Abstract
Variations in the initial structure of tropical cyclones (TCs) inevitably affect prediction results; however, the bogus model cannot accurately describe the structure of a weak tropical cyclone with increased initial field resolution. This study aims to construct a model to improve the prediction of weak TC in southern China. Based on the ECMWF 0.1° analysis data, several vortices were filtered out from tropical depressions and tropical storms in 2018 and 2019 to represent a weak TC reservoir in the South China Sea. For different simulation objects, filtered vortices were combined with the TC environmental field to form ensemble members. The observed TC information was assimilated for simulating TCs Bebinca, Mun, and Ewiniar to verify the feasibility of the proposed model, based on the Global/Regional Assimilation and Prediction Enhanced System (GRAPES) 9-km model developed by the Guangzhou Institute of Tropical and Marine Meteorology. The results show that the initialization scheme of the weak tropical cyclone model improved the intensity prediction of the TC by 26.81% (Bebinca), 18.65% (Mun), and 47.00% (Ewiniar), compared with the control experiment. Because typhoon intensity forecasting has not notably improved for many years, this scheme has certain scientific and operational significance.
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References
Huang, Y. Y., and B. Zheng, 2020: Tropical cyclone structure in the South China Sea based on high-resolution reanalysis data and comparison with that of ‘bogus’ vortices. Dyn. Atmos. Oceans, 89, 101128, doi: https://doi.org/10.1016/j.dynatmoce.2019.101128.
Huang, Y. Y., Z. T. Chen, G. F. Dai, et al., 2016: Investigation on effects of initial schemes for binary Typhoons Roke and Sonca in 2011. J. Trop. Meteor., 22, 1–14, doi: https://doi.org/10.16555/j.1006-8775.2016.S1.001.
Huang, Y. Y., J. S. Xue, Y. R. Feng, et al., 2018: An initialization scheme using forecast vortexes and its application in simulation of Typhoons Linfa and Chan-hom in 2015. J. Trop. Meteor., 34, 598–609, doi: https://doi.org/10.16032/j.issn.1004-4965.2018.05.003. (in Chinese)
Jin, S. L., S. H. Wu, Z. Q. Liu, et al., 2018: Regional discrepancies of the impact of tropical Indian Ocean warming on northwest Pacific tropical cyclone frequency in the years of decaying El Niño. J. Trop. Meteor., 24, 314–322, doi: https://doi.org/10.16555/j.1006-8775.2018.03.005.
Kurihara, Y., M. A. Bender, R. E. Tuleya, et al., 1995: Improvements in the GFDL hurricane prediction system. Mon. Wea. Rev., 123, 2791–2801, doi: https://doi.org/10.1175/1520-0493(1995)123<2791:IITGHP>2.0.CO;2.
Li, J. H., Y. Y. Huang, and Q. L. Wan, 2018a: Comparative analysis of tropical cyclone’s structure between ECMWF high resolution reanalysis data and Bogus model in 2015. J. Trop. Meteor., 34, 48–58, doi: https://doi.org/10.16032/j.issn.1004-4965.2018.01.005. (in Chinese)
Li, J. H., Y. D. Gao, and Q. L. Wan, 2018b: Sample optimization of ensemble forecast to simulate a tropical cyclone using the observed track. Atmosphere-Ocean, 56, 162–177, doi: https://doi.org/10.1080/07055900.2018.1500881.
Li, J. H., Q. L. Wan, Y. D. Gao, et al., 2018c: The effect of sample optimization on the ensemble Kalman filter in forecasting Typhoon Rammasun (2014). J. Trop. Meteor., 24, 433–447, doi: https://doi.org/10.16555/j.1006-8775.2018.04.003.
Meng, Z. Y., and F. Q. Zhang, 2008a: Tests of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part III: Comparison with 3DVAR in a real-data case study. Mon. Wea. Rev., 136, 522–540, doi: https://doi.org/10.1175/2007MWR2106.1.
Meng, Z. Y., and F. Q. Zhang, 2008b: Tests of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part IV: Comparison with 3DVAR in a month-long experiment. Mon. Wea. Rev., 136, 3671–3682, doi: https://doi.org/10.1175/2008MWR2270.1.
Xu, D. S., B. L. Zhang, Q. C. Zeng, et al., 2019: A typhoon initialization scheme based on incremental analysis updates technology. Acta Meteor. Sinica, 77, 1053–1061, doi: https://doi.org/10.11676/qxxb2019.060. (in Chinese)
Yuan, J. N., L. L. Song, Y. Y. Huang, et al., 2011: A method of initial vortex relocation and numerical simulation experiments on tropical cyclone track. J. Trop. Meteor., 17, 36–42.
Zhang, F., C. Snyder, and J. Z. Sun, 2004: Impacts of initial estimate and observation availability on convective-scale data assimilation with an ensemble Kalman filter. Mon. Wea. Rev., 132, 1238–1253, doi: https://doi.org/10.1175/1520-0493(2004)132<1238:IOIEAO>2.0.CO;2.
Zhu, L., Q. L. Wan, X. Y. Shen, et al., 2016: Prediction and predictability of high-impact western Pacific landfalling Tropical Cyclone Vicente (2012) through convection-permitting ensemble assimilation of Doppler radar velocity. Mon. Wea. Rev., 144, 21–13, doi: https://doi.org/10.1175/MWR-D-14-00403.1.
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Supported by the National Key Research and Development Program of China (2018YFC1507602), Science and Technology Planning Project of Guangdong Province (2017B020244002 and 2018B020208004), Natural Science Foundation of Guangdong Province (2019A1515011118), and National Natural Science Foundation of China (41705089).
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Li, J., Wan, Q., Xu, D. et al. An Initialization Scheme for Weak Tropical Cyclones in the South China Sea. J Meteorol Res 35, 358–370 (2021). https://doi.org/10.1007/s13351-021-0069-3
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DOI: https://doi.org/10.1007/s13351-021-0069-3