考虑飞沫影响的拖曳系数方案对台风条件下上层海洋海温数值模拟的影响

doi:10.11978/2016103

Abstract

Abstract:

To improve model forecast of upper ocean and offer a more proper momentum exchange scheme for an air-sea coupling model, a new drag coefficient scheme of C_D considering sea spay layer on the surface is established and is used in the three-dimensional oceanic circulation model of the Princeton Ocean Model (POM). A case of tropical cyclone Kalmaegi in 2014 is selected, which passed through the center of a buoys array set up by our field experiment in the northern South China Sea. Observation data were collected for both atmosphere and ocean in the process, and are used to verify the model simulation. It is found that the drag coefficient C_D under low wind condition is consistent with the traditional C_D scheme. However, they are different from each other under high wind condition with C_D increasing slowly, even decreasing slightly, if sea spay process is considered by the new C_D scheme. Furthermore, numerical experiments are conducted using the POM. The results show that the responses of upper ocean on temperature are more reasonable with a weaker cooling rate of ocean temperature and thermocline strength, and smaller deepening of mixed layer depth in the upper ocean if the new drag coefficient scheme is used.

Key words: sea spay, drag coefficient, buoy array in the South China Sea, tropical cyclone, upper ocean

LIU Xiaoyan, LI Yongping, DUAN Ziqiang. The influence of a new drag coefficient scheme considering sea spay on numerical simulation of upper-ocean temperature response to tropical cyclone[J].Journal of Tropical Oceanography, 2017, 36(5): 24-32.

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References 21

[1]	陈大可, 雷小途, 王伟, 等, 2013. 上层海洋对台风的响应和调制机理[J]. 地球科学进展, 28(10): 1077-1086.
	CHEN DAKE, LEI XIAOTU, WANG WEI, et al, 2013. Upper ocean response and feedback mechanisms to typhoon[J]. Advances in Earth Science, 28(10): 1077-1086 (in Chinese).
[2]	段自强, 李永平, 于润玲, 等, 2016. 海洋飞沫方案改进对台风“威马逊”强度预报的影响[J]. 海洋与湖沼, 47(6): 1075-1090.
	DUAN ZIQIANG, LI YONGPING, YU RUNLING, et al, 2016. On tropical cyclone intensity forecast using improved sea spray scheme in regional atmosphere-wave coupled model[J]. Oceanologia et Limnologia Sinica, 47(6): 1075-1090 (in Chinese).
[3]	罗蒋梅, 潘静, 杨支中, 2011. 海面风应力拖曳系数参数化方案对风暴潮数值模拟的影响[J]. 海洋预报, 28(3): 15-19.
	LUO JIANGMEI, PAN JING, YANG ZHIZHONG, 2011. Impact of the parameterization scheme about sea surface wind stress drag coefficients on numerical simulation of strom surge[J]. Marine Forecasts, 28(3): 15-19 (in Chinese).
[4]	王秀芹, 钱成春, 王伟, 2001. 风应力拖曳系数选取对风暴潮数值模拟的影响[J]. 青岛海洋大学学报, 31(5): 640-646.
	WANG XIUQIN, QIAN CHENGCHUN, WANG WEI, 2001. Test of influence of wind drag coefficient on typhoon storm surge simulations[J]. Journal of Ocean University of Qingdao, 31(5): 640-646 (in Chinese).
[5]	赵中阔, 梁建茵, 万齐林, 等, 2011. 强风天气条件下海气动量交换参数的观测分析[J]. 热带气象学报, 27(6): 899-904.
	ZHAO ZHONGKUO, LIANG JIANYIN, WAN QILIN, et al, 2011. Observational analysis of air-sea momentum exchange in strong wind condition[J]. Journal of Tropical Meteorology, 27(6): 899-904 (in Chinese).
[6]	中国气象局, 2016. 热带气旋年鉴2014[M]. 北京: 气象出版社: 123-125.
[7]	周婕, 曾诚, 王玲玲, 2009. 风应力拖曳系数选取对风生流数值模拟的影响[J]. 水动力学研究与进展, 24(4): 440-447.
	ZHOU JIE, ZENG CHENG, WANG LINGLING, 2009. Influence of wind drag coefficient on wind-drived flow simulation[J]. Chinese Journal of Hydrodynamics, 24(4): 440-447 (in Chinese).
[8]	ANDREAS E L, 2002. Parameterizing scalar transfer over snow and ice: A review[J]. Journal of Hydrometeorology, 2002, 3(4): 417-432.
[9]	ANDREAS E L, JORDAN R E, MAKSHTAS A P, 2004. Simulations of snow, ice, and near-surface atmospheric processes on ice station Weddell[J]. Journal of Hydrometeorology, 5(4): 611-624.
[10]	BAO J W, FAIRALL C W, MICHELSON S A, et al, 2011. Parameterizations of sea-spray impact on the air-sea momentum and heat fluxes[J]. Monthly Weather Review, 139(12): 3781-3797.
[11]	BLACK P G, D'ASARO E A, SANFORD T B, et al, 2007. Air-sea exchange in hurricanes: synthesis of observations from the coupled boundary layer air-sea transfer experiment[J]. Bulletin of the American Meteorological Society, 88(3): 357-374.
[12]	GARRATT J R, 1977. Review of drag coefficients over oceans and continents[J]. Monthly Weather Review, 105(7): 915-929.
[13]	GRYTHE H, STROM J, KREJCI R, et al, 2014. A review of sea-spray aerosol source functions using a large global set of sea salt aerosol concentration measurements[J]. Atmospheric Chemistry and Physics, 14(3): 1277-1297.
[14]	GRYTHE H,
[15]	LARGE W G, POND S, 1981. Open ocean momentum flux measurements in moderate to strong winds[J]. Journal of Physical Oceanography, 11(3): 324-336.
[16]	MAKIN V K, 2005. A note on the drag of the sea surface at hurricane winds[J]. Boundary-Layer Meteorology, 115(1): 169-176.
[17]	SMITH S D, 1980. Wind stress and heat flux over the ocean in gale force winds[J]. Journal of Physical Oceanography, 10(5): 709-726.
[18]	TROITSKAYA Y, SERGEEV D, ERMAKOVA O, et al, 2011. Statistical parameters of the air turbulent boundary layer over steep water waves measured by the PIV technique[J]. Journal of Physical Oceanography, 41(8): 1421-1454.
[19]	VICKERS D, MAHRT L, ANDREAS E L, 2013. Estimates of the 10-m neutral sea surface drag coefficient from aircraft eddy-covariance measurements[J]. Journal of Physical Oceanography, 43(2): 301-310.
[20]	XIE JIPING, ZHU JIANG, 2010. Ensemble optimal interpolation schemes for assimilating Argo profiles into a hybrid coordinate ocean model[J]. Ocean Modelling, 33(3-4): 283-298.
[21]	ZACHRY B C, SCHROEDER J L, KENNEDY A B, et al, 2013. A case study of nearshore drag coefficient behavior during hurricane Ike (2008)[J]. Journal of Applied Meteorology and Climatology, 52(9): 2139-2146.

浮标	EXP1	EXP2	OBS(观测)
B1	2.17	1.88	1.87
B2	2.02	1.90	1.44
B3	1.61	1.31	1.24
B4	1.96	1.67	1.80
B5	1.05	0.97	0.62

The influence of a new drag coefficient scheme considering sea spay on numerical simulation of upper-ocean temperature response to tropical cyclone

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