Submitted as: development and technical paper
31 Mar 2022
Submitted as: development and technical paper | 31 Mar 2022
Status: this preprint is currently under review for the journal GMD.

An EnKF-based ocean data assimilation system improved by adaptive observation error inflation (AOEI)

Shun Ohishi1,2,3, Takemasa Miyoshi1,2,4, and Misako Kachi5 Shun Ohishi et al.
  • 1RIKEN Center for Computational Science, Kobe, 6500047, Japan
  • 2RIKEN Cluster for Pioneering Research, Kobe, 6500047, Japan
  • 3Institute for Space-Earth Environmental Research, Nagoya University, Nagoya, 4648601, Japan
  • 4RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS), Kobe, 6500047, Japan
  • 5Earth Observation Research Center, Japan Aerospace Exploration Agency, Tsukuba, 3058505, Japan

Abstract. A previous study proposed an adaptive observation error inflation (AOEI) method for an ensemble Kalman filter-based atmospheric data assimilation system to assimilate all-sky infrared brightness temperatures. Brightness temperature differences between clear- and cloudy-sky radiances are large, and observation-minus-forecast differences or innovations are therefore likely to be large around boundaries between clear- and cloudy-sky regions. The AOEI method mitigates these discrepancies by adaptively inflating observation errors. Ocean frontal regions have similar characteristics to the borders between clear- and cloudy-sky regions with large innovations. Consequently, we have implemented the AOEI with an EnKF-based regional ocean data assimilation system, in which the assimilation interval is set to 1 day to utilize frequent satellite observations. We conducted sensitivity experiments to investigate the impacts of the AOEI on salinity structure, geostrophic balance, and accuracy. A control run, in which the AOEI is not applied, shows the degradation of low-salinity North Pacific Intermediate Water around the Kuroshio Extension region, where the innovation amplitude and forecast ensemble spread are large in association with the fronts and eddies. The resulting large temperature and salinity increments weaken the density stratification, leading to large vertical diffusivity. As a result, the low salinity water in the intermediate layer is lost through strong vertical diffusion. When the AOEI is used, the salinity structure in the ocean interior is preserved because the AOEI suppresses the salinity degradation by reducing the temperature and salinity increments. We also demonstrate that the AOEI provides significant improvement of the geostrophic balance and the accuracy of temperature, salinity, and surface flow fields.

Shun Ohishi et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2022-91', Juan Antonio Añel, 25 Apr 2022
    • AC1: 'Reply on CEC1', Shun Ohishi, 28 Jun 2022
  • RC1: 'Comment on gmd-2022-91', Anonymous Referee #1, 05 May 2022
    • AC2: 'Reply on RC1', Shun Ohishi, 28 Jun 2022
  • RC2: 'Comment on gmd-2022-91', Anonymous Referee #2, 09 May 2022
    • AC3: 'Reply on RC2', Shun Ohishi, 28 Jun 2022

Shun Ohishi et al.

Shun Ohishi et al.


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Short summary
An adaptive observation error inflation (AOEI) method was proposed for atmospheric data assimilation to mitigate erroneous analysis updates caused by large observation-minus-forecast differences for satellite brightness temperature around clear- and cloudy-sky boundaries. This study implemented the AOEI with an ocean data assimilation system, leading to an improvement of analysis accuracy and dynamical balance around the frontal regions with large meridional temperature differences.