10:45 〜 11:00
[ACG39-06] Numerical simulation of present and possible future ocean acidification states in the western Seto Inland Sea, Japan
キーワード：ocean acidification , Seto Inland Sea, Bungo Channel, biogeochemical model
The impacts of climate change on marine ecosystems and important fishery species have become a worldwide concern in recent decades. Aside from global warming, calcifying organisms that form calcium carbonate shells and skeletons, such as shellfish and corals, are also susceptible to ocean acidification, which is also a result of excessive anthropogenic CO2 emissions. While drivers of ocean acidification in the open ocean are relatively well understood, the situation in coastal areas may be influenced by various regional and local factors and requires further elucidation. The purpose of this study is to apply a numerical modeling approach to evaluate present and project future states of ocean acidification around the Bungo Channel in the western Seto Inland Sea, Japan.
The CROCO modeling system (ver. 1.3.1; Jullien et al., 2022), which is capable of coupling the ROMS ocean model (Shchepetkin and McWilliams, 2005) with the marine biogeochemical model PISCES-v2 (Aumont et al., 2015), was selected. The current model setup features a horizontal grid resolution of 1.5 km, with initial and boundary forcing of physical parameters derived from the Japan Coastal Ocean Predictability Experiment reanalysis dataset (JCOPE2M; Miyazawa et al., 2017). Biogeochemical forcing is derived by combining data from seasonal spatial monitoring, the World Ocean Atlas 2009 (WOA 2009), and literature-based approximations. Inputs from major rivers are also included, which were derived from available seasonal or monthly monitoring datasets. To run future projections, a candidate dataset for deriving model forcing is the Future Ocean Regional Projection 2km model for Japan (FORP-JPN02; Nishikawa et al., 2021), which features future projections under various Representative Concentration Pathway (RCP) emission scenarios based on climate prediction models such as the MRI-CGCM3 (Meteorological Research Institute (MRI), Japan Meteorological Agency (JMA)). Values of pH and aragonite saturation state (Ωarag), indicators of ocean acidification, are estimated using CO2SYS (Pierrot et al., 2006) from temperature, salinity, total alkalinity (TA), and dissolved inorganic carbon (DIC) values obtained from model outputs.
Preliminary comparisons with limited observations show that the model setup is able to realistically simulate physical and biogeochemical parameters. However, as the model domain features a relatively dynamic area at the intersection of three of the largest islands in Japan, additional comparisons with observations at various locations are needed to further evaluate model performance and make necessary modifications. With further development, the model setup can potentially be used to help determine which mitigation measures will be most appropriate to address ocean acidification concerns in the area.
The CROCO modeling system (ver. 1.3.1; Jullien et al., 2022), which is capable of coupling the ROMS ocean model (Shchepetkin and McWilliams, 2005) with the marine biogeochemical model PISCES-v2 (Aumont et al., 2015), was selected. The current model setup features a horizontal grid resolution of 1.5 km, with initial and boundary forcing of physical parameters derived from the Japan Coastal Ocean Predictability Experiment reanalysis dataset (JCOPE2M; Miyazawa et al., 2017). Biogeochemical forcing is derived by combining data from seasonal spatial monitoring, the World Ocean Atlas 2009 (WOA 2009), and literature-based approximations. Inputs from major rivers are also included, which were derived from available seasonal or monthly monitoring datasets. To run future projections, a candidate dataset for deriving model forcing is the Future Ocean Regional Projection 2km model for Japan (FORP-JPN02; Nishikawa et al., 2021), which features future projections under various Representative Concentration Pathway (RCP) emission scenarios based on climate prediction models such as the MRI-CGCM3 (Meteorological Research Institute (MRI), Japan Meteorological Agency (JMA)). Values of pH and aragonite saturation state (Ωarag), indicators of ocean acidification, are estimated using CO2SYS (Pierrot et al., 2006) from temperature, salinity, total alkalinity (TA), and dissolved inorganic carbon (DIC) values obtained from model outputs.
Preliminary comparisons with limited observations show that the model setup is able to realistically simulate physical and biogeochemical parameters. However, as the model domain features a relatively dynamic area at the intersection of three of the largest islands in Japan, additional comparisons with observations at various locations are needed to further evaluate model performance and make necessary modifications. With further development, the model setup can potentially be used to help determine which mitigation measures will be most appropriate to address ocean acidification concerns in the area.