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Modeling skin‐layer salinity with an extended surface‐salinity layer
Author(s) -
Song Y. Tony,
Lee Tong,
Moon JaeHong,
Qu Tangdong,
Yueh Simon
Publication year - 2015
Publication title -
journal of geophysical research: oceans
Language(s) - English
Resource type - Journals
eISSN - 2169-9291
pISSN - 2169-9275
DOI - 10.1002/2014jc010346
Subject(s) - argo , sss* , salinity , stratification (seeds) , climatology , environmental science , temperature salinity diagrams , satellite , mixed layer , meteorology , geology , oceanography , geography , computer science , seed dormancy , botany , germination , artificial intelligence , dormancy , aerospace engineering , engineering , biology
Abstract Due to near‐surface salinity stratification, it is problematic to compare satellite‐measured surface salinity within the first few centimeters (skin‐layer) of the ocean with Argo‐measured top‐level salinity at about 5 m or with ocean models that do not resolve the skin layer. Although an instrument can be designed to measure the surface salinity, a global scale measurement is currently not available. A regional model can be configured to have a vertical grid in centimeters but it would be computationally prohibited on a global scale due to time step constraints. Here we propose an extended surface‐salinity layer (ESSL) within a global ocean circulation model to diagnose skin SSS without increasing the computational cost, while allowing comparable solutions with both satellite and Argo salinity at the respective depths. Using a quarter‐degree global ocean model, we show that the ESSL improves near‐surface salinity significantly in comparisons with the Aquarius SSS and Argo salinity at 5 and 10 m, respectively. Comparing with data‐assimilated HYCOM results reveal that the ESSL provides much stronger seasonal variability of SSS, similar to the Aquarius observations. We also demonstrate that the ESSL solution can be used to constrain the global mean SSS in Aquarius SSS retrieval.