Projection of Sea Level Change in the South China Sea Based on Dynamical Downscaling

Abstract

The projection of future sea level change is usually based on the global climate models (GCMs); however, due to the low spatial resolution of the GCMs, the ability to reproduce the spatial heterogeneity of sea level is limited. In order to improve the sea level simulation capability in the South China Sea (SCS), a high-resolution ocean model has been established by using the dynamic downscaling technology. By evaluating and testing 20 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6), average results of seven models were selected as the forcing condition of the high-resolution ocean model. The ocean model conducted the historical (1980~2014) and future (2015~2100) simulation under three scenarios of Shared Socio-economic Pathways (SSP1–2.6, SSP2–4.5 and SSP5–8.5). The selected average results of seven models in CMIP6 are better than any of them individually. The downscaled dynamic ocean model provides fruitful spatial characteristics of the sea level change, with a decrease in the dynamic sea level (DSL) in the central and southeastern parts of the SCS, and with a significant increase in the coastal DSL. The local steric sea level (SSL) is dominated by the local thermosteric sea level (TSSL), and the changes of local TSSL more than half of the sea level rise in SCS, indicate the magnitude of total sea level rise is dominated by local TSSL. But the spatial variation in total sea level is dominated by the spatial variation in DSL. Compared with CMIP5, the rise magnitude of the DSL and the local TSSL have been increased under the CMIP6 scenarios. The dynamic downscaling of sea level reveals more spatial details, provides more reliable projection of future sea level under the background of global warming, and can provide a new reference for coastal areas in the SCS to cope with the increasing risk of extreme water level disasters in the future.