LETKF-based Ocean Research Analysis version 2.0 for a quasi-global domain (LORA-QG): validation and intercomparison with eddy-permitting global ocean reanalysis datasets

Ohishi, Shun; Miyoshi, Takemasa; Kachi, Misako

doi:10.5194/os-22-2915-2026

Articles | Volume 22, issue 5

https://doi.org/10.5194/os-22-2915-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Evaluation of ocean reanalyses to meet users’ needs

https://doi.org/10.5194/os-22-2915-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 5

Research article

|

25 Sep 2026

Research article |

| 25 Sep 2026

LETKF-based Ocean Research Analysis version 2.0 for a quasi-global domain (LORA-QG): validation and intercomparison with eddy-permitting global ocean reanalysis datasets

Shun Ohishi, Takemasa Miyoshi, and Misako Kachi

Data sets

Global Ocean Along Track L3 Sea Surface Heights Reprocessed 1993 Ongoing Tailored For Data Assimilation E.U. Copernicus Marine Service Information (CMEMS) https://doi.org/10.48670/moi-00146

Global Ocean Ensemble Physics Reanalysis E.U. Copernicus Marine Service Information (CMEMS) https://doi.org/10.48670/moi-00024

Model code and software

shunohishi/sbPOM_LETKF_v2: sbPOM-LETKF v2.0 (Version v2.0) [Computer software] S. Ohishi and N. Sakai https://doi.org/10.5281/zenodo.19229782

Short summary

We developed an eddy-permitting local ensemble Kalman filter (LETKF)-based Ocean Research Analysis (LORA) version 2.0 for a quasi-global domain (LORA-QG) covering the period from June 2002 onward. Validation shows that LORA-QG achieves accuracy comparable to existing global ocean reanalysis datasets. LORA-QG includes ensemble-based uncertainty estimates and individual terms of the heat and salinity budget equations, making it a valuable resource for ocean forecasting and process-based studies.