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…(Scopus)Thermocline Model for Estimating Argo Sea Surface Temperature
Zhang ChunLing
College of Marine Science, Shanghai Ocean University, Shanghai 201306, China
Zhang Meng-Li
College of Marine Science, Shanghai Ocean University, Shanghai 201306, China
Wang Zhen-Feng
Project Management Office of China National Scientific Seafloor Observatory, Tongji University, Shanghai 200092, China
Hu Song
College of Marine Science, Shanghai Ocean University, Shanghai 201306, China
Wang Dan-Yang
College of Marine Science, Shanghai Ocean University, Shanghai 201306, China
Yang Sheng-Long
Key Laboratory of East China Sea & Oceanic Fishery Resources Exploitation and Utilization，Ministry of Agriculture，Shanghai 200090, China
DOI: https://doi.org/10.36956/sms.v4i1.474
Received: 28 December 2021; Published: 7 January 2022
Copyright © 2022 Zhang ChunLing, Zhang Meng-Li, Wang Zhen-Feng, Hu Song, Wang Dan-Yang, Yang Sheng-Long. Published by Nan Yang Academy of Sciences Pte. Ltd..
Abstract
Argo has become an important constituent of the global ocean observation system. However, due to the lack of sea surface measurements from most Argo profiles, the application of Argo data is still limited. In this study, a thermocline model was constructed based on three key thermocline parameters, i.e, thermocline upper depth, the thermocline bottom depth, and thermocline temperature gradient. Following the model, we estimated the sea surface temperature of Argo profiles by providing the relationship between sea surface and subsurface temperature. We tested the effectiveness of our proposed model using statistical analysis and by comparing the sea surface temperature with the results obtained from traditional methods and in situ observations in the Pacific Ocean. The root mean square errors of results obtained from thermocline model were found to be significantly reduced compared to the extrapolation results and satellite retrieved temperature results. The correlation coefficient between the estimation result and in situ observation was 0.967. Argo surface temperature, estimated by the thermocline model, has been theoretically proved to be reliable. Thus, our model generates theoretically feasible data present the mesoscale phenomenon in more detail. Overall, this study compensates for the lack surface observation of Argo, and provides a new tool to establish complete Argo data sets.
Keywords: Argo, Sea surface temperature, Thermocline model, The Pacific Ocean