Language :
- English
- ISSN :
- 00948276
- Volume :
- 49
- Issue :
- 21
- Database :
- Complementary Index
- Journal :
- Geophysical Research Letters
- Publication Type :
- Academic Journal
- Accession number :
- 160200551
- Full Text :
- https://doi.org/10.1029/2022GL099445