Publications (in preparation):
Baldwind, J., C.-Y. Lee, B. J. Walsh, S. J. Camargo, and A. H. Sobel: A tropical cyclone disk model for the Philippines: Development and applications (submitted)
Meiler, S., T. Vogt, N. Bloemendaal, A. Ciullo, C.-Y. Lee, S. J. Camargo, K. Emanuel, and D. N. Bresch, Intercomparison of regional loss estimates from global synthetic tropical cyclone models, Nat. Commun., (submitted)
Li, H., J. H. Richter, C.-Y. Lee, and H. Kim: Subseasonal Tropical Cyclone prediction and the modulation of MJO and ENSO in CESM2 (submitted)
Peer-reviewed Publications Citations: 1030, H-index: 15, as March 04, 2022
Lee, C.-Y., A. H. Sobel, S. J. Camargo, M. K. Tippett, and Q. Yang*, 2022: New York State hurricane hazard: history and future projections, J. Appl. Meteorol. Climatol. (Accepted)
Sobel, A.H., A. A. Wing, S. J. Camargo, C. M. Patricola, G. A. Vecchi, C.-Y. Lee, and M. K. Tippett, 2021: Tropical cyclone frequency, Earth’s Future, 9, e2021EF00227. https://doi.org/10.1029/2021EF002275
Yang*, Q., C.-Y. Lee, M. K. Tippett, D. Chavas, T. Knutson, 2021: Machine learning based hurricane wind reconstruction, Wea. Forecast. https://doi.org/10.1175/WAF-D-21-0077.1
Stern D., G. Brian, C.-Y., Lee, and J. D. Doyle, 2021: Estimating the Risk of Extreme Wind Gusts in Tropical Cyclones Using Idealized Large-Eddy Simulations and a Statistical–Dynamical Model, Monthly Weather Review, 149(12), 4183-4204. https://doi.org/10.1175/MWR-D-21-0059.1
Camargo S. J., F. Vitart, C.-Y. Lee, and M. K. Tippett, 2021: Skill, Predictability, and Cluster Analysis of Atlantic Tropical Storms and Hurricanes in the ECMWF Monthly Forecasts, Monthly Weather Review, 149(11), 3781-3802. https://doi.org/10.1175/MWR-D-21-0075.1
Islam, M. R.*, C.-Y. Lee, K. T. Mandli, and H. Takagi, 2021: A new tropical cyclone surge index incorporating the effects of coastal geometry, bathymetry and storm information. Sci Rep 11, 16747. https://doi.org/10.1038/s41598-021-95825-7
Tan J.*, C.-Y. Lee, G. Dong, W. Hu, J. Wang, 2021: Projected changes of typhoon intensity in a regional climate model: Development of a machine learning bias correction scheme. Int J Climatol., 1– 16. https://doi.org/10.1002/joc.6987
Johnston, S. T. M., S. Wang, C.-Y. Lee, J. N. Moum, D. L. Rudnick1, and A. Sobel, 2021: Near-inertial wave propagation in the wake of Super Typhoon Mangkhut: Measurements from a profiling float array, J. Geophys. Res.: Ocean 126, e2020JC016749. https://doi.org/10.1029/2020JC016749
Wang, S., A. H. Sobel, C.-Y. Lee, D. Ma, S. S. Chen, M. Curcic, and J. Pullen, 2021: Propagating mechanisms of the 2016 summer BSISO event: air-sea coupling, vorticity, and moisture. J. Geophys. Res.: Atmospheres 126, e2020JD033284., https://doi.org/10.1029/2020JD033284
Hassanzadeh, P., C.-Y. Lee, E. Nabizadeh, S. J. Camargo, D. Ma, and L. Y. Yeung, 2020: Effects of climate change on the movement of future landfalling Texas tropical cyclones. Nature Communication 11, 3319, https://doi.org/10.1038/s41467-020-17130-7
Yang Q.*, C.-Y. Lee, M. K. Tippett, 2020: A long short-term memory model for global rapid intensification prediction. Wea. Forecasting, 35, 1203–1220, https://doi.org/10.1175/WAF-D-19-0199.1
Lee C.-Y., S. J. Camargo, F. Vitart, A. H. Sobel, J. Camp, S. Wang., M. K. Tippett, and Q. Yang, 2020: Subseasonal predictions of tropical cyclone intensity and occurrence in the S2S dataset. Wea. Forecasting, 35, 921-938, https://doi.org/10.1175/WAF-D-19-0217.1
Lee, C.-Y., and S. J. Camargo, A. H. Sobel and, M. K. Tippett, 2020: Statistical-dynamical downscaling projections of tropical cyclone activity in a warming climate: Two diverging genesis scenarios. J. Climate, 33, 4815–4834, https://doi.org/10.1175/JCLI-D-19-0452.1
Sobel, A.H., C.-Y. Lee, S.J. Camargo, K.T. Mandli, K.A. Emanuel, P. Mukhopadhyay, and M. Mahakur, 2019: Tropical cyclone hazard to Mumbai in the recent historical climate. Mon. Wea. Rev., 147, 2355-2366, https://doi.org/10.1175/MWR-D-18-0419.1
Lee, C.-Y., and S. J. Camargo, F. Vitart, A. H. Sobel, and M. K. Tippett, 2018: Sub-seasonal tropical cyclone genesis prediction and MJO in the S2S dataset, Wea. Forecast. 33, 967-988, https://doi.org/10.1175/WAF-D-17-0165.1
Lee, C.-Y., and M. K. Tippett, A. H. Sobel and S. J. Camargo, 2018: An environmentally forced tropical cyclone hazard model, J. Adv. Model. Earth Syst. 10, 223– 241, https://doi.org/10.1002/2017MS001186
Kuo, Y.-C., Z.-W. Zheng, Q. Zheng, G. Gopalakrishnan, C.-Y. Lee, S.-W. Cherna, Y.-H. Chao, 2017: Typhoon induced summer cold shock advected by Kuroshio off eastern Taiwan, Ocean Modelling, 109, 1-10. https://doi.org/10.1016/j.ocemod.2016.11.003
Sobel, A. H., S. J. Camargo, T. M. Hall, C.-Y. Lee, M. K. Tippett, A. A. Wing, 2016: Human influence on tropical cyclone intensity, Science, 353, 242-246. https://doi.org/10.1126/science.aaf6574
Zheng, Z.-W., Q. Zheng, Y.-C. Kuo, G. Galakrishnan, C.-Y. Lee, C.-R. Ho, N.-J. Kuo, S.-J. Huang, 2016: Impacts of coastal upwelling off east Vietnam on the regional winds system: An air-sea-land interaction, Dyn. Atmos. and Oceans, 76, 105-115. https://doi.org/10.1016/j.dynatmoce.2016.10.002
Lee, C.-Y., and M. K. Tippett, A. H. Sobel and S. J. Camargo, 2016: Autoregressive modeling for tropical cyclone intensity climatology, J. Clim. 29, 7815–7830. https://doi.org/10.1175/JCLI-D-15-0909.1
Lee, C.-Y., M. K. Tippett, A. H. Sobel, and S. J. Camargo, 2016: Rapid intensification and the bimodal distribution of tropical cyclone intensity. Nat. Commun. 7, 10625. https://doi.org/10.1038/ncomms10625
Chen, S. S., B. W. Kerns, N. Guy, D. P. Jorgensen, J. Delanoe, N. Viltard, C. Zappa, F. Judt, C.-Y. Lee, and A. Savarin, 2015: Aircraft Observations of Dry Air, ITCZ, Convective Cloud Systems and Cold Pools in MJO During DYNAMO. Bull. Amer. Met. Soc. 97, 405-423. https://doi.org/10.1175/BAMS-D-13-00196.1
Lee, C.-Y., M. K. Tippett, S. J. Camargo, and, A. H. Sobel, 2015: Probabilistic multiple linear regression modeling for tropical cyclone intensity. Mon. Wea. Rev., 143, 933–954. https://doi.org/10.1175/MWR-D-14-00171.1
Zheng, Z.-W., Q. Zheng, C.-Y. Lee, and G. Gopalarishnan, 2014: Transient modulation of Kuroshio upper layer flow by directly impinging typhoon Morakot in east of Taiwan in 2009. J. Geophys. Res. Oceans, 2169-9291. https://doi.org/10.1002/2014JC010090
Lee C.-Y., and S. S. Chen, 2014: Stable boundary layer and its impact on tropical cyclone structure in coupled atmosphere-ocean model. Mon. Wea. Rev., 142, 1927–1944, https://doi.org/10.1175/MWR-D-13-00122.1
Lee C.-Y., and S. S. Chen, 2012: Symmetric and asymmetric structures of hurricane boundary layer in coupled atmosphere-wave-ocean models and observations. J. Atmos. Sci., 69, 3576-3594. https://doi.org/10.1175/JAS-D-12-046.1
Sraj, I., M. Iskandarani, A. Srinvivasan, W. C. Thacker, J. Winokur, A. Alexanderian, C.-Y. Lee, S. S. Chen, and O. M. Kino, 2012: Bayesian inference of dependence of drag coefficient on wind speed using AXBT data from Typhoon Fanapi. Mon. Wea. Rev., 136, 4593-4661, https://doi.org/10.1175/MWR-D-12-00228.1
Yang, C.-C., C.-C. Wu, K.-H. Chou, and C.-Y. Lee, 2008: Binary interaction between Typhoons Fengshen (2002) and Fungwong (2002) based on the potential vorticity diagnosis. Mon. Wea. Rev., 136, 4593–4611. https://doi.org/10.1175/2008MWR2496.1
Wu, C.-C., C.-Y. Lee, and I-I Lin, 2007: The effect of the ocean eddy on tropical cyclone intensity. J. Atmos. Sci., 64, 3562-3578. https://doi.org/10.1175/2008MWR2496.1