• Abarca, S. F., and M. T. Montgomery, 2013: Essential dynamics of secondary eyewall formation. J. Atmos. Sci., 70, 32163230, doi:10.1175/JAS-D-12-0318.1.

    • Search Google Scholar
    • Export Citation
  • Abarca, S. F., and M. T. Montgomery, 2015: Are eyewall replacement cycles governed largely by axisymmetric balance dynamics? J. Atmos. Sci., 72, 8287, doi:10.1175/JAS-D-14-0151.1.

    • Search Google Scholar
    • Export Citation
  • Bell, M. M., M. T. Montgomery, and W. C. Lee, 2012: An axisymmetric view of concentric eyewall evolution in Hurricane Rita (2005). J. Atmos. Sci., 69, 24142432, doi:10.1175/JAS-D-11-0167.1.

    • Search Google Scholar
    • Export Citation
  • Black, M. L., G. A. Wick, J. R. Spackman, T. Hock, and R. Hood, 2011: Real-time data transmission, processing and dissemination of GPS dropwindsonde data from the NASA Global Hawk unmanned aircraft. 2011 Fall Meeting, San Francisco, CA, Amer. Geophys. Union, Abstract IN13C-04.

  • Bödewadt, U. T., 1940: Die Drehströmung übder fester Grund. Z. Angew. Math. Mech., 20, 241253, doi:10.1002/zamm.19400200502.

  • Bolton, D., 1980: The computation of equivalent potential temperature. Mon. Wea. Rev., 108, 10461053, doi:10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Braun, S. A., P. A. Newman, and G. M. Heymsfield, 2016: NASA’s Hurricane and Severe Storm Sentinel (HS3) Investigation. Bull. Amer. Meteor. Soc., doi:10.1175/BAMS-D-15-00186.1, in press.

    • Search Google Scholar
    • Export Citation
  • Bui, H. H., R. K. Smith, M. T. Montgomery, and J. Peng, 2009: Balanced and unbalanced aspects of tropical-cyclone intensification. Quart. J. Roy. Meteor. Soc., 135, 17151731, doi:10.1002/qj.502.

    • Search Google Scholar
    • Export Citation
  • DeMaria, M., and J. Kaplan, 1994: A Statistical Hurricane Intensity Prediction Scheme (SHIPS) for the Atlantic basin. Wea. Forecasting, 9, 209220, doi:10.1175/1520-0434(1994)009<0209:ASHIPS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • DeMaria, M., and J. Kaplan, 1999: An updated Statistical Hurricane Intensity Prediction Scheme (SHIPS) for the Atlantic and eastern North Pacific basins. Wea. Forecasting, 14, 326337, doi:10.1175/1520-0434(1999)014<0326:AUSHIP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • DeMaria, M., M. Mainelli, L. K. Shay, J. A. Knaff, and J. Kaplan, 2005: Further improvements to the Statistical Hurricane Intensity Prediction Scheme (SHIPS). Wea. Forecasting, 20, 531543, doi:10.1175/WAF862.1.

    • Search Google Scholar
    • Export Citation
  • Didlake, A. C., Jr., and R. A. Houze Jr., 2011: Kinematics of the secondary eyewall observed in Hurricane Rita (2005). J. Atmos. Sci., 68, 16201636, doi:10.1175/2011JAS3715.1.

    • Search Google Scholar
    • Export Citation
  • Elsberry, R. L., and P. A. Harr, 2008: Tropical Cyclone Structure (TCS08) field experiment science basis, observational platforms, and strategy. Asia-Pac. J. Atmos. Sci., 44, 209231.

    • Search Google Scholar
    • Export Citation
  • Hawkins, J. D., and M. Helveston, 2004: Tropical cyclone multiple eyewall characteristics. 26th Conf. on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., P1.7. [Available online at https://ams.confex.com/ams/26HURR/techprogram/paper_76084.htm.]

  • Hawkins, J. D., and M. Helveston, 2008: Tropical cyclone multiple eyewall characteristics. 28th Conf. on Hurricanes and Tropical Meteorology, Orlando, FL, Amer. Meteor. Soc., 14B.1. [Available online at https://ams.confex.com/ams/28Hurricanes/techprogram/paper_138300.htm.]

  • Hock, T., K. Young, and H. Voemel, 2016: Hurricane and Severe Storm Sentinel (HS3) Global Hawk Advanced Vertical Atmospheric Profiling System (AVAPS) Dropsonde System [dropsondes deployed during Storm Edouard]. NASA Global Hydrology Resource Center DAAC, Huntsville, AL, accessed January 2015, doi:10.5067/HS3/AVAPS/DROPSONDE/DATA201. [Dataset available online at https://hs3.nsstc.nasa.gov/pub/hs3/AVAPS/.]

  • Holton, J. R., 2004: An Introduction to Dynamic Meteorology. Elsevier Academic, 535 pp.

  • Houze, R. A. J., S. S. Chen, B. F. Smull, W. C. Lee, and M. M. Bell, 2007: Hurricane intensity and eyewall replacement. Science, 315, 12351239, doi:10.1126/science.1135650.

    • Search Google Scholar
    • Export Citation
  • Huang, Y.-H., M. T. Montgomery, and C.-C. Wu, 2012: Concentric eyewall formation in Typhoon Sinlaku (2008). Part II: Axisymmetric dynamical processes. J. Atmos. Sci., 69, 662674, doi:10.1175/JAS-D-11-0114.1.

    • Search Google Scholar
    • Export Citation
  • Jarvinen, B. R., C. J. Neumann, and M. A. S. Davis, 1984: A tropical cyclone data tape for the North Atlantic basin, 1886–1983: Contents, limitations, and uses. NOAA Tech. Memo. NWS NHC 22, 21 pp.

  • Kepert, J., 2001: The dynamics of boundary layer jets within the tropical cyclone core. Part I: Linear theory. J. Atmos. Sci., 58, 24692484, doi:10.1175/1520-0469(2001)058<2469:TDOBLJ>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kepert, J., 2013: How does the boundary layer contribute to eyewall replacement cycles in axisymmetric tropical cyclones? J. Atmos. Sci., 70, 28082830, doi:10.1175/JAS-D-13-046.1.

    • Search Google Scholar
    • Export Citation
  • Kepert, J., and Y. Wang, 2001: The dynamics of boundary layer jets within the tropical cyclone core. Part II: Nonlinear enhancement. J. Atmos. Sci., 58, 24852501, doi:10.1175/1520-0469(2001)058<2485:TDOBLJ>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kepert, J., and D. S. Nolan, 2014: Reply to “Comments on ‘How does the boundary layer contribute to eyewall replacement cycles in axisymmetric tropical cyclones?’” J. Atmos. Sci., 71, 46924704, doi:10.1175/JAS-D-14-0014.1.

    • Search Google Scholar
    • Export Citation
  • Kossin, J. P., and M. Sitkowski, 2009: An objective model for identifying secondary eyewall formation in hurricanes. Mon. Wea. Rev., 137, 876892, doi:10.1175/2008MWR2701.1.

    • Search Google Scholar
    • Export Citation
  • Kuo, H.-C., W. H. Schubert, C.-L. Tsai, and Y.-F. Kuo, 2008: Vortex interactions and barotropic aspects of concentric eyewall formation. Mon. Wea. Rev., 136, 51835198, doi:10.1175/2008MWR2378.1.

    • Search Google Scholar
    • Export Citation
  • Kuo, H.-C., C.-P. Chang, Y.-T. Yang, and H.-J. Jiang, 2009: Western North Pacific typhoons with concentric eyewalls. Mon. Wea. Rev., 137, 37583770, doi:10.1175/2009MWR2850.1.

    • Search Google Scholar
    • Export Citation
  • Maclay, K. S., M. DeMaria, and T. H. Vonder Haar, 2008: Tropical cyclone inner core kinetic energy evolution. Mon. Wea. Rev., 136, 48824898, doi:10.1175/2008MWR2268.1.

    • Search Google Scholar
    • Export Citation
  • Mallen, K. J., M. T. Montgomery, and B. Wang, 2005: Reexamining the near-core radial structure of the tropical cyclone primary circulation: Implications for vortex resiliency. J. Atmos. Sci., 62, 408425, doi:10.1175/JAS-3377.1.

    • Search Google Scholar
    • Export Citation
  • Montgomery, M. T., J. A. Zhang, and R. K. Smith, 2014: The low-level structure of rapidly intensifying and mature Hurricane Earl (2010). Quart. J. Roy. Meteor. Soc., 140, 21322146, doi:10.1002/qj.2283.

    • Search Google Scholar
    • Export Citation
  • Ooyama, K. V., 1969: Numerical simulation of the life cycle of tropical cyclones. J. Atmos. Sci., 26, 340, doi:10.1175/1520-0469(1969)026<0003:NSOTLC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Rogers, R. F., and Coauthors, 2013: NOAA’s Hurricane Intensity Forecasting Experiment: A progress report. Bull. Amer. Meteor. Soc., 94, 859882, doi:10.1175/BAMS-D-12-00089.1.

    • Search Google Scholar
    • Export Citation
  • Rozoff, C. M., D. S. Nolan, J. P. Kossin, F. Zhang, and J. Fang, 2012: The roles of an expanding wind field and inertial stability in tropical cyclone secondary eyewall formation. J. Atmos. Sci., 69, 26212643, doi:10.1175/JAS-D-11-0326.1.

    • Search Google Scholar
    • Export Citation
  • Schlichting, H., 1968: Boundary Layer Theory. 6th ed. McGraw-Hill, 747 pp.

  • Shapiro, L. J., and H. E. Willoughby, 1982: The response of balanced hurricanes to local sources of heat and momentum. J. Atmos. Sci., 39, 378394, doi:10.1175/1520-0469(1982)039<0378:TROBHT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Smith, R. K., M. T. Montgomery, and N. Van Sang, 2009: Tropical cyclone spin-up revisited. Quart. J. Roy. Meteor. Soc., 135, 13211335, doi:10.1002/qj.428.

    • Search Google Scholar
    • Export Citation
  • Stewart, S. R., 2014: National Hurricane Center Tropical Cyclone Report: Hurricane Edouard (11–19 September 2014). Tropical Cyclone Rep. AL062014, National Hurricane Center, 19 pp. [Available online at http://www.nhc.noaa.gov/data/tcr/AL062014_Edouard.pdf.]

  • Sun, Y. Q., Y. Jiang, B. Tan, and F. Zhang, 2013: The governing dynamics of the secondary eyewall formation of Typhoon Sinlaku (2008). J. Atmos. Sci., 70, 38183837, doi:10.1175/JAS-D-13-044.1.

    • Search Google Scholar
    • Export Citation
  • Willoughby, H. E., J. A. Clos, and M. G. Shoreibah, 1982: Concentric eye walls, secondary wind maxima, and the evolution of the hurricane vortex. J. Atmos. Sci., 39, 395411, doi:10.1175/1520-0469(1982)039<0395:CEWSWM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Yang, Y. T., H.-C. Kuo, E. A. Hendricks, and M. S. Peng, 2013: Structural and intensity changes of concentric eyewall typhoons in the western North Pacific basin. Mon. Wea. Rev., 141, 26322648, doi:10.1175/MWR-D-12-00251.1.

    • Search Google Scholar
    • Export Citation
  • Zhu, Z., and P. Zhu, 2014: The role of outer rainband convection in governing the eyewall replacement cycle in numerical simulations of tropical cyclones. J. Geophys. Res. Atmos., 119, 80498072, doi:10.1002/2014JD021899.

    • Search Google Scholar
    • Export Citation
  • View in gallery

    Edouard (2014) as captured by (top left) DMSP F15 SSM/I 85-GHz and (top right) DMSP F18 SSMIS 91-GHz microwave satellite imagery and the NHC/TCP best track dataset (middle) intensity and (bottom) track. The period of study, between 1506:37 UTC 16 Sep and 0828:03 UTC 17 Sep, is highlighted with solid thick lines. Also shown are the shear magnitude (blue line) and direction (green line), as captured by the Statistical Hurricane Intensity Predictor Scheme (SHIPS).

  • View in gallery

    Locations of dropsonde deployments, relative to the storm center, during (a) the secondary eyewall formation period (from 1413 to 1920 UTC 15 Sep) and (b) the mature and decaying secondary eyewall period (from 1606 UTC 16 Sep to 0828 UTC 17 Sep). The concentric circles indicate the radial distance (in km) from the center of the storm. [Note: Horizontal scale in (a) is larger than the scale in (b).]

  • View in gallery

    Composite (a) tangential wind velocity (m s−1) and (b) radial location of the dropsondes for the decaying double eyewalled storm period. In (a) a color bar is used to display the structure of tangential velocity. In (b) the black dots indicate the average measurement radius for each dropsonde in the analysis (distributed in the vertical to avoid superposition). The red lines indicate the radial location of the center of the analysis bins. The bins are delimited by the locations of the vertical blue lines. The numbers superposed on the red lines indicate the number of dropsondes in each radial bin (see text for further details).

  • View in gallery

    Composite (a) tangential wind velocity (m s−1), (b) agradient force (m s−1 h−1), and (c) radial location of the dropsondes for the secondary eyewall formation period. In (a) and (b) the orange and red colors indicate increasingly positive values, respectively; blue colors indicate negative values. In (c) the black dots indicate the average measurement radius for each dropsonde in the analysis. The red lines indicate the radial location of the center of the bins. The bins are delimited by the locations of the vertical blue lines. The numbers superposed on the red lines indicate the number of dropsondes in each radial bin (see text for further details).

  • View in gallery

    Composite (a) radial velocity (m s−1), (b) absolute vorticity (s−1, ×10−4), and (c) radial vorticity flux (m s−1 h−1) for the secondary eyewall formation period. In (a) and (c) the color bar indicates increasingly positive values beginning with light brown through dark red; increasingly negative values are indicated with darker shades of blue. In (b) the color bar indicates only positive values (see text for further details).

  • View in gallery

    (a) Vertically averaged (in the lowest km) radial flow as a function of radius, and (b) vertical profiles of equivalent potential temperature and saturated equivalent potential temperature (K). In (a) the vertical red lines indicate the radial location of the center of the bins. The bins are delimited by the locations of the vertical blue lines. The number superposed on the red lines indicates the number of dropsondes in each radial bin (see text for further details).

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 190 177 6
PDF Downloads 92 87 8

On the Secondary Eyewall Formation of Hurricane Edouard (2014)

View More View Less
  • 1 I. M. Systems Group, National Oceanic and Atmospheric Administration/National Weather Service/National Centers for Environmental Protection, College Park, Maryland
  • | 2 Naval Postgraduate School, Monterey, California
  • | 3 National Aeronautics and Space Administration Goddard Space Flight Center, Greenbelt, Maryland
  • | 4 University of Miami, Cooperative Institute for Marine and Atmospheric Studies, and NOAA/Atlantic Oceanographic and Meteorological Laboratory/Hurricane Research Division, Miami, Florida
© Get Permissions
Full access

Abstract

A first observationally based estimation of departures from gradient wind balance during secondary eyewall formation is presented. The study is based on the Atlantic Hurricane Edouard (2014). This storm was observed during the National Aeronautics and Space Administration’s (NASA) Hurricane and Severe Storm Sentinel (HS3) experiment, a field campaign conducted in collaboration with the National Oceanic and Atmospheric Administration (NOAA). A total of 135 dropsondes are analyzed in two separate time periods: one named the secondary eyewall formation period and the other one referred to as the decaying double eyewalled storm period. During the secondary eyewall formation period, a time when the storm was observed to have only one eyewall, the diagnosed agradient force has a secondary maximum that coincides with the radial location of the secondary eyewall observed in the second period of study. The maximum spinup tendency of the radial influx of absolute vertical vorticity is within the boundary layer in the region of the eyewall of the storm and the spinup tendency structure elongates radially outward into the secondary region of supergradient wind, where the secondary wind maximum is observed in the second period of study. An analysis of the boundary layer averaged vertical structure of equivalent potential temperature reveals a conditionally unstable environment in the secondary eyewall formation region. These findings support the hypothesis that deep convective activity in this region contributed to spinup of the boundary layer tangential winds and the formation of a secondary eyewall that is observed during the decaying double eyewalled storm period.

Corresponding author address: Sergio F. Abarca, I. M. Systems Group, NOAA/NWS/NCEP, 5830 University Research Court, College Park, MD 20740-3818. E-mail: sergio.abarca@noaa.gov

This article is included in the NASA Hurricane Severe Storm Sentinel (HS3) special collection.

Abstract

A first observationally based estimation of departures from gradient wind balance during secondary eyewall formation is presented. The study is based on the Atlantic Hurricane Edouard (2014). This storm was observed during the National Aeronautics and Space Administration’s (NASA) Hurricane and Severe Storm Sentinel (HS3) experiment, a field campaign conducted in collaboration with the National Oceanic and Atmospheric Administration (NOAA). A total of 135 dropsondes are analyzed in two separate time periods: one named the secondary eyewall formation period and the other one referred to as the decaying double eyewalled storm period. During the secondary eyewall formation period, a time when the storm was observed to have only one eyewall, the diagnosed agradient force has a secondary maximum that coincides with the radial location of the secondary eyewall observed in the second period of study. The maximum spinup tendency of the radial influx of absolute vertical vorticity is within the boundary layer in the region of the eyewall of the storm and the spinup tendency structure elongates radially outward into the secondary region of supergradient wind, where the secondary wind maximum is observed in the second period of study. An analysis of the boundary layer averaged vertical structure of equivalent potential temperature reveals a conditionally unstable environment in the secondary eyewall formation region. These findings support the hypothesis that deep convective activity in this region contributed to spinup of the boundary layer tangential winds and the formation of a secondary eyewall that is observed during the decaying double eyewalled storm period.

Corresponding author address: Sergio F. Abarca, I. M. Systems Group, NOAA/NWS/NCEP, 5830 University Research Court, College Park, MD 20740-3818. E-mail: sergio.abarca@noaa.gov

This article is included in the NASA Hurricane Severe Storm Sentinel (HS3) special collection.

1. Introduction

Secondary eyewalls are structures concentric to the primary eyewall of tropical cyclones and are characterized by maxima in tangential winds and convective activity. Given their frequency of occurrence (Hawkins and Helveston 2004, 2008; Kuo et al. 2008), their relationship with intensity change (e.g., Willoughby et al. 1982; Houze et al. 2007; Yang et al. 2013), their association with longer duration of higher storm intensity (Kuo et al. 2009), and their linkage to storm growth (Maclay et al. 2008), there is great interest in developing secondary eyewall forecasting tools. Today, the valuable and sophisticated forecasting tools tend to rely on empirical relationships (e.g., Kossin and Sitkowski 2009) and do not necessarily directly incorporate the physical processes of secondary eyewall formation.

Secondary eyewall formation dynamics have been the subject of intense contemporary research and contrasting views of the azimuthally averaged dynamics prevail. One line of thought suggests that the boundary layer contributes to the formation of secondary eyewalls by its participation in a feedback between a local enhancement of the radial vorticity gradient above the boundary layer, a corresponding frictional updraft, and increased convective intensity (Kepert 2013). This view is based on the conception that linearized idealizations of the boundary layer of the hurricane inner core are useful representations of the dynamics of such regions of the storm (Kepert 2001; Kepert and Wang 2001). In this view, supergradient winds are a result of the existence of eyewalls and not precursors of them.

Another view of the role of boundary layer dynamics in secondary eyewall formation envisions the Eliassen axisymmetric balanced vortex dynamics being an appropriate framework to describe secondary eyewall formation and evolution (e.g., Zhu and Zhu 2014). In this view, proposed initially by Shapiro and Willoughby (1982), the boundary layer plays a role only as a sink of tangential momentum. In this model, the boundary layer acts to spin down the tangential wind in the layer. Studies, like that of Rozoff et al. (2012), focus on the balanced aspects of the problem.

In contrast with the two foregoing lines of thought, another perspective suggests that nonlinear boundary layer dynamics are essential to secondary eyewall formation and evolution (Huang et al. 2012; Abarca and Montgomery 2013, 2015). Huang et al. (2012) proposed that secondary eyewall formation is a progressive process that begins with a broadening of the tangential winds above the boundary layer, which is then followed by an increase of boundary layer inflow and amplification of the tangential wind in the boundary layer. The radial region of strong boundary layer convergence is associated with the generation of supergradient winds in and just above the boundary layer. These supergradient winds act in the radial momentum equation to arrest the inflow and cause a vertical eruption of moist air out of the boundary layer. In this model, the rising moist air will induce deep convection if the local environment supports convective instability.

The foregoing views highlight distinct and largely incompatible physical processes in the secondary eyewall formation problem. Despite their contrasting nature, these views have been invoked recently as acting simultaneously in a positive feedback process (e.g., Sun et al. 2013). In the current debate regarding the essential role of boundary layer dynamics in secondary eyewall formation a key point is the existence of supergradient winds prior to the presence of the secondary eyewall itself.

While most secondary eyewall studies have been based on numerical evidence, some are based on observations. Remote sensing observational data of secondary eyewalls using various satellite microwave channels have resulted in useful knowledge of their frequency of occurrence around the world (e.g., Kuo et al. 2009; Yang et al. 2013). In situ observations of secondary eyewalls have confirmed, inter alia, the existence of supergradient flow in the secondary eyewall (Didlake and Houze 2011; Bell et al. 2012). Using a model-derived dataset based on observations collected during the Tropical Cyclone Structure-2008 (TCS-08) field experiment (Elsberry and Harr 2008), Huang et al. (2012) suggested that secondary eyewalls can be potentially predicted by diagnosing supergradient flow during secondary eyewall formation. To the knowledge of the authors, there has not been an attempt to assess the existence of supergradient flow in the boundary layer and its potential ramifications during secondary eyewall formation. In the light of the foregoing discussion, it is scientifically relevant to investigate the role of the boundary layer in supporting the formation of secondary eyewalls.

In the remainder of this article, we examine the secondary eyewall event of Hurricane Edouard (2014). Our emphasis is on the formation period of Edouard’s secondary eyewall as captured jointly by in situ observations made during the 2014 phase of the National Aeronautics and Space Administration’s (NASA) Hurricane and Severe Storm Sentinel (HS3) experiment (Braun et al. 2016) and Intensity Forecasting Experiment (IFEX; Rogers et al. 2013) research flights by the Hurricane Research Division of the National Oceanic and Atmospheric Administration (NOAA). Section 2 details the data and methodologies applied in the analysis of this work. Section 3 describes the synoptic evolution of Hurricane Edouard. Section 4 presents the scientific findings of this study. Section 5 offers conclusions and recommendations.

2. Summary of Hurricane Edouard (2014)

Figure 1 shows the track, maximum 1-min sustained surface winds, and minimum surface pressure of Edouard, as reported by the best track dataset (Jarvinen et al. 1984). The storm developed from a tropical wave accompanied by a broad low pressure system and disorganized deep convection. The system was designated a tropical depression on 11 September and maintained a northwestward motion (Fig. 1) for 5 days as it moved around the southwestern periphery of a subtropical ridge. Slow, but steady, strengthening occurred while the cyclone moved northwestward, with the system becoming a tropical storm on 12 September, a hurricane on 14 September, and a major hurricane on 16 September. Based on HS3 and satellite observations Braun et al. (2016) documented storm intensity and structural changes between 1500 UTC 14 September and 0900 UTC 15 September. The intensity changes included significant intensification before 0000 UTC 15 September and weakening afterward. They also included evidence of asymmetric eyewall convection and the existence of a larger eye at the end of the period than at its beginning. At 1500 UTC 14 September the storm exhibited strong winds in the northeastern quadrant (their Fig. 4a), including an asymmetric secondary wind maxima. The radius of maximum winds was ~25 km and the secondary wind maxima was located ~50 km from the center of the storm. At 1315 UTC 15 September 2014 (their Fig. 3f) the eye had a radius about 4–5 times larger than seen earlier (their Fig. 3c). The authors interpreted such evolution as a possible eyewall replacement cycle, although as they show, there is no evidence of a concentric wind and precipitation maxima on 14–15 September, and the storm was a category 1 on the Saffir–Simpson scale.

Fig. 1.
Fig. 1.

Edouard (2014) as captured by (top left) DMSP F15 SSM/I 85-GHz and (top right) DMSP F18 SSMIS 91-GHz microwave satellite imagery and the NHC/TCP best track dataset (middle) intensity and (bottom) track. The period of study, between 1506:37 UTC 16 Sep and 0828:03 UTC 17 Sep, is highlighted with solid thick lines. Also shown are the shear magnitude (blue line) and direction (green line), as captured by the Statistical Hurricane Intensity Predictor Scheme (SHIPS).

Citation: Monthly Weather Review 144, 9; 10.1175/MWR-D-15-0421.1

Based on microwave satellite imagery [85/91-GHz brightness temperatures of 180–225 K (red to yellow shading) in the inner 150 km of the storm], Fig. 1 shows observational evidence that Edouard evolved from a storm with a single eyewall on 15 September to one with a secondary eyewall on 17 September. The airborne data (as shown in upcoming sections) suggest that a secondary eyewall formed between these observation periods. For this reason, the time interval spanning the first set of observations will be referred to as the secondary eyewall formation period. After reaching its peak intensity (on 16 September), Edouard weakened quickly at a rate of 20 m s−1 day−1.

The eyewall replacement cycle that took place, along with cold upwelling/mixing [of about 7°C (Stewart 2014, their Fig. 5)], were likely factors involved in the initial weakening of Edouard’s maximum intensity. The vertical wind shear had a magnitude of 5–9 m s−1 (Fig. 1) for most of the intensification period of the storm and during the first 6 h of its weakening. At the time of its peak intensity, the storm changed its movement from northwestward to northeastward ahead of an approaching midlatitude trough. After the initial 6 h of weakening, the vertical wind shear magnitude dropped relatively rapidly, and it then slowly increased over the following 2 days up to a value of 17 m s−1 on 19 September as the storm became embedded in the midlatitude westerlies. On 19 September, Edouard was downgraded to a tropical storm and on 21 September, it merged with a frontal system (Stewart 2014).

3. Data and methodology

The data used in this study consist of GPS dropsondes deployed from the unmanned Global Hawk as part of the HS3 campaign (Hock et al. 2016) and the NOAA G-IV jet and WP-3Ds as part of the NOAA IFEX program, the National Hurricane Center (NHC)–Tropical Prediction Center (TPC) best track dataset, the Statistical Hurricane Intensity Prediction Scheme (SHIPS) 200–850-hPa vertical wind shear analyses (DeMaria and Kaplan 1994; DeMaria and Kaplan 1999; DeMaria et al. 2005), and 85/91-GHz microwave satellite imagery from the Defense Meteorological Satellite Program (DMSP) microwave imagers [Special Sensor Microwave Imager (SSM/I; F15) and the Special Sensor Microwave Imager/Sounder (SSMIS; F18)].

This study focuses on two study periods defined by the dropsonde availability. The first study period is referred to hereafter as the secondary eyewall formation period. This period uses 48 GPS dropsondes deployed from the NOAA research missions on 15 September between 1413 and 1920 UTC. The flights are NOAA 42 (13 GPS dropsondes; while 14 GPS dropsondes were deployed, the 1802 UTC drop had no altitude information and was not included in this study), NOAA 43 (19 GPS dropsondes), and NOAA 49 (16 GPS dropsondes). The GPS dropsondes during the secondary eyewall formation period were deployed at about 700-hPa pressure altitude, which roughly corresponds to 3-km height.

The second period of study is referred to hereafter as the decaying double eyewalled storm. It includes 87 GPS dropsondes (Black et al. 2011) deployed from the Global Hawk at altitudes of ~17–19 km during the period from 1506 UTC 16 September to 0828 UTC 17 September. While three NOAA research missions deployed 52 GPS dropsondes between 1357 UTC 16 September and 1656 UTC 17 September (i.e., within our second period of study), these GPS dropsondes were mostly deployed in the south-southwest region of the storm. This quadrant of the storm was characterized by inflow throughout the troposphere (not shown) and is not representative of the azimuthal averages aimed in this study (see below). As a result, these NOAA GPS dropsondes deployed on 16–17 September are not included in this work.

The best track tropical cyclone latitude, longitude, and intensity (originally every 6 h) were linearly interpolated to a temporal frequency of 10 min. The 10-min storm center was then used to determine the storm-relative locations of GPS dropsondes throughout their descent. Figure 2 shows the radial and azimuthal locations of all GPS dropsondes relative to the center of the storm. Note in the figure the homogeneity of the azimuthal distribution of the dropsondes and the high density of data within 400 km from the storm center. The dropsondes are also well distributed in the observation periods with about 10 GPS dropsondes per hour in the secondary eyewall formation period and about 5 dropsondes per hour in the decaying double eyewalled storm period.

Fig. 2.
Fig. 2.

Locations of dropsonde deployments, relative to the storm center, during (a) the secondary eyewall formation period (from 1413 to 1920 UTC 15 Sep) and (b) the mature and decaying secondary eyewall period (from 1606 UTC 16 Sep to 0828 UTC 17 Sep). The concentric circles indicate the radial distance (in km) from the center of the storm. [Note: Horizontal scale in (a) is larger than the scale in (b).]

Citation: Monthly Weather Review 144, 9; 10.1175/MWR-D-15-0421.1

The secondary eyewall formation period spans 5 h. This unprecedented observational density of the phenomena offers a unique opportunity to capture essentially a snapshot of the storm’s processes resulting in the secondary eyewall. The decaying double eyewalled storm observation period spanned 18 h. During this time the inner core of the storm evolved substantially as the eyewall replacement was taking place, and here the observations are not to be interpreted as a snapshot of the storm, but rather diagnosing the processes that were ongoing during the 18 h.

The GPS dropsonde wind and pressure/temperature/humidity observations have a frequency of 4 and 2 Hz, respectively, and were interpolated to a uniform vertical grid with 301 points with 50 m of distance between grid points. This choice of vertical resolution represents a reduction of resolution from the original ~10 m. Such reduction does not impact the conclusions of this study. The lowest point was chosen at 10-m height and the highest point was chosen at 15 010 m. Each GPS dropsonde profile interpolated to the fixed vertical grid was assigned to a radial bin according to the radial location of its deployment. In this work, it is assumed that the storm is axisymmetric enough to get estimates of the azimuthal averages of the different variables by averaging all GPS dropsondes available in a given radial bin. The radial bins are uniformly distributed using a subjective criterion as a compromise between number of radial bins and number of GPS dropsondes in each bin. For the secondary eyewall formation period, the radial bins are centered at 8.7-, 22.5-, 32.5-, 48.8-, 69.6-, 101.0-, 150.0-, 212.5-, and 305.0-km radius (see Figs. 46) and for the decaying double eyewalled storm the radial bins are centered at 5.0, 16.3, 31.3, 51.3, 76.3, 121.3, 188.8, 255.0, 322.5, 400.0, 475.0, 550.0, and 720.0 km (Fig. 3). While GPS dropsondes drift radially as they descend through the troposphere, such displacements are smaller than the radial length of the bins considered in this study. The results discussed here are robust to data being assigned to radial bins using their individual radius, irrespective of the dropsonde they belong to. The data are also robust to different bin-length choices (not shown).

Fig. 3.
Fig. 3.

Composite (a) tangential wind velocity (m s−1) and (b) radial location of the dropsondes for the decaying double eyewalled storm period. In (a) a color bar is used to display the structure of tangential velocity. In (b) the black dots indicate the average measurement radius for each dropsonde in the analysis (distributed in the vertical to avoid superposition). The red lines indicate the radial location of the center of the analysis bins. The bins are delimited by the locations of the vertical blue lines. The numbers superposed on the red lines indicate the number of dropsondes in each radial bin (see text for further details).

Citation: Monthly Weather Review 144, 9; 10.1175/MWR-D-15-0421.1

The quantities reported by the GPS dropsondes used in this study are height,1 horizontal wind velocities, pressure, temperature, and relative humidity. We present results of composite (azimuthally averaged) quantities derived as described above, of (storm relative) radial and tangential velocities, relative humidity, and the following quantities: radial vorticity flux −uζa [where is the azimuthally averaged absolute vertical vorticity, r is the radial distance, υ is the azimuthally averaged tangential velocity, and f is the Coriolis parameter at the latitude of the measurement], equivalent potential temperature θe, as defined by the Bolton formula (Bolton 1980), and the agradient force per unit mass, as defined by Smith et al. (2009):
eq1
where the indicated variables have their usual meaning, ρ is the azimuthally averaged density (computed with the equation of state), and is the azimuthally averaged pressure. The centrifugal and Coriolis forces are computed at every measurement location, then interpolated to the vertical grid and finally composited, similar to the other quantities, into the radial bins introduced above. The radial derivatives (e.g., pressure gradient in the computation of the agradient force) are computed as centered differences, based on the radial grid introduced above. One-sided centered differences are used in the first and last radial grid points.

4. Results

Figure 3 shows the estimated azimuthal average tangential velocity during the double eyewalled storm period along with the radial location of the GPS dropsondes as discussed in section 2. The tangential velocity exhibits a deep cyclonic circulation extending through the troposphere to an altitude in excess of 15 km within 100-km radius. The cyclonic circulation extends outward to approximately 600 km and is surrounded by an anticyclonic circulation confined to the upper troposphere between 200 and 500 km that deepens with increasing radius beyond 500 km. The dropsonde analysis reveals two maxima in the tangential wind field. The inner maximum is located in the radial bin centered at 31.3-km radius. The outer maximum is located in the radial bin centered near 100-km radius. These wind maxima are approximately superposed with convective maxima in the storm, as evidenced by microwave imagery (e.g., Fig. 1). This combined evidence establishes the existence of a secondary eyewall in the second period of observation.

Figures 4 and 5 show the composite analysis during the secondary eyewall formation period. The figures include the radial location of the dropsondes in the analysis (section 2) and focus on the lower troposphere below 3 km within 310-km radius of the storm center. This focus enables one to examine the physical processes of secondary eyewall formation in the boundary layer, the region containing the tangential wind maxima in both the primary and secondary eyewalls. Figure 4a shows the composite tangential velocity. This variable reaches its maximum (of roughly 60 m s−1) at 310-m altitude and 25-km radius. At all altitudes observed in the domain, the tangential wind decreases monotonically with radius beyond the radius of maximum tangential wind and there is no evidence of a secondary wind maximum. Along with the satellite imagery corresponding to 15 September (Fig. 1), the data demonstrate the one eyewall configuration of the storm at the time of the analysis.

Fig. 4.
Fig. 4.

Composite (a) tangential wind velocity (m s−1), (b) agradient force (m s−1 h−1), and (c) radial location of the dropsondes for the secondary eyewall formation period. In (a) and (b) the orange and red colors indicate increasingly positive values, respectively; blue colors indicate negative values. In (c) the black dots indicate the average measurement radius for each dropsonde in the analysis. The red lines indicate the radial location of the center of the bins. The bins are delimited by the locations of the vertical blue lines. The numbers superposed on the red lines indicate the number of dropsondes in each radial bin (see text for further details).

Citation: Monthly Weather Review 144, 9; 10.1175/MWR-D-15-0421.1

Fig. 5.
Fig. 5.

Composite (a) radial velocity (m s−1), (b) absolute vorticity (s−1, ×10−4), and (c) radial vorticity flux (m s−1 h−1) for the secondary eyewall formation period. In (a) and (c) the color bar indicates increasingly positive values beginning with light brown through dark red; increasingly negative values are indicated with darker shades of blue. In (b) the color bar indicates only positive values (see text for further details).

Citation: Monthly Weather Review 144, 9; 10.1175/MWR-D-15-0421.1

Figure 4b shows the composite agradient force during the secondary eyewall formation period. As expected, the agradient force in the outer region of the domain is relatively weak and negative (i.e., the force is directed radially inward). Because the pressure gradient is essentially independent of height in the boundary layer, the inward-directed agradient force is a reflection of the frictional reduction of the tangential wind and related reduction of the (outwardly directed) centrifugal and Coriolis forces. In the inner region of the vortex, the agradient force has two distinct regions of positive values. A positive agradient force implies that the tangential winds are supergradient. A positive agradient force in the boundary layer is dynamically important because it acts to arrest the inflow and influences where the air ascends into the vortex interior. In the presence of a convectively unstable environment, air lifted out of the boundary layer can reach its level of free convection and result in deep convective activity.

One of the regions of positive agradient force corresponds to the eyewall of the storm. This region roughly extends radially from 10- to 65-km radius. This region of supergradient flow exhibits a maximum agradient force of several hundred meters per second per hour. Large values of agradient force are expected in the boundary layer of the primary eyewall (Smith et al. 2009) of the storm and have been shown to extend vertically upward several kilometers (e.g., Abarca and Montgomery 2015).

There is a second region of positive agradient force that is distinct from that of the primary eyewall. This region of supergradient flow roughly extends from 90- to 150-km radius (Fig. 4b). The maximum agradient force in this region surpasses 20 m s−1 h−1. Within the constraints of the radial and temporal sampling of the data, the secondary maxima in agradient force coincides with the radial location of the secondary eyewall observed in the second period of observation of this study, as discussed above (Fig. 3a). The secondary maximum in the agradient force occurs before the secondary tangential wind maximum is observed. The existence of this secondary agradient force maximum supports the hypothesis that the processes of secondary eyewall formation are under way.

Figure 5 shows the estimated azimuthally averaged radial flow, absolute vorticity, and radial vorticity flux. The azimuthally averaged radial flow is characterized by large inflow at the lowest levels, with inflow larger than 2 m s−1 below about 1-km height. This layer of strong inflow is due primarily to the agradient force (Smith et al. 2009; Bui et al. 2009). In the analyzed grid (lowest vertical level at 10 m and 50-m vertical grid spacing), the vertical location of the inflow maxima increases with radius, going from 10-m to about 110-m height. The low elevation of the inflow maxima is consistent with fluid dynamical considerations for a swirling-flow boundary layer (e.g., Bödewadt 1940; Schlichting 1968, chapter 11) and with observations of a mature hurricane (e.g., Montgomery et al. 2014). In the domain, there are two extended regions of outflow. One corresponds to the eyewall of the storm, located above 700-m height, between 30- and 70-km radius. Within the analysis domain, the outflow reaches its maximum at 2.3-km height in the radial bin centered near 50-km radius. The other extended region of outflow is roughly located between 85- and 170-km radius and between about 1.7- and 2.1-km height.

Figure 5b shows the estimated azimuthally averaged absolute vorticity. In the inner core of mature tropical cyclones, this field is generally characterized by a central region of large vorticity surrounded by a skirt of smaller values (Mallen et al. 2005). Notwithstanding the limitations of the data, the overall vorticity structure is as expected, with the largest values in the innermost points. The absolute vorticity structure includes a monotonic decrease of vorticity with radius above 1-km height. The field exhibits no discernable relative maxima of vorticity near the top of the boundary layer. Near 211-km radius, there is a small relative maximum in vorticity below 1 km.

Figure 5c shows the estimated mean radial absolute vertical vorticity flux (hereafter radial vorticity flux), as it appears in the right-hand side of the tangential momentum equation [with a minus sign, see Eq. (4) in Abarca and Montgomery (2013)]. Radial vorticity flux is a key diagnostic of whether the secondary eyewall formation process is under way at the time analyzed. We present radial vorticity flux as it can be directly interpreted as a term in the tangential tendency equation, but we note here that such a quantity only differs from the radial advection of absolute angular momentum by a factor of r. From the perspective of the azimuthally averaged system-scale flow, the radial vorticity flux is one of the dominant terms in the tangential tendency equation during the spinup of tropical cyclones in general (Ooyama 1969; Smith et al. 2009), and during secondary eyewall formation in particular (e.g., Abarca and Montgomery 2013, their Fig. 5). The maximum spinup tendency of the vorticity flux is within the boundary layer in the region of the eyewall of the storm and it elongates radially outward into the secondary region of supergradient wind where the secondary wind maxima is observed in the second period of study. Note that while the secondary eyewall formation is under way, there is no evidence of a vorticity bump above the boundary layer (Fig. 5b) to support the idea that secondary eyewall formation is a feedback process that begins once a local vorticity maximum is present above the boundary layer (Kepert 2013; Kepert and Nolan 2014).

To gain additional insight into the relevant physical processes in the boundary layer of the storm during this early period of study, we calculate the vertical average of radial inflow. Collapsing the data in this way helps highlight the bulk features of the storm’s boundary layer as it is undergoing secondary eyewall formation. Figure 6a shows the storm-relative radial velocity averaged below 1-km height (the results hereafter are not dependent on the choice of height, they are robust to other choices, like 0.8, 0.9, and 1.2 km, not shown). As suggested by Fig. 5a, this height is chosen as the nominal depth of the boundary layer as it contains the region of relatively strong inflow. Figure 6a shows that, at the time of the analysis, the radial inflow depicts a structure with two maxima. The primary inflow maximum is at the radial bin centered near 30-km radius and is associated with the primary eyewall. The secondary inflow maximum is located at the radial bin centered near 100-km radius. It can be shown that the double inflow maximum structure cannot be explained by an argument based on frictional stress alone. The secondary inflow maximum can be explained plausibly by the action of the positive agradient force shown in Fig. 4b around the interval centered near 100-km radius. As discussed above, this force field acts to arrest the inflow and promote ascent of moist air out of the boundary layer.

Fig. 6.
Fig. 6.

(a) Vertically averaged (in the lowest km) radial flow as a function of radius, and (b) vertical profiles of equivalent potential temperature and saturated equivalent potential temperature (K). In (a) the vertical red lines indicate the radial location of the center of the bins. The bins are delimited by the locations of the vertical blue lines. The number superposed on the red lines indicates the number of dropsondes in each radial bin (see text for further details).

Citation: Monthly Weather Review 144, 9; 10.1175/MWR-D-15-0421.1

Figure 6b shows the composite vertical profile of the equivalent potential temperature θe and the corresponding saturated equivalent potential temperature θes at the radial bin centered near 100-km radius. The figure depicts a conditionally unstable environment in the secondary eyewall formation region. As an example, if one vertically averages θe in the lowest 200 m, the result renders a mean value of 349.6 K. A parcel lifted from 100 m with such a θe would acquire positive buoyancy above about 1-km height (e.g., Holton 2004). Thus, this thermodynamic structure is capable of supporting deep convective activity in the radial region of secondary eyewall formation.

5. Conclusions

Secondary eyewall formation (SEF) dynamics have been the subject of intense contemporary research and contrasting views of the SEF azimuthally averaged dynamics prevail. In an effort to help provide an improved understanding of the physical processes controlling the formation of secondary eyewalls in real storms, we presented herein an estimation of azimuthally averaged dynamical and thermodynamical fields derived from in situ observations during SEF. The case study is that of Atlantic Hurricane Edouard (2014). This storm was intensely observed during the 2014 phase of the NASA HS3 experiment, in conjunction with NOAA IFEX research flights by the Hurricane Research Division. A total of 135 GPS dropsondes were analyzed. The GPS dropsondes were deployed in two time periods: one named the secondary eyewall formation period (48 dropsondes deployed on 14 September within 5 h) and the other one referred to as the decaying double eyewalled storm period (87 GPS dropsondes deployed on 16–17 September within 18 h).

During the period designated as the secondary eyewall formation period, the estimates of azimuthally averaged fields reveal that the storm had a single tangential wind maximum. During the double eyewall storm period, the azimuthally averaged wind data confirmed a double tangential wind maximum, with the tangential wind maxima located within the boundary layer of the storm. During the secondary eyewall formation period, the agradient force had a secondary maximum that coincided with the radial location of the secondary eyewall observed in the second period of study. The storm-relative radial velocity averaged below 1-km height depicted a structure with two maxima, with the secondary inflow maximum coinciding with the radial location of the secondary eyewall observed in the second period of study. The maximum spinup tendency of the radial influx of absolute vertical vorticity was within the boundary layer in the region of the eyewall of the storm and it elongated radially outward into the secondary region of supergradient wind, where the secondary wind maximum was observed in the second period of study. An analysis of the average vertical structure of potential temperature revealed a conditionally unstable environment in the secondary eyewall formation region.

The evidence presented supports the hypothesis that secondary eyewall formation is under way during the first period of observations and the underlying mechanisms at work are in line with the dynamical and thermodynamical processes as articulated in Smith et al. (2009) and Huang et al. (2012).

The vertical coherence of the azimuthally averaged estimates (using the 2–4-Hz GPS dropsonde observations interpolated to a regular vertical grid with spacing of 50 m) and the robustness of the results to radial bin choices suggest that the data presented herein are physically meaningful and useful.

In the light of the results presented, it is scientifically desirable from the operational point of view to investigate the role of the boundary layer in supporting the formation of secondary eyewalls in other observational cases. Analogous estimates of the quantities examined here in other storms are recommended to assess the generality of the results.

Acknowledgments

The first author gratefully acknowledges the support from the National Research Council (NRC) through its Research Associateship Program; the host institution, the Naval Postgraduate School (NPS) in Monterey, California; and Scott Braun for the funding that made it possible for him to participate in the HS3 deployment during the 2014 hurricane season. MTM acknowledges the support of NSF Grant AGS-1313948, NOAA HFIP Grant N0017315WR00048, NASA HS3 Grant NNG11PK021, and the U.S. Naval Postgraduate School.

REFERENCES

  • Abarca, S. F., and M. T. Montgomery, 2013: Essential dynamics of secondary eyewall formation. J. Atmos. Sci., 70, 32163230, doi:10.1175/JAS-D-12-0318.1.

    • Search Google Scholar
    • Export Citation
  • Abarca, S. F., and M. T. Montgomery, 2015: Are eyewall replacement cycles governed largely by axisymmetric balance dynamics? J. Atmos. Sci., 72, 8287, doi:10.1175/JAS-D-14-0151.1.

    • Search Google Scholar
    • Export Citation
  • Bell, M. M., M. T. Montgomery, and W. C. Lee, 2012: An axisymmetric view of concentric eyewall evolution in Hurricane Rita (2005). J. Atmos. Sci., 69, 24142432, doi:10.1175/JAS-D-11-0167.1.

    • Search Google Scholar
    • Export Citation
  • Black, M. L., G. A. Wick, J. R. Spackman, T. Hock, and R. Hood, 2011: Real-time data transmission, processing and dissemination of GPS dropwindsonde data from the NASA Global Hawk unmanned aircraft. 2011 Fall Meeting, San Francisco, CA, Amer. Geophys. Union, Abstract IN13C-04.

  • Bödewadt, U. T., 1940: Die Drehströmung übder fester Grund. Z. Angew. Math. Mech., 20, 241253, doi:10.1002/zamm.19400200502.

  • Bolton, D., 1980: The computation of equivalent potential temperature. Mon. Wea. Rev., 108, 10461053, doi:10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Braun, S. A., P. A. Newman, and G. M. Heymsfield, 2016: NASA’s Hurricane and Severe Storm Sentinel (HS3) Investigation. Bull. Amer. Meteor. Soc., doi:10.1175/BAMS-D-15-00186.1, in press.

    • Search Google Scholar
    • Export Citation
  • Bui, H. H., R. K. Smith, M. T. Montgomery, and J. Peng, 2009: Balanced and unbalanced aspects of tropical-cyclone intensification. Quart. J. Roy. Meteor. Soc., 135, 17151731, doi:10.1002/qj.502.

    • Search Google Scholar
    • Export Citation
  • DeMaria, M., and J. Kaplan, 1994: A Statistical Hurricane Intensity Prediction Scheme (SHIPS) for the Atlantic basin. Wea. Forecasting, 9, 209220, doi:10.1175/1520-0434(1994)009<0209:ASHIPS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • DeMaria, M., and J. Kaplan, 1999: An updated Statistical Hurricane Intensity Prediction Scheme (SHIPS) for the Atlantic and eastern North Pacific basins. Wea. Forecasting, 14, 326337, doi:10.1175/1520-0434(1999)014<0326:AUSHIP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • DeMaria, M., M. Mainelli, L. K. Shay, J. A. Knaff, and J. Kaplan, 2005: Further improvements to the Statistical Hurricane Intensity Prediction Scheme (SHIPS). Wea. Forecasting, 20, 531543, doi:10.1175/WAF862.1.

    • Search Google Scholar
    • Export Citation
  • Didlake, A. C., Jr., and R. A. Houze Jr., 2011: Kinematics of the secondary eyewall observed in Hurricane Rita (2005). J. Atmos. Sci., 68, 16201636, doi:10.1175/2011JAS3715.1.

    • Search Google Scholar
    • Export Citation
  • Elsberry, R. L., and P. A. Harr, 2008: Tropical Cyclone Structure (TCS08) field experiment science basis, observational platforms, and strategy. Asia-Pac. J. Atmos. Sci., 44, 209231.

    • Search Google Scholar
    • Export Citation
  • Hawkins, J. D., and M. Helveston, 2004: Tropical cyclone multiple eyewall characteristics. 26th Conf. on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., P1.7. [Available online at https://ams.confex.com/ams/26HURR/techprogram/paper_76084.htm.]

  • Hawkins, J. D., and M. Helveston, 2008: Tropical cyclone multiple eyewall characteristics. 28th Conf. on Hurricanes and Tropical Meteorology, Orlando, FL, Amer. Meteor. Soc., 14B.1. [Available online at https://ams.confex.com/ams/28Hurricanes/techprogram/paper_138300.htm.]

  • Hock, T., K. Young, and H. Voemel, 2016: Hurricane and Severe Storm Sentinel (HS3) Global Hawk Advanced Vertical Atmospheric Profiling System (AVAPS) Dropsonde System [dropsondes deployed during Storm Edouard]. NASA Global Hydrology Resource Center DAAC, Huntsville, AL, accessed January 2015, doi:10.5067/HS3/AVAPS/DROPSONDE/DATA201. [Dataset available online at https://hs3.nsstc.nasa.gov/pub/hs3/AVAPS/.]

  • Holton, J. R., 2004: An Introduction to Dynamic Meteorology. Elsevier Academic, 535 pp.

  • Houze, R. A. J., S. S. Chen, B. F. Smull, W. C. Lee, and M. M. Bell, 2007: Hurricane intensity and eyewall replacement. Science, 315, 12351239, doi:10.1126/science.1135650.

    • Search Google Scholar
    • Export Citation
  • Huang, Y.-H., M. T. Montgomery, and C.-C. Wu, 2012: Concentric eyewall formation in Typhoon Sinlaku (2008). Part II: Axisymmetric dynamical processes. J. Atmos. Sci., 69, 662674, doi:10.1175/JAS-D-11-0114.1.

    • Search Google Scholar
    • Export Citation
  • Jarvinen, B. R., C. J. Neumann, and M. A. S. Davis, 1984: A tropical cyclone data tape for the North Atlantic basin, 1886–1983: Contents, limitations, and uses. NOAA Tech. Memo. NWS NHC 22, 21 pp.

  • Kepert, J., 2001: The dynamics of boundary layer jets within the tropical cyclone core. Part I: Linear theory. J. Atmos. Sci., 58, 24692484, doi:10.1175/1520-0469(2001)058<2469:TDOBLJ>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kepert, J., 2013: How does the boundary layer contribute to eyewall replacement cycles in axisymmetric tropical cyclones? J. Atmos. Sci., 70, 28082830, doi:10.1175/JAS-D-13-046.1.

    • Search Google Scholar
    • Export Citation
  • Kepert, J., and Y. Wang, 2001: The dynamics of boundary layer jets within the tropical cyclone core. Part II: Nonlinear enhancement. J. Atmos. Sci., 58, 24852501, doi:10.1175/1520-0469(2001)058<2485:TDOBLJ>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kepert, J., and D. S. Nolan, 2014: Reply to “Comments on ‘How does the boundary layer contribute to eyewall replacement cycles in axisymmetric tropical cyclones?’” J. Atmos. Sci., 71, 46924704, doi:10.1175/JAS-D-14-0014.1.

    • Search Google Scholar
    • Export Citation
  • Kossin, J. P., and M. Sitkowski, 2009: An objective model for identifying secondary eyewall formation in hurricanes. Mon. Wea. Rev., 137, 876892, doi:10.1175/2008MWR2701.1.

    • Search Google Scholar
    • Export Citation
  • Kuo, H.-C., W. H. Schubert, C.-L. Tsai, and Y.-F. Kuo, 2008: Vortex interactions and barotropic aspects of concentric eyewall formation. Mon. Wea. Rev., 136, 51835198, doi:10.1175/2008MWR2378.1.

    • Search Google Scholar
    • Export Citation
  • Kuo, H.-C., C.-P. Chang, Y.-T. Yang, and H.-J. Jiang, 2009: Western North Pacific typhoons with concentric eyewalls. Mon. Wea. Rev., 137, 37583770, doi:10.1175/2009MWR2850.1.

    • Search Google Scholar
    • Export Citation
  • Maclay, K. S., M. DeMaria, and T. H. Vonder Haar, 2008: Tropical cyclone inner core kinetic energy evolution. Mon. Wea. Rev., 136, 48824898, doi:10.1175/2008MWR2268.1.

    • Search Google Scholar
    • Export Citation
  • Mallen, K. J., M. T. Montgomery, and B. Wang, 2005: Reexamining the near-core radial structure of the tropical cyclone primary circulation: Implications for vortex resiliency. J. Atmos. Sci., 62, 408425, doi:10.1175/JAS-3377.1.

    • Search Google Scholar
    • Export Citation
  • Montgomery, M. T., J. A. Zhang, and R. K. Smith, 2014: The low-level structure of rapidly intensifying and mature Hurricane Earl (2010). Quart. J. Roy. Meteor. Soc., 140, 21322146, doi:10.1002/qj.2283.

    • Search Google Scholar
    • Export Citation
  • Ooyama, K. V., 1969: Numerical simulation of the life cycle of tropical cyclones. J. Atmos. Sci., 26, 340, doi:10.1175/1520-0469(1969)026<0003:NSOTLC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Rogers, R. F., and Coauthors, 2013: NOAA’s Hurricane Intensity Forecasting Experiment: A progress report. Bull. Amer. Meteor. Soc., 94, 859882, doi:10.1175/BAMS-D-12-00089.1.

    • Search Google Scholar
    • Export Citation
  • Rozoff, C. M., D. S. Nolan, J. P. Kossin, F. Zhang, and J. Fang, 2012: The roles of an expanding wind field and inertial stability in tropical cyclone secondary eyewall formation. J. Atmos. Sci., 69, 26212643, doi:10.1175/JAS-D-11-0326.1.

    • Search Google Scholar
    • Export Citation
  • Schlichting, H., 1968: Boundary Layer Theory. 6th ed. McGraw-Hill, 747 pp.

  • Shapiro, L. J., and H. E. Willoughby, 1982: The response of balanced hurricanes to local sources of heat and momentum. J. Atmos. Sci., 39, 378394, doi:10.1175/1520-0469(1982)039<0378:TROBHT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Smith, R. K., M. T. Montgomery, and N. Van Sang, 2009: Tropical cyclone spin-up revisited. Quart. J. Roy. Meteor. Soc., 135, 13211335, doi:10.1002/qj.428.

    • Search Google Scholar
    • Export Citation
  • Stewart, S. R., 2014: National Hurricane Center Tropical Cyclone Report: Hurricane Edouard (11–19 September 2014). Tropical Cyclone Rep. AL062014, National Hurricane Center, 19 pp. [Available online at http://www.nhc.noaa.gov/data/tcr/AL062014_Edouard.pdf.]

  • Sun, Y. Q., Y. Jiang, B. Tan, and F. Zhang, 2013: The governing dynamics of the secondary eyewall formation of Typhoon Sinlaku (2008). J. Atmos. Sci., 70, 38183837, doi:10.1175/JAS-D-13-044.1.

    • Search Google Scholar
    • Export Citation
  • Willoughby, H. E., J. A. Clos, and M. G. Shoreibah, 1982: Concentric eye walls, secondary wind maxima, and the evolution of the hurricane vortex. J. Atmos. Sci., 39, 395411, doi:10.1175/1520-0469(1982)039<0395:CEWSWM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Yang, Y. T., H.-C. Kuo, E. A. Hendricks, and M. S. Peng, 2013: Structural and intensity changes of concentric eyewall typhoons in the western North Pacific basin. Mon. Wea. Rev., 141, 26322648, doi:10.1175/MWR-D-12-00251.1.

    • Search Google Scholar
    • Export Citation
  • Zhu, Z., and P. Zhu, 2014: The role of outer rainband convection in governing the eyewall replacement cycle in numerical simulations of tropical cyclones. J. Geophys. Res. Atmos., 119, 80498072, doi:10.1002/2014JD021899.

    • Search Google Scholar
    • Export Citation
1

Using geopotential height renders plots virtually indistinguishable from those presented here (not shown).

Save