4:30 PM - 4:45 PM
[AOS21-11] Numerical forecast simulation of the occurrence of hypoxic water mass in Ariake Sea, Japan.
Keywords:Hypoxic water mass, Heavy rain, Ariake Sea, Ecosystem model
The numerical model is based on the unstructured grid ocean model FVCOM (Finite Volume Community Ocean Model, Chen et al., 2006) and a numerical ecosystem model (Yamaguchi and Hayami, 2018), with Dreams_Ep (Hirose et al., 2005) for open boundary conditions, the rainfall-runoff-inundation model (Sayama and Iwami, 2014) for freshwater input, and analysis rain, short-range rain forecast, mesoscale model (MSM), and global spectral model (GSM (Japan region)) by Japan Meteorological Agency for meteorological conditions.
On July 29, 2024, we investigated the occurrence of hypoxic water masses in collaboration with relevant institutions (for a summary of the survey, see Tokunaga et al. (2024)) and confirmed the occurrence of large-scale hypoxic water masses. This study, targeting this hypoxia, performed hindcast simulation (HC) and forecast simulation (FC) from 6 day to 1 day prior to the survey date, using the results of the HC as the initial condition.
Although the HC calculated lower DO concentrations in the tidal-flat area than observed values, it succeeded in reproducing the occurrence of a severe hypoxic water mass (minimum DO concentration below 1.0 mg/l) on July 29, 2024 extending from the inner Ariake Sea to Isahaya Bay. According to the HC results, this hypoxia developed within one week. Hypoxia was formed under a strong halocline due to an increase in river water volume. It was shown that FC with HC result as the initial condition could predict the occurrence from 1 day to 5 days in advance. However, in 6-day prediction, the accuracy of predicting the DO concentration was reduced and the predicted hypoxic water masses became smaller in size than observed, because overestimation of wind strength forecast by GSM collapsed density stratification, especially in shallow water areas. It was suggested that in order to make longer-period prediction, it will be necessary to reconsider the weather forecast values given to FC.