Data Assimilation Research Team Events / Media

Various ocean analysis products have been produced and used for geoscience research. In the Pacific region, four high-resolution regional analysis datasets are currently available: JCOPE2M (Miyazawa et al. 2017) and FRA-ROMS II (Kuroda et al. 2017) with 3D-VAR; NPR-4DVAR (Hirose et al. 2019) with 4D-VAR; and DREAMS with a Kalman filter (Hirose et al. 2013). However, to the best of the authors' knowledge, no EnKF-based analysis dataset exists.

Recently, geostationary satellites such as Himawari-8 and -9 have provided sea surface temperature (SST) data at high spatiotemporal resolution. To use these data effectively, we have developed an eddy-permitting EnKF-based ocean data assimilation system with a short assimilation interval of 1 day. Sensitivity experiments demonstrated that the combination of three schemes -incremental analysis update (IAU; Bloom et al. 1996), relaxation-to-prior perturbation (RTPP; Zhang et al. 2004), and adaptive observation error inflation (AOEI; Minamide and Zhang 2017)- significantly improved dynamical balance and accuracy of the analyses (Ohishi et al. 2022a, b).

With enhanced computational resources, we have further developed higher-resolution eddy-resolving ocean data assimilation systems and produced ensemble analysis products for the western North Pacific (WNP) and Maritime Continent (MC) regions, referred to as the LETKF-based Ocean Research Analysis (LORA)-WNP and -MC, respectively (Ohishi et al. 2023). Validation results indicated that the LORA has sufficient accuracy for geoscience research and various applications such as fisheries and marine transport. The LORA-WNP and -MC have been available on the JAXA-RIKEN Ocean Analysis website since March 2023 (https://www.eorc.jaxa.jp/ptree/LORA/index.html; Ohishi et al. 2024).

To utilize the uncertainty included in the LORA product, we compared between the deterministic and ensemble forecast experiments initialized with the analysis ensemble mean and 128-ensemble analyses. For the Kuroshio south of Japan, validation results showed that the predictability limit of the ensemble mean forecast is 100-110 days and approximately 1 month longer than that of the deterministic forecast (Ohishi et al. in prep.).