燕颱風是2013年相當有代表性的強烈颱風，在登陸時的強度超過五級颶風的強度，從這部分來看是歷史少有，根據聯合颱風警報中心(JTWC) 的資料顯示，海燕颱風於2013年11月7日1200 UTC達到最強的狀態，其一分鐘平均最大風速達到了170 knots，中心氣壓895hPa，此強度也已經達到五級颶風的標準，海燕颱風本身帶來的災害以登陸時帶來的風暴潮為主。
本研究使用名古屋大學開發的CReSS(Cloud-Resolving Storm Simulaor) 雲解析模式與Wang et al.(2016) 提出的差時系集預報方式，具備高水平和垂直解析度，大的高解析度區域，及更長的預報時間長度，有機會能及早對災害有所掌握，本文進行每6小時的事後預報，討論上述這些優勢是否能夠在預報上對海燕颱風這個案例達到改進，以求日後對於此類容易造成重大災情的案例，有更有效的預報示警手段，減少生命與經濟上的巨大損失。
本研究除了使用差時系集策略外，其他幫助改善預報的作法，包含提高模式設定的層頂高度，同時對初始時間格點資料和觀測強度落差較大的時段，使用先前模式在該時間表現最好，強度最接近的預報來做為初始資料進行預報，以減少初始資料跟觀測資料的差距，進一步降低颱風登陸前兩天內的誤差。
結果顯示，差時系集的高解析度，對於颱風強度的預報結果有明顯幫助，對海燕颱風其路徑也有良好的掌握。自11月4日開始CReSS預報的颱風登陸位置與JTWC的最佳路徑就僅有小於150公里誤差的成員出現，而扣除徑向路徑誤差則有小於100公里誤差的成員。在11月6號0000 UTC之後，誤差都小於100公里，登陸點的誤差則小於50公里。由於良好的路徑預報，颱風在登陸前後有在雷伊泰灣內產生明顯風向轉變，與觀測相符。
強度的表現不採用額外作法時以11月6日0000 UTC的表現為最佳，最大風速達到76.2 m∙s^(-1)，最低海平面氣壓則達到891 hPa，相較於JTWC的84.9 m∙s^(-1)和895 hPa，強度的表現已經相當接近，另外由於路徑誤差亦小，能捕捉到Takagi et al.(2015) 所提出，海燕颱風造成風暴潮的原因，因此本差時系集預報所產出的資料，若套用到暴潮模式後是有機會預報出接近真實的風暴潮的出現。而使用了先前CReSS預報作為初始資料，進行了從6日0600 UTC開始的6個預報，這成員預報的最大風速都有超過70 m∙s^(-1)，而最低氣壓低於900 hPa，相較於初始場使用GFS資料的預報，風速上又增加了10 m∙s^(-1)以上，而氣壓則下降約20 hPa，故有相當的程度的改善。
總結而言，本研究的CReSS差時系集預報，能夠在海燕颱風登陸前2天內，對於其登陸階段的風速預報誤差大致小於10 m∙s^(-1)，中心氣壓則與觀測接近甚至更低，登陸的位置誤差則能在50公里以內，預報表現十分突出。

Hendricks, E. A., M. S. Peng, B. Fu, and T. Li, 2010: Quantifying environmental control on tropical cyclone intensity change. Mon. Wea. Rev., 138, 3243-3271.
Islam T, Srivastava PK, Rico-Ramirez MA, Dai Q, Gupta M, Singh SK (2014) Tracking a tropical cyclone through WRF–ARW simulation and sensitivity of model physics. Nat Hazards 76(3) :1473–1495.
Kennedy, A., Mori, N., Zhang, Y., Yasuda, T., Chen, S.-E.,Tajima, Y., Pecor, W., and Toride, K.: Observations andmodelling of coastal boulder transport and loading during super typhoon Haiyan, Coast. Eng. J., 58, 1640004,1-25.
Kuo, H. C., S. Tsujino, and C. C. Huang 2019: Diagnosis of the Dynamic Efficiency of Latent Heat Release and the Rapid Intensification of Supertyphoon Haiyan (2013) Mon. Wea. Rev., 147, 1127-1147
Lin, I. I., I. F. Pun, and C. C. Lien, 2014: ‘Category-6’ Supertyphoon Haiyan in global warming hiatus: contribution from subsurface ocean warming. Geophys. Res. Lett. 41, 8547–8553.
Mori, N. et al. Local amplification of storm surge by Super Typhoon Haiyan in Leyte Gulf. Geophys. Res. Lett. 41, 1–8.
Nguyen, H. V., and Y.-L. Chen, 2011: High resolution initialization and simulations of Typhoon Morakot (2009) . Mon. Wea. Rev., 139, 1463-1491.
Shu, S., and F. Zhang, 2015: Influence of equatorial waves on the genesis of Super Typhoon Haiyan (2013) . J. Atmos. Sci., 72, 4591–4613.
Shu, S., F. Zhang, J. Ming, and Y. Wang, 2014: Environmental influences on the intensity changes of tropical cyclones over the western North Pacific. Atmos. Chem. Phys., 14, 6329–6342
Takagi, H. et al. Track analysis, simulation, and field survey of the 2013 Typhoon Haiyan and Storm Surge. J. Flood Risk Manag. doi:10.1111/jfr3.12136 (2015) .
Tsuboki, K., and A. Sakakibara, 2002: Large-scale parallel computing of cloud resolving storm simulator. High Performance Computing, Springer, H. P. Zima et al. Eds., 243-259.
Tsuboki, K., and A. Sakakibara, 2007: Numerical Prediction of High-Impact Weather Systems. The Textbook for Seventeenth IHP Training Course in 2007. HyARC, Nagoya University and UNESCO, 273 pp.
Wang, C.-C., 2015: The more rain, the better the model performs---The dependency of quantitative precipitation forecast skill on rainfall amount for typhoons in Taiwan. Mon. Wea. Rev., 143, 1723-1748.
Wang, C.-C., 2016: Paper of notes: The more rain from typhoons, the better the models perform. Bull. Amer. Meteor. Soc., 97, 16-17.
Wang, C.-C., G. T.-J. Chen, T.-C. Chen, and K. Tsuboki, 2005: A numerical study on the effects of Taiwan topography on a convective line during the Mei-yu season. Mon. Wea. Rev., 133, 3217-3242.
Wang, C. C., S. Y. Huang, S. H. Chen, C. S. Chang, and K. Tsuboki, 2016: Cloud-resolving typhoon rainfall ensemble forecasts for Taiwan with large domain and extended range through time-lagged approach. Wea. Forecasting, 31, 151–172.
Wang, C.-C., H.-C. Kuo, Y.-H. Chen, H.-L. Huang, C.-H. Chung, and K. Tsuboki, 2012: Effects of asymmetric latent heating on typhoon movement crossing Taiwan: The case of Morakot (2009) with extreme rainfall. J. Atmos. Sci., 69, 3172-3196.
Wang, C.-C., H.-C. Kuo, T.-C. Yeh, C.-H. Chung, Y.-H. Chen, S.-Y. Huang, Y.-W. Wang, and C.-H. Liu, 2013: High-resolution quantitative precipitation forecasts and simulations by the Cloud-Resolving Storm Simulator (CReSS) for Typhoon Morakot (2009) . J. Hydrol., 506, 26-41.
Wang, C.-C., S.-Y. Huang, S.-H. Chen, C.-S. Chang, and K. Tsuboki, 2016a: Cloud-resolving typhoon rainfall ensemble forecasts for Taiwan with large domain and extended range through time-lagged approach. Wea. Forecasting, 31, 151-172. Wang, C.-C., S.-Y. Huang, S.-H. Chen, C.-S. Chang, and K. Tsuboki, 2016b: Paper of notes: Cloud-resolving, time-lagged typhoon rainfall ensemble forecasts. Bull. Amer. Meteor. Soc., 97, 1128-1129.
Xiang, B., S.-J. Lin, M. Zhao, S. Zhang, G. Vecchi, T. Li, X. Jiang, L. Harris, and J.-H. Chen, 2015a: Beyond weather time scale prediction for Hurricane Sandy and Super Typhoon Haiyan in a global climate model. Mon. Wea. Rev., 143, 524–535.