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A Numerical Study of Megi (2010). Part I: Rapid Intensification

HUI WANG Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, , and International Pacific Research Center and Department of Meteorology, School of Ocean and Earth Science and Technology, University of Hawai‘i at Manoa, Honolulu, Hawaii

YUQING WANG International Pacific Research Center and Department of Meteorology, School of Ocean and Earth Science and Technology, University of Hawai‘i at Manoa, Honolulu, Hawaii, and Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China

(Manuscript received 21 February 2013, in final form 14 August 2013)

ABSTRACT

Typhoon Megi (15W) was the most powerful and longest-lived (TC) over the western North Pacific during 2010. While it shared many common features of TCs that crossed Island in the northern , Megi experienced unique intensity and structural changes, which were reproduced reasonably well in a simulation using the Advanced Research Weather Research and Forecasting Model (ARW-WRF) with both dynamical initialization and large-scale spectral nudging. In this paper processes responsible for the rapid intensification (RI) of the modeled Megi before it made landfall over Luzon Island were analyzed. The results show that Megi experienced RI over the warm ocean with high ocean heat content and decreasing environmental vertical shear. The onset of RI was triggered by convective bursts (CBs), which penetrate into the upper troposphere, leading to the upper-tropospheric warming and the formation of the upper-level warm core. In turn, CBs with their roots inside of the eyewall in the boundary layer were buoyantly triggered/supported by slantwise convective available potential energy (SCAPE) accumulated in the region. During RI, convective area coverage in the inner-core region was increasing while the updraft velocity in the upper troposphere and the number of CBs were both decreasing. Different from the majority of TCs that experience RI with a significant eyewall contraction, the simulated Megi, as the observed, rapidly intensified without an eyewall contraction. This is attributed to diabatic heating in active spiral rainbands, a process previously proposed to explain the inner-core size increase, enhanced by the interaction of the typhoon vortex with a low-level synoptic depression in which Megi was embedded.

1. Introduction and JTWC upgraded it to a category-1 typhoon. On 15 October, JMA upgraded Megi to a typhoon. Megi (15W) was first identified as a tropical distur- As shown in Fig. 1, Megi initially moved northwest- bance over the western North Pacific (WNP) by the ward and then turned west-southwestward. It experi- Joint Typhoon Warning Center (JTWC) on 12 October enced two periods of intensification before it made 2010. The Meteorological Agency (JMA) and landfall at Luzon Island in the northern Philippines. The JTWC began to monitor the low pressure circulation as first intensification occurred from 1200 UTC 12 October a tropical depression (TD). The TD further intensified to 0000 UTC 15 October during which the maximum into a tropical storm (TS), named Megi by JMA at 21 1200 UTC on 12 October. Later on 14 October, the eye 10-m wind speed increased by 35 m s and the central of the storm could be clearly seen from satellite image sea level pressure (SLP) dropped by 45 hPa. The second and JMA thus upgraded Megi to a severe tropical storm intensification occurred from 0000 UTC 16 October to 1200 UTC 17 October. During this 36-h period the 2 maximum 10-m wind speed also increased by 35 m s 1 Corresponding author address: Dr. Yuqing Wang, IPRC/SOEST, while the central SLP dropped by 52 hPa. In the end, Rm. 409G, POST Bldg., University of Hawai‘i at Manoa, 1680 East–West Rd., Honolulu, HI 96822. Megi attained its peak intensity with a central SLP of 2 E-mail: [email protected] 905 hPa and a maximum 10-m wind speed of 80 m s 1,

DOI: 10.1175/MWR-D-13-00070.1

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FIG. 1. (a) Track of (2010) with every 6-h position indicated by solid circles with different colors for different categories 2 in storm intensity, (b) the storm’s central sea level pressure (hPa), and (c) the maximum sustained 10-m wind speed (m s 1)from0000UTC 12 Oct to 0600 UTC 24 Oct 2010 based on the JTWC best track data. The modeled track, central sea level pressure, and maximum 10-m wind speed from 0000 UTC 15 Oct to 0000 UTC 22 Oct are also shown in red. the most powerful supertyphoon over the WNP and Province, China, on 23 October and finally became a TD (SCS) in 2010. Based on the definition and dissipated gradually on the next day. of rapid intensification (RI) by Holliday and Thompson While Megi shared many common features of TCs (1979) for WNP tropical cyclones (TCs) and Kaplan and that crossed Luzon Island (Chou et al. 2011), it also DeMaria (2003) for Atlantic TCs,1 the first intensifica- experienced some unique intensity, structural, and track tion was not rapid. However, the second intensification changes. In addition to the subtle track and intensity can be classified as an RI case according to the definition changes (Fig. 1), Megi also experienced interesting proposed by Kaplan and DeMaria (2003). In this study, structural changes (Fig. 3). For example, deep convec- we will focus on the second intensification period, namely tion in the eyewall was widening without any signal of an the RI phase of Typhoon Megi. During the RI period, eyewall contraction during RI. This is different from the Typhoon Megi moved west-southwestward east of the majority of TCs experiencing RI. The RI ended as a Philippines over the WNP with high sea surface temper- concentric eyewall signal appeared before it made land- ature (SST) and high upper-ocean heat content (OHC) as fall over Luzon Island (Fig. 3), a not uncommon process shown in Fig. 2, both of which are favorable ocean con- at the end of an RI event (e.g., Kossin and Sitkowski ditions for RI of a TC (Lin et al. 2008). 2009), but with the concentric eyewall cycle being in- Megi made landfall over Luzon Island at around terrupted by landfall for the Megi case. The storm ex- 0330 UTC on 18 October. It weakened to a category-2 perienced an eyewall breakdown when it crossed Luzon typhoon immediately after its landfall. After crossing Island, and later on, a new outer eyewall formed at a Luzon Island, Megi entered the SCS and turned north- larger radius as a result of the axisymmetrization of outer westward and then suddenly north-northeastward on spiral rainbands after Megi entered the SCS (Fig. 3). Soon 20 October. During its northwest-to-north turning after, a small inner eyewall, which could have been the motion over the SCS on 19 October, Megi slowed down redevelopment of its original eyewall, appeared for sev- as it reintensified from category 2 to category 4 with a eral hours when it moved over the SCS. This could be the central SLP of 935 hPa and a maximum 10-m wind speed first double-eyewall structure observed to date as a result 2 of 57 m s 1. Early on 20 October, Megi turned north- of the reappearance of the original eyewall within a newly northeastward. It then weakened to a tropical storm, formed outer eyewall. Compared with the well-studied and made its second landfall at Zhangpu in of 1998 (Wu et al. 2003, 2009), Megi ex- perienced much richer structural changes, such as the lack of the eyewall contraction during RI before landfall and the development of the concentric eyewall structure, as 1 RI was defined as the deepening rate of greater than 2 42 hPa day 1 in the central SLP by Holliday and Thompson (1979) well as a reintensification as it entered the SCS. 2 2 for western Pacific TCs and as 15 m s 1 day 1 in the maximum 10-m In this study, based on a reasonable, week-long con- wind speed by Kaplan and DeMaria (2003) for Atlantic TCs. trol simulation of Typhoon Megi in Wang et al. (2013),

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22 FIG. 2. (a) Satellite altimetry SST (8C) and (b) the upper OHC (kJ cm ) on 17 Oct 2010 (shadings and white contours), overlapped with the track of Typhoon Megi (2010) from JTWC, with the storm track overlaid with the colored circles, indicating the intensity of the storm according to the Saffir–Simpson scale, which were produced by the Remote Sensing Laboratory at National University and can be accessed online (http://data.eol.ucar.edu/codiac/dss/id5209.027). we focus on understanding some unique features of control simulation. The RI processes of the simulated Megi, including its RI with no eyewall contraction, its Megi are analyzed in section 3. Our major results are structural changes during its landfall over Luzon Island, summarized and discussed in the final section. and its reintensification after it entered the SCS. In this paper, after a brief introduction of the high-resolution 2. Model setup, dynamical TC initialization, and control simulation of Megi, we will present the analyses verification of simulation of RI before Megi made landfall over Luzon Island. The a. Model setup rest of the paper is organized as follows. Section 2 de- scribes briefly the model setup, the dynamical initiali- The numerical simulation for Typhoon Megi presented zation for Typhoon Megi, and the verification of the in this study was performed using version 3.3.1 of the

FIG. 3. The satellite images at given times showing (top) the structural change before Typhoon Megi (2010) made landfall over Luzon Island and (bottom) the remarkable structural changes when the typhoon crossed Luzon Island and after it entered the SCS.

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TABLE 1. Configuration of the ARW-WRF used for the simulation of Megi in this study.

Domain Mesh 1 Mesh 2 Mesh 3 Grid points (x, y) 455 3 375 436 3 436 328 3 328 Grid size (km) 18 6 2 Land data resolution 5 min 2 min 30 s Time step (s) 54 18 6 Longwave radiation RRTM (Hong and Lim 2006) RRTM RRTM Shortwave radiation Dudhia (Dudhia 1989) Dudhia Dudhia Cloud microphysics WSM6 (Hong and Lim 2006) WSM6 WSM6 Cumulus convection Kain–Fritsch (Kain 2004) No No PBL scheme MYNN2.5 (Nakanishi and Niino 2004) MYNN2.5 MYNN2.5 Surface flux over ocean Monin–Obukhov (Moon et al. 2007) Monin–Obukhov Monin–Obukhov Land surface processes Noah (Ek et al. 2003) Noah Noah

Advanced Research Weather Research and Forecasting model was initialized at 0000 UTC 15 October 2010 Model (ARW-WRF; Skamarock et al. 2008). Details of and integrated for 168 h up to 0000 UTC 22 October. the model settings can be found in Wang et al. (2013). The model initial and lateral boundary conditions for Table 1 summarizes the main parameters and selections both the dynamical TC vortex initialization and the of different physics parameterizations used in the sim- model simulation were interpolated from the National ulation. The model domain is two-way interactive and Centers for Environment Prediction (NCEP) Global triply nested (Fig. 4). The three meshes have sizes of Forecast System (GFS) Final Analysis (FNL), which 455 3 375, 436 3 436, and 328 3 328 grid points and has horizontal resolution of 18318 on 27 uneven horizontal grid spacings of 18, 6, and 2 km, respectively. pressure levels. The daily SST dataset at 18318 res- The resolutions of the terrain height and land-use data for olution is also from the GFS FNL. Since our interest the three meshes are 5 min, 2 min, and 30 s (about 9, 4, is in achieving improved simulation, not prediction, and 1 km), respectively. There are 36 uneven s levels we applied spectral nudging (SN) to preserve the in the vertical using terrain-following, hydrostatic pressure large-scale flow with wavelengths longer than 1000 km as the vertical coordinate extending from the surface to the both in the dynamical initialization and throughout model top at 50 hPa. While the outermost 18-km mesh is the model simulation (Wang et al. 2013). This is ac- fixed, the two nested inner meshes automatically move ceptable since our focus is on both subsynoptic- and following the TC during the model integration so that mesoscale processes. The large-scale SN is only ap- the model TC is always located near the mesh centers. plied to the outermost domain, which provides the The model physics include (i) the WRF single-moment lateral boundary conditions to the two nested inner 6-class cloud microphysics scheme (WSM6; Hong and meshes. Lim 2006) for grid-scale moist processes; (ii) the Mellor– Yamada–Nakanishi–Niino (MYNN) level-2.5 turbulence closure scheme (Nakanishi and Niino 2004) for subgrid- scale vertical mixing coupled with the Monin-Obukhov similarity theory for surface flux calculations over the ocean where the roughness length for momentum is modified for TC strength winds (Moon et al. 2007); (iii) the Rapid Radiative Transfer Model (RRTM; Mlawer et al. 1997) for longwave radiation calculation and the Dudhia scheme (Dudhia 1989) for shortwave radiation calculation; (iv) the Noah land surface scheme (Ek et al. 2003) for land surface processes; and (v) the Kain–Fritsch scheme (Kain 2004) for subgrid-scale deep and shallow convection parameterization in the outermost domain. Convection is assumed to be explicitly resolved in the two nested inner meshes. Dissipative heating is considered in all meshes.

The simulation discussed in this study was the con- FIG. 4. Model domains with triply nested, movable meshes used for trol simulation documented in Wang et al. (2013). The the Typhoon Megi (2010) simulation in this study.

Unauthenticated | Downloaded 10/03/21 09:59 PM UTC JANUARY 2014 W A N G A N D W A N G 33 b. Dynamical initialization for Typhoon Megi over Luzon Island, the rapid weakening over Luzon Island, and the reintensification of the storm after it Since both the intensity and structure of Typhoon enteredtheSCS.However,themodelfailedtosimu- Megi in the FNL are unrealistic (not shown), we used the late the slow weakening in the last 2 days of the simu- dynamical initialization (DI) scheme with the large-scale lation and thus overestimated the storm intensity after SN to spin up the axisymmetric TC vortex, as docu- 0600 UTC 20 October when the storm moved north- mented in Wang et al. (2013). The core of the DI scheme northeastward over the SCS. This might be partially due is to spin up the axisymmetric TC vortex through the 3-h to the exclusion of the negative ocean feedback because cycle runs [instead of 1-h cycle runs used in Nguyen and the daily mean SST was used in the simulation. Chen (2011)] and the combined use of the large-scale Verification of the simulated storm structure is diffi- SN. This allowed the TC vortex to better adapt to the cult since few observations are available over the open environment and to achieve the dynamical balance more ocean. Here, we compare the modeled and satellite- sufficiently. The vortex separation algorithm developed observed infrared cloud-top brightness temperature by Kurihara et al. (1993) and later modified by Nguyen (TBB) during the RI period. The modeled TBB was and Chen (2011) was utilized to subtract the axisym- calculated based on our outgoing longwave radiation metric vortex. In the first cycle run, the axisymmetric (OLR) and the satellite TBB is the high-resolution (1 km) TC vortex in the FNL was relocated to the observed TC Multifunctional Transport Satellite (MTSAT) infrared center. From the second cycle run, the axisymmetric TC image. Figure 5 shows the modeled and satellite-observed vortex from the current cycle run was used to replace TBB at three given times. At 0300 UTC 16 October just the axisymmetric TC vortex in the previous cycle run. after RI started, Megi displayed considerable convec- The cycle run was repeated until the intensity of the TC tive asymmetric structure in the eyewall with an en- vortex was comparable to that observed. hanced convective area in the northwest quadrant and The DI scheme was used to spin up Typhoon Megi at outer spiral rainbands that extended southeastward 0000 UTC 15 October 2010. After five cycle runs, the east of the eyewall. By 2000 UTC 16 October, Megi intensity of the modeled Megi with the central SLP was was in the middle of RI and showed a clear eye and 956.4 hPa and the maximum 10-m sustained wind speed 2 closed eyewall with a rainband extended from the north was 45.2 m s 1, which are comparable with the observed 2 to the east. By 2300 UTC 17 October, just several hours results in the JTWC best track data (956 hPa and 45 m s 1, before the storm made landfall, the storm increased respectively). However, in the FNL field, the central its convective coverage in the inner-core region with SLP pressure of the TC vortex is 1002 hPa, which is too a much-widened eyewall and somewhat of an increase weak compared to the 956 hPa from the JTWC best track in the eye diameter. data, mainly because the storm core was not resolved well The modeled TBB is not as low as the observed, in- in the coarse-resolution global analysis. dicating that convection in the eyewall in the simulation was not as deep as in the observation. This might be c. Verification of simulation partly because the model resolution is not high enough The track and intensity of the simulated Megi are to resolve the convective cores in the eyewall and partly compared with those from the JTWC best track data in because the model vertical grid spacing is not high Fig. 1. The model simulated the west-northwestward enough near the cloud top to properly resolve the thick movement in the first 2 days and the west-southwestward cirrus outflow cloud structure. In spite of the systematic movement before the storm made landfall over Luzon bias in TBB, the modeled Megi shows a relatively larger Island. The location of landfall over Luzon Island was eye size than the observed. Nevertheless, the modeled also captured in the model simulation except that the storm has a similar trend in the widening of the eyewall simulated storm made landfall about 4–5 h later than during RI to the observed Megi. Realistic simulation of the observed. Nevertheless, the model captured nicely the eyewall structure and its evolution are still quite the timing of the observed northward-turning motion on challenging. Therefore, in our analysis below we keep 20 October (Fig. 1a). This can be attributed to the use of in mind that the simulated Megi is not the real Typhoon the large-scale SN, which kept the large-scale environ- Megi. Nevertheless, we consider that understanding of mental flow in the model simulation close to that in the the model Megi could still have implications for the FNL, as demonstrated in Wang et al. (2013). real Typhoon Megi. Note that we only focus on the RI The model simulated reasonably well the intensity phase of the modeled Megi in this part of this paper, the change as well in terms of the central SLP and the max- detailed structural changes after Megi made landfall imum sustained surface wind speed (Figs. 1b and 1c). The and entered the SCS will be analyzed in a forthcoming model captured the RI of Megi before it made landfall Part II.

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FIG. 5. (a)–(c) (top) The model-simulated TBB (8C) and (bottom) the satellite infrared high-resolution (1 km) TBB at times given at the top of each panel for Typhoon Megi.

3. RI of Typhoon Megi due to ocean upwelling resulting from the intensifying cyclonic wind stress curl and turbulent vertical mixing Megi experienced its RI from 0000 UTC 16 October across the mixed layer base (Cione and Uhlhorn 2003; to 1200 UTC 17 October and reached its peak intensity Lin et al. 2008). Megi traveled over the warm WNP with with a central SLP of 905 hPa and a maximum 10-m wind 8 21 SSTs above 29 C along its track (Fig. 2a) and high upper speed of 80 m s . In this section, the RI processes of 2 OHC of over 100 kJ cm 2 (Fig. 2b) during its RI period. the modeled Megi will be analyzed based on the high- Therefore, the ocean conditions are favorable for the RI resolution model simulation discussed in section 2c. Fol- of Typhoon Megi. lowing the analysis of Rogers (2010), we will discuss the VWS is a key atmospheric parameter for the RI of large-scale settings, vortex-scale evolution, and convective a TC. A common explanation of the effect of VWS activities during RI of the simulated Megi. concerns the ventilation of the upper-level warm core relative to the low-level cyclonic circulation, inhibiting a. Large-scale settings the deepening of a TC (Gray 1968). Weak VWS can The RI of a TC often occurs under some favorable ensure that the warm core forms and is maintained over environmental conditions, including high SST and large the low-level cyclonic circulation center and thus is fa- upper OHC, weak vertical wind shear (VWS), and high vorable for RI. Megi intensified rapidly when the VWS 2 midtropospheric relative humidity (Molinari et al. 1995; magnitude decreased sharply from 10–12 to 1–2 m s 1, Bosart et al. 2000; Kaplan and DeMaria 2003; Lin et al. regardless of the fact that the averaged winds were cal- 2008). In particular, both the OHC and VWS are key culated in the inner-core region or a large area (Fig. 6). environmental parameters for RI (Park et al. 2013). A This is consistent with the result of Chen and Zhang TC experiencing RI obtains considerable energy from (2013) for (2005). Note that the VWS the underlying ocean. High upper OHC serves as the calculated from the model simulation (Fig. 6) has the energy source for RI and also limits the negative effect same trend as that calculated from the FNL but the

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mean tangential wind is consistent with the widening of the eyewall convection in both the observed and simu- lated Typhoon Megi, as seen in Fig. 5. Although this outward expansion is partly a result of the storm in- tensification, showing little evidence of outward expan- sion of the normalized azimuthal mean tangential wind by its maximum value at the corresponding time (Fig. 8a), it also indicates an increase of inner-core size as inferred from the widening of eyewall convection as already FIG. 6. Time evolution of vertical wind shear over the storm, discussed in Wang and Wang (2013). This is in sharp shown are large-scale shear averaged between radii of 502 and contrast to the majority of TCs during RI, where an 900 km (dotted) and shear between radii of 396 and 600 km (dashed) from domain 2, as well as shear averaged within 250-km radius in eyewall contraction often occurs during RI with little the nested domain 3 (solid). increase in the outer-core circulation strength (Ooyama 1982; Schubert and Hack 1982; Holland and Merrill 1984; magnitude is slightly larger, partially due to the coarse Rogers 2010). resolution of the FNL (not shown). Similar to the time evolution of the azimuthal mean Figure 7 shows the 200- and 850-hPa geopotential and tangential wind, the azimuthal mean vertical motion wind fields at 0000 UTC 15 and 17 October from the shows an eyewall contraction in the first 18 h of simu- FNL. On 15 October prior to RI, Megi already de- lation as well but shows no eyewall contraction during veloped an outflow layer with an outflow jet toward the the subsequent RI period (Fig. 8b). In addition to strong northeast and then east-southeast at 200 hPa (Fig. 7a). eyewall updrafts, relatively large azimuthal mean up- The main midlatitude westerlies were located north of ward motion outside the eyewall reflects active spiral 308N, far away from Megi. In the lower troposphere, rainbands throughout the simulation. This suggests Megi was located south-southwest of the WNP sub- the possible contribution of diabatic heating in spiral tropical high and was embedded in a large-scale cyclonic rainbands in preventing the eyewall contraction and circulation (depression) centered near 108N, 1308Eto meanwhile increasing the outer-core strength (and the the south-southwest of Megi (Fig. 7c). By 17 October inner-core size) of the simulated Megi during RI (Wang during RI, the upper-level outflow intensified signifi- and Wang 2013), a process previously proposed to ex- cantly (Fig. 7b). In addition to the outflow jet to the plain the inner-core size increase in idealized simula- northeast, an outflow channel appeared southwest of tions by Wang (2009) and Xu and Wang (2010a,b). the storm center. At this point, the midlatitude upper- Figure 8c shows the time evolution of the normalized tropospheric westerlies extended southward, reaching inertial stability (normalized by the square of the Coriolis 258N and potentially enhancing the outflow jet to the parameter) at the lowest model level in the simulated northeast of the storm (Fig. 7b). In the lower tropo- Megi. Inertial stability2 is an important dynamical sphere (Fig. 7d), Megi was still located in the easterlies parameter that can measure the resistance to radial in- south of the WNP subtropical high. flow and also determine the efficiency of the upper- tropospheric warming by eyewall heating (Shapiro and b. Vortex- (storm) scale evolution Willoughby 1982; Hack and Schubert 1986). Rogers Figure 8 shows the time evolution of several azimuthal (2010) suggested that the time evolution of inertial sta- mean variables of the simulated Typhoon Megi. Megi bility in the inner core could be an indicator of whether exhibited a slow contraction in the first 18 h of simula- a TC is undergoing its RI. The inertial stability in the tion before it started its RI phase as inferred from the simulated Megi shows an off-center maximum inside the time evolution of the azimuthal mean tangential wind RMW prior to and during RI. This distribution is con- (Fig. 8a). The radius of maximum wind (RMW) of the sistent with the off-centered maximum relative vorticity simulated Megi was reduced by about 10 km from 50 to or potential vorticity (PV) distribution in the lower 40 km during this period. Although the RMW remained troposphere in a TC (e.g., Wang 2008a). After the onset almost unchanged during the subsequent RI phase, the of RI on 0000 UTC 16 October, inertial stability inside tangential wind field expanded outward considerably until the end of RI just before Megi made landfall over

Luzon Island. For example, the radius of the azimuthal 2 21 Inertial stability is defined as for an axisymmetric vortex, where mean hurricane force wind (33 m s ) was doubled, from f is the Coriolis parameter at the storm center, y is the azimuthal 105 km at 0000 UTC 16 October to 210 km at 2100 UTC mean tangential wind, and r is radius. Here, we show the normal- 17 October. This outward expansion of the azimuthal ized inertial stability, which is defined as I2/f 2.

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FIG. 7. Wind vectors and geopotential height field (contours, gpm) from the NCEP GFS FNL at (a),(b) 200 and (c),(d) 850 hPa at 0000 UTC on (a),(c) 15 and (b),(d) 17 Oct 2010. the RMW increased steadily as Megi intensified. Note the strengthening of the radial mass and moisture con- that although inertial stability is the highest inside the vergence in the boundary layer, contributing to strong RMW, relatively high azimuthal mean inertial stability eyewall updrafts and intense convection in the eyewall. is obvious outside the RMW and expanded radially Latent heating released in eyewall convection would outward during RI. This outward expansion of relatively effectively enhance the upper-tropospheric warming of high inertial stability is consistent with the outward ex- the high inertial stability core (Schubert and Hack 1982) pansion of the azimuthal mean tangential wind and the and lower the central SLP of the storm. The latter in turn increase in the inner-core size. would drive stronger boundary layer inflow, further Radial inflow in the boundary layer penetrated pro- enhancing eyewall updrafts and convection. This forms gressively inward outside the RMW and decelerated a positive feedback (among inertial stability, eyewall sharply near the RMW where the radial gradient in in- updraft and convection, and upper-tropospheric warm- ertial stability is the largest (Fig. 8c). The maximum ing) that contributes to RI of the simulated Megi, as 2 azimuthal mean radial inflow was only about 10 m s 1 collectively discussed in earlier studies (e.g., Ooyama 2 prior to the onset of RI but increased to 20 m s 1 near 1982; Schubert and Hack 1982; Hack and Schubert 1986; the radius of about 50 km immediately outside the eye- Vigh and Schubert 2009; Smith et al. 2009). wall by the end of RI. The increase in both low-level Another important parameter is the axisymmetricity, inflow and inertial stability inside the RMW implies which is a measure of the degree of axisymmetry for a

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21 FIG. 8. The radius–time cross section of the azimuthal mean (a) tangential wind (m s ) at 1-km height (contours) 2 normalized by the maximum value at a given time (shading), (b) vertical velocity (cm s 1) at 3-km height, (c) nor- 2 malized inertial stability (shading) and radial wind (m s 1, contours) at the lowest model level (about 28 m above the 2 surface), and (d) surface rain rate (mm h 1).

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FIG. 9. Radius–time cross section of the axisymmetricity parameter averaged in the layers between (a) 2 and 6, (b) 7 and 11, and (c) 12 and 16 km, respectively.

TC vortex (e.g., Fudeyasu et al. 2010; Miyamoto and with the onset of RI, in particular in the middle tropo- Takemi 2013). Fudeyasu et al. (2010) defined the axi- sphere in the simulated Megi case. The axisymmetriza- symmetricity as the ratio of the azimuthal mean kinetic tion started from the mid- to lower troposphere upward energy to the total kinetic energy within a radius of during RI. The maximum axisymmetricity parameter 301 km. Miyamoto and Takemi (2013) defined the axi- (close to 1.0) appeared just outside the eyewall where symmetricity as the ratio of the squared azimuthal the filamentation time is relative short (Rozoff et al. mean PV to the azimuthal mean squared total PV. 2006; Wang 2008a). The storm became more axisym- Here, following Fudeyasu et al. (2010), we define the metric at larger radii during RI. axisymmetricity using kinetic energy. Note that instead The axisymmetrization during RI was also a sub- of the area-averaged axisymmetricity used in Fudeyasu sequence of the merging of a low-level synoptic de- et al. (2010), we calculated the axisymmetricity for each pression into the typhoon vortex. As already discussed radial band of 2 km to examine the time evolution of axi- in Wang and Wang (2013), there was a binary interac- symmetricity as a function of radius and height. Figure 9 tion between the typhoon vortex and a low-level syn- shows the time evolution of the axisymmetricity in the optic depression in which Megi was embedded prior simulated Typhoon Megi as a function of the radius av- to RI (Figs. 7c and 7d). This binary interaction played eraged in three layers, representing the lower, middle, a critical role in causing the inner-core size increase of and upper troposphere, respectively. Consistent with Megi during its RI phase. On one hand, the shear de- earlier studies, the storm experienced axisymmetrization formation, filamentation, and merging of the low-level

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FIG. 10. CFAD (%) of simulated vertical velocity within 80-km radius in 24-h periods on (a) 15, (b) 16, and (c) 17 Oct. synoptic-scale depression by the typhoon vortex and of the CFADs 24 h prior to and after the onset of RI the subsequent axisymmetrization enlarged both the were very similar, with peak updrafts at 13–14-km alti- inner- and outer-core sizes of Megi considerably. On the tude. Large differences occurred on the second day of other hand, the binary interaction also played a role in RI (17 October; Fig. 10c). Compared to the first day of triggering/enhancing active spiral rainbands in Megi. RI, the intense updrafts (top 0.01%) were largely re- Diabatic heating in spiral rainbands drove inflow in the duced at the upper levels but increased at the middle mid- to lower troposphere, accelerating tangential winds levels, with the peak of updrafts at 8–9-km altitude. outside the RMW, leading to the significant outward Another distinct feature were the greatly reduced down- expansion of the tangential wind and thus the inner-core drafts, in particular in the mid- to upper troposphere. size increase of the storm. This also prevented the The downdrafts showed a second peak in a layer between eyewall’s contraction during its RI phase. 4- and 5-km altitude. This was where the freezing level was located in the inner-core region, suggesting that c. Convective-scale structure and evolution downdrafts were driven by both the melting of snow and Convective activity in the inner-core region is the key graupel and the evaporation of rain. The upper-level to the upward transport of energy gained from the ocean peak in downdrafts on 15 and 16 October could be par- to the atmosphere above and, thus, is critical to the in- tially due to sublimation of ice-phase hydrometeors par- tensification and maintenance of a TC. Here, we will tially forced by large vertical wind shear (Fig. 6). examine the convective-scale structure and evolution in The above features of vertical velocity in the inner- the simulated Megi prior to and during its RI stage fol- core region can be seen more clearly in the time evo- lowing the analysis done by Rogers (2010). We first ex- lution of the cumulative contour frequency for both amine the contoured frequency by altitude diagrams updrafts and downdrafts within a radius of 80 km at (CFADs; Yuter and Houze 1995) for vertical velocity; three altitudes (2, 8, and 13 km), as plotted in Fig. 11. The the CFADs illustrate the frequency distribution of the three levels are chosen as representatives of the lower, vertical velocity of the indicated values at different alti- middle, and upper troposphere, respectively. The distri- tudes. Figure 10 shows 24-h-averaged CFADs of the bution of the cumulative contour frequency for vertical 2 simulated vertical velocity binned every 0.1 m s 1 at each motion shows upward motion confined mostly within 2 altitude within a radius of 80 km. Three panels in Fig. 10 4ms 1 throughout the depth of the troposphere during show the three stages of the simulated Megi: prior to and the analyzed time period. There are also differences in after the onset of RI, and during RI, respectively. magnitude from the middle to the upper troposphere: A comparison of the vertical velocity CFADs 24 h the outliers (the envelope of the extreme values) at 8-km prior to and after the onset of RI (Figs. 10a and 10b) in- altitude increased during RI, while those at the upper dicates that the distributions are broader on 16 October levels showed a shrinking trend. The outliers of the up- 2 after the onset of RI, with peak updrafts of 24 m s 1 and ward motion at 13 km increased prior to RI and reached 2 downdrafts of 28ms 1 compared to peak updrafts of their maximum at the beginning of RI, and then de- 2 2 20 m s 1 and downdrafts of 211 m s 1 on 15 October prior creased continuously during RI. A similar narrowing of to the onset of RI. Nevertheless, the overall distributions the outliers in vertical velocity in the upper troposphere

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FIG. 11. Cumulative contour frequency of distributions of vertical velocity within 80-km radius as a function of time for the simulated Typhoon Megi at (a) 2-, (b) 8-, and (c) 13-km heights. was also found during RI of the simulated Hurricane RI to about 60% by the end of RI, with significant Dennis (2005) by McFarquhar et al. (2012). They sug- fluctuations in between. This increase in stratiform cov- gested that the narrowing could be related to the in- erage in the outer-core region was mainly related to the creased precipitation loading. In the simulated Megi, the active outer spiral rainbands (Li and Wang 2012) and increased outward tilt of the eyewall (Wang 2008b) and played an important role in preventing the eyewall con- the stabilization due to the rapid upper-level warming traction while increasing the inner-core size during RI of could be responsible for the narrowing of the cumulative the simulated Meg (Wang and Wang 2013). contour frequency distribution for both updrafts and The above results suggest that the percentage of con- downdrafts at upper levels in the inner-core region. vective coverage increased while the cumulative contour The results above suggest that convection in the inner- frequency of vertical velocity in the inner-core region core region become less strong and less penetrative as decreased at the upper levels during RI of the simulated the simulated Megi rapidly intensified. It is interesting to Megi. Previous studies have found that convective bursts examine the evolution of the area coverage by convec- (CBs, deep and intense convective cells) are important tion in the inner-core region during RI. Based on the to RI of TCs (Kelley et al. 2005; Montgomery et al. 2006; convective-stratiform partitioning algorithm used in Reasor et al. 2009; Rogers 2010; Zhang and Chen 2012; Steiner et al. (1995) and Rogers (2010), we obtained the time evolution of different precipitation types for both the inner-core region (within a radius of 80 km) and the outer-core region (between radii of 80 and 160 km) as shown in Fig. 12. The percentages of convective cover- age decreased slightly in both regions before the onset of RI. After the onset of RI, the convective coverage in the inner-core region increased steadily from about 50% to 80% during RI. The convective coverage in the outer-core region showed little change and remained around 30% from 1500 UTC 15 October to 1200 UTC 17 October, and then slightly increased to about 40% later on 17 October, which reflects the enhanced con- vection in the outer-core region due to the interaction of the storm with orography when it approached Luzon Island. The percentage coverage by stratiform precip- itation in the inner-core region increased from 15% to 35% in the first 12 h of RI, and then decreased to about FIG. 12. Time series of the convective (solid) and stratiform 5% by the end of RI. In the outer-core region, the strat- (dashed) percentages (a) within 80-km radius and (b) between iform coverage increased from 20% prior to the onset of 80- and 160-km radii.

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Chen and Zhang 2013). This indeed is the case, as we can see from Fig. 13, which shows the time evolution of the total number of grid points with CBs defined as vertical 2 velocity at 11-km altitude greater than 7.5 m s 1 (Fig. 13a) or as the maximum vertical velocity in the layer between 2 2 and 12 km greater than 7.5 m s 1 (Fig. 13b) within a ra- dius of 80 km in the simulated Megi case.3 Consistent with the results of Chen and Zhang (2013), in the simulated Megi CBs in the inner-core region showed a significant increase associated with the onset of RI and then a de- crease during RI. This indicates that CBs played an im- portant role in triggering the initial warm-core formation while they would be suppressed as the storm rapidly in- tensified, although the convective coverage increased in the inner-core region (Fig. 12). A question arises as to what triggered CBs during the onset of RI. The occurrence of maximum updrafts in the upper troposphere suggests the dominant control of CBs FIG. 13. Number of grid points with convective bursts within by convective available potential energy (CAPE), which 80-km radius: (a) convective bursts where the vertical velocity is 21 is defined as greater than 7.5 m s at 12-km height and (b) the maximum ver- tical velocity in the column between 2- and 12-km heights is greater 2 ð ! than 7.5 m s 1. 2 z T 2 T w LNB y y CAPE 5 max 5 g parcel env dz, (1) 2 z Ty LFC env negative buoyancy due to water loading are ignored. Figure 14a shows the time evolution of the azimuthal where the subscript ‘‘env’’ denotes environmental vari- mean CAPE together with the boundary layer equiva- able while ‘‘parcel’’ denotes the variable of a parcel, Ty lent potential temperature u and the RMW. The azi- is virtual temperature, z is the level of free convec- e LFC muthal mean CAPE as well as boundary layer u inside tion (LFC), and z is the level of neutral buoyancy e LNB the RMW increased with time prior to the onset of RI of (LNB) following the motion of the parcel. CAPE is the simulated Megi. Large CAPE occurred in the eye a measure of the maximum kinetic energy per unit mass region within a radius of 30 km prior to RI while de- that a buoyant parcel could obtain by ascending from creased with time during RI. However, u in the eye a state of rest at the LFC to the LNB near the tropo- e region increased continuously during RI. pause. The maximum vertical motion is thus expected to In an observational study for Hurricane Lili (2002), occur nearpffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi the LNB and can be approximated by Barnes and Fuentes (2010) defined an eye excess energy w 5 2CAPE. Note that the CAPE defined in (1) is max as the difference in u between the eye and the eyewall an overestimate of the actual updraft velocity because e and in the depth over which u in the eye is larger than both the entrainment of the environmental air and the e that in the eyewall. They found that the eye excess en- ergy was large at the beginning of RI but diminished during RI. They hypothesized that the eye excess energy 3 There are different definitions of CBs in the literature: 1) Rogers (2010) defined CBs as the vertical velocity averaged might serve as a boost for deep convection in the eyewall 2 between 700 and 300 hPa exceeding 5 m s 1; 2) Reasor et al. (2009) and thus the onset of RI. In a recent study, Miyamoto defined CBs as the layer-averaged vertical velocity between 2- and and Takemi (2013) found high CAPE in the eye region 2 6-km altitudes larger than 5 m s 1; 3) Montgomery et al. (2006) prior to RI and suggested that the high CAPE was ac- defined CBs as the vertical velocity through the deep layer between 2 cumulated due to the long residence time of boundary 1 and 15 km, all greater than 1 m s 1; 4) Chen and Zhang (2013) 2 defined CBs as updrafts of at least 15 m s 1 in the upper tropo- layer air inside the RMW where inertial stability was sphere (at 11-km height); and 5) Kelley et al. (2005) defined CBs as high. They proposed that high CAPE triggered deep the extremely tall convective cells with 20 dBZ at least up to convection inside the RMW and the onset of RI. How- 14.5 km. In numerical simulations, the effect of model resolution ever, they did not show whether or how the enhanced needs to be considered when CBs are defined. Here, with a 2-km 2 eyewall convection was really supported by high CAPE horizontal resolution, we found that 7.5 m s 1 or higher in the up- per troposphere (or the maximum updraft velocity in the layer in the eye region. 2 between 2 and 12 km greater than 7.5 m s 1) can be a good in- In the simulated Megi case, CBs associated with the dicator of deep convective cells. onset of RI and in the early stage of RI (from 1200 UTC

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21 FIG. 14. (a) Time–radius cross section of the azimuthal mean CAPE (J kg , shading), equivalent potential temperature (green contours with interval of 5 K), and RMW (dashed white). (b) The radial distribution of the number of grid points with vertical velocity greater 2 than 7.5 m s 1 at 11-km altitude between 1200 UTC 15 Oct and 1200 UTC 16 Oct 2010.

15 October to 1200 UTC 16 October) occurred mainly velocity and radial wind averaged on 15 and 16 October, between 40- and 70-km radii (Fig. 14b), outside the re- respectively, as shown in Fig. 15. We can see that upward gion with high CAPE (Fig. 14a). Nevertheless, consid- motion in the eyewall tilted outward with height with the ering the outward slope of eyewall updrafts [slantwise maximum upward motion at 11 km occurring at a radius nature of eyewall convection; Emanuel (1987)], high of 70 km on 15 October and of 55 km on 16 October, CAPE in the eye region could contribute to CBs in the respectively. The inner edge of the upward motion at the eyewall and to the onset of RI in the simulated Megi top of the inflow boundary layer was located at about although CAPE in the eye region might contribute little 25 km on 15 October and 20 km on 16 October, re- to the maximum storm intensity at the mature stage (- spectively, corresponding to low-level outflow there as Bryan and Rotunno 2009; Wang and Xu 2010). This a result of supergradient wind (Kepert and Wang 2001). can be demonstrated by the azimuthal mean vertical This indicates that boundary layer high-ue air in the eye

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21 FIG. 15. The radius–height cross section of the azimuthal mean vertical velocity (m s , shading) and radial wind 2 (m s 1, contours) averaged on (a) 15 and (b) 16 Oct of the simulated Megi based on hourly model outputs. region was being transported into the eyewall, increasing (2012) showed that SCAPE arises in the boundary layer the buoyancy, and thus enhancing updrafts, convection, outside of the eyewall and could contribute to the maxi- and CBs in the eyewall. mum potential intensity of a TC. Here, we would show In addition, the effect of high CAPE in the eye region that SCAPE arising from the eye region does contribute on eyewall updrafts can also be understood in terms of to buoyancy and CBs in the eyewall. To simplify the lateral mixing between the eye and the eyewall. These calculation of SCAPE in the simulated Megi, we assume processes have been well demonstrated in several pre- that the simulated storm was quasi-axisymmetric and vious studies (Braun 2002; Persing and Montgomery estimate the SCAPE along the azimuthal mean AAM 2003; Barnes and Fuentes 2010; Wang and Xu 2010). The surface. In this case, SCAPE can be calculated using the decrease in CAPE in the eye region during RI is consistent following modified form of (1): with both the decrease in the frequency of occurrence of ð ! CBs (Fig. 13) and the lowering of the height with maxi- 2 z T 2 T w LNB y y mum upward motion in the inner-core region (Fig. 10). SCAPE 5 max 5 g parcel env dz, (2) 2 z Ty The decrease in CAPE in the eye region during RI in- LFC env AAM dicates the stabilization of the air column in the eye region due to the rapid development of the upper-level warm- where the buoyancy at each height on the right-hand core structure. Although deep convection in the eyewall side was calculated following the azimuthal mean AAM might consume some CAPE in the eye region through surface with the origin at the lowest model level (we lateral mixing, this could be secondary since ue remained tested different starting levels between the lowest model high or even increased during RI (Fig. 14a). level and 1-km height; the results were quite similar). The above process can be understood alternatively in Figure 16 shows the time evolution of the azimuthal the notion of slantwise CAPE (SCAPE; e.g., Emanuel mean SCAPE, together with the vertical velocity at 1988; Shutts 1990; Gray and Thorpe 2001). In (1), CAPE 1-km height. In general SCAPE shows the distribution is defined as the undiluted air parcel ascending verti- and time evolution very similar to the CAPE shown in cally. However, this is not the case in the eyewall of Fig. 14a, but with relatively higher values extending to a strong TC since the eyewall ascent generally follows the inner edge of the eyewall updrafts at the top of the the absolute angular momentum (AAM) surface. Braun inflow boundary layer. We can see clearly that part of (2002) showed that SCAPE should be larger than CAPE the parcels arising in the eyewall stem from the eye re- in the eyewall because a part of the air parcels have their gion with high SCAPE, indicating that SCAPE in the origin in the eye region in the boundary layer (see his eye region contributes considerably to the slantwise Fig. 18). In a more recent study, Frisius and Schonemann€ convection and upper-tropospheric CBs in the simulated

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from the high potential temperature air detrained from the lower stratosphere in the simulated Megi (Fig. 17a). This is similar to that documented for Hurricane Wilma (2005) by Chen and Zhang (2013), although Wilma was stronger than Megi. Chen and Zhang (2013) showed that the air detrained from the eyewall surrounding tall CBs into the eye region warmed the TC eye, initiating the formation of the upper-level warm core and the onset of RI. In the simulated Megi case, CBs were not as strong as those in Hurricane Wilma, but the overall structure and evolution were similar. A question arises as to why CBs became less active as the storm rapidly intensified. We have already men- tioned above that the weakening of CBs was consistent with the decrease in CAPE in the eye region (Figs. 14a and 17b). This is largely due to the increased static sta- bility as a result of the upper-level warming (Fig. 17a). The reduction in CBs does not mean the slowing down of the upper-level warming. Since the efficiency of the upper-level warming is not only determined by CBs and updrafts in the eyewall but also depends on the inertial FIG. 16. As in Fig. 14a, but for SCAPE calculated with the stability in the region of diabatic heating (Schubert and ascending air parcel arising from the lowest model level and following the azimuthal mean AAM surface and vertical veloci- Hack 1982; Hack and Schubert 1986). As shown in 2 ties at 1-km altitude, with a contour interval of 0.2 m s 1 starting Schubert and Hack (1982), the efficiency of the upper- 2 from 0.1 m s 1. level warming induced by eyewall convective heating increases as inertial stability in the inner-core region Megi. Therefore, SCAPE provides buoyancy to con- increases. In the simulated Megi case, the inertial sta- vection and CBs in the mid- to upper troposphere, bility in the inner-core region increased continuously contributing to the onset of RI and the early RI of the throughout the troposphere (similar to that in Fig. 17b) simulated Megi. as the storm rapidly intensified, indicating the increasing efficiency in the upper-tropospheric warming forced by d. Development of the upper-level warm core and RI eyewall convection during RI. Figure 17a shows the time evolution of the tempera- Vigh and Schubert (2009) examined the dependence ture anomalies and potential temperature averaged in of the warm-core development on the radial location the eye region (within 20-km radius) of the simulated of the diabatic heating based on the balanced vortex Megi. The warm core first appeared in the midtropo- model. They found that the response of the upper-level sphere between 3 and 8 km prior to RI. The midlevel warming to diabatic heating reaches its maximum when warm core remained in both height and magnitude diabatic heating is centered in the region with high in- during RI, suggesting that it contributed little to the RI ertial stability inside the RMW. In the simulated Megi of the simulated Megi. A new upper-level warm core case, diabatic heating in the eyewall was indeed located formed at about 16–17 km after the RI started, and then inside the RMW and near the edge of the maximum amplified and extended downward during RI. By the radial gradient of low-level inertial stability during RI end of RI, the upper-level warm core was located be- (Fig. 8). The large radial gradient of inertial stability also tween 14- and 16-km heights. This downward develop- infers the large deceleration of the boundary layer in- ment of the upper-level warm core is consistent with the flow and, thus, the strengthening of the forced upward descent of the contour of 380-K potential temperature motion in the eyewall. Therefore, although CBs became that originated from the tropopause. This suggests that less active as the storm intensified rapidly, the mean the high potential temperature air detrained from the eyewall updrafts were still strong but less penetrative lower stratosphere by CBs could contribute to RI of than those prior to RI (Fig. 10). This led to the lowering the simulated storm. The results suggest that in the of the height of the upper-level warm core during RI environment with decreasing vertical wind shear, CBs (Fig. 17a). triggered the onset of RI and the formation of the upper- In their numerical study for Hurricane Wilma (2005), tropospheric warm core with a possible contribution Chen and Zhang (2013) showed that there was a shallow

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FIG. 17. Time evolution of the (a) temperature anomalies (K, shading) and equivalent po- tential temperature (K, contours) averaged within a 20-km radius and (b) inertial stability 2 2 parameter in the boundary layer (s 2, red) and CAPE (J kg 1, blue) averaged within a 60-km radius of the simulated Megi. inflow layer immediately above the prevailing upper- many common features of TCs that crossed Luzon level outflow layer, which originated in the lower strato- Island in the northern Philippines, Megi experienced sphere and emerged at the time of the eye formation. unique intensity and structural changes, such as the lack They considered the shallow inflow layer to be a result of of an eyewall contraction and an increase in inner-core mass continuity due to the mass sink in the eye region size during its RI phase, drastic structural changes when as the storm rapidly intensified. They also argued that it made landfall and crossed Luzon Island, and rein- the inflow can effectively carry environmental potential tensification with the reformation of a large eyewall and temperature air all the way into the eye, where air de- the redevelopment of the original eyewall as an inner scends adiabatically to enhance the warm core due to eyewall after it entered the SCS. Most of these features the absence of inertial stability. We also observed similar were reasonably well reproduced in a week-long control processes in the simulated Megi case. Prior to the onset of simulation using the ARW-WRF with both DI and RI, the upper-level inflow appeared but less organized large-scale SN, as documented in Wang et al. (2013). (Fig. 15a). However, during RI a systematic shallow in- The DI scheme spun up the axisymmetric component of flow layer developed immediately above the upper-level the TC vortex, which was rather weak in the coarse- outflow layer (Fig. 15b), which arguably contributed resolution global analysis, and the large-scale SN kept positively to the formation and maintenance of the the environmental flow with the wavelength longer than upper-level warm core in the simulated Megi. 1000 km as close to the driving field as possible in both DI and subsequent simulations. This has paper presented an investigation into the 4. Conclusions and discussion processes responsible for the RI of the simulated Megi Typhoon Megi was the most powerful and longest- before it made landfall over Luzon Island based on the lived TC over the WNP and SCS in 2010. While it shared control simulation of Wang et al. (2013). The results

Unauthenticated | Downloaded 10/03/21 09:59 PM UTC 46 MONTHLY WEATHER REVIEW VOLUME 142 show that, as is the case in most other TC cases studied Our results are in agreement with those of Rogers earlier, Typhoon Megi experienced its RI over the WNP (2010), who studied the role of convective processes in with high upper OHC and in an environment with de- the RI of Hurricane Dennis (2005) via a high-resolution creasing vertical wind shear. On the storm scale, inertial simulation, and those of Chen and Zhang (2013), who stability in the inner-core region was already high prior numerically studied the RI processes in Hurricane Wilma to the onset of RI and the axisymmetrization throughout (2005). Our results however seem to differ from those the troposphere was accompanied by RI. Frictionally of McFarquhar et al. (2012), who compared different induced boundary layer inflow penetrated progressively definitions of CBs and found that in their simulated inward outside the RMW and decelerated sharply near Hurricane Dennis (2005) the number of CBs did not the RMW where the radial gradient in inertial stability show any increase prior to RI, but continuously increased is the largest. This strengthened the radial mass and during RI. The difference might reflect the case depen- moisture convergence in the boundary layer, leading to dence of convective activities. Similar analyses should be strong eyewall updrafts and intense convection in the undertaken for more cases in future studies to examine eyewall. Latent heating released in eyewall convection the majority of the convective evolution and robustness effectively enhanced the upper-tropospheric warming of of the RI triggering mechanisms. the high inertial stability core and lowered the central sea level pressure of the storm. The latter in turn drove Acknowledgments. We thank two anonymous re- stronger boundary layer inflow, further enhancing eye- viewers for their constructive review comments that wall updrafts and convection. This forms a positive resulted in substantial improvements to the manuscript. feedback among inertial stability, eyewall updraft and This study has been supported in part by the National convection, and upper-tropospheric warming, contrib- Basic Research Program of China (2009CB421505) and uting to RI of the simulated Megi, as has been collec- the National Natural Science Foundation of China un- tively documented in earlier studies (Ooyama 1982; der Grant 41130964 and in part by NSF Grants ATM- Schubert and Hack 1982; Hack and Schubert 1986; Vigh 0754039 and AGS-1326524. Additional support has been and Schubert 2009; Smith et al. 2009). provided by the JAMSTEC through its sponsorship of Different from the majority of TCs that experience RI the International Pacific Research Center (IPRC) in the with an eyewall contraction, Megi rapidly intensified School of Ocean and Earth Science and Technology without any eyewall contraction. The lack of eyewall (SOEST) at the University of Hawaii. contraction is attributed to diabatic heating in active spiral rainbands, a process previously proposed to ex- plain the inner-core size increase in idealized simula- REFERENCES tions by Wang (2009) and Xu and Wang (2010a,b). Barnes, G. M., and P. Fuentes, 2010: Eye excess energy and the Actually, in the Megi case the inner-core size also in- rapid intensification of Hurricane Lili (2002). Mon. Wea. Rev., creased considerably during its RI (Wang and Wang 138, 1446–1458. 2013). This is largely attributed to the binary interaction Bosart, L. F., C. S. Velden, W. E. 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