The FORMOSAT-7/COSMIC-2 Global Navigation Satellite System (GNSS) Radio Occultation (RO) satellite constellation was launched in June 2019 as a successor of the FORMOSAT-3/COSMIC mission. The Central Weather Bureau (CWB) of Taiwan has received FORMOSAT-7/COSMIC-2 GNSS RO data in real time from the Taiwan Analysis Center for COSMIC. With the global numerical prediction system at CWB, a parallel semioperational experiment assimilating the FORMOSAT-7/COSMIC-2 bending angle data with all other operational observation data has been conducted to evaluate the impact of the FORMOSAT-7/COSMIC-2 data. The first seven-month results show that the quality of the early FORMOSAT-7/COSMIC-2 data has been satisfactory for assimilation. Consistent and significant positive impacts on global forecast skills have been observed since the start of the parallel experiment, with the most significant impact found in the tropical region, reflecting the low-inclination orbital design of the satellites. The impact of the FORMOSAT-7/COSMIC-2 RO data is also estimated using the ensemble forecast sensitivity to observation impact (EFSOI) method, showing an average positive impact per observation similar to other existing GNSSROdatasets, while the total impact is impressive by virtue of its large amount. Sensitivity experiments suggest that the quality control processes built in the Gridpoint Statistical Interpolation (GSI) system for RO data work well to achieve a positive impact by the lowlevel FORMOSAT-7/COSMIC-2 RO data, while more effort on observation error tuning should be focused to obtain an optimal assimilation performance. This study demonstrates the usefulness of the FORMOSAT-7/COSMIC-2 RO data in global numerical weather prediction during the calibration/validation period and leads to the operational use of the data at CWB.
CITATION STYLE
Lien, G. Y., Lin, C. H., Huang, Z. M., Teng, W. H., Chen, J. H., Lin, C. C., … Huang, C. Y. (2021, July 1). Assimilation impact of early formosat-7/cosmic-2 gnss radio occultation data with taiwan s cwb global forecast system. Monthly Weather Review. American Meteorological Society. https://doi.org/10.1175/MWR-D-20-0267.1
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