Method to Improve the Equatorial Components of Effective Angular Momentum Forecasts Based on Real Environments
Abstract The findings from the Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC) suggest that integrating effective angular momentum (EAM) is vital for enhancing the accuracy of polar motion (PM) predictions. Building on Dill et al. (2021), https://doi.org/10.1029/2021...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Geophysical Union (AGU)
2025-06-01
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| Series: | Earth and Space Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2024EA004174 |
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| Summary: | Abstract The findings from the Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC) suggest that integrating effective angular momentum (EAM) is vital for enhancing the accuracy of polar motion (PM) predictions. Building on Dill et al. (2021), https://doi.org/10.1029/2021ea002070, who identified systematic errors in the motion terms of atmospheric angular momentum (AAM), we discovered additional systematic errors in mass and motion terms of forecasts for the AAM, oceanic angular momentum (OAM) and hydrologic angular momentum (HAM), and promptly implemented corrections following their updates. During the hindcast experiment period from 20/5/2021 to 31/12/2023, and in the first three days in the X and Y directions, the proposed method showed advantages over the Helmholtz‐Centre Potsdam—German Research Centre for Geosciences (GFZ) and Eidgenössische Technische Hochschule Zürich (ETH Zürich). Then, the corrected EAM forecasts and reference values were used in the PM forecasting experiments, which showed no improvement, likely due to the existing PM forecasting system and overcompensation. However, when employing the perfect analysis of GEAM (the difference between geodesic angular momentum (GAM) and EAM), the proposed method herein achieves a maximum improvement of 30.0% and 55.5% in the X direction and 8.4% and 48.4% in the Y direction, compared to the official EAM forecasts of GFZ and ETH Zürich. This fully demonstrates that improvements in both EAM and GEAM are essential for enhancing PM predictions, and the EAM forecasts corrected by the proposed method are more competitive than those of GFZ and ETH Zürich. |
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| ISSN: | 2333-5084 |