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

In 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. Plain Language Summary Altimetry data are widely used in ocean assimilation. Compared with standalone ocean model assimilation, assimilation in a coupled model framework is more realistic due to consideration of the air-sea interaction processes and draws more attention from the modeling community. To reasonably assimilate altimetry data, mean dynamic topography (MDT) is an essential factor that can coordinate the observed sea level anomalies with the modeled sea surface temperature (SSH). In this study, to choose a best MDT for altimetry data assimilation in the coupled model (CAS-ESM-C), three different MDTs were used in SSH assimilation in CAS-ESM-C. We concluded that the MDT derived from assimilating the climatological World Ocean Atlas (WOA) temperature into the coupled model can significantly improve the ability of the ocean data assimilation system to assimilate the SSH observations. Then, using this selected MDT scheme, long-term SSH assimilation experiments were conducted and the performances of SSH assimilation were compared with those of sea surface temperature (SST) assimilation. In comparison with SST assimilation, SSH assimilation achieves better performances in reproducing the mean states and seasonal-interannual variability of the ocean. DONG ET AL.

Comparison of East Asian Summer Monsoon Simulation between an Atmospheric Model and a Coupled Model: An Example from CAS-ESM

“…The outputs from the current version of the Chinese Academy of Sciences' Earth System Model Version 2 (CAS-ESM2), which consists of IAP4.0 [31] for the atmosphere, a revised LICOM2.0 for the ocean [32][33][34], CoLM for the land surface [35,36], and CICE4.0 for the sea ice [37], were analyzed in this study. Predecessors of CAS-ESM2, along with its component models, have been widely adopted in previous studies focusing on climate change and variability, including global and regional surface air temperature change during the 20th century [38], decadal variation in the Aleutian Low-Icelandic Low seesaw [39], decadal variation in the EASM [40,41], and coupled data assimilation and short-term climate predictions for China [25,42].…”