1. Introduction
Satellite imagery can provide massive amounts of information over extensive areas, and multiple previous studies have used infrared (IR) brightness temperature to examine convective clouds related to tropical cyclones (TCs) (Browner et al. 1977; Muramatsu 1983; Steranka et al. 1986; Harnos and Nesbitt 2011, 2016; Jiang 2012; Kieper and Jiang 2012; Monette et al. 2012). In general, since the IR window channel around 11 μm is not significantly absorbed by atmospheric gases, it has been widely used to monitor convective or stratiform clouds. Previous studies have shown that cold brightness temperature suitable for indicating the convective area could be used as one of the indicators of TC intensification (Gentry et al. 1980; Jiang 2012; Monette et al. 2012; Fischer et al. 2018). For example, Gentry et al. (1980) demonstrated that a future (+24 h) TC intensity change is strongly correlated with the mean brightness temperature at a correlation coefficient of −0.781. This relationship was also similarly confirmed by Monette et al. (2012) using a tropical overshooting tops algorithm for rapid intensification (RI) prediction.
In total, 85 GHz microwave satellite imagery may have an advantage in detecting deep convective cells related to ice scattering (Jiang 2012; Fischer et al. 2018), and these deep convective cells may release abundant latent heat above the freezing level. Jiang (2012) demonstrated that RI TCs have the lowest 11-μm brightness temperature ranging from 174 to 223 K and the tallest 20-dBZ echo height compared to other TC phases such as slow intensification (SI), weakening (W), and neutral (N). Fischer et al. (2018) also showed that TCs in the RI stage exhibit more concentrated cold brightness temperatures inside the 100-km radius than in other stages. These results support the statement that convective bursts (CBs) can contribute to TC intensification by releasing substantial latent heat, as much as 6.6 × 1017 J in a 12-h period inside the inner-core area (Kelley and Halverson 2011). This additional latent heat may increase TC intensity at a rate that satisfies the general RI threshold of Kaplan and DeMaria (2003) in a 24-h period. The increase in convective cells can also contribute to a significant contraction of the radius of maximum wind (RMW) through radially varying diabatic heating (Schubert and Hack 1982; Willoughby 1990). This contracted RMW could be an efficient configuration for TC spinup by concentrating diabatic heating in the high-inertial stability area, e.g., inside the RMW excluding the eye region (Vigh and Schubert 2009).
RI is primarily initiated at the tropical storm and category 1 hurricane intensity stage (Kaplan and DeMaria 2003; Hendricks et al. 2010; Jiang 2012). Previous studies have shown that right before the onset of RI, CBs are frequently observed near the RMW and also in downshear quadrants (Braun et al. 2006; Braun and Wu 2007; Reasor et al. 2009; Rogers 2010; Guimond et al. 2010, 2016; Rogers et al. 2013, 2015; DeHart et al. 2014; Chang and Wu 2017; Hazelton et al. 2017a,b; Fischer et al. 2018; Lee and Wu 2018). However, these deep convective cells could be suppressed and tilted outward in upshear quadrants as a result of significant convective-scale subsidence or the vertical wind shear (VWS) (Chen and Gopalakrishnan 2015; Lee and Wu 2018). In the moderate or strong VWS environments, the vortex structure is typically tilted according to the VWS direction, but intensifying TCs could overcome such tilted structure as a result of sufficient inner-core convective cells that serve to reduce the precession motion of the vortex (Gray 1968; Jones 1995; DeMaria 1996; Frank and Ritchie 1999, 2001; Reasor et al. 2004; Braun and Wu 2007; Rios-Berrios et al. 2018; Lee and Wu 2018). These processes in sequence may be how a TC reintensifies in a moderate or strong VWS environment. Under a strong VWS (>10 m s−1) environment, TC frequently fails to intensify due to significant precession motion or decoupling between the lower troposphere circulation and the upper-troposphere circulation, but the above mechanism is not as clear for moderate VWS (5–10 m s−1).
Meanwhile, deep convective cells are recognized as a primary source of the cirrus shield, which is also referred to as the central dense overcast or cirrus canopy in the upper troposphere (Malkus et al. 1961; Sadler 1964; Merritt and Wexler 1967; Weickmann et al. 1977; Gray and Jacobson 1977; Dunion et al. 2014). According to Merritt and Wexler (1967), the maximum areal extent of these cirrus clouds appears 12 to 18 h after deep convection initiation, that is, the cirrus cloud coverage is out of phase approximately 12 h from the diurnal signal of convective clouds (Browner et al. 1977; Muramatsu 1983; Steranka et al. 1984; Kossin 2002; Dunion et al. 2014; Leppert and Cecil 2016). Browner et al. (1977) discussed that the maximum 253-K area decreases as TC intensity increases. For example, the average magnitude of the diurnal oscillation in the area of the cloud canopy computed by comparing the maximum area with the minimum area in the tropical depression and hurricane is 3.03 and 2.09, respectively. This result indicates that the diurnal area oscillation appears to be more significant in tropical depressions than in hurricanes.
Gray and Jacobson (1977) showed that the upper disturbance area could experience a significant net radiational warming and cooling for one day. However, in the disturbance area, e.g., thick cloud area, the temperature remains warm in the midtroposphere and lower troposphere despite temperature changes induced by the net radiation. It may be due to longwave emission-reabsorption and condensate heat from the vapor. It may be due to longwave emission-reabsorption and condensate heat from the vapor. Therefore, the net radiational contrast between daytime and nighttime may significantly contribute to the stability between the upper and lower clouds. Navarro and Hakim (2016) showed contrasting daytime and nighttime vertical flow patterns (see their Figs. 8 and 9). Specifically, the vertical circulation related to the net radiative tendency appears as cyclonic circulation in the afternoon and changes into anticyclonic circulation in the early morning, which could explain certain physical mechanisms concerning the convective activity invigorated between late afternoon and midnight. Tang et al. (2019) discussed that the diurnal radiation contrast was significant for changes in the RMW. For example, the RMW contraction tends to be more accelerated during the nighttime due to the radiative destabilization and moistening in the lower troposphere compared to the daytime. Muramatsu (1983) discussed the diurnal variation of the maximum extent of convective clouds and the eye diameter in mature TCs and stated that the convective area corresponding to a −70°C brightness temperature could reach its maximum size between the afternoon-evening and early morning, whereas the minimum occurs in the afternoon. In addition, Muramatsu (1983) stated that the maximum eye diameter occurs during the daytime due to the dissipation of cirrus clouds from the eye region. Dunion et al. (2014) similarly confirmed that mature TCs exhibit diurnal variation and found that TC diurnal pulse speed ranges from 5 to 10 m s−1. Elsberry and Park (2017) also commented on the diurnal variation of the convective maximum and minimum that could affect VWS.
These previous studies focused mainly on mature TCs (category 2 and higher); however, since convective activity is one of the predominant indicators of TC intensification or weakening, the diurnal variation in the convective area related to RI needs to be examined from before the onset of RI to the end of RI. Therefore, the primary purpose of this study is to characterize the diurnal variation of both the convective area and eye size related to RI TCs in the western North Pacific from 2015 to 2017 based on Himawari-8 satellite imagery.
The remainder of this study is composed as follows: section 2 introduces the data and methodology; a comprehensive summary of RI TCs from 2015 to 2017 is given in section 3; sections 4, 5, and 6 elaborate the results concerning the diurnal variation of the convective area depending on TC intensity categories, statistical analysis between TC intensification stages and eyewall convective cloud estimated by the normalized convective area between 2 and 3 times the RMW, and the diurnal variation of the eye size, respectively; and section 7 summarizes the findings of this study.
2. Data and methodology
a. Himawari-8 satellite, ERA-Interim reanalysis, and best track dataset
The next generation Japan Meteorological Agency (JMA) geostationary meteorological satellite, the Himawari-8 satellite, was launched successfully in 2014, replacing the Multifunctional Transport Satellites (MTSATs) previously used for monitoring the area between 60°S and 60°N and between 80°E and 160°W. Compared to MTSATs, the Himawari-8 satellite can provide several specific bands, such as water vapor (WV) absorption channels (6.2–7.3 μm) and atmospheric window channels (10–12 μm), with higher spatial and temporal resolution (Bessho et al. 2016). The Himawari-8 satellite provides three visible channels, three near-IR channels, and 10 IR channels. Since the IR window channels between 10 and 12 μm are not significantly absorbed by atmospheric gases, these wavelengths have been widely used to monitor severe weather systems like supercells or intensifying TCs. Olander and Velden (2009) proposed a methodology for the detection of intense convective clouds based on the difference between the atmospheric window channel and WV absorption channel, herein referred to as IRWV, details of which are addressed in the next subsection. In this study, the solar zenith angle provided by Himawari-8 is used to distinguish between day and night. For example, when the averaged solar zenith angle within the area of a TC (e.g., approximately 800 km × 800 km) is higher than 80°, it is defined as nighttime. In addition to the Himawari-8 satellite dataset, ERA-Interim reanalysis data with 0.25° spatial resolution and 6-h temporal resolution is used to compute VWS between 850 and 200 hPa within a 500 km radius. In this study, the vortex scale of the reanalysis data is filtered out by using a high-order filter equation (Cheong et al. 2004), which allows VWS to be computed thoroughly on a large-scale wind field. Also, the Hybrid Coordinate Ocean Model data are used to investigate the ocean condition, and the Joint Typhoon Warning Center (JTWC) best track data are used as the standard reference for TCs in this study.
b. Modification of the IRWV calculation using a natural logarithm
The Himawari-8 geostationary satellite provides more segmentalized wavelength bands than previous geostationary satellites such as the MTSAT series. These segmentalized bands are more useful for monitoring detailed atmospheric characteristics such as humidity, thin ice clouds, and other atmospheric gases (Bessho et al. 2016). The preexisting IRWV methodology, which is useful for diagnosing intense convective clouds (Olander and Velden 2009), was used by Kurino (1997) and Schmetz et al. (1997). The atmospheric window channels generally have warmer brightness temperature than that of the WV channels in the clear-sky and a colder brightness temperature than that in the convective area, which is caused by water vapor reemitting the absorbed radiation from the upper troposphere or lower stratosphere (Schmetz et al. 1997). As a result, IRWV predominantly appears negative in the convective area. However, this IRWV could be less accurate in representing deep convection related to ice scattering compared with microwave satellite imagery, even though it can still provide a better temporal resolution. For this reason, if IRWV can represent the intense convective area similar to that of microwave satellite imagery, it would be extremely useful in monitoring TC structure and intensity changes at a much higher temporal resolution for examining severe weather systems such as supercells or TCs occurring over the open ocean, making it possible to examine the diurnal variation of TC convective clouds over the open ocean. Therefore, in this study, the preexisting IRWV has been modified as follows:
where Tb is the brightness temperature of each wavelength obtained from 6.2, 6.9, and 11.2 μm. The mean brightness temperature of 11.2 μm can be obtained by summing the water vapor term that becomes zero in the bracket. The natural logarithm is taken to reduce the scale of IRWVln. Figure 1 shows the weighting functions relative to 6.2, 6.9, and 11.2 μm Himawari-8 Advanced Himawari Imager (AHI), and each wavelength shows a different peak spectral response depending on the pressure level. For instance, under the given settings shown in Fig. 1, the peak spectral response of the 6.2 and 6.9 μm water vapor channels appear at 329 and 391 hPa, respectively (Figs. 1a,b); however, the peak spectral response of the atmospheric window channel (11.2 μm) is observed at 1000 hPa (Fig. 1c). These results show that although the water vapor channels have similar wavelengths, their differences share the same characteristics as the IRWV. From Eq. (1), the negative IRWVln appears when the convective cells penetrate the layer between 329 and 391 hPa, which is referred to as the critical level in this study. Therefore, if IRWV primarily represents the characteristics of convective clouds below the midtroposphere, IRWVln can be used to determine whether the convective clouds are deep or shallow. Figure 2 shows examples of Typhoon Meranti (2016) observed by Global Change Observation Mission Water (GCOM-W1) Advanced Microwave Scanning Radiometer 2 (AMSR2) microwave satellite imagery, Himawari-8 satellite imagery, and synthetic products of IRWV and IRWVln, respectively. A colder brightness temperature relative to the periphery generally represents the convective area, but the brightness temperature range seems to be ambiguous. Therefore, the question “What is an exact brightness temperature to indicate the convective area?” is raised. The IRWV outputs could represent the convective clouds; however, compared to microwave satellite imagery, the IRWV results still exaggerate the deep convective area (Figs. 2a–d). As mentioned above, because IRWV shows the difference between the atmospheric window and water vapor channels, it may include all information between the low and midtroposphere. Meanwhile, since the IRWVln indicates the difference between water vapor channels, it seems better to represent deep convection penetrating the critical level. Overall, the IRWVln output is very similar to the microwave satellite imagery (Figs. 2a,b,e), even though there are limitations in identification of detailed structures such as the small inner core with a moat and the outer band under the deep convective clouds. Nevertheless, IRWVln derived from Himawari-8 satellite imagery may be useful for examination of the diurnal variation of convective clouds related to TCs through the improved temporal and spatial resolution.
AHI vertical weighting functions for (a) 6.2, (b) 6.9, and (c) 11.2 μm from the CIMSS website (http://cimss.ssec.wisc.edu/goes/wf/examples/AHI/). The maximum spectral response of each wavelength corresponds to 329, 391, and 1000 hPa, respectively. The gray area in (a),(b) indicates a critical level by which convective cells are determined to be shallow or deep. These profiles are obtainable when the standard tropical atmosphere, 10° zenith angle, 100% column moisture, and +0 K skin temperature adjustment are set.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
AHI vertical weighting functions for (a) 6.2, (b) 6.9, and (c) 11.2 μm from the CIMSS website (http://cimss.ssec.wisc.edu/goes/wf/examples/AHI/). The maximum spectral response of each wavelength corresponds to 329, 391, and 1000 hPa, respectively. The gray area in (a),(b) indicates a critical level by which convective cells are determined to be shallow or deep. These profiles are obtainable when the standard tropical atmosphere, 10° zenith angle, 100% column moisture, and +0 K skin temperature adjustment are set.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
AHI vertical weighting functions for (a) 6.2, (b) 6.9, and (c) 11.2 μm from the CIMSS website (http://cimss.ssec.wisc.edu/goes/wf/examples/AHI/). The maximum spectral response of each wavelength corresponds to 329, 391, and 1000 hPa, respectively. The gray area in (a),(b) indicates a critical level by which convective cells are determined to be shallow or deep. These profiles are obtainable when the standard tropical atmosphere, 10° zenith angle, 100% column moisture, and +0 K skin temperature adjustment are set.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
Various satellite images of Typhoon Meranti (2016): (a) GCOM-W1 AMSR2 minimum 85-GHz polarization corrected brightness temperature and (b) 85-GHz at 0347 UTC 13 Sep (https://www.nrlmry.navy.mil/tc-bin/tc_home2.cgi); (c) IRWV (IR11.2–IR6.2 μm), (d) IRWV (IR11.2–IR6.9 μm), (e) IRWVln, and (f) IRWVln displayed with three colors at 0350 UTC, respectively. In (f), the white and black areas represent ACA and mixed phase, respectively. The definitions of ACA, mixed phase, and IACA can be found in section 2c. All figures are in temperature (K).
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
Various satellite images of Typhoon Meranti (2016): (a) GCOM-W1 AMSR2 minimum 85-GHz polarization corrected brightness temperature and (b) 85-GHz at 0347 UTC 13 Sep (https://www.nrlmry.navy.mil/tc-bin/tc_home2.cgi); (c) IRWV (IR11.2–IR6.2 μm), (d) IRWV (IR11.2–IR6.9 μm), (e) IRWVln, and (f) IRWVln displayed with three colors at 0350 UTC, respectively. In (f), the white and black areas represent ACA and mixed phase, respectively. The definitions of ACA, mixed phase, and IACA can be found in section 2c. All figures are in temperature (K).
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
Various satellite images of Typhoon Meranti (2016): (a) GCOM-W1 AMSR2 minimum 85-GHz polarization corrected brightness temperature and (b) 85-GHz at 0347 UTC 13 Sep (https://www.nrlmry.navy.mil/tc-bin/tc_home2.cgi); (c) IRWV (IR11.2–IR6.2 μm), (d) IRWV (IR11.2–IR6.9 μm), (e) IRWVln, and (f) IRWVln displayed with three colors at 0350 UTC, respectively. In (f), the white and black areas represent ACA and mixed phase, respectively. The definitions of ACA, mixed phase, and IACA can be found in section 2c. All figures are in temperature (K).
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
c. Definitions of the active convective area, mixed phase, and inactive convective area
The existence of cold brightness temperature inside the TC inner-core area correlates with TC intensification (Gentry et al. 1980; Muramatsu 1983; Ebert and Holland 1992; Jiang 2012; Monette et al. 2012). Convective clouds in supercells or TCs are normally colder than the 225 K brightness temperature (Bedka et al. 2010; Monette et al. 2012). Since the Himawari-8 satellite full-disk resolution has a 2-km spatial resolution, each grid point represents a 4-km2 area; therefore, the active convective area (ACA), mixed phase, and inactive convective area (IACA) can be defined by the following three thresholds: IRWVln ≤ −1 K, −1 < IRWVln < 1 K, and IRWVln ≥ 1 K, respectively (Figs. 2e,f). The mixed phase may represent a change in state from ACA to IACA. ACA typically indicates deep convection that could penetrate the critical level (Figs. 1a,b), while the mixed phase and IACA could primarily represent moderate or shallow convection that develops under the critical level.
3. Summary of RI TCs from 2015 to 2017 in the western North Pacific
Similar to the climatologically normal frequency1 of 25.6 TCs, the average TC genesis frequency in the western North Pacific is 26.6 TCs from 2015 to 2017, during which the number of TCs with RI is 10, 11, and 9 in 2015, 2016, and 2017, respectively. This RI occurrence frequency seems to be significantly higher than the climatological RI frequency of approximately 5.2 TCs per year from 1979 to 2015 (Fudeyasu et al. 2018); however, this climatological RI number may vary slightly depending on the definition of maximum surface wind speed. Considering that intense category 4 or 5 TCs generally undergo RI at least once during their lifetime (Kaplan and DeMaria 2003), this could reduce the TC intensity forecast accuracy. Table 1 shows the sea level forecast errors induced by intense storms, for example, over 6.5 current intensity (CI; Dvorak 1975) index value, adopted from the JMA annual reports from 2012 to 2017. It turns out that the sea level pressure forecast tends to deteriorate when the number of intense TCs increases.
The sea level pressure (hPa) forecast error caused by intense storms occurring in the western North Pacific. The information is adopted from JMA annual reports from 2012 to 2017. Here, an intense storm is defined when the CI index is greater than or equal to 6.5. The storms migrated from the eastern North Pacific are excluded.
Figure 3 represents the track and intensity of RI TCs from 2015 to 2017 based on JTWC best track data. In this study, the Saffir–Simpson hurricane wind scale2 is adopted to classify the TC intensity. From the 30 samples, RI frequently occurs as the TCs move westward or northwestward. This is consistent with Kaplan and DeMaria (2003). Some TCs experienced RI near the recurvature point; however, after passing the recurvature point, these TCs are prone to weaken significantly. Meanwhile, the genesis of RI TCs between 2015 and 2016 is slightly different. For example, RI TCs in 2015 were concentrated over the area between 147° and 164°E and between 10° and 20°N, while in 2016, the RI concentration shifted approximately 10° westward compared to 2015 (Figs. 3a,b), which may be attributed to El Niño–Southern Oscillation (Kim et al. 2011). The oceanic Niño index3 shows a stronger El Niño year in 2015 than in 2016 and 2017, and that the TC track appeared quite erratic (Fig. 3c), although the ocean had returned to normal conditions in 2017. Furthermore, there were no category 5 storms in 2017. As a result, the TC intensity predictability seems to be temporarily improved compared to other years (Table 1).
The track and intensity of JTWC best track for RI storms over the western North Pacific in (a) 2015, (b) 2016, and (c) 2017. The storm intensities are drawn based on the Saffir–Simpson hurricane wind scale. The dotted box in (a),(b) indicates the area with the most frequent formation of RI TC in that year.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The track and intensity of JTWC best track for RI storms over the western North Pacific in (a) 2015, (b) 2016, and (c) 2017. The storm intensities are drawn based on the Saffir–Simpson hurricane wind scale. The dotted box in (a),(b) indicates the area with the most frequent formation of RI TC in that year.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The track and intensity of JTWC best track for RI storms over the western North Pacific in (a) 2015, (b) 2016, and (c) 2017. The storm intensities are drawn based on the Saffir–Simpson hurricane wind scale. The dotted box in (a),(b) indicates the area with the most frequent formation of RI TC in that year.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
A comprehensive summary of the current RI TCs is presented in Tables 2–4, showing that RI TCs normally concentrate between August and October, during which 22 RI TCs occurred. This RI activity is also consistent with the climatological seasonal-TC distribution (Holliday and Thompson 1979) and RI occurrence (Fudeyasu et al. 2018). In addition, RI tends to commence within 72-h after a tropical depression develops into a tropical storm (Tables 2–4). Although RI typically represents an increase in the maximum surface wind of more than 30 kt (1 kt ≈ 0.51 m s−1) in 24 h, Typhoons Nepartak (2016) and Meranti (2016) significantly surpassed this general RI definition with a maximum surface wind increase of approximately 70-kt in 24 h based on the 1-min average maximum surface wind. During the RI period, both TCs passed through very warm oceanic heat content (OHC) regions of 9.4 and 10.0 GJ m−2, respectively (Table 3). This intensification rate corresponds to the lowest 24-h intensity change frequency (Kaplan and DeMaria 2003). Consequently, both storms explosively intensified from the tropical storm stage to the category 5 hurricane wind intensity at the end of RI. Interestingly, both TCs had similar initial locations and tracks (Fig. 3b), but underwent different VWS evolutions (Figs. 4b,d). During the RI period, Nepartak primarily experienced weak VWS, whereas Meranti experienced a significant change in VWS (Figs. 4b,d). This significant change in the magnitude of VWS was also observed for Typhoons Champi (2015), Malakas (2016), and Chaba (2016) (Figs. 4a,e,f), and Typhoon Megi (2010) (Lee and Wu 2018). This dramatic weakening of the VWS may be explained by either of the following two scenarios: 1) when the TC moves into a region with reduced VWS, and 2) when deep convective updrafts partially cancel the VWS caused by the enhanced outflow. Typhoons Namtheun (2016), Malakas (2016), Songda (2016), and Talim (2017) showed a recurving and abnormal track and experienced an increase in VWS during the RI period (Figs. 3b,c and 4c,e,g,h). The increased VWS appears to be partially related to a midlatitude trough that can enhance the TC’s outflow (Fig. S1 in the online supplemental material; Rogers et al. 2015; Elsberry and Park 2017; Fischer et al. 2019). Molinari and Vollaro (2010) indicated that a sheared tropical storm could undergo RI by means of intense convection when it interacts with a midlatitude trough. In addition to the VWS magnitude, an abrupt change in the VWS direction may disrupt the development of an ACA. For example, Meranti had maintained an ACA with a consistent VWS direction during the RI period (Fig. 5a), while Malakas and Talim experienced a dissipation of ACA after an abrupt change in the VWS direction at the onset of RI (Fig. 5c, not shown for Malakas). In addition, in the tropical depression stage, Chaba experienced considerable dissipation of the ACA after a sudden change in VWS direction (Fig. 5b). Compared to Talim, Chaba experienced significant shear impact on the development of ACA at an early stage due to the absence of a stable structure, e.g., an eye structure established from the lower to upper troposphere.
A summary of RI TCs occurring in 2015. The ∆ represents the change of pressure, maximum surface wind speed, category, and VWS computed between 850 and 200 hPa from the onset of RI to the mature stage. The category refers to the Saffir–Simpson hurricane wind scale. The OHC represents the average value over the RI period. To eliminate cold wake effects induced by TC, OHC is computed under free ocean conditions (e.g., before TC genesis).
The VWS magnitude (on the left axis) and direction (on the right axis) computed from different pressure levels denoted by solid lines and pentagrams of different colors. The magnitude and direction of 850–200 hPa VWS is highlighted by a thick solid line and large pentagram. The VWS direction in the right ordinate indicates a downshear direction; for example, the W represents a shear direction from East to West. The abscissa denotes the time in the month–day–hour format. The RI period is indicated by two vertical-dashed lines.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The VWS magnitude (on the left axis) and direction (on the right axis) computed from different pressure levels denoted by solid lines and pentagrams of different colors. The magnitude and direction of 850–200 hPa VWS is highlighted by a thick solid line and large pentagram. The VWS direction in the right ordinate indicates a downshear direction; for example, the W represents a shear direction from East to West. The abscissa denotes the time in the month–day–hour format. The RI period is indicated by two vertical-dashed lines.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The VWS magnitude (on the left axis) and direction (on the right axis) computed from different pressure levels denoted by solid lines and pentagrams of different colors. The magnitude and direction of 850–200 hPa VWS is highlighted by a thick solid line and large pentagram. The VWS direction in the right ordinate indicates a downshear direction; for example, the W represents a shear direction from East to West. The abscissa denotes the time in the month–day–hour format. The RI period is indicated by two vertical-dashed lines.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The sequential IRWVln images at 12-h intervals of (a) Meranti, (b) Chaba, and (c) Talim. The innermost blue concentric circle indicates the RMW adopted from JTWC best track data, and the second and third circles represent 2 or 3 times the RMW, respectively. The black arrow denotes VWS computed between 850 and 200 hPa based on ERA-Interim reanalysis data (see more Fig. 4).
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The sequential IRWVln images at 12-h intervals of (a) Meranti, (b) Chaba, and (c) Talim. The innermost blue concentric circle indicates the RMW adopted from JTWC best track data, and the second and third circles represent 2 or 3 times the RMW, respectively. The black arrow denotes VWS computed between 850 and 200 hPa based on ERA-Interim reanalysis data (see more Fig. 4).
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The sequential IRWVln images at 12-h intervals of (a) Meranti, (b) Chaba, and (c) Talim. The innermost blue concentric circle indicates the RMW adopted from JTWC best track data, and the second and third circles represent 2 or 3 times the RMW, respectively. The black arrow denotes VWS computed between 850 and 200 hPa based on ERA-Interim reanalysis data (see more Fig. 4).
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
4. The diurnal variation of ACA
To compare the diurnal variation of ACA based on TC intensity, 30 RI TCs have been grouped into three categories: category 3 or below, category 4, and category 5, based on the maximum intensity according to the Saffir–Simpson hurricane wind scale. In this study, the exact diurnal and semidiurnal signals of ACA are obtained by applying an inverse Fourier transform to the ACA computed inside the RMW. For example, if a TC has a 5-day lifespan, the diurnal and semidiurnal pulses of ACA could be obtained by synthesizing wavenumbers from 0 to 5, and 0 to 10, respectively.
a. Category 3 or below
Figures 6 and 7 show a time series of the ACA, mixed phase, IACA, diurnal and semidiurnal signals, and the eyewall convective cloud for nine RI TCs. In this study, the eyewall convective cloud is determined by the normalized IRWVln between 2 and 3 times the RMW, called the eyewall area. The normalization is completed by the following procedure: first, the region is divided into positive and negative areas; second, the positive area is divided by its maximum while the negative area is divided by its minimum. Therefore, if the average value taken from the eyewall area is negative, the eyewall is considered to be solid. On the contrary, a broken or disorganized eyewall is manifested by a positive value. In the time series figures, ACA tends to develop from late afternoon to midnight, while it shrinks significantly during the day. Meanwhile, the maximum mixed phase and IACA occur during the day. This pattern indicates that ACA could potentially evolve into mixed phase or IACA over time (Merritt and Wexler 1967; Muramatsu 1983; Dunion et al. 2014; Leppert and Cecil 2016). During the RI period, most RI storms of this group exhibited a single diurnal variation of ACA, and formed a solid eyewall, although they fluctuated slightly (Figs. 6 and 7). If the ACA can be treated the same as CBs, a single-completed diurnal variation of the ACA inside the RMW may be adequate to trigger RI. Note that CBs typically release extra latent heat of approximately 6.6 × 1017 J in 12 h, which may enhance the maximum surface wind from 9 to 16 m s−1 (Kelley and Halverson 2011). However, Typhoons Mujigae (2016) and Hato (2017) experienced a sudden dissipation of ACA in the form of significant fluctuation in the eyewall convective clouds inside the RMW and within 3 times the RMW (Figs. 6, 7b,e). This can result in partially broken or disorganized eyewalls that allow interactions between the TC inner-core and outer environments (Tang and Emanuel 2010). Once low equivalent potential temperature air flows into the TC inner-core area, it could stabilize the convective activity, which could eventually weaken the TC intensity. This abrupt ACA disappearance may be due to the complex flows caused by the land as the TCs travel into the South China Sea or the direct/indirect interaction of terrain (Figs. 3b,c). Other RI storms of this category also experienced fluctuations in the ACA development, however to a lesser degree. Meanwhile, despite the small number of convective cells inside the RMW of midget typhoons Namtheun (2016) and Sanvu (2017), they underwent RI (Figs. 6c,f). Although midget TCs may not include sufficient CBs inside the RMW, small CBs could facilitate a significant contraction of the RMW of a midget TC (Figs. 7c,f). After the RMW contraction, they quickly formed an eye structure during the RI period (not shown). Namtheun had a greater maximum intensity than Sanvu, which appears to be caused by the different oceanic conditions during the RI period. For example, Namtheun passed through high OHC region (7.2 GJ m−2), due to the Kuroshio, while Sanvu passed through a low OHC region (2.4 GJ m−2) (see Tables 3 and 4). Among the 9 RI TCs, Typhoon Banyan (2017) seems to have a relatively more favorable environment for the development of ACA because it did not interact with terrain and passed through 7.7 GJ m−2 OHC region (Fig. 3c and Table 4). Consequently, ACA seems to be maintained longer without any significant dissipation from the onset of RI, and the diurnal signal can more accurately describe the time series of ACA inside the RMW (Fig. 6d). If thick convective clouds are covered throughout the day, net radiational cooling could be significantly reduced in the mid- or lower troposphere, possibly caused by longwave emission-reabsorption and condensate heat from the vapor (Gray and Jacobson 1977). As a result, destabilization caused by net radiative forcing (net radiational contrast) between the upper clouds and mid- or lower clouds may promote convective activity at night. Therefore, unless the TC experiences substantial ACA dissipation during the day, it could significantly influence the next convective activity by increasing destabilization. This feature is more apparent in Category 4 and 5 hurricanes as described below.
The time series analysis of the ACA, mixed phase, and IACA for category 3 hurricane wind intensity or below. The blue solid line (scaled by a one-third ratio) indicates the ACA computed inside the RMW, and black and gray dashed lines represent the ACA and mixed phase+IACA calculated within 3 times the RMW. The solid and dotted red lines denote the diurnal and semidiurnal signals obtained by applying the inverse Fourier transform to ACA inside the RMW. The yellow line overlaid with the maximum surface wind speed line represents the period from the onset of RI to the mature stage.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The time series analysis of the ACA, mixed phase, and IACA for category 3 hurricane wind intensity or below. The blue solid line (scaled by a one-third ratio) indicates the ACA computed inside the RMW, and black and gray dashed lines represent the ACA and mixed phase+IACA calculated within 3 times the RMW. The solid and dotted red lines denote the diurnal and semidiurnal signals obtained by applying the inverse Fourier transform to ACA inside the RMW. The yellow line overlaid with the maximum surface wind speed line represents the period from the onset of RI to the mature stage.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The time series analysis of the ACA, mixed phase, and IACA for category 3 hurricane wind intensity or below. The blue solid line (scaled by a one-third ratio) indicates the ACA computed inside the RMW, and black and gray dashed lines represent the ACA and mixed phase+IACA calculated within 3 times the RMW. The solid and dotted red lines denote the diurnal and semidiurnal signals obtained by applying the inverse Fourier transform to ACA inside the RMW. The yellow line overlaid with the maximum surface wind speed line represents the period from the onset of RI to the mature stage.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The time series of the RMW in gray and the eyewall convective cloud in black for category 3 hurricane intensity or below. The eyewall convective cloud represents the averaged value of the normalized IRWVln between 2 and 3 times the RMW. For example, if the value is negative (positive), it shows that the eyewall is well organized (partially disorganized or disorganized). The two vertical-dashed lines indicate the period from the onset of RI to the mature stage.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The time series of the RMW in gray and the eyewall convective cloud in black for category 3 hurricane intensity or below. The eyewall convective cloud represents the averaged value of the normalized IRWVln between 2 and 3 times the RMW. For example, if the value is negative (positive), it shows that the eyewall is well organized (partially disorganized or disorganized). The two vertical-dashed lines indicate the period from the onset of RI to the mature stage.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The time series of the RMW in gray and the eyewall convective cloud in black for category 3 hurricane intensity or below. The eyewall convective cloud represents the averaged value of the normalized IRWVln between 2 and 3 times the RMW. For example, if the value is negative (positive), it shows that the eyewall is well organized (partially disorganized or disorganized). The two vertical-dashed lines indicate the period from the onset of RI to the mature stage.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
b. Category 4
Fourteen RI TCs reached category 4 hurricane intensity after RI. Compared to the previous group, category 4 RI TCs typically display sufficient and extended development of the ACA inside the RMW and within 3 times the RMW (Figs. 6 and 8). In addition, the diurnal signal better replicates the development of the ACA inside the RMW, except for Typhoons Melor (2015), Songda (2016), Sarika (2016), Talim (2017), and Lan (2017). These 5 RI storms were specifically affected by unfavorable environmental conditions such as terrain (Melor and Sarika, Figs. 3a,b), significant changes in OHC (Melor and Songda) and VWS (Songda and Talim, Figs. 4g,h), and mesoscale convective clouds (Lan). In particular, mesoscale convective clouds in the TC’s moving direction could foster the low equivalent potential temperature environment in the low levels as a result of downdraft cooling with substantial precipitation. If these low equivalent potential temperature air parcels flow into the storm’s inner-core area along with the radial inflow in the boundary layer, it could potentially affect TC intensification as well as the disorganization of convective cells. As a result, the ACA appears to fluctuate temporarily (Fig. 8n). In this case, the semidiurnal signal synthesized with the diurnal signal could better describe the development of the ACA. However, these category 4 RI storms rarely experienced a complete loss of ACA inside the RMW or within 3 times the RMW compared to storms of category 3 or below. As stated in the previous subsection and the Introduction, thick clouds can reduce net radiational cooling in the mid- or lower troposphere regardless if it is daytime or nighttime. In contrast, the upper troposphere may experience a significant net radiational warming and cooling during daytime and nighttime. This strong radiational contrast may enhance destabilization that can enhance convective activity at night, and this sequential process may result in a positive convective activity feedback cycle. In addition, the onset of RI normally commences with an increase of the ACA inside the RMW and a significant contraction of the RMW (Figs. 8 and 9). Meanwhile, most TCs passed through a moderate or high OHC region during the RI period (Tables 2–4). When Typhoon Koppu (2017) underwent RI, it showed a sustainable ACA inside the RMW (Fig. 8c), while being located in a high OHC region (10.9 GJ m−2) and under moderate VWS (Table 2). By contrast, despite insufficient ACA inside the RMW and unfavorable environments such as strong VWS and low OHC, Songda underwent RI. This unusual intensification may be related to the substantial RMW contraction, the enhanced ventilation flow in the upper troposphere due to a midtrough interaction, and quick development of a tiny eye structure inside the RMW during the RI period (Figs. 8j and 9j). Except for the VWS, characteristics on the amount of ACA inside the RMW and substantial RMW contraction are similar to Namtheun (2016) and Sanvu (2017) (Figs. 6c,f and 7c,f). Previous studies demonstrated that TC eye formation is indicative of both stabilization and intensification of the vortex structure (Schubert and Hack 1982; Shapiro and Willoughby 1982; Jorgensen 1984; Weatherford and Gray 1988; Vigh and Schubert 2009; Vigh et al. 2012). If TC adequately satisfies thermal wind balance, the momentum field could be balanced with the thermodynamic field at the levels at which the friction sufficiently decreases (Schubert and Hack 1982; Shapiro and Willoughby 1982). Subsequently, the maximum gradient of the inertial stability, which generally coincides with the RMW, could move quickly toward the maximum heating area, and the heating induced by the ACA inside the RMW could possibly be responsible for this considerable RMW contraction. This could explain why convective cells, like CBs inside the RMW, are considered necessary for TC intensification (Rogers et al. 2013). Therefore, the differences in the ACA sustainability inside the RMW and eyewall convective cloud may be important to TC intensification. Overall, category 4 RI TCs showed sufficient development of the ACA inside the RMW and maintain eyewall convective cloud as compared with the storms of category 3 or below (Figs. 8 and 9). As a result, the diurnal signal of the ACA can better describe the ACA development inside the RMW, although some cases have exhibited many semidiurnal variations in ACA development and fluctuations in the eyewall convective cloud (Figs. 8 and 9).
As in Fig. 6, but for category 4 storms.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
As in Fig. 6, but for category 4 storms.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
As in Fig. 6, but for category 4 storms.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
As in Fig. 7, but for category 4 storms.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
As in Fig. 7, but for category 4 storms.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
As in Fig. 7, but for category 4 storms.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
c. Category 5
From the 30 RI samples, seven storms reached a category 5 intensity (Tables 2 and 3 and Fig. 10), which represent a higher frequency in 2016, while there were no category 5 storms in 2017 (Tables 3 and 4). As seen in Fig. 3c, the track of the RI TCs in 2017 appears much more erratic compared to the other two years. These erratic tracks may show that largescale currents are complex, which may be unfavorable to TC intensification. For example, category 5 storms tend to have consistent westward or northwestward tracks (Figs. 3a,b) and the OHC in 2017 was lower than in 2015 and 2016 (Tables 2–4). Figure 10 shows the time series of the ACA of category 5 RI TCs. During the RI period, they have exhibited a persistent ACA inside the RMW and within 3 times the RMW without significant fluctuations until the TC’s eye forms, which is distinct compared to the other previous groups. In this case, the ACA’s diurnal signal tends to better account for their changes inside the RMW. These very intense storms tend to maintain eyewall convective clouds by means of persistent or long-lived convective clouds within 3 times the RMW since the onset of RI (Figs. 10 and 11). In addition, they passed through a moderate or high OHC region and favorable VWS environment during the RI period (Tables 2–4). This solid eyewall structure could prevent unfavorable interactions such as dry air intrusion from the outer environment and help maintain the favorable internal structure of the TC. Most of the category 5 RI storms maintained a solid eyewall until making landfall or encountering the region with low OHC. For example, significant fluctuations in the eyewall convective cloud of Typhoons Soudelor (2015) and Atsani (2015) were observed at the end of RI (Figs. 11a,b), after which both storms had considerably weakened (Figs. 10a,b). These characteristics seem to be highly related to OHC. For instance, after RI, Soudelor encountered the locally developed lower OHC, which also included cold wakes induced by the storm (Figs. 12a,c), whereas Atsani experienced a gradual decrease in OHC as it moved northwestward (Figs. 12b,d). During this period, both storms experienced significant ACA dissipation within 3 times the RMW and collapse of the eyewall convective cloud (Figs. 10 and 11a,b), while simultaneously, the TC intensity had weakened significantly (Figs. 10a,b). These results may represent a good example of the relationship between OHC and ACA.
As in Fig. 6, but for category 5 storms.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
As in Fig. 6, but for category 5 storms.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
As in Fig. 6, but for category 5 storms.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
As in Fig. 7, but for category 5 storms.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
As in Fig. 7, but for category 5 storms.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
As in Fig. 7, but for category 5 storms.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The OHC (GJ m−2) overlaid with TC tracks of (a),(c) Soudelor and (b),(d) Atsani. The status of OHC (top) before RI and (bottom) after RI. The RI period is displayed in Table 2. The black arrow indicates the TC position of each date, and the contour is drawn at 4 GJ m−2 intervals. The OHC has been explicitly calculated by using the Global Hybrid Coordinate Ocean Model data.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The OHC (GJ m−2) overlaid with TC tracks of (a),(c) Soudelor and (b),(d) Atsani. The status of OHC (top) before RI and (bottom) after RI. The RI period is displayed in Table 2. The black arrow indicates the TC position of each date, and the contour is drawn at 4 GJ m−2 intervals. The OHC has been explicitly calculated by using the Global Hybrid Coordinate Ocean Model data.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The OHC (GJ m−2) overlaid with TC tracks of (a),(c) Soudelor and (b),(d) Atsani. The status of OHC (top) before RI and (bottom) after RI. The RI period is displayed in Table 2. The black arrow indicates the TC position of each date, and the contour is drawn at 4 GJ m−2 intervals. The OHC has been explicitly calculated by using the Global Hybrid Coordinate Ocean Model data.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
To summarize this section, these category 5 RI storms tend to have a more persistent ACA inside the RMW and maintain eyewall convective cloud as compared with two previous RI groups. This sustainable ACA may be possible under moderate or high OHC, weak or moderate VWS, no apparent mesoscale convection close to the storm, and no terrain interaction. Also, these category 5 storms rarely have accompanied mesoscale convective clouds in front of the TC’s heading direction during the intensifying period.
5. The relationship between eyewall convective cloud and TC intensity change
As previously discussed, the eyewall convective cloud is believed to be associated with TC intensity change. For example, convective clouds in the eyewall region of category 5 TCs tends to persist without significant dissipation, as compared to relatively weak TCs (Figs. 7, 9, and 11). In this section, a simple linear regression analysis has been carried out to understand the relationship between the eyewall convective cloud and TC intensity change. Figure 13 shows the results of the scatterplots, which illustrate the relationship between the normalized IRWVln and four TC intensity changes such as SI, RI, N, and W, in Table 5. Each scatterplot includes both an instantaneous IRWVln normalized in the eyewall area and a successive TC intensity change at 6-h intervals, which explains the dependency of TC intensity changes on the normalized IRWVln in the eyewall. The concentration of scatter points from the first two columns from the left shows that RI is likely to begin after the SI phase (Figs. 13a,b,e,f,i,j). This result indicates that the onset of RI requires improvements in the eyewall convective activity and TC’s primary circulation during the SI phase. This characteristic is more apparent in intense storms such as those of categories 4 and 5. After SI, the TC intensity almost reached the category 1 hurricane intensity, which may explain why the onset of RI is normally highly concentrated around the category 1 hurricane intensity (Kaplan and DeMaria 2003; Hendricks et al. 2010; Jiang 2012). Meanwhile, during the RI period, TC tends to rapidly form a solid eyewall structure (Figs. 13b,f,j). In this case, the TC is able to withstand unfavorable interactions such as dry air intrusion. However, for category 3 or below, since TCs are prone to have a single diurnal variation, eyewall convective clouds are usually short lived (Figs. 6 and 7). As a result, the scatter points are somewhat less concentrated as compared with category 4 or 5 RI TCs (Figs. 13a,b,e,f,i,j). In other words, it appears that the correlation between the normalized IRWVln in the eyewall area and maximum wind speed is low.
The scatterplots that account for a relationship between the normalized IRWVln and TC intensity change at 30-min intervals of satellite imagery. Four TC intensity changes such as SI, RI, N, and W, are divided by the definitions shown in Table 5. Each scatter point includes both the current maximum surface wind and the normalized IRWVln in the eyewall area. The colored vertical lines denote the hurricane intensity. The cyan line indicates a linear regression between these two variables.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The scatterplots that account for a relationship between the normalized IRWVln and TC intensity change at 30-min intervals of satellite imagery. Four TC intensity changes such as SI, RI, N, and W, are divided by the definitions shown in Table 5. Each scatter point includes both the current maximum surface wind and the normalized IRWVln in the eyewall area. The colored vertical lines denote the hurricane intensity. The cyan line indicates a linear regression between these two variables.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The scatterplots that account for a relationship between the normalized IRWVln and TC intensity change at 30-min intervals of satellite imagery. Four TC intensity changes such as SI, RI, N, and W, are divided by the definitions shown in Table 5. Each scatter point includes both the current maximum surface wind and the normalized IRWVln in the eyewall area. The colored vertical lines denote the hurricane intensity. The cyan line indicates a linear regression between these two variables.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
Four phases of TC intensity change. The threshold indicates a 6-h intensity change, and the amount represents the number of scatterplots for each phase depending on categories.
The N phase represents the changes in the eyewall convective cloud without any significant maximum surface wind enhancement (Fig. 13c). In other words, it manifests a temporary cessation of TC intensification or weakening. For example, both typhoons Dujuan and Chaba showed a substantial ACA in the tropical storm stage, but they did not form any eye structure in the upper troposphere (Fig. 14). This vast convective cloud is typically referred to as the central cold cover, which is typically associated with steady intensity (Dvorak 1984; Lander 1999). Despite substantial convective clouds, these typhoons did not intensify at all during this period. Such nonintensification may be associated with the weak primary circulation or the absence of eye structure in the early TC development (Fig. 14). Finally, TC weakening generally occurs after the mature stage. During this period, both the eyewall convective cloud and the primary circulation tend to weaken (Figs. 13d,h,l). Of the four intensity changes, the W phase shows the highest correlation coefficient, indicating that a weakening of the eyewall convective clouds can lead to a weakening of TC intensity. Since most scatterplots show moderate or high linear regression correlation coefficients, these results may account for that the close association of TC intensification with the convective clouds in the eyewall region (Fig. 13).
Snapshots of the field of IRWVln (K) for tropical storms (a) Dujuan (2015) at 2300 UTC 22 Sep and (b) Chaba (2016) at 1400 UTC 29 Sep. Both typhoons show an expansive area of ACA, mixed phase, and IACA.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
Snapshots of the field of IRWVln (K) for tropical storms (a) Dujuan (2015) at 2300 UTC 22 Sep and (b) Chaba (2016) at 1400 UTC 29 Sep. Both typhoons show an expansive area of ACA, mixed phase, and IACA.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
Snapshots of the field of IRWVln (K) for tropical storms (a) Dujuan (2015) at 2300 UTC 22 Sep and (b) Chaba (2016) at 1400 UTC 29 Sep. Both typhoons show an expansive area of ACA, mixed phase, and IACA.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
6. The diurnal variation of TC eye diameter
The formation of the eye structure typically represents both stabilization and intensification of the TC (Schubert and Hack 1982; Shapiro and Willoughby 1982; Jorgensen 1984; Weatherford and Gray 1988; Vigh and Schubert 2009; Vigh et al. 2012). Weatherford and Gray (1988) showed that TC eye size tends to decrease with TC intensity. Muramatsu (1983) noted that the maximum and minimum eye sizes could be observed typically during daytime and early morning, respectively, due to cloud dissipation or development from the eye area. To further investigate the diurnal variation of TC eye size, four category 5 storms, which maintain eyewall convective clouds until the mature stage without any interruption such as dry air intrusion, are selected.
Figure 15 shows the TC eye size estimated by positive IRWVln within 2 times the RMW. From satellite imagery, it was confirmed that all four category 5 storms formed an eye structure during the RI period. The estimated TC eye size generally expands considerably during the day, while remaining constant or shrinking at night, which is in concurrence with the findings of Muramatsu (1983). Since the eye is always an open area, it may experience a significant radiational cooling, and is very stable, that is, a nonconvective area, as compared with the eyewall. While the convective activity is suppressed during the day, significant radiational cooling in the eye region may contribute to the removal of clouds that encroach into the eye because of the convective activity. As a result, this diurnal variation in TC eye size estimated from satellite imagery exhibits an opposite pattern compared to the convective activity (Figs. 10a,c,e and 15).
The estimated TC’s eye area calculated within 2 times the RMW: (a) Soudelor, (b) Nepartak, (c) Meranti, and (d) Chaba, respectively. The two vertical-dashed lines indicate the RI period. The blue line indicates the percentage of ACA computed within 3 times the RMW (Figs. 10a,c–e).
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The estimated TC’s eye area calculated within 2 times the RMW: (a) Soudelor, (b) Nepartak, (c) Meranti, and (d) Chaba, respectively. The two vertical-dashed lines indicate the RI period. The blue line indicates the percentage of ACA computed within 3 times the RMW (Figs. 10a,c–e).
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
The estimated TC’s eye area calculated within 2 times the RMW: (a) Soudelor, (b) Nepartak, (c) Meranti, and (d) Chaba, respectively. The two vertical-dashed lines indicate the RI period. The blue line indicates the percentage of ACA computed within 3 times the RMW (Figs. 10a,c–e).
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
Figure 16 shows schematic diagrams that summarize the diurnal variation of the convective cloud and eye diameter identified through satellite imagery. Thick convective clouds can reduce the radiational cooling and simultaneously enhance radiational warming (Gray and Jacobson 1977); therefore, solar radiation can suppress convective clouds because of radiatively stabilized upper clouds during the day (Fig. 16a). If these convective clouds do not dissipate significantly during the day, destabilization could increase, caused by the contrast of net radiation between the upper and mid- or lower clouds at night. Navarro and Hakim (2016) elucidated this diurnal contrast through idealized numerical results. From their Figs. 8 and 9, the radial-vertical anomalous vectors are manifested as cyclonic circulation during the daytime, while it is anticyclonic circulation in the nighttime. This anticyclonic circulation in the midtroposphere may enhance the convective activity at night. Zhang et al. (2020) recently discussed that the boundary layer inflow is deeper and stronger during the nighttime than in the daytime. During nighttime and in the boundary layer, high equivalent potential temperature and relative humidity were observed in the inner and outer areas, respectively. These previous studies may support the theory that kinetic and thermodynamic structures of the storm can be altered by the diurnal variation. These favorable inner-core variations caused by the diurnal variation may explain why the TC’s convective activity becomes active mainly at night. Once the TC eye forms inside the RMW, the eye size tends to change inversely to the convective activity, which is evidenced by the satellite imagery that shows a large eye is usually identified during the day and shrinks at night (Fig. 15). Since the TC eye is represented as the cloud-free area, the radiational cooling could always be significant; therefore, some of the clouds that encroach from the innermost eyewall could dissipate considerably during the day, while the convective clouds could again encroach into the eye region at night. This eventually contributes to contraction of the TC eye.
Schematic diagrams for the diurnal variation of convection and eye diameter during the (a) daytime and (b) nighttime. The long solid black arrows indicate vertical flows. During the day, the convective area could shrink due to solar radiation that makes the upper clouds stabilized. If thick clouds do not dissipate considerably during the day, it could act to reduce the radiational cooling in the mid- and lower troposphere. In this case, the radiational contrast between the upper clouds and mid- or lower clouds becomes significant at night. As a result, destabilization caused by this radiational contrast could enhance the convective activity. The arrows in the cylinder indicate the changes in TC eye size related to the diurnal cycle. The eye size is sensitive to the convective activity. For example, convective clouds developed from the innermost eyewalls may invade the eye area. In the early morning, the eye could seem small in the satellite imagery (Fig. 15). In contrast, since the radiational cooling is always significant in the eye region, some clouds could naturally dissipate from that region. As a result, the eye could become larger and more distinct during the day.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
Schematic diagrams for the diurnal variation of convection and eye diameter during the (a) daytime and (b) nighttime. The long solid black arrows indicate vertical flows. During the day, the convective area could shrink due to solar radiation that makes the upper clouds stabilized. If thick clouds do not dissipate considerably during the day, it could act to reduce the radiational cooling in the mid- and lower troposphere. In this case, the radiational contrast between the upper clouds and mid- or lower clouds becomes significant at night. As a result, destabilization caused by this radiational contrast could enhance the convective activity. The arrows in the cylinder indicate the changes in TC eye size related to the diurnal cycle. The eye size is sensitive to the convective activity. For example, convective clouds developed from the innermost eyewalls may invade the eye area. In the early morning, the eye could seem small in the satellite imagery (Fig. 15). In contrast, since the radiational cooling is always significant in the eye region, some clouds could naturally dissipate from that region. As a result, the eye could become larger and more distinct during the day.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
Schematic diagrams for the diurnal variation of convection and eye diameter during the (a) daytime and (b) nighttime. The long solid black arrows indicate vertical flows. During the day, the convective area could shrink due to solar radiation that makes the upper clouds stabilized. If thick clouds do not dissipate considerably during the day, it could act to reduce the radiational cooling in the mid- and lower troposphere. In this case, the radiational contrast between the upper clouds and mid- or lower clouds becomes significant at night. As a result, destabilization caused by this radiational contrast could enhance the convective activity. The arrows in the cylinder indicate the changes in TC eye size related to the diurnal cycle. The eye size is sensitive to the convective activity. For example, convective clouds developed from the innermost eyewalls may invade the eye area. In the early morning, the eye could seem small in the satellite imagery (Fig. 15). In contrast, since the radiational cooling is always significant in the eye region, some clouds could naturally dissipate from that region. As a result, the eye could become larger and more distinct during the day.
Citation: Monthly Weather Review 148, 10; 10.1175/MWR-D-19-0345.1
7. Summary
Based on Himawari-8 satellite imagery, this study examines the diurnal variation of the convective area and eye size of RI TCs occurring in the western North Pacific from 2015 to 2017. The findings are summarized as follows:
The ACA generally develops at night, while shrinking significantly during the day (Figs. 6, 8, and 10). Generally, the RI TCs experience at least a single diurnal variation of the ACA inside the RMW during the RI period (Figs. 6, 8, and 10). For intense TCs, the ACA is maintained longer both inside the RMW and within 3 times the RMW, in which case the diurnal signal appears continuous (Figs. 8 and 10). During the RI period, eyewall convective clouds tend to be further organized (Figs. 9 and 11). However, when the TC encounters low OHC, it could cause weakening of TC intensity as a result of the weakening of the original eyewall convective clouds (disorganization of the ACA) (Figs. 10a,b, 11a,b, and 12).
From the results of the linear regression analysis, the scatterplots demonstrate that RI tends to commence after SI stage (Figs. 13a,b,e,f,i,j), which indicates that RI may require enhancement of the eyewall convective cloud and the primary circulation during the SI phase. The N phase simply represents a change of the eyewall convective cloud without any significant enhancement of the primary circulation (Figs. 13c,g,k) and indicates a temporary cessation of TC intensification or weakening. Of the four intensity changes, the W phase shows the highest correlation coefficient (Figs. 13d,h,l), indicating that TC intensification and weakening could be highly related to TC eyewall convective clouds.
From satellite imagery, the eye structure is normally formed during the RI period (Fig. 15). Once the TC eye forms inside the RMW, the eye size tends to change inversely with the convective activity. For example, a large eye is usually identified during the day, while contracting at night. Since the TC eye is located in the cloud-free area, the radiational cooling is always significant, and thereby causing the clouds in the eye region to dissipate over time, which may explain the appearance of a large eye during the day. In contrast, since the convective activity is invigorated at night, the convective clouds could limit the eye size.
In future work, we plan to quantitatively examine the difference in the ACA derived from IRWVln and convective area observed from microwave satellite imagery. In particular, we will think about how this IRWVln technique could address not only deep convection, but also shallow or moderate convection in conjunction with other observations such as microwave satellite. In addition, three brightness temperature definitions used to distinguish the convective area remain to be thoroughly verified with in situ aircraft observation data. Finally, to elaborate the impact of diurnal variation on RI in terms of kinetic or thermodynamic perspectives, numerical simulations would also be conducted.
Acknowledgments
This work is supported by the Ministry of Science and Technology of Taiwan under Grants MOST 106-2111-M-002-013-MY3, MOST 107-2111-M-002-016-MY3, and by the Office of Naval Research through Grant N62909-16-1-2169. We thank Dr. Russell L. Elsberry for an excellent discussion about the diurnal variation of the tropical cyclone. Also, we thank Japan Aerospace Exploration Agency for providing a full-disk dataset of Himawari-8/AHI operated by JMA through the P-Tree System. Last, helpful comments from Anna Vaughan, Yi-Hsuan Hwang, and two anonymous reviewers are also highly appreciated.
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