Abstract
The relative impact of environmental parameters on tropical cyclone (TC) intensification rate (IR) was investigated through a box difference index (BDI) method, using TC best track data from Joint Typhoon Warning Center and environmental fields from the NCEP final analysis data over the western North Pacific (WNP) during 2000–2018. There are total 6307 TC samples with a 6-h interval, of which about 14% belong to rapid intensification (RI) category. The analysis shows that RI occurs more frequently with higher environmental sea surface temperature, higher oceanic heat content, and lower upper-tropospheric temperature. A moderate easterly shear is more favorable for TC intensification. TC intensification happens mostly equatorward of 20°N while TC weakening happens mostly when TCs are located in the northwest of the basin. Mid-tropospheric relative humidity and vertical velocity are good indicators separating the intensification and non-intensification groups. A statistical model for TC intensity prediction was constructed based on six environmental predictors, with or without initial TC intensity. Both models are skillful based on Brier skill score (BSS) relative to climatology and in comparison with other statistical models, for both a training period (2000–2018) and an independent forecast period (2019–2020).
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References
Bhatia, K. T., G. A. Vecchi, T. R. Knutson, et al., 2019: Recent increases in tropical cyclone intensification rates. Nat. Commun., 10, 635, doi: https://doi.org/10.1038/s41467-019-08471-z.
DeMaria, M., C. R. Sampson, J. A. Knaff, et al., 2014: Is tropical cyclone intensity guidance improving?. Bull. Amer. Meteor. Soc., 95, 387–398, doi: https://doi.org/10.1175/BAMS-D-12-00240.1.
DeMaria, M., J. L. Franklin, M. J. Onderlinde, et al., 2021: Operational forecasting of tropical cyclone rapid intensification at the National Hurricane Center. Atmosphere, 12, 683, doi: https://doi.org/10.3390/atmos12060683.
Dunion, J. P., and C. S. Velden, 2004: The impact of the Saharan air layer on Atlantic tropical cyclone activity. Bull. Amer. Meteor. Soc., 85, 353–366, doi: https://doi.org/10.1175/BAMS-85-3-353.
Elsberry, R. L., T. D. B. Lambert, and M. A. Boothe, 2007: Accuracy of Atlantic and eastern North Pacific tropical cyclone intensity forecast guidance. Wea. Forecasting, 22, 747–762, doi: https://doi.org/10.1175/WAF1015.1.
Emanuel, K., 2017: Will global warming make hurricane forecasting more difficult? Bull. Amer. Meteor. Soc., 98, 495–501, doi: https://doi.org/10.1175/BAMS-D-16-0134.1.
Emanuel, K., and F. Q. Zhang, 2016: On the predictability and error sources of tropical cyclone intensity forecasts. J. Atmos. Sci., 73, 3739–3747, doi: https://doi.org/10.1175/JAS-D-16-0100.1.
Emanuel, K. A., 1986: An air-sea interaction theory for tropical cyclones. Part I: Steady-state maintenance. J. Atmos. Sci., 43, 585–605, doi: https://doi.org/10.1175/1520-0469(1986)043<0585:AASITF>2.0.CO;2.
Emanuel, K. A., 1988: The maximum intensity of hurricanes. J. Atmos. Sci., 45, 1143–1155, doi: https://doi.org/10.1175/1520-0469(1988)045<1143:TMIOH>2.0.CO;2.
Gray, W. M., 1998: The formation of tropical cyclones. Meteor. Atmos. Phys., 67, 37–69, doi: https://doi.org/10.1007/BF01277501.
Hanley, D., J. Molinari, and D. Keyser, 2001: A composite study of the interactions between tropical cyclones and upper-tropospheric troughs. Mon. Wea. Rev., 129, 2570–2584, doi: https://doi.org/10.1175/1520-0493(2001)129<2570:ACSOTI>2.0.CO;2.
Holland, G. J., 1997: The maximum potential intensity of tropical cyclones. J. Atmos. Sci., 54, 2519–2541, doi: https://doi.org/10.1175/1520-0469(1997)054<2519:TMPIOT>2.0.CO;2.
Kanada, S., and A. Wada, 2015: Numerical study on the extremely rapid intensification of an intense tropical cyclone: Typhoon Ida (1958). J. Atmos. Sci., 72, 4194–4217, doi: https://doi.org/10.1175/JAS-D-14-0247.1.
Kaplan, J., and M. DeMaria, 2003: Large-scale characteristics of rapidly intensifying tropical cyclones in the North Atlantic basin. Wea. Forecasting, 18, 1093–1108, doi: https://doi.org/10.1175/1520-0434(2003)018<1093:LCORIT>2.0.CO;2.
Kaplan, J., M. DeMaria, and J. A. Knaff, 2010: A revised tropical cyclone rapid intensification index for the Atlantic and eastern North Pacific basins. Wea. Forecasting, 25, 220–241, doi: https://doi.org/10.1175/2009WAF2222280.1.
Knaff, J. A., C. R. Sampson, and K. D. Musgrave, 2018: An operational rapid intensification prediction aid for the western North Pacific. Wea. Forecasting, 33, 799–811, doi: https://doi.org/10.1175/WAF-D-18-0012.1.
Lee, C.-Y., M. K. Tippett, S. J. Camargo, et al., 2015: Probabilistic multiple linear regression modeling for tropical cyclone intensity. Mon. Wea. Rev., 143, 933–954, doi: https://doi.org/10.1175/MWR-D-14-00171.1.
Leighton, H., S. Gopalakrishnan, J. A. Zhang, et al., 2018: Azimuthal distribution of deep convection, environmental factors, and tropical cyclone rapid intensification: A perspective from HWRF ensemble forecasts of Hurricane Edouard (2014). J. Atmos. Sci., 75, 275–295, doi: https://doi.org/10.1175/JAS-D-17-0171.1.
Lin, I.-I., R. F. Rogers, H. C. Huang, et al., 2021: A tale of two rapidly intensifying supertyphoons: Hagibis (2019) and Haiyan (2013). Bull. Amer. Meteor. Soc., 102, E1645–E1664, doi: https://doi.org/10.1175/BAMS-D-20-0223.1.
Montgomery, M. T., M. E. Nicholls, T. A. Cram, et al., 2006: A vortical hot tower route to tropical cyclogenesis. J. Atmos. Sci., 63, 355–386, doi: https://doi.org/10.1175/JAS3604.1.
Peng, M. S., B. Fu, T. Li, et al., 2012: Developing versus nondeveloping disturbances for tropical cyclone formation. Part I: North Atlantic. Mon. Wea. Rev., 140, 1047–1066, doi: https://doi.org/10.1175/2011MWR3617.1.
Rogers, R. F., J. A. Zhang, J. Zawislak, et al., 2016: Observations of the structure and evolution of Hurricane Edouard (2014) during intensity change. Part II: Kinematic structure and the distribution of deep convection. Mon. Wea. Rev., 144, 3355–3376, doi: https://doi.org/10.1175/MWR-D-16-0017.1.
Saha, S., S. Nadiga, C. Thiaw, et al., 2006: The NCEP climate forecast system. J. Climate, 19, 3483–3517, doi: https://doi.org/10.1175/JCLI3812.1.
Schubert, W. H., and J. J. Hack, 1982: Inertial stability and tropical cyclone development. J. Atmos. Sci., 39, 1687–1697, doi: https://doi.org/10.1175/1520-0469(1982)039<1687:ISATCD>2.0.CO;2.
Shay, L. K., and J. K. Brewster, 2010: Oceanic heat content variability in the eastern Pacific Ocean for hurricane intensity forecasting. Mon. Wea. Rev., 138, 2110–2131, doi: https://doi.org/10.1175/2010MWR3189.1.
Shu, S. J., J. Ming, and P. Chi, 2012: Large-scale characteristics and probability of rapidly intensifying tropical cyclones in the western North Pacific basin. Wea. Forecasting, 27, 411–423, doi: https://doi.org/10.1175/WAF-D-11-00042.1.
Stevenson, S. N., K. L. Corbosiero, M. DeMaria, et al., 2018: A 10-year survey of tropical cyclone inner-core lightning bursts and their relationship to intensity change. Wea. Forecasting, 33, 23–36, doi: https://doi.org/10.1175/WAF-D-17-0096.1.
Tallapragada, V., C. Kieu, S. Trahan, et al., 2016: Forecasting tropical cyclones in the western North Pacific basin using the NCEP operational HWRF model: Model upgrades and evaluation of real-time performance in 2013. Wea. Forecasting, 31, 877–894, doi: https://doi.org/10.1175/WAF-D-14-00139.1.
Titley, D. W., and R. L. Elsberry, 2000: Large intensity changes in tropical cyclones: A case study of Supertyphoon Flo during TCM-90. Mon. Wea. Rev., 128, 3556–3573, doi: https://doi.org/10.1175/1520-0493(2000)128<3556:LICITC>2.0.CO;2.
Ventham, J. D. and B. Wang, 2007: Large-scale flow patterns and their influence on the intensification rates of western North Pacific tropical storms. Mon. Wea. Rev., 135, 1110–1127, doi: https://doi.org/10.1175/MWR3327.1.
Wada, A., and N. Usui, 2007: Importance of tropical cyclone heat potential for tropical cyclone intensity and intensification in the western North Pacific. J. Oceanogr., 63, 427–447, doi: https://doi.org/10.1007/s10872-007-0039-0.
Wei, N., X. H. Zhang, L. S. Chen, et al., 2018: Comparison of the effect of easterly and westerly vertical wind shear on tropical cyclone intensity change over the western North Pacific. Environ. Res. Lett., 13, 034020, doi: https://doi.org/10.1088/1748-9326/aaa496.
Wilks, D. S., 2005: Statistical Methods in the Atmospheric Sciences. 2nd Ed., Elsevier, Amsterdam, 627 pp.
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We thank the editor and anonymous reviewers for their constructive comments and suggestions. We acknowledge the High Performance Computing Center of Nanjing University of Information Science & Technology for their support to this study.
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Supported by the National Natural Science Foundation of China (42088101), US National Oceanic and Atmospheric Administration (NA18OAR4310298), and Jiangsu Meteorological Bureau (KQ202205). These are SOEST contribution number 11539, IPRC contribution number 1571, and ESMC number 381.
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Ma, C., Li, T. An Empirical Model of Tropical Cyclone Intensity Forecast in the Western North Pacific. J Meteorol Res 36, 691–702 (2022). https://doi.org/10.1007/s13351-022-2016-3
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DOI: https://doi.org/10.1007/s13351-022-2016-3