Tropical Cyclogenesis in the Western North Pacific Improved by GNSS RO Data Assimilation Using Hybrid 3DEnVar with a Nonlocal Excess Phase Operator.
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| Title: | Tropical Cyclogenesis in the Western North Pacific Improved by GNSS RO Data Assimilation Using Hybrid 3DEnVar with a Nonlocal Excess Phase Operator. |
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| Authors: | Pham Xuan, Quan1 (AUTHOR), Chen, Shu-Ya1 (AUTHOR) shuyachen@ncu.edu.tw, Huang, Ching-Yuang1,2 (AUTHOR), Kuo, Ying-Hwa3 (AUTHOR) |
| Source: | Weather & Forecasting. Nov2025, Vol. 40 Issue 11, p2255-2271. 17p. |
| Subjects: | Cyclone forecasting, Data assimilation, Global Positioning System, Atmospheric boundary layer, Tropical storms, Water vapor, Forecasting methodology |
| Geographic Terms: | North Pacific Ocean |
| Abstract: | Accurate tropical cyclogenesis predictions are crucial for typhoon forecasting and disaster mitigation. Satellite observations are valuable for improving tropical cyclogenesis over the ocean, where there are few traditional radiosonde observations. Global Navigation Satellite System (GNSS) Radio Occultation (RO) data, mostly from Formosa Satellite mission-7/Constellation Observing System for the Meteorology, Ionosphere, and Climate mission-2 (FORMOSAT-7/COSMIC-2), provide extensive coverage of tropical regions with valuable atmospheric boundary layer information due to its deep penetration into the lower tropical troposphere. This study assessed the impact of GNSS RO data assimilation (DA) on the predictions of tropical cyclogenesis using 10 typhoon cases in the western North Pacific from 2020 to 2022. Conventional data and GNSS RO data were assimilated for each case using the WRF hybrid 3D ensemble-variational data assimilation (3DEnVar) system. The results show that including RO data with the nonlocal excess phase operator considerably improves the accuracy of cyclogenesis predictions in terms of both location and timing. Detailed case studies for Typhoons Chanthu (2021) and Hagupit (2020) reveal enhanced midtropospheric moisture by RO data assimilation, highlighting the important role of water vapor in tropical cyclogenesis. Although satellite radiances are also assimilated for both typhoons, the impacts of RO data are still evident in providing improved initial conditions that are more favorable for capturing genesis. For ensemble forecasts, more ensemble members successfully detect Chanthu's genesis and give a higher probability of detection for Typhoon Hagupit when RO data are included. The positive ensemble impacts highlight the fact that the RO data with the nonlocal operator may give steady improvement for operational forecasting of tropical cyclogenesis. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Accurate tropical cyclogenesis predictions are crucial for typhoon forecasting and disaster mitigation. Satellite observations are valuable for improving tropical cyclogenesis over the ocean, where there are few traditional radiosonde observations. Global Navigation Satellite System (GNSS) Radio Occultation (RO) data, mostly from Formosa Satellite mission-7/Constellation Observing System for the Meteorology, Ionosphere, and Climate mission-2 (FORMOSAT-7/COSMIC-2), provide extensive coverage of tropical regions with valuable atmospheric boundary layer information due to its deep penetration into the lower tropical troposphere. This study assessed the impact of GNSS RO data assimilation (DA) on the predictions of tropical cyclogenesis using 10 typhoon cases in the western North Pacific from 2020 to 2022. Conventional data and GNSS RO data were assimilated for each case using the WRF hybrid 3D ensemble-variational data assimilation (3DEnVar) system. The results show that including RO data with the nonlocal excess phase operator considerably improves the accuracy of cyclogenesis predictions in terms of both location and timing. Detailed case studies for Typhoons Chanthu (2021) and Hagupit (2020) reveal enhanced midtropospheric moisture by RO data assimilation, highlighting the important role of water vapor in tropical cyclogenesis. Although satellite radiances are also assimilated for both typhoons, the impacts of RO data are still evident in providing improved initial conditions that are more favorable for capturing genesis. For ensemble forecasts, more ensemble members successfully detect Chanthu's genesis and give a higher probability of detection for Typhoon Hagupit when RO data are included. The positive ensemble impacts highlight the fact that the RO data with the nonlocal operator may give steady improvement for operational forecasting of tropical cyclogenesis. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 08828156 |
| DOI: | 10.1175/WAF-D-25-0010.1 |
