福爾摩沙衛星七號(福衛七號)於 2019 年 6 月發射，並能提供一天超過 6000多筆的無線電掩星(RO)觀測資料，其中 RO 偏折角能夠使用 NCEP 偏折角反演法以及 Abel 轉換兩種技術，將偏折角反演成大氣剖面資訊如氣壓、氣溫以及水氣等等。本研究旨在使用氣象局的全球模式 TGFS 探討福衛七號 RO 觀測資料對於颱風預報的影響，模式解析度約為 25 公里，並選擇了 7 個颱風個案進行 83 組預報。每組預報分為兩個敏感度實驗，即包含福衛七號偏折角同化的實驗（WB）和不包含福衛七號偏折角同化的實驗（NB）。同化策略採用 GSI 的 Hybrid 4DEnVar 方法，首先進行 NB 實驗的同化循環，直到颱風生成前四天。在此時間點，將實驗分為 WB 和 NB 兩個敏感度實驗，每六小時執行一次同化，同化各自的觀測資料。在颱風生成後，進行每六小時一次的 120 小時長期預報，同時持續進行各自實驗的同化循環。統計結果顯示，在 83 個預報中，WB 在路徑誤差整體表現上較 NB 差，直到 60 小時後 WB 的強度誤差才低於 NB，此結果與先前針對 5 個颱風個案、42組預報的研究結果相反。梅花颱風個案分析中的掩星偏折角校驗結果顯示，三組實驗的趨勢基本相似，高層的掩星偏折角偏差較小，底層偏差較大，剃除 4 公里以下福衛七號資料後，路徑誤差在前期與 NB 結果差異不大，到後半段誤差則急劇增加。在全球校驗方面，NB 和 WB 在 U、V 分量風以及溫度場的表現呈現好壞交錯。然而，在水氣方面，WB 在對流層有明顯的改善，尤其在北半球改善效果最為明顯。
綜合而言，本研究結果顯示同化福衛七號掩星觀測對於颱風預報的正面影響
並不明顯。這可能與福衛七號在同化過程中存在的一些限制有關，尤其是與低層觀測的不確定性相關。

The FORMOSAT-7 (FS7) satellite, which was launched in 2019, has the capability to provide over 6000 Radio Occultation (RO) observation profiles per day. To conduct
our analysis, we employed the CWB's Taiwan Global Forecast System (TGFS) numerical weather prediction model, which features a fine grid resolution of 25 km. We simulated 7 Typhoon cases, consisting of 83 individual runs between 2021 and 2022. For each case, we conducted two experiments: one utilizing the FS7 RO bending angle data (WB), and the other without it (NB).To assimilate the RO bending angle data, we
employed the GSI hybrid 4DEnVar data assimilation system. The assimilation process spins up for 4 days. This was followed by a 120-hour forecast.The statistical analysis of the total 83 runs reveals that the assimilation of FS7 RO
bending angle data leads to a degradation in track forecast performance, with a slight positive impact on intensity forecast after 60-hour.The case study of Muifa exhibited a
similar overall trend in track and intensity errors as observed in the overall statistical
results. However, it demonstrated a more substantial improvement in intensity forecast beyond the 60-hour threshold. Additionally, we observed that the Root Mean Square Errors (RMSEs) of U, V, and T variables were comparable between the WB and NB. Notably, WB exhibited a notable positive impact on water vapor for each atmospheric layer. Despite the abundance of available FS7 RO data on a daily basis, the positive impact on Typhoon forecasting seems to be implicit. This could be attributed to the
limited utilization of FS7 RO data, primarily influenced by observation errors in the lower levels of the atmosphere.

Barker, D., W. Huang, Y.-R. Guo, and A. Bourgeois, 2003: A three-dimensional
variational (3DVAR) data assimilation system for use with MM5. NCAR Technical
Note NCAR/TN-453+STR, 68 pp.
Barker, D., W. Huang, Y.-R. Guo, A. J. Bourgeois, and Q. N. Xiao, 2004: A threedimensional variational data assimilation system for MM5: Implementation and
initial results. Mon. Wea. Rev., 132, 897–914.
Born, M.; Wolf, E. Principles of Optics, 6th ed.; Pergamon: Oxford, UK, 1980; p. 808
Chen,S.Y., Huang, C. Y., Kuo, Y. H., Guo, Y. R., & Sokolovskiy, S. (2009). Assimilation
of GPS refractivity from FORMOSAT-3/COSMIC using a nonlocal operator with
WRF 3DVAR and its impact on the prediction of a Typhoon event. Terrestrial,
Atmospheric and Oceanic Sciences, 20(1), 133-
154. https://doi.org/10.3319/TAO.2007.11.29.01(F3C)
Chen, Y.-C., Hsieh, M.-E., Hsiao, L.-F., Kuo, Y.-H., Yang, M.-J., Huang, C.-Y., and Lee,
C.-S.: Systematic evaluation of the impacts of GPSRO data on the prediction of
Typhoons over the northwestern Pacific in 2008–2010, Atmos. Meas. Tech. 2015,
8, 2531–2542, https://doi.org/10.5194/amt-8-2531-2015, 2015.
Chen, J.-H., S.-J. Lin, L.-J. Zhou, X. Chen, S. Rees, M. Bender, M. Morin, 2019:
Evaluation of tropical cyclone forecasts in the next generation global prediction
system. Mon. Wea. Rev., 147, 3409–3428.
Chen, S., Y. Kuo, and C. Huang, 2020: The impact of GPS RO data on the prediction
of tropical cyclogenesis using a nonlocal observation operator: An initial
assessment. Mon. Wea. Rev., 148, 2701–2717, https://doi.org/10.1175/MWR-D19-0286.1.
Chen, S., C. Shih, C. Huang, and W. Teng, 2021: An impact study of GNSS RO data on
the prediction of Typhoon Nepartak (2016) using a multiresolution global model
with 3D-Hybrid data assimilation. Wea. Forecasting, 36, 957–
977, https://doi.org/10.1175/WAF-D-20-0175.1.
Chen, Y.-J.; Hong, J.-S.; Chen, W.-J. Impact of assimilating FORMOSAT-7/COSMIC2 radio occultation data on Typhoon prediction using a regional model.
Atmosphere 2022, 13, 1879. https:// doi.org/10.3390/atmos13111879
Chien, T.-Y.; Chen, S.-Y.; Huang, C.-Y.; Shih, C.-P.; Schwartz, C.S.; Liu, Z.; Bresch, J.;
Lin, J.-Y. Impacts of radio occultation data on Typhoon forecasts as explored by
the global MPAS-GSI System. Atmosphere 2022, 13, 1353. https://
doi.org/10.3390/atmos13091353
39
Chu, C.-H., C.-Y. Huang, C.-J. Fong, S.-Y. Chen, Y.-H. Chen, W.-H. Yeh, and Y.-H.
Kuo, 2021: Atmospheric remote sensing using global navigation satellite systems:
from FORMOSAT-3/COSMIC to FORMOSAT-7/COSMIC-2. Terr. Atmos. Ocean.
Sci., 32, 1001-1013, doi: 10.3319/TAO.2021.11.15.02
Cucurull, L. Improvement in the use of an operational constellation of GPS radio
occultation receivers in weather forecasting. Weather Forecast. 2010, 25, 749–767.
Cucurull, L.; Derber, J.; Purser, R. A bending angle forward operator for global
positioning system radio occultation measurements. J. Geophys. Res. Atmos. 2013,
118, 14–28.
Cucurull, L.; Derber, J.; Treadon, R.; Purser, R. Assimilation of global positioning
system radio occultation observations into NCEP’s global data assimilation
system. Month. Weather Rev. 2007, 135, 3174–3193.
Huang, C., Y. Kuo, S. Chen, and F. Vandenberghe, 2005: Improvements in Typhoon
forecasts with assimilated GPS occultation refractivity. Wea. Forecasting, 20,
931–953, https://doi.org/10.1175/WAF874.1.
Huang, C., S. Chen, S. K. A. V. P. Rao Anisetty, S. Yang, and L. Hsiao, 2016: An impact
study of GPS radio occultation observations on frontal rainfall prediction with a
local bending angle operator. Wea. Forecasting, 31, 129–
150, https://doi.org/10.1175/WAF-D-15-0085.1.
Huang, C., T. Juan, H. Kuo, and J. Chen, 2020: Track deflection of Typhoon Maria
(2018) during a westbound passage offshore of northern Taiwan: Topographic
influence. Mon. Wea. Rev., 148, 4519–4544, https://doi.org/10.1175/MWR-D-20-
0117.1.
Huang, B., X. Wang, D. T. Kleist, and T. Lei, 2021: A simultaneous multiscale data
assimilation using scale-dependent localization in GSI-based hybrid 4DEnVar for
NCEP FV3-Based GFS. Mon. Wea. Rev., 149, 479–
501,https://doi.org/10.1175/MWR-D-20-0166.1
Huang, C., S. Sha, and H. Kuo, 2022: A modeling study of Typhoon Lekima (2019)
with the topographic influence of Taiwan. Mon. Wea. Rev., 150, 1993–
2011, https://doi.org/10.1175/MWR-D-21-0183.1.
Hazelton, A. T, M. Bender, M. Morin, L. Harris, S.-J. Lin, 2018a: 2017 Atlantic
hurricane forecasts from a high-resolution version of the GFDL fvGFS model:
evaluation of track, intensity, and structure. Wea. Forecasting, 33, 1317–1337.
Hazelton, A. T., L. Harris, S. J. Lin, 2018b: Evaluation of tropical cyclone structure
forecasts in a high-resolution version of the multiscale GFDL fvGFS model. Wea.
Forecasting, 33, 419–442.
40
Hong T-X, Huang C-Y, Lin C-Y, Lien G-Y, Huang Z-M, Chen S-Y. Impacts of GNSS
RO data on Typhoon forecasts using global FV3GFS with GSI
4DEnVar. Atmosphere. 2023; 14(4):735. https://doi.org/10.3390/atmos14040735
Ho, S.-P.; Zhou, X.; Shao, X.; Zhang, B.; Adhikari, L.; Kireev, S.; He, Y.; Yoe, J.G.;
Xia-Serafino, W.; Lynch, E. Initial assessment of the COSMIC-2/FORMOSAT-7
neutral atmosphere data quality in NESDIS/STAR using in situ and satellite
data. Remote Sens. 2020, 12, 4099. https://doi.org/10.3390/rs12244099
Hamill, T.M.; Snyder, C. A hybrid ensemble Kalman filter–3D variational analysis
scheme. Mon. Weather. Rev. 2000, 128, 2905–2919.
Kleist, D.T.; Ide, K. An OSSE-based evaluation of hybrid variational–ensemble data
assimilation for the NCEP GFS. Part II: 4DEnVar and hybrid variants. Mon.
Weather. Rev. 2015, 143, 452–470.
Lien, G., and Coauthors, 2021: Assimilation impact of early FORMOSAT-7/COSMIC2 GNSS radio occultation data with Taiwan’s CWB global forecast system. Mon.
Wea. Rev., 149, 2171–2191, https://doi.org/10.1175/MWR-D-20-0267.1
Lin, Y.-L., R. D. Farley, and H. D. Orville, 1983: Bulk parameterization of the snow
field in a cloud model. J. Clim. Appl. Meteorol. 22, 1065–1092.
Lin, S.-J., and R. B. Rood, 1996: Multidimensional flux-form semi-Lagrangian
transport schemes. Mon. Wea. Rev., 124, 2046–2070.
Lin, S. J., 1997: A finite‐volume integration method for computing pressure gradient
force in general vertical coordinates. Quart. J. Roy. Meteor. Soc., 123, 1749– 1762.
Lin, S. J., and R. B. Rood, 1997: An explicit flux‐ form semi‐Lagrangian shallow‐ water
model on the sphere. Quart. J. Roy. Meteor. Soc., 123, 2477–2498. Lin, S.-J., 2004:
A “vertically Lagrangian” finite-volume dynamical core for global models. Mon.
Wea. Rev., 132, 2293–2307.
Lin, Y.-L., S.-Y. Chen, C. M. Hill, and C.-Y. Huang, 2005: Control parameters for the
influence of a mesoscale mountain range on cyclone track continuity and
deflection. J. Atmos. Sci., 62, 1849–1866.
Ruston, B, Healy, S. Forecast impact of FORMOSAT-7/COSMIC-2 GNSS radio
occultation measurements. Atmos Sci
Lett. 2021; 22:e1019. https://doi.org/10.1002/asl.1019
Schreiner, W. S., Weiss, J. P., Anthes, R. A., Braun, J., Chu, V., Fong, J., et al.
(2020). COSMIC-2 radio occultation constellation: First results. Geophysical
Research Letters, 47, e2019GL086841. https://doi.org/10.1029/2019GL086841
Wu, L., and B. Wang, 2000: A potential vorticity tendency diagnostic approach for
tropical cyclone motion. Mon. Wea. Rev., 128, 1899–
1911, https://doi.org/10.1175/1520-0493(2000)128<1899:APVTDA>2.0.CO;2.
41
Wang, X.; Lei, T. GSI-bsed four-dimensional ensemble–variational (4DEnsVar) data
assimilation: Formulation and single-resolution experiments with real data for
NCEP Global Forecast System. Mon. Weather. Rev. 2014, 142, 3303–3325.
Wang, X.; Barker, D.; Snyder, C.; Hamill, T.M. A hybrid ETKF-3DVAR data
assimilation scheme for the WRF model. Part I: Observing system simulation
experiment. Mon. Weather. Rev. 2008, 136, 5116–5131.
Wang, X.; Barker, D.; Snyder, C.; Hamill, T.M. A hybrid ETKF-3DVAR data
assimilation scheme for the WRF model. Part II: Real observation experiments.
Mon. Weather. Rev. 2008, 136, 5132–5147.
Wang, X.; Parrish, D.; Kleist, D.T.; Whitaker, J.S. GSI 3DVarbased ensemblevariational hybrid data assimilation for NCEP Global Forecast System: Singleresolution experiments. Mon. Weather. Rev. 2013, 141, 4098–4117.
Yang, S., S. Chen, S. Chen, C. Huang, and C. Chen, 2014: Evaluating the impact of the
COSMIC RO bending angle data on predicting the heavy precipitation episode on
16 June 2008 during SoWMEX-IOP8. Mon. Wea. Rev., 142, 4139–
4163, https://doi.org/10.1175/MWR-D-13-00275.1.
Zou, X., Y.-H. Kuo, and Y.-R. Guo, 1995: Assimilation of atmospheric radio refractivity
using a nonhydrostatic adjoint model. Mon. Wea. Rev., 123, 2229-2249.
Zou, X., B. Wang, H. Liu, R. A. Anthes, T. Matsumura, and Y.-J. Zhu, 2000: Use of
GPS/MET refraction angles in 3D variational analysis. Quart. J. Roy. Meteor. Soc.,
126, 3013-3040.
Zou, X., F. Vandenberghe, B. Wang, M. E. Gorbunov, Y.-H. Kuo, S. Sokolovskiy, J. C.
Chang, J. G. Sela, and R. Anthes, 1999: A raytracing operator and its adjoint for
the use of GPS/MET refraction angle measurements. J. Geophys. Res., 104,
22301-22318.
Zhang, H., Y. Kuo, and S. Sokolovskiy, 2023: Assimilation of radio occultation data
using measurement-based observation error specification: preliminary
results. Mon. Wea. Rev., 151, 589–601, https://doi.org/10.1175/MWR-D-22-
0122.1