[August 24, 2011] On the Characteristic Height Scales of the Hurricane Boundary Layer [Monthly Weather Review] Tweet (Monthly Weather Review Via Acquire Media NewsEdge) ABSTRACT In this study, data from 794 GPS dropsondes deployed by research aircraft in 13 hurricanes are analyzed to study the characteristic height scales of the hurricane boundary layer. The height scales are defined in a variety of ways: the height of the maximum total wind speed, the inflow layer depth, and the mixed layer depth. The height of the maximum wind speed and the inflow layer depth are referred to as the dynamical boundary layer heights, while the mixed layer depth is referred to as the thermodynamical boundary layer height. The data analyses show that there is a clear separation of the thermodynamical and dynamical boundary layer heights. Consistent with previous studies on the boundary layer structure in individual storms, the dynamical boundary layer height is found to decrease with decreasing radius to the storm center. The thermodynamic boundary layer height, which is much shallower than the dynamical boundary layer height, is also found to decrease with decreasing radius to the storm center. The results also suggest that using the traditional critical Richardson number method to determine the boundary layer height may not accurately reproduce the height scale of the hurricane boundary layer. These different height scales reveal the complexity of the hurricane boundary layer structure that should be captured in hurricane model simulations. (ProQuest: ... denotes formulae omitted.) 1. Introduction The boundary layer is known to play an important role in the energy transport processes of a hurricane, regulating the radial and vertical distributions of momentum and enthalpy that are closely related to storm development and intensification (e.g., Ooyama 1969; Emanuel 1986; Wroe and Barnes 2003; Smith et al. 2008; Rotunno et al. 2009; Smith and Montgomery 2010). Numerical studies have shown that the simulated hurricane intensity is very sensitive to the selection of planetary boundary layer (PBL) parameterization schemes (e.g., Braun and Tao 2000; Nolan et al. 2009a,b; Smith and Thomsen 2010). Understanding of the hurricane boundary layer structure has become increasingly important in the ongoing effort toward developing high-resolution numerical models to improve hurricane intensity forecasts (e.g., Marks and Shay 1998;Rogers et al. 2006; Chen et al. 2007;Davis et al. 2008). In many PBL schemes used in full-physics numerical models, one of the crucial elements is the determination of the atmospheric boundary layer height (H), because it is coupled with the maintenance of low-level clouds and energy transport from the surface layer to the boundary layer above (e.g., Troen and Mahrt 1986; Hong and Pan 1996;Vogelezang andHoltslag 1996; Beljaars andViterbo 1998; Noh et al. 2003). The boundary layer height is also a key variable that regulates the vertical distribution of turbulent fluxes and helps determine where turbulent fluxes tend to become negligible (Stull 1988). Despite the importance in defining the boundary layer top in hurricane models, there has been no consensus on what should define this top in the hurricane research community. In the slab model used in the seminal theoretical hurricane model of Emanuel (1986), a constant boundary layer height is used. Early boundary layer studies (e.g., Powell 1990; Anthes and Chang 1978) adopted a thermodynamic definition of the boundary layer, characterized by the layer in which the potential temperature or virtual potential temperature is appreciably well mixed. The thermodynamic definition is mainly based on one observational study of the boundary layer of Tropical StormEloise (1975) by Moss and Merceret (1976), who found that momentum fluxes tend to become near zero near the top of the mixed layer defined using the potential temperature profile, similar to the vertical flux profile in a typical tropical boundary layer over the ocean. Bryan and Rotunno (2009) define the top of the boundary layer to be the height of the maximum wind usually around 1 km. Kepert and Wang (2001, see their Fig. 2) show that the stress divergence becomes small near the height of the maximum wind or azimuthal jet, similar to Bryan and Rotunno's result. Smith et al. (2009) adopt another dynamical definition, considering the strong inflow layer as the boundary layer because of the frictional disruption of the gradientwind balance near the surface (see their Fig. 6). The purpose of this paper is to use observational data from multiple hurricanes to examine the structure of the hurricane boundary layer. We focus on investigating the characteristic height scales of the hurricane boundary layer through analyses of 794 global positioning system (GPS) dropsonde data collected by National Oceanic and Atmospheric Administration (NOAA) research aircraft in 13 hurricanes. As part of NOAA's Hurricane Forecast Improvement Project (HFIP), this work also builds a dataset that can be used to evaluate the representation of boundary layer structure in model simulations. Section 2 describes the data sources and analysis method, and includes a detailed description of how different hurricane boundary layer heights are defined. In section 3, we present the results by comparing different boundary layer height scales determined using our data to those from previous studies. Section 4 summarizes the results and discusses future work. 2. Data and methodology a. Analysis method The dropsonde data are analyzed and grouped within a composite framework. The composite analysis technique has been used in previous studies investigating the hurricane inner-core structure (Jorgensen 1984; Frank 1977a,b, 1984), boundary layer structure (Franklin et al. 2003; Powell et al. 2003), and surface layer air-sea thermal structure (Cione et al. 2000). The advantage of the composite analysis is that it provides a general picture and characterization of the fields that are investigated. In this case, we intend to improve our understanding of the mean boundary layer structure in hurricanes in terms of the boundary layer height. Themost important drawback to compositing is that it tends to smooth the data from a large number of storms that may not be similar (Frank 1977a). The success of a compositing analysis depends on the similarity of the events studied. For this purpose, only sondes in storms of at least hurricane intensity (>64 kt; 1 kt = 0.5144 m s-1) are used in the analysis. The data are grouped as a function of the radius to the storm center (r) that is normalized by the radius of themaximum wind speed (RMW; i.e., r* =r/RMW). The center positions have been determined using the flight level to fix the storm center using the algorithm developed by Willoughby and Chelmow (1982). Values of RMW are mainly determined using the Doppler radar data from the tangential winds at 2 km. When there are no radar data available, theRMWis determined fromthe flight level data. When compositing the data, the radial bin width is 0.2r* for the inner core (r* <2), and it is 0.4r* for the outer part. The data are also bin averaged vertically at 10-m resolution. The final averaged data are also smoothed using a simple 1-2-1 filter both vertically and horizontally, repeated 5 times. b. Data coverage and quality control The dropsonde data used in this study were collected by a total of 106 NOAA research flights in 13 hurricanes (Table 1). A detailed description of the instrumentation related to the dropsonde can be found in Hock and Franklin (1999). The fall speed of a sonde is 12-14 m s-1, while the typical sampling rate is 2 Hz, providing measurements with 6-7 m of separation in the vertical on average. The dropsonde gives measurements of air temperature, relative humidity, pressure, and horizontal and vertical wind speed. Typical measurement errors for pressure, temperature, and relative humidity are 1.0 hPa, 0.2°C, and 5%, respectively (Hock and Franklin 1999). The accuracy of the horizontal wind speed measurements is 2.0 m s-1 and <0.5 m s-1 for the vertical winds with approximately 0.2 m s-1 precision. The dropsonde data have been processed and quality controlled using the EDITSONDE software developed by the Hurricane Research Division (Franklin et al. 2003). Data from 2231 GPS dropsondes have been processed and analyzed. However, only 794 of these that have continuous measurements of wind speed, temperature, and humidity from the flight level to the surface (10 m) in mature storms are used in the final analysis. Table 1 summarizes the storm information and numbers of sondes used in this work. The intensity range of each storm is also included in Table 1, showing that all of the storms were of at least category 1 intensity on the Saffir- Simpson scale at the time of the analyses, according to the National Hurricane Center's best track. The majority of the data are from category 1 and 2 storms, while a quarter of the data are from category 4 and 5 storms. The sonde locations and the storm centers are plotted in Fig. 1, demonstrating a broad geographic area of coverage of storms used in the composite analysis described below. Figure 2 shows the data coverage relative to the storm center. The dropsondes are nearly evenly distributed in the azimuth. Figure 2 also shows that a majority of sondes were dropped near the radius of maximum wind speed (r* = 1). Figure 3 shows that the number of sondes decreases as a function of distance away from r* = 1. The peak number of sondes (>80) is located between r* = 0.5 and 1.2, while the number drops to ~40 between r* = 2 and 3 and ~25 between r* = 3 and 5. Figure 3b indicates that most of the sondes were dropped near the eyewall region where the RMW is approximately 40 km. c. Defining characteristic boundary layer height scales Traditionally, the boundary layer is defined as the part of the troposphere that is directly influenced by the presence of the earth's surface, and responds to surface forcing with a time scale of about an hour or less (Stull 1988). Taking this definition, the boundary layer height represents the height where turbulent fluxes become negligible, often taken in numerical models as the height where the momentum flux is nearly 5% of the surface flux. However, direct measurements of turbulent fluxes in the high-wind hurricane boundary layer have been scarce. Until now, there have been only two studies that have presented vertical profiles of turbulent fluxes in tropical cyclones. Moss (1978) presented a case study of Tropical Storm Eloise (1975) showing the momentum flux profile from one stepped descent period of an aircraft. Zhang et al. (2009) presented vertical profiles of directly measured fluxes in the hurricane boundary layer between the rainbands of four intense hurricanes. Furthermore, indirect derivation of themomentumfluxes has been confined to the surface layer below 200 m (Powell et al. 2003). Thus, at the present time it is not possible to determine the boundary layer height using its traditional definition, which relies on turbulent flux data. Alternatively, observational data such as vertical soundings have been widely used to determine the boundary layer height. For a nearly neutral or convective boundary layer, a common method is to define the boundary layer height as the mixed layer depth based on the virtual potential temperature profile. The mixed layer depth is often taken as the base of the inversion layer or stable layer in a typical tropical boundary layer over the ocean (e.g., Barnes et al. 1980; Nicholls and Readings 1979; Yin and Albrecht 2000; Johnson et al. 2001; Zeng et al. 2004). Here, we determine the mixed layer depth from this definition, that is, as the nearly constant virtual potential temperature (??) layer. We take the top of the mixed layer to be defined as being where ?? increases by 0.5 K from its mean value in the lowest 150 m (Anthes and Chang 1978). We also estimate the mixed layer depth using the method given by Zeng et al. (2004), who defined it as the lowest level where d??/dz = 3 K km-1. In terms of dynamics and/or kinematics, the height of the maximum wind speed (hvmax) can be used to define the boundary layer height (e.g., Bryan and Rotunno 2009). Another dynamical height scale of the hurricane boundary layer is the inflow layer depth (e.g., Smith et al. 2009). The boundary layer inflow is driven by an imbalance between the pressure gradient and theCoriolis and centrifugal forces.Here, we define the inflow layer as the layer that is directly induced by surface friction, excluding the midlevel (above 2 km) weak inflow arising from a balanced response to heating. After testing different methods, such as taking the height where the radial wind velocity is either 0 or -2 m s-1 as the inflow layer top, we take the height where the radial velocity is 10% of the peak inflow as the inflow layer depth (hinfl). This definition gives consistent results when we composite the data by different hurricane intensity groups. Note that to estimate the inflow layer depth using the dropsonde data, the wind is first rotated into the radial and tangential wind components before compositing. In numerical models, including hurricane models, the bulk Richardson number has been widely used to determine the boundary layer height in PBL parameterization schemes (e.g., Troen and Mahrt 1986; Vogelezang andHoltslag 1996; Bender et al. 2007; Noh et al. 2003). For instance, the bulk Richardson number method has been used in both the local and nonlocal schemes in the fifthgeneration National Center for Atmospheric Research- Pennsylvania State University (NCAR-Penn State) MesoscaleModel (MM5) and theWeather Research and Forecasting (WRF) model, such as the Medium-Range Forecast (MRF) and Yonsei University (YSU) schemes. A detailed explanation of such schemes is given in Nolan et al. (2009a,b). The bulk Richardson number (Rib) represents the ratio of buoyancy to shear forcing, which are responsible for reducing and generating turbulence, respectively. This ratio can be defined as ... (1) where Rib is the Richardson number between an atmospheric level zs and the boundary layer top H, ?? is the virtual potential temperature, and subscripts s and H represents the levels of zs and H. A critical Rib is usually used to define the top of the boundary layer. A range of critical Rib that defines the boundary layer top has been used in previous studies,mostly varying between 0.25 and 0.5 (e.g., Hanna 1969; Wetzel 1982; Mahrt 1981; Troen and Mahrt 1986; Holtslag et al. 1995). Using the dropsonde data, we calculate the bulk Richardson number as a function of height. 3. Results The normalized-radius-height representation of the total wind speed is shown in Fig. 4. A wind maximum known as the boundary layer jet is located around r* = 1 and z = 500 m. This wind maximum or ''azimuthal jet'' has been recognized in many previous studies in both individual and mean wind profiles (e.g., Kepert 2006a,b; Bell and Montgomery 2008; Schwendike and Kepert 2008; Franklin et al. 2003; Powell et al. 2003). The hurricane boundary layer jet is one of the distinct features that is different from a typical boundary layer in nonhurricane conditions. Figure 4 shows a broad wind maximum between 200- and 1000-m altitude, consistent with the analysis of Franklin et al. (2003), which used much less data than were employed in this study. Outside the eyewall, the wind maximum occurs at a higher altitude (~1-1.5 km). Below the wind maximum, the wind speed tends to decrease logarithmically with decreasing height, especially below 200 m. This structure is similar to that obtained from idealized numerical simulations of the hurricane boundary layer (e.g., Eliassen and Lystad 1977; Kepert 2001; Kepert and Wang 2001; Nolan 2005; Foster 2009; Kepert 2010a). Figures 5a and 5b, respectively, show the tangential (Vt) and radial (Vr) wind velocities as a function of r* and altitude. The tangential wind speed maximum at the core is located between 400 and 1300 m, which is similar to but slightly higher than that of the total wind speed. Again, below the low-level jet, the tangential wind speed tends to decrease nearly logarithmically. The radial inflow is strongest at 150 m above the sea surface, decreasing gradually with height.Above 1500 mat r* =1, a pronounced outflow jet is evident. It is interesting to note that the depth of the inflow layer (defined by where Vr equals 10% of the peak inflow) is above the height of themaximum tangential wind speed. We found that the tangential wind maximum is located at the height where Vr is 25% of the peak inflow. This pattern of behavior for the boundary layer flow appears to be evident even when we composite the data by different storm intensities (to be discussed later). Modeling studies (e.g., Kepert and Wang 2001; Nolan et al. 2009b) have also shown that the wind maximum occurs within the inflow layer, in agreement with our analysis. From the composite mean r* -z profiles of Vt and Vr, it is evident that the inflow layer depth and the height of the maximum wind speed both tend to decrease with decreasing radius, especially near the core. The r* -z plot of the virtual potential temperature (??) is shown in Fig. 6, depicting a well-mixed layer roughly below 500 m beyond r* = 3. The mixed layer depth (zi) decreases to about 250 m near the eyewall. The decrease of the mixed layer depth with decreasing radius is also shown in Fig. 7, where zi is defined using the method mentioned in section 2. There is no inversion layer as in a typical tropical boundary layer where there is a subsidence (e.g., Nicholls 1985; Albrecht et al. 1985). The hurricane boundary layer basically contains amixed layer, a transition layer, and a stable layer (e.g., Powell 1990; Barnes 2008). The magnitude of ?? generally increases with decreasing radius, with the warmcore clearly evident inside r* = 1.5. The mixed layer depth in the outer core (i.e., r* > 2) is very similar to that in a typical tropical boundary layer over the ocean (e.g.,Nicholls and LeMone 1980; Barnes et al. 1980; Albrecht et al. 1985). The innercore mixed layer is much shallower. Figure 8 shows the lapse rate of ?? as a function of r* and altitude. Note that we used dz = 10 m when we computed the lapse rate. If the mixed layer depth is where d?? /dz = 3 K km-1 following Zeng et al. (2004), it is very close to that defined using our constant ?? definition, as mentioned earlier (Fig. 7), which is found again to decrease with decreasing radius. The bulk Richardson number is calculated using Eq. (1) and is shown in Fig. 9 as a function of r* and height. If Rib 5 0.25 is taken as the top of the boundary layer (solid black line in Fig. 10), it generally lies between the mixed layer depth and the inflow layer depth. However, this depth increases with decreasing radius, in contrast to the depths defined by zi, hvmax, and hinfl. This indicates that using the Richardson number method may not capture the correct radial variation of the boundary layer depth. As mentioned earlier, the data used to generate the plots of axisymmetric low-level kinematic and thermodynamic structure are from multiple storms ranging from categories 1 to 5. To assess the variability between stronger and weaker storms, we group the data by storm intensity before the composite analysis, by dividing the data into two groups: one using sondes in storms with intensity <120 kt (i.e., category 1-3 storms, referred to as group cat 1-3 hereafter), and the other using sondes in storms with intensity >120 kt (i.e., category 4-5 storms, referred to as group cat 4-5 hereafter). In group cat 1-3, the data are mainly from category 1 and 2 storms. In group cat 4-5, the sondes were mainly dropped at locations r* < 1.5 and below 2 km. Figure 10 shows a comparison of the composites of Vt and Vr between groups cat 1-3 and cat 4-5, as well as the whole dataset. For comparison purpose, we have also normalized Vt and Vr by their peak values. As expected, the peak mean values of Vt and Vr, labeled in the header of each panel in Fig. 10, are found to increase with increasing storm intensity. The height of the maximum Vt is found to be within the inflow layer, which is located at the height of the 25% peak inflow for all the intensity groups. Figure 10 also indicates that there is almost no difference in the inflow layer depth and height of maximum Vt between group cat 1-3 and the whole dataset (Fig. 5). However, the inflow layer depth in group cat 4-5 is higher than that in group cat 1-3 as well as the whole dataset in the inner-core region, while it is lower in the outer region. At first thought, this inflow layer height difference may be due to the differences in the numbers of storms and sondes used in the composites. However, we found that both groups cat 1-3 and 4-5 have more than 200 sondes with good spatial coverage in the inner-core region. We believe the result is robust, especially for the region within r* <1.5.According to theoretical scaling arguments (e.g., Kepert 2001), the boundary layer depth is scaled as a function of the square root of the vertical eddy diffusivity divided by inertial stability. It is conceivable that in stronger hurricanes the vertical eddy diffusivity is larger due to increased turbulence in the boundary layer (Zhang et al. 2011). The data in group cat 4-5 are mainly from Hurricanes Mitch (1998), Isabel (2003), and Ivan (2004), which are large storms, in which the inertial stabilitywould not be greater than that for group cat 1-3. It is possible that these two factorsmake the boundary layer height higher in group cat 4-5. Note that there may be a difference in the inertial stability between the inner core and the outer vortex in a storm (e.g., Kepert 2006b). Another interesting feature we noticed in Fig. 10 is that the depth of the strong inflow layer increases (to some extent) with decreasing radius for the group cat 4-5 storms at radius of roughly r* =1.5-3.0. In this region, the slope of the 10%peak inflow contour in themiddle panel of Fig. 10 is upward, while in the bottom panel the slope is downward. Since there is a much smaller sample of data for outside r* = 1.5 than inside r* = 1.5 for group cat 4-5, the trend of increasing inflow layer height with decreasing radius beyond 1.5r* may not be conclusive.1 We recommend that more dropsondes should be released in the outer-core region in future field programs, especially for strong hurricanes. Although there is an apparent difference in inflowlayer depth by storm intensity, there is little difference in the mixed layer depth by storm intensity, as seen in Fig. 11. The inner-core region of the stronger storms (group cat 4-5) is warmer, however. 4. Discussion and conclusions Characteristic height scales of the hurricane boundary layer are analyzed using a large quantity of dropsonde data from 13 hurricanes. Figure 12 is a schematic diagram that summarizes the characteristic height scales such as the height of the maximum wind speed (hvmax), the inflow layer depth (hinfl), and the mixed layer depth (zi), as a function of normalized distance (r* = r/RMW). Here, each height scale is based on the composite analysis results discussed above. Also shown in Fig. 12 is the boundary layer depth estimated using the critical bulk Richardson number method (Fig. 9). The results show a clear separation between the dynamical and thermodynamical boundary layer heights (Fig. 12). Zhang et al. (2009) has highlighted this difference in the outer-core region. They showed that turbulent momentum fluxes are near zero, not at the top of the mixed layer, but at a height that is close to the depth of the inflow layer. The separation of the dynamical and thermodynamical boundary layer height scales was also evident in the numerical simulations of Nolan et al. (2009a) and in an observational study of Hurricane Isabel (2003) given by Montgomery et al. (2006, see their Fig. 4).While theZhang et al. observations are constrained to a nearly rain-free region between outer rainbands with mean surface wind speeds less than 30 m s-1, this finding highlights the limitation of a thermodynamic definition of the hurricane boundary layer. When advocating that the thermodynamic definition is not suitable for the hurricane boundary layer, Kepert (2010a) argued that turbulence is predominately shear generated and the height scale is determined by dynamics, not thermodynamics. In addition, all three height scales (hvmax, hinfl, and zi) tend to decrease with decreasing radius to the storm center, in particular, in the inner-core region. It is found that hvmax decreases more than the other two height scales. There is a tendency toward a leveling off of the three height scales in the outer-core region (r* >3.5). The subsidence warming is likely the reason the boundary layer depth is reduced at large radius (e.g., Kepert 2010b). The decreases in hvmax and hinfl have been recognized in previous studies of individual storms (e.g., Kepert 2006a,b; Schwendike andKepert 2008; Sitkowski and Barnes 2009). These decreases are consistent with the scaling-height argument according to theories of rotating boundary layers (Eliassen 1971; Carrier 1971; Montgomery et al. 2001; Kepert 2001; Kepert and Wang 2001; Nolan 2005; Foster 2009; Kepert 2010a,b). We also found that the heights of both the maximum wind speed and the tangential wind speed are within the inflow layer. The height of the tangential wind speed (Vt) is located at the height where the radial wind speed (Vr) is 25% of the peak inflow. This feature appears to be independent of storm intensity. From its traditional definition the mixed layer depth is found to decrease with decreasing radius from the storm center, especially near the core. Schneider and Barnes (2005) showed that the lifting condensation level (LCL) decreased with decreasing radius in Hurricane Bonnie (1998), consistent with this result. Previous studies of the tropical boundary layer near squall lines or hurricane rainbands have shown that the mixed layer is usually shallower due to convective downdrafts that transport dry and cool air to the low-level boundary layer (Zipser 1977; Betts and Simpson 1987; Powell 1990; Barnes and Powell 1995). However, the traditional boundary layer entrainment processesmay not be at work in the eyewall, because the flow there is nearly saturated, which tends to prevent downdrafts from bringing appreciably drier air to the boundary layer. It is possible that the increase in precipitation and sea spray toward the storm center may be responsible for the decrease of the mixed layer depth. It is also possible that the mixed layer depth is controlled by, or related to, boundary layer dynamics, in that the entire boundary layer depth is constrained by the increasing rotational stability toward the center. Certainly, further analysis is required to confirm the above hypotheses. The boundary layer depth estimated using the critical Richardson number method is found to behave differently from all the above-mentioned three height scales (i.e., hvmax, hinfl, zi), in that the depth increases toward the eyewall. This indicates that using the Richardson number method to estimate the boundary layer depth may not produce the correct pattern of behavior in numerical models. Notwithstanding the variability of different boundary layer height scales, it is thought that the inflowlayer depth represents the top of the hurricane boundary layer better than does the thermodynamic boundary layer depth. Direct flux measurements in the outer-core regions of hurricanes suggest the turbulent flux transport mainly occurs in the inflow layer (Zhang et al. 2009). The budgets and discussion presented by Kepert andWang (2001) and Kepert (2010a) support the statement that the momentum flux occurs mainly in the inflow layer. In his numerical simulations, Kepert (2010a) also showed that the momentumflux is a significant part of the dynamics of the layer of outflow immediately above the inflow and suggested that it is therefore appropriate to include at least part of this layer in the boundary layer. We note that defining the boundary layer top as the inflow layer depth presents its own problems, in that real storms may have highly asymmetric inflow layers. The flow can be outward relative to the storm center near the surface in a moving storm, as seen for example in Hurricane Frederic, given by Powell (1982, see his Fig. 6). Modeling studies also show weaker inflow, or occasionally outflow, on the left side of moving storms (e.g., Kepert 2010a; Nolan et al. 2009b), consistent with theoretical arguments given by Kepert (2001). A recent observational study by Lorsolo et al. (2010) showed that the turbulent kinetic energy (TKE) estimated from Doppler radar data in the eyewall region can extend up to the top of the troposphere. The elevated levels of TKE in the eyewall suggest that it is difficult to precisely define the boundary layer in the hurricane inner core using a turbulence argument, as discussed by Smith and Montgomery (2010). However, we note that TKE and turbulent fluxes are different properties. The former represents the turbulence intensity, which is derived from the variance of the flow,while the latter represents the vertical transports, which depends on the covariance of the fields. Zhu et al. (2010) pointed out that the mechanisms for generating TKE and fluxes by different types of turbulent eddies are different in the hurricane surface layer. From the turbulent variance profiles shown by Zhang et al. (2009), one can also deduce that while the turbulent fluxes tend to become zero near the top of the inflow layer, the turbulent intensity or TKE does not vanish. To accurately identify the top of the hurricane boundary layer, we believe it will be required to measure turbulent fluxes near the top of the inflow layer. Fortunately, turbulence sensors that have been successfully used during the Coupled Boundary Layer Air-Sea Transfer (CBLAST) hurricane experiment (Black et al. 2007; Drennan et al. 2007; French et al. 2007; Zhang et al. 2008) are still on board the NOAA P3 aircraft. It has been planned in HRD's annual hurricane field project to conduct flux measurements near the top of the inflow layer (Rogers et al. 2010, 96-100). Such an experiment would also help quantify entrainment processes near the top of the boundary layer that are crucial to close the energy budget (Barnes and Powell 1995; Wroe and Barnes 2003). The results presented in this study should be useful for evaluating numerical simulations for hurricane prediction. Future work will involve adding more dropsonde data to the database. Emphasis will be placed on the investigation of the asymmetric boundary layer structure, and possible structural differences between weakening, quasi-steady, and intensifying storms. Acknowledgments. This work was supported by the NOAAHurricane Forecast Improvement Project (HFIP). We gratefully acknowledge all the scientists who were involved in the Hurricane Research Division's field program collecting the data. We appreciate the efforts of all the scientists and students who helped with postprocessing the sonde data used in this work.Without their efforts, this work would not have been possible. In particular, we are grateful to Kathryn Sellwood for putting the dropsonde data together. We acknowledge Eric Uhlhorn, Joe Cione, Sylvie Lorsolo, Mike Montgomery, Peter Black, and Mark Powell for valuable discussions.We appreciate the efforts of Jeff Kepert, Gary Barnes, and an anonymous reviewer in reviewing our paper and providing comments that led to substantial improvements. We also thank the editor, George Bryan, for providing valuable suggestions to improve this paper. 1 Previous P3 flights have focused on dropping sondes in the eyewall region. REFERENCES Albrecht, B. A., R. S. Penc, and W. H. Schubert, 1985: An observational study of cloud-topped mixed layers. J. Atmos. Sci., 42, 800-822. Anthes, R. A., and S. W. Chang, 1978: Response of the hurricane boundary layer to changes of sea surface temperature in a numerical model. J. Atmos. Sci., 35, 1240-1255. Barnes, G. M., 2008: Atypical thermodynamic profiles in hurricanes. Mon. Wea. Rev., 136, 631-643. _____, andM.D. Powell, 1995: Evolution of the inflow boundary layer of Hurricane Gilbert (1988). Mon. Wea. Rev., 123, 2348-2368. _____, G. D. Emmitt, B. Brummer, M. A. LeMone, and S. Nicholls, 1980: The structure of a fair weather boundary layer based on the results of several measurement strategies. Mon. Wea. Rev., 108, 349-364. Beljaars, A. C. M., and P. Viterbo, 1998: Role of the boundary layer in a numerical weather prediction model. Clear and Cloudy BoundaryLayers,A.A.M.Holtslag and P.G.Duynkerke,Eds., Royal Netherlands Academy of Arts and Sciences, 287-304. Bell, M. M., and M. T. Montgomery, 2008: Observed structure, evolution, and intensity of category fiveHurricane Isabel (2003) from 12 to 14 September. Mon. Wea. Rev., 136, 2023-2036. Bender,M.A., I. Ginis, R. Tuleya, B. Thomas, and T. Marchok, 2007: The operational GFDL hurricane-ocean prediction system and a summary of its performance. Mon. Wea. Rev., 135, 3965-3989. Betts, A. K., and J. Simpson, 1987: Thermodynamic budget diagram for the hurricane subcloud layer. J. Atmos. Sci., 44, 842-848. Black, P. G., and Coauthors, 2007: Air-sea exchange in hurricanes: Synthesis of observations fromtheCoupled Boundary Layer Air- Sea Transfer experiment. Bull. Amer. Meteor. Soc., 88, 357-374. Braun, S. A., and W.-K. Tao, 2000: Sensitivity of high-resolution simulations of Hurricane Bob (1991) to planetary boundary layer parameterizations. Mon. Wea. Rev., 128, 3941-3961. Bryan, G. H., and R. Rotunno, 2009: The maximum intensity of tropical cyclones in axisymmetry numerical model simulations. Mon. Wea. Rev., 137, 1770-1789. Carrier, G. F., 1971: Swirling flow boundary layers. J. Fluid Mech., 49, 133-144. Chen,S. S., J.F.Price,W.Zhao,M.A.Donelan,andE. J.Walsh, 2007: The CBLAST-Hurricane Program and the next-generation fully coupled atmosphere-wave-ocean models for hurricane research and prediction. Bull. Amer. Meteor. Soc., 88, 311-317. Cione, J. J., P. G. Blasck, and S. H. Houston, 2000: Surface observations in the hurricane environment. Mon. Wea. Rev., 128, 1550-1561. Davis, C., and Coauthors, 2008: Prediction of landfalling hurricanes with the Advanced Hurricane WRF model. Mon. Wea. Rev., 136, 1990-2005. Drennan, W. M., J. A. Zhang, J. R. French, C. McCormick, and P.G. Black, 2007: Turbulent fluxes in the hurricane boundary layer. Part II: Latent heat fluxes. J. Atmos. Sci., 64, 1103- 1115. Eliassen, A., 1971: On the Ekman layer in a circular vortex. J. Meteor. Soc. Japan, 49, 784-789. _____, and M. Lystad, 1977: The Ekman layer of a circular vortex.A numerical and theoretical study. Geophys. Norv., 7, 1-16. Emanuel, K. A., 1986: An air-sea interaction theory for tropical cyclones. Part I: Steady-state maintenance. J. Atmos. Sci., 43, 585-605. Foster, R. C., 2009: Boundary-layer similarity under an axisymmetric, gradient wind vortex. Bound.-Layer Meteor., 131, 321-344. Frank, W. M., 1977a: The structure and energetics of the tropical cyclone I. Storm structure. Mon. Wea. Rev., 105, 1119- 1135. _____, 1977b: The structure and energetics of the tropical cyclone II. Dynamics and energetics. Mon. Wea. Rev., 105, 1136-1150. _____, 1984: A composite analysis of the core of a mature hurricane. Mon. Wea. Rev., 112, 2401-2420. Franklin, J. L., M. L. Black, and K. Valde, 2003: GPS dropwindsonde wind profiles in hurricanes and their operational implications. Wea. Forecasting, 18, 32-44. French, J. R., W. M. Drennan, J. A. Zhang, and P. G. Black, 2007: Turbulent fluxes in the hurricane boundary layer. Part I: Momentum flux. J. Atmos. Sci., 64, 1089-1102. Hanna, S. R., 1969: The thickness of the planetary boundary layer. Atmos. Environ., 3, 519-536. Hock, T. F., and J. L. Franklin, 1999: The NCAR GPS dropwindsonde. Bull. Amer. Meteor. Soc., 80, 407-420. Holtslag, A. A. M., E. van Meijgaard, and W. C. de Rooij, 1995: A comparison of boundary layer diffusion schemes in unstable conditions over land. Bound.-Layer Meteor., 76, 69-95. Hong, S. Y., and H. L. Pan, 1996: Nonlocal boundary layer vertical diffusion in a medium-range forecast model. Mon. Wea. Rev., 124, 2322-2339. Johnson, R. H., P. E. Ciesielski, and J. A. Cotturone, 2001: Multiscale variability of the atmospheric mixed layer over the western Pacific warm pool. J. Atmos. Sci., 58, 2729- 2750. Jorgensen, D. P., 1984: Mesoscale and convective scale characteristics of mature hurricanes. Part I: General observations by research aircraft. J. Atmos. Sci., 41, 1268-1285. Kepert, J. D., 2001: The dynamics of boundary layer jets within the tropical cyclone core. Part I: Linear theory. J. Atmos. Sci., 58, 2469-2484. ______, 2006a: Observed boundary layer wind structure and balance in the Hurricane core. Part I: Hurricane Georges. J. Atmos. Sci., 63, 2169-2193. _____, 2006b: Observed boundary layer wind structure and balance in the Hurricane core. Part II: Hurricane Mitch. J. Atmos. Sci., 63, 2194-2211. _____, 2010a: Slab- and height-resolving models of the tropical cyclone boundary layer. Part I: Comparing the simulations. Quart. J. Roy. Meteor. Soc., 136A, 1686-1699, doi:10.1002/ qj.667. _____, 2010b: Slab- and height-resolving models of the tropical cyclone boundary layer. Part II: Why the simulations differ. Quart. J. Roy. Meteor. Soc., 136A, 1700-1711, doi:10.1002/ qj.685. _____, and Y. Wang, 2001: The dynamics of boundary layer jets within the tropical cyclone core. Part II: Nonlinear enhancement. J. Atmos. Sci., 58, 2485-2501. Lorsolo, S., J. A. Zhang, F. D. Marks, and J. Gamache, 2010: Estimation and mapping of hurricane turbulent energy using airborne Doppler measurements. Mon. Wea. Rev., 138, 3656- 3670. Mahrt, L., 1981: Modeling the depth of the stable boundary layer. Bound.-Layer Meteor., 21, 3-19. Marks, F. D., Jr., and L. K. Shay, 1998: Landfalling tropical cyclones: Forecast problems and associated research opportunities. Bull. Amer. Meteor. Soc., 79, 305-323. Montgomery,M. T., H. D. Snell, and Z. Yang, 2001: Axisymmetric spindown dynamics of hurricane-like vortices. J. Atmos. Sci., 58, 421-435. _____, M. M. Bell, S. Aberson, and M. Black, 2006: Hurricane Isabel (2003): New insights into the physics of intense storms. Part I: Mean vortex structure and maximum intensity estimate. Bull. Amer. Meteor. Soc., 87, 1335-1347. Moss, M. S., 1978: Low-level turbulence structure in the vicinity of a hurricane. Mon. Wea. Rev., 106, 841-849. _____, and F. J. Merceret, 1976: A note on several low-layer features of Hurricane Eloise (1975). Mon. Wea. Rev., 104, 967-971. Nicholls, S., 1985: Aircraft observations of the Ekman layer during the Joint Air-Sea Interaction experiment. Quart. J. Roy. Meteor. Soc., 111, 391-426. _____, andC. J.Readings, 1979:Aircraft observations of the structure on the lower boundary layer over the sea.Quart. J.Roy.Meteor. Soc., 105, 785-802. _____, andM. A. LeMone, 1980: The fair weather boundary layer in GATE: The relationship of subcloud fluxes and structure to the distribution and enhancement of cumulus clouds. J. Atmos. Sci., 37, 2051-2067. Noh, Y., W. G. Cheon, S. Y. Hong, and S. Raasch, 2003: Improvement of the K-profile model for the planetary boundary layer based on large eddy simulation data. Bound.-Layer Meteor., 107, 421-427. Nolan, D. S., 2005: Instabilities in hurricane-like boundary layers. Dyn. Atmos. Oceans, 40, 209-236. _____, J. A. Zhang, and D. P. Stern, 2009a: Evaluation of planetary boundary layer parameterizations in tropical cyclones by comparison of in situ data and high-resolution simulations of Hurricane Isabel (2003). Part I: Initialization, maximum winds, and outer-core boundary layer structure. Mon. Wea. Rev., 137, 3651-3674. _____, D. P. Stern, and J. A. Zhang, 2009b: Evaluation of planetary boundary layer parameterizations in tropical cyclones by comparison of in situ data and high-resolution simulations of Hurricane Isabel (2003). Part II: Inner-core boundary layer and eyewall structure. Mon. Wea. Rev., 137, 3675-3698. Ooyama, K. V., 1969: Numerical simulation of the life cycle of tropical cyclones. J. Atmos. Sci., 26, 3-40. Powell, M. D., 1982: The transition of the Hurricane Frederic boundary-layer wind field from the open Gulf of Mexico to landfall. Mon. Wea. Rev., 110, 1912-1932. _____, 1990: Boundary layer structure and dynamics in outer hurricane rainbands. Part II: Downdraft modification and mixed layer recovery. Mon. Wea. Rev., 118, 918-938. _____, P. J. Vickery, and T. A. Reinhold, 2003: Reduced drag coefficient for high wind speeds in tropical cyclones. Nature, 422, 279-283. Rogers, R. F., and Coauthors, 2006: The Intensity Forecasting Experiment: A NOAA multiyear field program for improving tropical cyclone intensity forecasts. Bull. Amer. Meteor. Soc., 87, 1523-1537. _____, and Coauthors, 2010: The 2010 Hurricane Field Program Plan. NOAA/AOML, 104 pp. [Available online at http:// www.aoml.noaa.gov/hrd/HFP2010/HFP2010_part1.pdf.] Rotunno, R., Y. Chen, W. Wang, C. Davis, J. Dudhia, and G. J. Holland, 2009: Large-eddy simulation of an idealized tropical cyclone. Bull. Amer. Meteor. Soc., 90, 1783-1788. Schneider, R., and G. M. Barnes, 2005: Low-level kinematic, thermodynamic, and reflectivity fields associated with Hurricane Bonnie (1998) at landfall. Mon. Wea. Rev., 133, 3243-3259. Schwendike, J., and J. D. Kepert, 2008: The boundary layer winds in Hurricanes Danielle (1998) and Isabel (2003). Mon. Wea. Rev., 136, 3168-3192. Sitkowski, M., and G. M. Barnes, 2009: Low-level thermodynamic, kinematic, and reflectivity fields ofHurricaneGuillermo (1997) during rapid intensification. Mon. Wea. Rev., 137, 645-663. Smith, R. K., and M. T. Montgomery, 2010: Hurricane boundarylayer theory. Quart. J. Roy. Meteor. Soc., 136A, 1665-1670, doi:10.1002/qj.679. _____, and G. L. Thomsen, 2010: Dependence of tropical-cyclone intensification on the boundary layer representation in a numerical model. Quart. J. Roy. Meteor. Soc., 136A, 1671-1685, doi:10.1002/qj.687. _____,M. T.Montgomery, and S.Vogl, 2008:Acritique ofEmanuel's hurricane model and potential intensity theory. Quart. J. Roy. Meteor. Soc., 134, 551-561. _____, _____, and S. V. Nguyen, 2009: Tropical cyclone spinup revisited. Quart. J. Roy. Meteor. Soc., 135, 1321-1335. Stull, R. B., 1988: An Introduction to Boundary Layer Meteorology. Kluwer Academic, 666 pp. Troen, I., and L. Mahrt, 1986: A simple model of the atmospheric boundary layer: Sensitivity to surface evaporation. Bound.- Layer Meteor., 37, 129-148. Vogelezang, D. H. P., and A. A. M. Holtslag, 1996: Evaluation and model impacts of alternative boundary-layer height formulations. Bound.-Layer Meteor., 81, 245-269. Wetzel, P. J., 1982: Toward parameterization of the stable boundary layer. J. Appl. Meteor., 21, 7-13. Willoughby, H. E., and M. Chelmow, 1982: Objective determination of hurricane tracks from aircraft observations. Mon. Wea. Rev., 110, 1298-1305. Wroe, D. R., and G. M. Barnes, 2003: Inflow layer energetics of Hurricane Bonnie (1998) near landfall. Mon. Wea. Rev., 131, 1600-1612. Yin, B., and B. Albrecht, 2000: Spatial variability of atmospheric boundary layer structure over the eastern equatorial Pacific. J. Climate, 13, 1574-1592. Zeng, X., M. A. Bruke, M. Zhou, C. Fairall, N. A. Bond, and D. H. Lenschow, 2004: Marine atmospheric boundary layer height over the eastern Pacific: Data analysis and model evaluation. J. Climate, 17, 4159-4170. Zhang, J. A., P. G. Black, J. R. French, and W. M. Drennan, 2008: First direct measurements of enthalpy flux in the hurricane boundary layer: The CBLAST results. Geophys. Res. Lett., 35, L14813, doi:10.1029/2008GL034374. _____, W. M. Drennan, P. G. Black, and J. R. French, 2009: Turbulence structure of the hurricane boundary layer between the outer rainbands. J. Atmos. Sci., 66, 2455- 2467. _____, F. D. Marks, M. T. Montgomery, and S. Lorsolo, 2011: An estimation of turbulent characteristics in the low-level region of intense Hurricanes Allen (1980) and Hugo (1989). Mon. Wea. Rev., 139, 1447-1462. Zhu, P., J. A. Zhang, and F. J. Masters, 2010: Wavelet analysis of turbulence in the hurricane surface layer during landfalls. J. Atmos. Sci., 67, 3793-3805. Zipser, E. J., 1977: Mesoscale and convective-scale downdrafts as distinct components of squall line circulation. Mon. Wea. Rev., 105, 1568-1589. JUN A. ZHANG Rosenstiel School of Marine and Atmospheric Science, University of Miami, and NOAA/AOML/Hurricane Research Division, Miami, Florida ROBERT F. ROGERS NOAA/AOML/Hurricane Research Division, Miami, Florida DAVID S. NOLAN Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida FRANK D. MARKS JR. NOAA/AOML/Hurricane Research Division, Miami, Florida (Manuscript received 26 October 2010, in final form 9 March 2011) Corresponding author address: Dr. Jun Zhang, Rosenstiel School of Marine and Atmospheric Science, University of Miami, 4600 Rickenbacker Cswy., Miami, FL 33149. E-mail: [email protected] (c) 2011 American Meteorological Society [ Back To TMCnet.com's Homepage ]