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<p>This study investigates observation error adjustment strategies for three recent Global Navigation Satellite System Radio Occultation (GNSS RO) datasets (GRACE-D, Sentinel-6&#xa0;A, and SPIRE) within the Korean Integrated Model (KIM), aiming to mitigate forecast degradation of mid-tropospheric geopotential height. Experiments were conducted using a low-resolution KIM (July-August 2022), with verification against European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) analyses. The standard GNSS RO error model (20% observation error at the surface and 1% at 10&#xa0;km) was used as the control (EXP_ctl). Two adjustment strategies were tested: EXP_zfrac, which increased the lowest-level error to 40%, thereby reducing the influence below 10&#xa0;km; and EXP_obserr, which applied a uniform inflation factor (√2, from 2.2 to 3.1) across all levels to account for doubled observation counts. Relative to the Baseline, EXP_ctl degraded the global 500&#xa0;hPa geopotential height analysis by 4.01%, while EXP_zfrac and EXP_obserr improved performance by 2.01% and 2.28%, respectively. For 5-day forecasts of Northern Hemisphere 500&#xa0;hPa geopotential height, EXP_ctl degraded performance by 0.11%, while EXP_zfrac and EXP_obserr demonstrated improvements of 0.74% and 0.99%, respectively. These findings demonstrate that uniform observation error inflation, which reflects increased data density, is more effective for KIM than selective layer-specific error adjustments.</p>

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A Study on the Adjustment of Global Navigation Satellite System Radio Occultation Observation Errors to Improve KIM Forecast Performance

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月29日

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  • Eun-Hee Kim,
  • Hyoung-Wook Chun,
  • Jiyoung Son,
  • Yong Hee Lee

摘要

This study investigates observation error adjustment strategies for three recent Global Navigation Satellite System Radio Occultation (GNSS RO) datasets (GRACE-D, Sentinel-6 A, and SPIRE) within the Korean Integrated Model (KIM), aiming to mitigate forecast degradation of mid-tropospheric geopotential height. Experiments were conducted using a low-resolution KIM (July-August 2022), with verification against European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) analyses. The standard GNSS RO error model (20% observation error at the surface and 1% at 10 km) was used as the control (EXP_ctl). Two adjustment strategies were tested: EXP_zfrac, which increased the lowest-level error to 40%, thereby reducing the influence below 10 km; and EXP_obserr, which applied a uniform inflation factor (√2, from 2.2 to 3.1) across all levels to account for doubled observation counts. Relative to the Baseline, EXP_ctl degraded the global 500 hPa geopotential height analysis by 4.01%, while EXP_zfrac and EXP_obserr improved performance by 2.01% and 2.28%, respectively. For 5-day forecasts of Northern Hemisphere 500 hPa geopotential height, EXP_ctl degraded performance by 0.11%, while EXP_zfrac and EXP_obserr demonstrated improvements of 0.74% and 0.99%, respectively. These findings demonstrate that uniform observation error inflation, which reflects increased data density, is more effective for KIM than selective layer-specific error adjustments.