## 5 Conclusions  
High-resolution general ocean circulation models are also called \"eddy-resolving\" ocean circulation models, and they are usually models with resolutions higher than 10 km. This kind of model is capable of simulating the characteristics of mesoscale eddies and  
Figure 13: Correctness of simulations.  
their climate effects. Moreover, an \"eddy-resolving\" ocean model can describe submarine topography, the land-sea distribution, and the spatial and temporal structure of an ocean's west boundary circulation well. Therefore, the development of global \"eddy-resolving\" ocean circulation models has been drawing people's attention in the field of physical oceanography and climate research.  
In this work, we applied several parallel optimization methods on LICOM, including improvements in the parallelization scheme, communication optimization, the floating-point performance, the asynchronous IO, hybrid programming of MPI and OpenMP, and the redesign of the software structure. The performance of the distributed cluster was fully utilized. The computing speed of the optimized version of LICOM reached 12.6 model years per day when 19,200 processor cores were used, which was twice that of the original LICOM. The optimized LICOM could scale up to 245,760 processor cores. However, for the old version, there would not be much of a speedup when more than 19,200 processor cores were used. This is a vital improvement thanks to the optimization in this work. As mentioned in Section 1, swPOM can be scaled up to 250,000 cores. Although it is not appropriate to simply compare the scalability of different systems on different machines, the results of our work are around the same level as that of other researchers' work. We found that the optimization of communications and the tackling of load imbalance have considerable benefits in improving the performance of LICOM according to our test results.  
In addition, we conducted simulations of a real scenario from 1993 to 2007 by using the optimized LICOM. The results showed that mesoscale vortexes were well simulated by the model. In conclusion, our optimization work considerably improved the performance of LICOM in terms of computing speed and scalability.  
Conceptualization, H.L., P.L., B.N. and J.J. ; methodology, J.J.; software, T.W., H.H. and J.J.; validation, H.H. and T.W.; formal analysis, B.N.; investigation, H.H.; resources, J.J.; data curation, [PERSON] and T.W.; writing--original draft preparation, [PERSON]; writing--review and editing, [PERSON]; visualization, [PERSON] and Z.Z.; supervision, [PERSON]; project administration, [PERSON]; funding acquisition, [PERSON] All authors have read and agreed to the published version of the manuscript.  
This research was supported by the National Natural Science Foundation of China (Grant No. 41931183) and the National Key Scientific and Technological Infrastructure project, \"Earth System Science Numerical Simulator Facility\" (EarthLab).  
Data Availability Statement: Data sharing is not applicable.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} IO & Input and Output \\ LICOM & LASG/IAP Climate System Ocean Model \\ LASG & State Key Laboratory of Numerical Modeling for Atmospheric Sciences \\  & Geophysical Fluid Dynamics \\ IAP & Institute of Atmospheric Physics \\ HYCOM & Hybrid Coordinate Ocean Model \\ NEMO & Nucleus for the European Modeling of the Ocean \\ MOM & Modular Ocean Model \\ CMIP6 & The Sixth Coupled Model Intercomparison Project \\ \end{tabular}