Comparative Analysis of Two Approaches for Correcting the Systematic Ocean Temperature Bias of CAS-ESM-C

Mengjiao Du,Fei Zheng,Renping Lin,Kan Yi,Jiang Zhu

doi:10.3390/jmse9090925

Abstract

Currently, several ocean data assimilation methods have been adopted to increase the performance of air–sea coupled models, but inconsistent adjustments between the sea temperature with other oceanic fields can be introduced. In the coupled model CAS-ESM-C, inconsistent adjustments for ocean currents commonly occur in the tropical western Pacific and the eastern Indian Ocean. To overcome this problem, a new ensemble-based bias correction approach—a simple modification of the Ensemble Optimal Interpolation (EnOI) approach for multi-variable into a direct approach for a single variable—is proposed to minimize the model biases. Compared with the EnOI approach, this new approach can effectively avoid inconsistent adjustments. Meanwhile, the comparisons suggest that inconsistent adjustment mainly results from the unreasonable correlations between temperature and ocean current in the background matrix. In addition, the ocean current can be directly corrected in the EnOI approach, which can additionally generate biases for the upper ocean. These induced ocean biases can produce unreasonable ocean heat sinking and heat storage in the tropical western Pacific. It will generate incorrect ocean heat transmission toward the east, further amplifying the inconsistency introduced through the tropical air–sea interaction process.

Highlights

The ocean records climate change information through air–sea interactions, playing an essential role in the climate system due to its own physical characteristics
In the evaluation of the ocean data assimilation system in Chinese Academy of Sciences (CAS)-ESM-C, we found that adjustments in the current field are not significant when assimilating the sea surface temperature (SST) [53], but when assimilating the Argo profiles, the adjusted current field and the model biases have a great influence on the assimilation, even resulting in a simulation that cannot be effectively improved by the assimilation
In the eastern tropical Pacific Ocean, the depth of OBS is slightly shallower than the model results—that is, the OBS thermocline has a large slope in the tropical Pacific Ocean

Summary

Introduction

The ocean records climate change information through air–sea interactions, playing an essential role in the climate system due to its own physical characteristics. The climate system model can reflect the complex interactions among the components of the climate system. It has been widely applied in various fields of climate research [1]. The climate system model is an irreplaceable tool to investigate the characteristics and behaviors of the current climate, understand the climate’s past evolution, and predict future changes of the climate [2]. The initial field of the climate system model remains uncertain. To provide more accurate initial conditions for forecast or prediction, ocean data assimilation is usually used to reduce biases in model simulation [3–9]

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