OS003-0007
Projected Sea Level Changes in the China Marginal Seas Based on Dynamical Downscaling

Monday, 7 December 2020
Poster
YI Jin, Ocean University of China, Ocean and Atmosphere, Qingdao, China; CSIRO Marine and Atmospheric Research Hobart, Hobart, Australia, Xuebin Zhang, CSIRO, Oceans & Atmosphere, Centre for Southern Hemisphere Oceans Research (CSHOR), Hobart, TAS, Australia, John Church, University of New South Wales, Climate Change Research Centre, Sydney, NSW, Australia and Xianwen Bao, Ocean University of China, Key Laboratory of Physical Oceanography.MOE.China, Qingdao, China
Abstract:
The regional projections of future sea level changes are usually produced based on global climate models (GCMs). However, the changes in shallow coastal regions like the China marginal seas cannot be fully described by GCMs. To improve the regional ocean simulation, a high-resolution (~8 km) regional ocean model based on the Regional Ocean Modeling System (ROMS) is set up for the China marginal seas for both historical (1994-2015) and future (2079-2100) periods. The model validation during the historical period indicates that this regional model can reproduce historical ocean states reasonably well at different spatio-temporal scales. The same model is then integrated for the future period, driven by monthly climatological climate changes signals from 8 CMIP5 GCMs individually via both open boundary and surface conditions. The downscaled climate changes derived by comparing historical and future experiments are similar with those from corresponding GCMs but with greater details. Furthermore, perturbation experiments with changes of surface or open boundary condition turned off reveal that the dynamic sea level (DSL) change in the South China Sea is dominated by the climate change signals from Pacific basin resulting in cyclonic circulation change, while the DSL change in the East China marginal seas is caused by the signals from both the local atmosphere and remote Pacific basin. Dynamical downscaling method is also extended to study future extreme sea level changes. Our method of dynamical downscaling of DSL change in coastal regions should be a useful tool for adaptation and mitigation planning for future climate and sea level changes.