A Reasonable Mean Dynamic Topography State on Improving the Ability of Assimilating the Altimetry Observations into a Coupled Climate System Model: An Example With CAS‐ESM‐C

Abstract

AbstractIn this study, based on an ocean data assimilation system for the coupled climate model CAS‐ESM‐C, how to reasonably assimilate altimetry data are explored. In sea surface height (SSH) assimilations, the mean dynamic topography (MDT) is an important factor that can coordinate the observed sea level anomalies with the modeled SSH. The SSH assimilation results are first compared through assimilation experiments using three different MDTs, including the observed reference height, the MDT from model control run, and the MDT from the assimilation experiment in CAS‐ESM‐C, with the climatological World Ocean Atlas (WOA) temperature assimilated into the coupled model. The results show that the third one can significantly improve the ability of the ocean data assimilation system to assimilate the SSH observations. Using this MDT, the SSH assimilation scheme of the ocean data assimilation system was established for the CAS‐ESM‐C, and a long‐term SSH assimilation experiment from 1994 to 2017 was carried out. The results show that the SSH assimilation performs much better than the SST assimilation in reproducing the ocean states and seasonal‐interannual variability. The improvements of SSH assimilation compared with SST assimilation may be due to the different properties of the two ocean variables. While SST is a thermodynamic variable used to evaluate the thermal condition of the ocean surface layer, SSH is a dynamic variable linked to the dynamical information of the whole ocean layer. Thus, SSH assimilation can constrain the ocean model with observed dynamic information, which is more important to the state estimation and temporal evolution of the ocean.