Dynamics of Atmospheres and Oceans Upper Ocean Response Of

Dynamics of Atmospheres and Oceans 47 (2009) 165–175 Contents lists available at ScienceDirect Dynamics of Atmospheres and Oceans journal homepage: www.elsevier.com/locate/dynatmoce Upper ocean response of the South China Sea to Typhoon Krovanh (2003) Jiang Xiaoping a, Zhong Zhong a,b,∗, Jiang Jing b a Institute of Meteorology, PLA University of Science and Technology, Nanjing 211101, China b Department of Atmospheric Sciences, Nanjing University, Nanjing 210093, China article info abstract Article history: To quantitatively investigate the dynamic and thermal responses of Available online 22 October 2008 the South China Sea (SCS) during and subsequent to the passage of a real typhoon, a three-dimensional, regional coupled air–sea model is developed to study the upper ocean response of the Keywords: SCS to Typhoon Krovanh (2003). Owing to the scarcity of ocean Coupled model observations, the three-dimensional numerical modeling with high South China Sea resolution, as a powerful tool, offers a valuable opportunity to Typhoon investigate how the air–sea process proceeds under such extreme Response conditions. The amplitude and distribution of the cold path pro- duced by the coupled model compare reasonably well with the TRMM/TMI-derived data. The maximum SST cooling is 5.3 ◦C, about 80 km to the right of the typhoon track, which is consistent with the well-documented rightward bias in the SST response to typhoons. In correspondence to the SST cooling, the mixed layer depth exhibits an increase; the increases in the mixed layer depth on the right of typhoon track are significantly higher than those on the left, with maxima of 58 m. This correspondence indicates that the SST cooling is caused mainly by entrainment. Under the influence of typhoon, a cyclonic, near-surface current field is generated in the upper ocean layer, which moves with the typhoon. The typhoon-induced horizontal currents in the wake of the storm have strong near-inertial oscillation, which gradually propagates downward. The unique fea- tures of the SCS response to Typhoon Krovanh are also discussed, such as Kuroshio intrusion and coastal subsurface jets. © 2008 Published by Elsevier B.V. ∗ Corresponding author at: Institute of Meteorology, PLA University of Science and Technology, Zhong Hua Men Wai, Nanjing 211101, Jiangsu, China. Tel.: +86 25 80830255; fax: +86 25 80830255. E-mail address: [email protected] (Z. Zhong). 0377-0265/$ – see front matter © 2008 Published by Elsevier B.V. doi:10.1016/j.dynatmoce.2008.09.005 166 X. Jiang et al. / Dynamics of Atmospheres and Oceans 47 (2009) 165–175 1. Introduction Strong atmospheric forcing events such as tropical cyclones and the upper ocean response represent an extreme case of mesoscale air–sea interactions (Polonsky et al., 1992). When a tropical cyclone propagates over the ocean surface, significant exchange of momentum, heat, and mass occurs at the air–sea interface, inducing an intense response of the ocean. The effects of tropical cyclones on the ocean are large, the horizontal extent may span several hundred kilometers, while the vertical depth may extend to 1000 m (Kwon and Riser, 2003). Observational and numerical studies on ocean responses to tropical cyclones have been conducted during the past decades. However, in light of the scarcity of ocean observations, numerical studies offer valuable opportunities to investigate the evolution of air–sea processes under such extreme conditions. Undoubtedly, providing accurate wind stress forcing and thermal fluxes is vital to proper simulation. Zedler et al. (2002) simulated the temperature evolution during the passage of Hurri- cane Felix (1995) using four one-dimensional mixed layer models: Price–Weller–Pinkel (PWP), K Profile Parameterization (KPP), Mellor–Yamada (MY) 2.5, and a modified version of MY 2.5 (MY2). The surface heat flux and wind-forcing time series were constructed using mooring measurements of wind speed and direction. In the numerical experiment of Jacob and Shay (2003), constant air temperature and humidity were assumed to estimate the surface heat fluxes. Rao et al. (2004) studied the response of a coastal ocean excited by a tropical cyclone in the Bay of Bengal using a three- dimensional numerical model. In their study, the model was used to understand the dynamic and thermal responses of the ocean to different cyclonic systems approaching from different directions, but ignoring the effect of air–sea heat exchange on the tropical cyclone-induced sea surface temperature (SST) cooling. Wada (2005) simulated the ocean response to Typhoon Rex (1998) using a mixed layer model. As the atmospheric forcing field, the global analysis (GANAL) data implanted a typhoon-like vortex was used. Sheng et al. (2006) adopted a nested-grid ocean circulation modeling system to assess the upper ocean response of the Scotian Shelf and adjacent slope to Hurricane Juan (2003). A simple Rankine vortex was used to represent the wind stress associated with the hurricane. A mesoscale air–sea coupled model is a useful tool for the study of tropical cyclone–ocean interactions. Coupled models describe the feedback between the tropical cyclone and ocean, which is important both for storm development and the ocean response. For example, the effects of atmo- spherically forced sea state variation on the atmospheric boundary layer and the effects of oceanically forced atmospheric variation on the upper ocean can be addressed. However, most numerical studies on tropical cyclone–ocean interactions have focused on the effects of the SST cooling on the tropical cyclone (Bender and Ginis, 2000; Hong et al., 2000; Chan et al., 2001; Zhu et al., 2004). Few numerical studies have been conducted on the upper ocean response to a tropical cyclone using a real-case forcing field provided by a coupled atmospheric model. The South China Sea (SCS) is the largest marginal sea in the Northwest Pacific. Because of its semien- closed nature, the SCS is subject to high spatial and temporal variability from external forcing factors. One significant source of variability is the tropical cyclones that routinely affect the region. On average, 10.3 tropical cyclones pass through the SCS annually (Wang et al., 2007). However, due to the difficulty of making shipboard measurements during and even after the passage of tropical cyclones and the sparseness of moored instrumentation, observational studies on the upper ocean response of SCS to tropical cyclones are rare. Up to the present, numerical simulations of the upper ocean response to tropical cyclones in the SCS are very few in number. Chu et al. (2000b) used the Princeton Ocean Model (POM) to study the response of the SCS to Typhoon Ernie (1996). A tropical cyclone wind profile model was used to simulate the wind stress caused by Ernie and to force POM. To examine the dynamic and thermal responses of the SCS to a real typhoon, we developed a mesoscale coupled air–sea model based on the nonhydrostatic mesoscale model MM5 (Pennsylvania State University-National Center for Atmospheric Research fifth-generation Mesoscale Model) and the regional ocean model POM, and the upper ocean response to Typhoon Krovanh (2003) was investigated. The outline of this paper is as follows: Section 2 briefly describes the development of the coupled model. The thermal response to Typhoon Krovanh is discussed in Section 3, while the dynamic response is analyzed in Section 4. Summary and conclusions are presented in Section 5. X. Jiang et al. / Dynamics of Atmospheres and Oceans 47 (2009) 165–175 167 2. The coupled model 2.1. Brief description of Krovanh (2003) and the models Typhoon Krovanh (2003) was selected for the case study. Krovanh originally developed as a tropical depression on August 17. It intensified into a tropical storm on August 20 and reached typhoon strength on August 22. Adopting a west-northwest track, Krovanh entered SCS on August 23 and then moved across the northern part of SCS. After skirting the northeastern part of Hainan Province, China, Krovanh entered Beibu Wan on August 25 and weakened into a severe tropical storm on August 26 after making landfall over northern Vietnam. It further weakened into a tropical storm and dissipated inland. In this study, POM is implemented in the domain of 0◦Nto30◦N and 99◦Eto130◦E, covering all of the SCS and the western portion of the Pacific. A uniform horizontal resolution of 0.25◦ × 0.25◦ is used. In the vertical, there are 21 sigma layers with a finer resolution over the upper ocean. The external time step is taken to be 60 s, and internal time step 1800 s. The western boundary is fixed and the other three boundaries are open. The monthly velocity, elevation, salinity, and temperature fields from the Simple Ocean Data Assimilation (SODA) data are interpolated to the model grid as dynamic forcing at the open boundaries, with the in- and out-flux being balanced (Alfonso et al., 2000; Ezer and Mellor, 2000). The gravity wave radiation condition is used for the velocity component perpendicular to the open boundaries. An upwind-advection scheme is applied to the temperature, salinity, and velocity components parallel to the boundary so that in case of inflow, the boundaries conditions derived from the SODA data are imported by inward velocities. MM5 uses one nested domain with a grid spacing of 15 km and 29 terrain-following coordinate surfaces in vertical. The time step is 50 s. The model initial conditions and lateral boundary conditions are obtained from the NCEP 1◦ × 1◦ reanalysis data. Because the NCEP analysis contains a vortex weaker than the observed, an observation-based vortex is implanted into the model initial conditions (Davis and Lownam, 2001). The model physics include the Betts–Miller cumulus parameterization scheme (implicit) and the Reisner II (explicit) microphysics scheme.

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