**1. Introduction**

18 ATMOSPHERIC MODELS

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regional prediction system (ARPS), storm-scale numerical weather prediction and

The ocean is an indispensable source of energy for tropical cyclones (TCs). TCs enable extraction of heat and moisture from the sea surface through the transfer of turbulent heat energy in the atmospheric boundary layer. TCs are often generated where sea-surface temperature (SST) is higher than 26.5ºC (Palmén, 1948), and they intensify in areas that have high SST and deep oceanic mixed layer, thus having high upper-ocean heat content. Previous studies reported that TC intensity is related to 'tropical-cyclone heat potential', which is oceanic heat content integrated from the surface to the depth of the 26°C-isotherm (Wada & Usui, 2007; Wada, 2010). However, most of people believe that TCs intensify when SST is higher than 26-28ºC.

The oceans affect both the genesis and intensification of TCs, which in turn apply wind stresses to the ocean that induce sea-surface cooling (SSC) during their passages (Ginis, 1995). Numerous numerical modeling studies leave no doubt that SSC affects both the evolution of TCs and prediction of their intensities (Bender & Ginis, 2000; Wada et al., 2010). Nevertheless, uncertainties remain in the use of numerical models to predict TC intensity: these are related to initial atmospheric and oceanic conditions, the spatial and temporal resolution of the models, and the physical processes incorporated into the models (Wang & Wu, 2004; Wada, 2007). It may appear that a sophisticated model such as an atmospherewave-ocean coupled model can produce valid predictions of TC intensity when TC intensity predicted by that model matches best-track intensity derived from satellite observations. However, best-track intensity is not always valid, particularly in the western North Pacific where there is a lack of direct observation such as aircraft observations for measuring TC intensity directly. Furthermore, a coupled model that has successfully calculated TC intensities in one situation may provide erroneous results in another situation because of unexpected interactions among the specifications, physical processes, and initial and boundary conditions used in the model. One particular combination of model specifications and parameters may thus not always be valid for other TC predictions.

However, studies using a numerical model provide us scientific explanations on dynamical and physical processes associated with TC intensification. (Wada, 2009) explained the effects on TC intensification of atmospheric dynamics such as filamentation, the formation of

Effect of the Ocean on TC 45

enthalpy fluxes in the atmospheric surface-boundary layer, exchange coefficients for momentum and enthalpy transfers over the sea based on the bulk formulas of (Kondo, 1975), a turbulent closure model in the atmospheric boundary layer formulated from the work of (Klemp & Wilhelmson, 1978) and (Deardorff, 1980), and an atmospheric radiation

The JMANHM used here for numerical simulations of Typhoon Choi-wan in 2009 is an older version of the current nonhydrostatic mesoscale model of (Wada et al., 2010), but it is coupled with not only a multilayer ocean model but also a third-generation ocean-wave model developed for operational use at JMA (Wada et al., 2010). No cumulus

A reduced-gravity approximation, a hydrostatic approximation, and Boussinesq fluid are assumed in the multilayer ocean model. The model has three layers and four levels. The uppermost layer represents a mixed layer where density is vertically uniform, the middle layer represents a seasonal thermocline where the vertical temperature gradient is greatest, and the bottom layer is assumed to be undisturbed by entrainment. Entrainment is calculated by using a multi-limit entrainment formulation proposed by (Deardorff, 1983) and modified by (Wada et al., 2009). The model calculates water temperature and salinity at the surface and at the base of the mixed layer, and calculates layer thickness and 2-

The JMA third-generation ocean-wave model is coupled with JMANHM to estimate changes in surface roughness lengths, drag coefficients and enthalpy coefficients. The method of (Taylor & Yelland, 2001) in which surface roughness length over the ocean depends on wave steepness is adopted here. The detailed wave-ocean coupling procedure is

The atmosphere-ocean coupling procedure in MRINHM and JMANHM is as follows. Shortwave and long-wave radiation, sensible and latent heat fluxes, wind stresses, and precipitation are provided to the ocean model for every time step of the ocean model. Land and sea distributions extracted from GTOPO30 digital elevation data from the US Geological Survey are provided from the atmosphere model to the ocean model only at the initial time in order to adjust the land and sea distributions between the atmosphere and ocean models. Oceanic topography is provided by ETOPO-5 data from the National Oceanic and Atmospheric Administration (NOAA) National Geophysical Data Center; these elevations are spaced at 5-minute intervals of latitude and longitude. Conversely, SST calculated by the ocean model is provided to MRINHM and JMANHM for every time step

This study presents the results of two numerical experiments. One is a series of idealized numerical experiments applying MRINHM. MRINHM covers a 600 km x 600 km square computational domain with a horizontal grid spacing of 2 km. The other is a series of numerical simulations of Typhoon Choi-Wan in 2009 performed using JMANHM. JMANHM covers a 2700 km x 3600 km rectangular domain with a horizontal grid spacing of either 6 km or 12 km. Both MRINHM and JMANHM have 40 vertical levels with variable intervals from 40 m for the lowermost (near-surface) layer to 1180 m for the uppermost

parameterization was used in either MRINHM or JMANHM in this study.

scheme based on (Sugi et al., 1990).

dimentional flows for all three layers.

as described by (Wada et al., 2010).

of the ocean model.

**3. Experimental design** 

mesovortices and vortex Rossby waves. Mesovortices and vortex merger events are directly affected by SSC, which slows the formation of an annular potential-vorticity (PV) ring, whereas SST changes have little effect on the radius of maximum wind speed (MWS) at the mature phase of a TC when the annular PV ring is completely formed, even though mature TCs continue to cool the underlying ocean (Wada, 2009).

TC-induced SSC is caused mostly by vertical turbulent mixing in the oceanic mixed layer and upwelling below a seasonal thermocline. In addition, strong wind stresses that accompany TCs cause variations in sea state or surface roughness length, leading to changes in frictional velocity and exchange coefficients for drag and enthalpy. Breaking surface waves are caused by variations of sea state under high winds and the resultant high waves. The breaking surface waves play an essential role in mechanical mixing near the surface (Wada et al., 2010). However, improvement of vertical turbulent mixing schemes and parameterizations in the ocean model is a challenging issue owing to a lack of *in situ* observations under high winds.

Changes in exchange coefficients lead to changes in surface wind stresses and turbulent heat fluxes from the ocean to the atmosphere. The change in turbulent heat fluxes, particularly latent heat flux, enhances the secondary circulation of a TC through a planetary-boundarylayer process (Emanuel, 1986; Smith, 2008). In particular, turbulent heat fluxes vertically transferred from the warm ocean affect cloud microphysics and atmospheric radiation in the middle to upper troposphere, causing latent heat release through condensation, thus resulting in the formation of a warm core within the inner core of a TC.

These atmospheric dynamics are confined to within the inner core of a TC. We need also to consider the role of atmospheric and oceanic environmental influences, such as vertical shear, synoptic thermal stratification, and warm-core oceanic eddies with a few hundred kilometers, in the evolution of a TC. (Wada & Usui, 2010) reported that changes in preexisting oceanic conditions are synoptically related to the formation of spiral rainbands that accompanied Typhoon Hai-Tang in 2005 and are thus important for predictions of the intensity of Hai-Tang.

This chapter explores the effect of the ocean on TC intensity, intensification and structural change from the viewpoints of internal dynamical and pre-existing external atmospheric and oceanic environmental conditions. Section 2 describes the numerical model used in this study, and section 3 describes the experimental design. Section 4 provides the results of numerical experiments of an idealized TC and simulations of Typhoon Choi-Wan in 2009. The effect of the ocean on TC evolution at the mature phase and associated numerical issues are discussed in section 5. Section 6 presents the conclusion of this study.
