Abstract
Parametric cyclone wind models with storm characteristics derived from statistical representation do not agreeably delineate the wind field in the East China Sea, leading to uncertain errors in the numerical simulations of Typhoon waves. A new approach to adjust the cyclone wind field in the framework of the Holland model is proposed. The radius of maximum wind speed and the logarithmically varied shape parameter B from the Holland model are iterated out with in situ data and extended to the cyclone track in the East China Sea. This event-based Holland parametric assimilation scheme can model different kinds of unimodal wind profiles and deliver a significant improvement over the original Holland model. The simulated wind fields of three typhoon events, Typhoons Saomai (200608), Fitow (201312) and Maria (201808), are then used to drive the Simulating Waves Nearshore (SWAN) wave model, and wave fields during the three typhoon events show better agreement with the in situ observations. Compared with satellite scatterometer and altimeter products, the effectiveness of modelled typhoon events is largely limited by temporal changes of typhoon structure. This approach is recommended for typhoon events with small temporal changes. Overall, the approach to adjusting wind profiles with observations satisfactorily improves the simulation performances of cyclonic winds and wave heights at a low computation cost.
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References
Amrutha MM, Kumar VS, Sandhya KG, Nair TB, Rathod JL (2016) Wave hindcast studies using SWAN nested in WAVEWATCH III-comparison with measured nearshore buoy data off Karwar, eastern Arabian Sea. Ocean Eng 119:114–124. https://doi.org/10.1016/j.oceaneng.2016.04.032
Booij N, Holthuijsen LH, Ris RC (1996) The “SWAN” wave model for shallow water. Coast Eng 1:668–676. https://doi.org/10.1061/9780784402429.053
Chan KTF, Chan JCL (2012) Size and strength of tropical cyclones as inferred from QuikSCAT data. Mon Weather Rev 140:811–824. https://doi.org/10.1175/MWR-D-10-05062.1
Chavas DR, Emanuel KA (2010) A QuikSCAT climatology of tropical cyclone size. Geophys Res Lett 37:L18816. https://doi.org/10.1029/2010GL044558
Chavas DR, Lin N, Emanuel K (2015) A model for the complete radial structure of the tropical cyclone wind field. Part I: comparison with observed structure. J Atmos Sci 72:3647–3662. https://doi.org/10.1175/JAS-D-15-0014.1
Chavas DR, Reed KA, Knaff JA (2017) Physical understanding of the tropical cyclone wind-pressure relationship. Nat Commun 8:1360. https://doi.org/10.1038/s41467-017-01546-9
Collard F, Ardhuin F, Chapron B (2009) Monitoring and analysis of ocean swell fields from space: new methods for routine observations. J Geophys Res 114:C07023. https://doi.org/10.1029/2008JC005215
Dvorak VF (1975) Tropical cyclone intensity analysis and forecasting from satellite imagery. Mon Weather Rev 103:420–430. https://doi.org/10.1175/1520-0493(1975)103<0420:TCIAAF>2.0.CO;2
Emanuel K (2004) Tropical cyclone energetics and structure. Atmospheric turbulence and mesoscale meteorology. Cambridge University Press, New York, pp 165–191
Emanuel K, Rotunno R (2011) Self-stratification of tropical cyclone outflow. Part I: implications for storm structure. J Atmos Sci 68:2236–2249. https://doi.org/10.1175/JAS-D-10-05024.1
Fan YL, Ginis I, Hara T, Wright C, Walsh E (2009a) Numerical simulations and observations of surface wave fields under an extreme tropical cyclone. J Phys Oceanogr 39:2097–2116. https://doi.org/10.1175/2009JPO4224.1
Fan YL, Ginis I, Hara T (2009b) The effect of wind–wave–current interaction on air–sea momentum fluxes and ocean response in tropical cyclones. J Phys Oceanogr 39:1019–1034. https://doi.org/10.1175/2008JPO4066.1
Feng X, Zheng J, Yan Y (2012) Wave spectra assimilation in typhoon wave modeling for the East China Sea. Coast Eng 69:29–41. https://doi.org/10.1016/j.coastaleng.2012.05.007
Feng X, Yang D, Yin B, Li J (2018) The change and trend and of the typhoon waves in Zhe Jiang and Fu Jian coastal areas of China. Oceanol Limnol Sin 49:233–241. https://doi.org/10.11693/hyhz20180200036
Fujita T (1952) Pressure distribution within typhoon. Geophys Mag 23:437–451
Group T (1988) The WAM model—a third generation ocean wave prediction model. J Phys Oceanogr 18:1775–1810. https://doi.org/10.1175/1520-0485(1988)018<1775:TWMTGO>2.0.CO;2
Hasselmann S, Hasselmann K, Allender JH, Barnett TP (1985) Computations and parameterizations of the nonlinear energy transfer in a gravity-wave spectrum. Part II: parameterizations of the nonlinear energy transfer for application in wave models. J Phys Oceanogr 15(11):1378–1391. https://doi.org/10.1175/1520-0485(1985)015<1369:CAPOTN>2.0.CO;2
Holland GJ (1980) An analytic model of the wind and pressure profiles in hurricanes. Mon Weather Rev 108:1212–1218. https://doi.org/10.1175/1520-0493(1980)108<1212:AAMOTW>2.0.CO;2
Holland GJ, Belanger JI, Fritz A (2010) A revised model for radial profiles of hurricane winds. Mon Weather Rev 138:4393–4401. https://doi.org/10.1175/2010MWR3317.1
Hu K, Chen Q (2011) Directional spectra of hurricane-generated waves in the Gulf of Mexico. Geophys Res Lett 38:L19608. https://doi.org/10.1029/2011GL049145
Hu K, Chen Q, Kimball S (2012a) Consistency in hurricane surface wind forecasting: an improved parametric model. Nat Hazards 61:1029–1050. https://doi.org/10.1007/s11069-011-9960-z
Hu K, Chen Q, Fitzpatrick P (2012b) Assessment of a parametric hurricane surface wind model for tropical cyclones in the Gulf of Mexico. In: Advances in hurricane research-modelling meteorology, preparedness and impacts. InTech, Croatia
Hu T, Wu Y, Zheng G, Zhang D, Zhang Y, Li Y (2018) Tropical cyclone center automatic determination model based on HY-2 and QuikSCAT wind vector products. IEEE Trans Geosci Remote Sens. https://doi.org/10.1109/TGRS.2018.2859819
Jelesnianski CP (1965) A numerical calculation of storm tides induced by a tropical storm impinging on a continental self. Mon Weather Rev 93:343–358. https://doi.org/10.1175/2010MWR3317.1
Klotz BW, Jiang H (2016) Global composites of surface wind speeds in tropical cyclones based on a 12 year scatterometer database. Geophys Res Lett. https://doi.org/10.1002/2016GL071066
Klotz BW, Jiang H (2017) Examination of surface wind asymmetries in tropical cyclones. Part I: general structure and wind shear impacts. Mon Weather Rev 145:3989–4009. https://doi.org/10.1175/MWR-D-17-0019.1
Knaff JA, Harper BA, Brown D (2010) Tropical cyclone surface wind structure and wind-pressure relationships. In: Proc WMO Int Workshop on Tropical Cyclones—VII
Knaff JA, Longmore SP, DeMaria RT, Molenar DA (2015) Improved tropical-cyclone flight-level wind estimates using routine infrared satellite reconnaissance. J Appl Meteorol Clim 54:463–478. https://doi.org/10.1175/JAMC-D-14-0112.1
Knaff JA, Slocum CJ, Musgrave KD, Sampson CR, Strahl BR (2016) Using routinely available information to estimate tropical cyclone wind structure. Mon Weather Rev 144:1233–1247. https://doi.org/10.1175/MWR-D-15-0267.1
Kudryavtsev V, Golubkin P, Chapron B (2016) A simplified wave enhancement criterion for moving extreme events. J Geophys Res Oceans 120:7538–7558. https://doi.org/10.1002/2015JC011284
Lin N, Chavas D (2012) On hurricane parametric wind and applications in storm surge modeling. J Geophys Res 117:D09120. https://doi.org/10.1029/2011JD017126
Liu B, Liu H, Xie L, Guan C, Zhao D (2011) A coupled atmosphere–wave–ocean modeling system: simulation of the intensity of an idealized tropical cyclone. Mon Weather Rev 139(1):132–152. https://doi.org/10.1016/S0029-8018(02)00033-1
Liu Q, Babanin AV, Guan C, Zieger S, Sun J, Jia Y (2016) Calibration and validation of HY-2 altimeter wave height. J Atmos Ocean Tech 33:919–936. https://doi.org/10.1175/JTECH-D-15-0219.1
Maclay KS, DeMaria M, Vonder Haar TH (2008) Tropical cyclone inner-core kinetic energy evolution. Mon Weather Rev 136:4882–4898. https://doi.org/10.1175/2008MWR2268.1
Mass CF, Warner MD, Steed R (2014) Strong westerly wind events in the Strait of Juan de Fuca. Weather Forecast 29(2):445–465. https://doi.org/10.1175/WAF-D-13-00026.1
Mattocks C, Forbes C (2008) A real-time, event-triggered storm surge forecasting system for the state of North Carolina. Ocean Model 25:95–119. https://doi.org/10.1016/j.ocemod.2008.06.008
Miyazaki M (1961) The theoretical investigations of typhoon surges along the Japanese coast. Oceanogr Mag 13:51–75
Muis S, Verlaan M, Winsemius H, Aerts J, Ward P (2016) A global reanalysis of storm surges and extreme sea levels. Nat Commun 7:11969. https://doi.org/10.1038/ncomms11969
Murty PLN, Sandhya KG, Bhaskaran PK, Jose F, Gayathri R, Balakrishnan NTM, Srinivasa KT, Shenoi SSC (2014) A coupled hydrodynamic modeling system for PHAILIN cyclone in the Bay of Bengal. Coast Eng 93:71–81. https://doi.org/10.1016/j.coastaleng.2014.08.006
Olfateh M, Callaghan DP, Nielsen P, Baldock TE (2017) Tropical cyclone wind field asymmetry—development and evaluation of a new parametric model. J Geophys Res Oceans 122:458–469. https://doi.org/10.1002/2016JC012237
Phadke AC, Martino CD, Cheung KF, Houston SH (2003) Modeling of tropical cyclone winds and waves for emergency management. Ocean Eng 30(4):553–578. https://doi.org/10.1175/2010MWR3396.1
Powell MD, Reinhold TA (2007) Tropical cyclone destructive potential by integrated kinetic energy. Bull Am Meteorol Soc 88:513–526. https://doi.org/10.1175/BAMS-88-4-513
Powell MD, Uhlhorn EW, Kepert JD (2009) Estimating maximum surface winds from hurricane reconnaissance measurements. Weather Forecast 24:868–883. https://doi.org/10.1175/2008WAF2007087.1
Quilfen Y, Tournadre J, Chapron B (2006) Altimeter dual-frequency observations of surface winds, waves, and rain rate in tropical cyclone Isabel. J Geophys Res 111:C01004. https://doi.org/10.1029/2005JC003068
Reul N, Chapron B, Zabolotskikh E, Donlon C, Quilfen Y, Guimbard S, Piolle JF (2016) A revised L-band radio-brightness sensitivity to extreme winds under tropical cyclones: the five year SMOS-storm database. Remote Sens Environ 180:274–291. https://doi.org/10.1016/j.rse.2016.03.011
Ricciardulli L, Wentz F (2011) Reprocessed QuikSCAT (V04) wind vectors with Ku-2011 geophysical model function. Remote Sens Syst Tech Rep 043011. http://www.ssmi.com/qscat/qscat_Ku2011_tech_report.pdf
Schloemer RW (1954) Analysis and synthesis of hurricane wind patterns over Lake Okechobee. Fla US Weather Bur Hydromet Rep 31:1–49
Uhlhorn EW, Klotz BW, Vukicevic T, Reasor PD, Rogers RF (2014) Observed hurricane wind speed asymmetries and relationships to motion and environmental shear. Mon Weather Rev 142:1290–1311. https://doi.org/10.1175/MWR-D-13-00249.1
Vickery PJ, Skerlj PF, Twisdale LA (2000) Simulation of hurricane risk in the US using empirical track model. J Struct Eng 126:1222–1237. https://doi.org/10.1061/(ASCE)0733-9445(2000)126:10(1222)
Vickery PJ, Masters FJ, Powell MD, Wadhera D (2009) Hurricane hazard modeling: the past, present, and future. J Wind Eng Ind Aerod 97:392–405. https://doi.org/10.1016/j.jweia.2009.05.005
Willoughby HE, Darling RWR, Rahn ME (2006) Parametric representation of the primary hurricane vortex. Part II: a new family of sectionally continuous profiles. Mon Weather Rev 134:1102–1120. https://doi.org/10.1175/MWR3106.1
Wu S, Liu C, Chen X (2015) Offshore wave energy resource assessment in the East China Sea. Renew Energ 76:628–636. https://doi.org/10.1016/j.renene.2014.11.054
Xie L, Bao S, Pietrafesa LJ, Foley K, Fuentes M (2006) A real-time hurricane surface wind forecasting model: formulation and verification. Mon Weather Rev 134:1355–1370. https://doi.org/10.1175/MWR3126.1
Xu D, Lin Z, Liao S, Stiassnie M (2012) On the steady-state fully resonant progressive waves in water of finite depth. J Fluid Mech 710:379–418. https://doi.org/10.1017/jfm.2012.370
Ying M et al (2014) An overview of the China Meteorological Administration tropical cyclone database. J Atmos Ocean Tech 31:287–301. https://doi.org/10.1175/JTECH-D-12-00119.1
Young IR (1988) Parametric hurricane wave prediction model. J Waterw Port Coast 114:637–652. https://doi.org/10.1061/(ASCE)0733-950X(1988)114:5(637)
Young IR (2017) A Review of parametric descriptions of tropical cyclone wind-wave generation. Atmosphere 8:194. https://doi.org/10.3390/atmos8100194
Young IR, Babanin AV, Zieger S (2013) The decay rate of ocean swell observed by altimeter. J Phys Oceanogr 43:2322–2333. https://doi.org/10.1175/JPO-D-13-083.1
Zhang L, Oey L (2019) An observational analysis of ocean surface waves in tropical cyclones in the western North Pacific Ocean. J Geophys Res Ocean 124(1):184–195. https://doi.org/10.1029/2018JC014517
Zhang J, Huang L, Wen Y, Deng J (2009) A distributed coupled atmosphere–wave–ocean model for typhoon wave numerical simulation. Int J Comput Math 86:2095–2103. https://doi.org/10.1080/00207160802047632
Zhang G, Perrie W, Li X, Zhang JA (2017) A hurricane morphology and sea surface wind vector estimation model based on C-band cross-polarization SAR imagery. IEEE Trans Geosci Remote Sens 55:1743–1751. https://doi.org/10.1109/TGRS.2016.2631663
Acknowledgements
In this research, Guoping Gao, Xuan Wang and Zhao Zhang are supported by the Strategic Priority Research Program of the Chinese Academy of Sciences under Grant XDA20060501, XDA20060503 and Zhejiang Sea Grant to typhoon prevention assessment of fishery ports. Ge Chen is supported by the National Key Research and Development Program of China under Grant 2016YFC1401008 and the Scientific and Technological Innovation Project of the Qingdao National Laboratory for Marine Science and Technology under Grant 2018ASKJ01. Haoyu Jiang is supported by the National Natural Science Foundation of China under Project 41806010. The in situ station data were obtained from Wenzhou Marine Environmental Monitoring Center Station. The satellite data were obtained freely from Remote Sensing Systems and AVISO.
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Wang, X., Yao, C., Gao, G. et al. Simulating tropical cyclone waves in the East China Sea with an event-based, parametric-adjusted model. J Oceanogr 76, 439–457 (2020). https://doi.org/10.1007/s10872-020-00555-5
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DOI: https://doi.org/10.1007/s10872-020-00555-5