11:45 AM - 12:00 PM
[MGI24-10] Deterministic and ensemble forecasts of Kuroshio south of Japan
Keywords:Ocean data assimilation, Ensemble Kalman filter, Deterministic forecast, Ensemble forecast, Kuroshio, Predictability
Kuroshio flows eastward along the southern coast of Japan and has a variety of flow paths such as straight and large meander paths south of Japan at an interannual–decadal timescale. The Kuroshio path variations cause substantial damage to the fisheries, marine transport, and marine environment (e.g., Nakata et al. 2000; Barreto et al. 2021). Consequently, Japanese research institutions have conducted Kuroshio path predictions using regional ocean data assimilation systems with the Kalman filter (Hirose et al. 2013) and the three- and four-dimensional variational methods (Miyazawa et al. 2017; Kuroda et al. 2017; Hirose et al. 2019). However, these data assimilation methods are not designed for ensemble forecasts, and the predictions have been limited to deterministic ones so far.
We have developed a new local ensemble transform Kalman filter (LETKF)-based regional ocean data assimilation system (Ohishi et al. 2022a, b) and released ensemble ocean analysis datasets called the LETKF-based Ocean Research Analysis (LORA) for the western North Pacific and Maritime Continent regions (Ohishi et al. 2023). The LORA datasets are shown to have sufficient accuracy for geoscience research, especially in the mid-latitude regions (Ohishi et al. 2023), and therefore, we can perform both deterministic and ensemble forecasts initialized by the LORA. This study aims to compare the predictability of the Kuroshio path south of Japan between deterministic and ensemble forecasts.
We performed 6-month deterministic and ensemble forecasts initialized every month on the first day from January 2016–December 2018 (total 36 cases) using the initial conditions of the analysis ensemble mean and 128 analysis ensembles from the LORA dataset, respectively. The results show that the predictability ranges of the Kuroshio path are about 100–110 and 130–140 days in the deterministic and ensemble forecasts, respectively, indicating a significantly longer predictability range of the ensemble forecasts than the deterministic forecasts.
We have developed a new local ensemble transform Kalman filter (LETKF)-based regional ocean data assimilation system (Ohishi et al. 2022a, b) and released ensemble ocean analysis datasets called the LETKF-based Ocean Research Analysis (LORA) for the western North Pacific and Maritime Continent regions (Ohishi et al. 2023). The LORA datasets are shown to have sufficient accuracy for geoscience research, especially in the mid-latitude regions (Ohishi et al. 2023), and therefore, we can perform both deterministic and ensemble forecasts initialized by the LORA. This study aims to compare the predictability of the Kuroshio path south of Japan between deterministic and ensemble forecasts.
We performed 6-month deterministic and ensemble forecasts initialized every month on the first day from January 2016–December 2018 (total 36 cases) using the initial conditions of the analysis ensemble mean and 128 analysis ensembles from the LORA dataset, respectively. The results show that the predictability ranges of the Kuroshio path are about 100–110 and 130–140 days in the deterministic and ensemble forecasts, respectively, indicating a significantly longer predictability range of the ensemble forecasts than the deterministic forecasts.