Gulf of Mexico Loop Current Mechanical Energy and Vorticity Response to a Tropical Cyclone

Transcription

1 University of Miami Scholarly Repository Open Access Dissertations Electronic Theses and Dissertations Gulf of Mexico Loop Current Mechanical Energy and Vorticity Response to a Tropical Cyclone Eric W. Uhlhorn University of Miami, eric.uhlhorn@noaa.gov Follow this and additional works at: Recommended Citation Uhlhorn, Eric W., "Gulf of Mexico Loop Current Mechanical Energy and Vorticity Response to a Tropical Cyclone" (28). Open Access Dissertations This Open access is brought to you for free and open access by the Electronic Theses and Dissertations at Scholarly Repository. It has been accepted for inclusion in Open Access Dissertations by an authorized administrator of Scholarly Repository. For more information, please contact repository.library@miami.edu.

2 UNIVERSITY OF MIAMI GULF OF MEXICO LOOP CURRENT MECHANICAL ENERGY AND VORTICITY RESPONSE TO A TROPICAL CYCLONE By Eric Walter Uhlhorn A DISSERTATION Submitted to the Faculty of the University of Miami in partial fulfillment of the requirements for the degree of Doctor of Philosophy Coral Gables, Florida May 28

3 UNIVERSITY OF MIAMI A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy GULF OF MEXICO LOOP CURRENT MECHANICAL ENERGY AND VORTICITY RESPONSE TO A TROPICAL CYCLONE Eric Walter Uhlhorn Approved: Dr. Lynn K. Shay Professor of Meteorology and Physical Oceanography Dr. Terri A. Scandura Graduate School Dean Dr. Bruce A. Albrecht Professor of Meteorology and Physical Oceanography Dr. Mark A. Donelan Professor of Applied Marine Physics Dr. Kevin D. Leaman Professor of Meteorology and Physical Oceanography Dr. Peter G. Black Meteorologist SAIC/NRL-Monterey

4 UHLHORN, ERIC WALTER Gulf of Mexico Loop Current Mechanical Energy and Vorticity Response to a Tropical Cyclone (Ph.D., Meteorology and Physical Oceanography) (May 28) Abstract of a dissertation at the University of Miami. Dissertation supervised by Professor Lynn K. Shay. No. of pages in text. (148) The ocean mixed layer response to a tropical cyclone within, and immediately adjacent to, the Gulf of Mexico Loop Current is examined using a combination of ocean profiles and a numerical model. A comprehensive set of temperature, salinity, and current profiles acquired from aircraft-deployed expendable probes is utilized to analyze the threedimensional oceanic energy and circulation evolution in response to Hurricane Lili s (22) passage. Mixed-layer temperature analyses show that the Loop Current cooled < 1 C in response to the storm, in contrast to typically observed larger decreases of 3 5 C. Correspondingly, vertical current shears, which are partly responsible for entrainment mixing, were found to be up to 5% weaker, on average, than observed in previous studies within the directly-forced region. The Loop Current, which separates the warmer, lighter Caribbean Subtropical water from the cooler, heavier Gulf Common water, was found to decrease in intensity by.18 ±.25 ms 1 over an approximately 1-day period within the mixed layer. Contrary to previous tropical cyclone ocean response studies which have assumed approximately horizontally homogeneous ocean structure prior to storm passage, a kinetic energy loss of 5.8 ± 6.3 kjm 2, or approximately 1 wind stress-scaled energy unit, was observed. Using near-surface currents derived from satellite altimetry data, the Loop Current is found to vary similarly in magnitude, suggesting storm-generated energy is rapidly removed by the pre-exiting Loop Current.

5 Further examination of the energy response using an idealized numerical model reveals that due to: 1) favorable coupling between the wind stress and pre-existing current vectors; and 2) wind-driven currents flowing across the large horizontal pressure gradient; wind energy transfer to mixed-layer kinetic energy can be more efficient in these regimes as compared to the case of an initially horizontally homogeneous ocean. However, nearly all of this energy is removed by advection by 2 local inertial periods after storm passage, and little evidence of the storm s impact remains. Mixed-layer vorticity within the idealized current also shows a strong direct response, but little evidence of an near-inertial wave wake results.

6 For my father. iii

7 Acknowledgments First and foremost, I wish to acknowledge the support and dedication of my adviser, Professor Nick Shay. His belief in my abilities and understanding of conflicting external commitments is truly appreciated. Special thanks are due to Dr. Peter Black (formerly of the NOAA Hurricane Research Division), who provided invaluable mentorship and support not only while I conducted my Ph.D. research, but also during my growth as a scientist at HRD over the past ten years. I sincerely thank my other three committee members, Professors Bruce Albrecht, Kevin Leaman, and Mark Donelan for helpful suggestions and willingness to accommodate scheduling difficulties as I completed my dissertation. This research would not have been possible without the resources provided by numerous entities. Prof. Shay s grant from the National Science Foundation (ATM ; ATM ) provided most of the expendable ocean profilers which forms the basis for much of this research. The expertise of pilots, crew, and engineers at the NOAA Aircraft Operations Center made the experiments a reality; special thanks to Dr. Jim McFadden, AOC Director, for his many years of support and cooperation in observational hurricane research. The Hurricane Research Division supported this effort by providing aircraft flight hours, and Dr. Frank Marks, HRD Director, continued the traditional positive environment to develop research skills since my arrival in Over much of this time, the Office of Naval Research sponsored CBLAST experiment program (N14-1-F-9), through Dr. Peter Black s direction, supported my employment at HRD, for which I am grateful. I want iv

8 to thank my colleagues who participated in the research experiments: Dr. Joe Cione and Michael Black of HRD; and Tom Cook and Scott Guhin, both formerly of UM/RSMAS. Thanks to my loving wife, Susan, for her understanding and unusual patience over the years, and to my beautiful daughter, Elizabeth, who unknowingly provided me with the emotional drive to complete my formal education. I love you both very much. I want to thank my mother-in-law, Barbara Brunner, who unselfishly spent months helping Susan and myself adjust to parenthood while I completed my research. Finally, I wish to thank my parents who provided me with a strong work ethic and sense of perseverance to complete the doctoral dissertation process, even if it did take a seemingly ridiculous amount of time. v

9 Table of Contents List of Tables x List of Figures xiii List of Acronyms xxiv Chapter 1: Introduction Motivation Scientific objectives Chapter 2: Data and analyses Hurricane Lili chronology Data summary Pre-storm In-storm Atmospheric data Ocean data Post-storm Temperature and salinity analyses Pre-storm In-storm Post-storm Mass-density fields vi

10 2.4.1 Pre-storm Post-storm Current analysis In situ profiles Geostrophic currents Atmospheric near-surface fields Winds Thermodynamic variables Observational error estimates OML and thermocline quantities Mixed-layer depth Stratification, shear, and bulk Richardson number Chapter 3: Observed upper-ocean response Surface forcing Wind stress Enthalpy flux Freshwater flux Surface heat exchange Air-sea parameters and scaling Loop Current definition Thermal response SST cooling Sub-surface response Mechanical response Currents Kinetic energy and vorticity Background Loop Current variability vii

11 3.5.1 Altimetric analysis Derived currents, vorticity, and spectra Chapter 4: Numerical model simulations Previous model studies Model description Turbulent flux parameterizations Wind stress Entrainment mixing Model storm Numerics Lateral boundary condition Upper-ocean structure initialization Layer depth and mass density Model experiments Test case OML currents and depth Kinetic energy and vorticity Shear and Richardson number Horizontally-variable case OML currents and depth Kinetic energy and vorticity Shear and Richardson number Comparison with STW and GCW responses OML Budgets Mechanical energy Vorticity Dynamic similarity and parameter sensitivity viii

12 Variable current U g Variable storm speed V s Summary Chapter 5: Summary and conclusions 114 Bibliography 119 Appendix A: Budget equations 127 A.1 Mass conservation A.2 Momentum equations A.3 Boussinesq approximation A.4 Reynolds stresses A.5 Layered model A.6 Mechanical energy equation A.7 Vorticity equation A.8 Application to the OML Appendix B: Scaling analyses 142 B.1 Mechanical energy equation B.2 Vorticity budget Appendix C: AXCP current fits 146 ix

13 List of Tables 2.1 Summary of relevant ocean probe deployments during the series of research flights in Hurricanes Isidore (9/18 9/23) and Lili (1/2 1/4). The flight ID is given as date, and H or I identifies the aircraft. In the number columns, the number of profiles used for this research is listed first, and the total number deployed is listed in parenthesis. A dash in a particular column indicates that no probes were used in the overall analysis due to geographic location Summary of center locations estimated from the wind speed minima in the SFMR measurements shown in Figure 2.6. The storm motion vector (speed and heading) computed from the centers is also indicated. The average motion over the observation time is 7.1 ms 1 at 298 from true north GPS dropwindsonde thermodynamic variable errors, expressed as both standard deviations (σ) and percentages relative to typical TC values Horizontal and vertical correlation scales used in the objective analyses Summary of observation error statistics Observed current shear from AXCP profiles deployed in TCs. Means and standard deviations are stated Statistical summary of observed Brunt-Väisälä frequency (N), vertical shear (S), and logarithm of bulk Richardson number (R). Values are means and standard deviations. Units of N and S are 1 2 s x

14 3.1 Maximum surface heat flux estimates and uncertainty. All values are in Wm 2. Note here that Q s + Q l Q k, since peak Q s and Q l locations do not coincide Storm scaling parameters based on observations in Hurricane Lili Upper-ocean scaling parameters based on pre-storm observations Dependent variable scales of the upper-ocean response Summary statistics for observed currents obtained directly from AXCP profiles. Pre- and post-columns are mean and standard deviations, and n is number of observations. Change ( ) column is mean difference (post minus pre) and 9% confidence limit. Bold values indicate statistical significance from zero mean difference Summary statistics for changes in OML currents obtained from analyzed fields. Bold values indicate significance at the 99% confidence level Summary statistics (means and standard deviations) for K and ζ from -2 to +4 R max. Units for K are kjm 2 and for ζ are 1 5 s Parameters values in Eqns. 4.7 and 4.8 which define the initial upper-ocean mass structure associated with an idealized baroclinic current Initial vertical structure at each of three model locations whose response is examined. LC is at the location in the center of the current jet as previously described. The two other locations, STW and GCW, bear resemblance to pre-storm vertical mass structure observed in the Hurricane Lili experiment. Along-track model gridpoint locations are in inertial wavelengths (Λ) relative to center of model grid Fixed parameters for response experiments Varied parameters for response experiments. For reference, U g /V s.12 in Lili xi

15 4.5 Varied parameters for response experiments in which V s is varied while holding U g fixed at.68 ms Rossby numbers (Ro) for variable storm speed (V s ) experiments B.1 Summary of dimensional scaling parameters relevant to analysis of the mechanical energy budget of the OML in response to a moving TC B.2 Non-dimensional coefficients of the OML mechanical energy balance equation C.1 Coefficients from fits with the Sanford et al. (1987) model for Hurricane Lili in-storm AXCP profiles in the upper 2 m where Z is the start depth of the good data used in the fit, T is the period of the surface wave with coefficients of C and S, Z 1,2,3, V 1,2,3 and S 1,2,3 x 1 2 represent layer depth, layered-averaged currents and current shear in each layer, respectively. R is the residual current not explained by the model to a depth of z = 2k C.2 Same as Table C.1 except for Lili Post-Storm AXCP profiles acquired on 4 Oct xii

16 List of Figures 1.1 Sea surface temperature on 4 Oct. 22 from microwave imagery, 2 days after Hurricane Lili passed over the SE Gulf of Mexico. Arrow points to area of significant surface cooling, which is sharply delineated from the LC s intrusion into the Gulf. Courtesy of Remote Sensing Systems, Inc Hurricane Lili storm track. The geographic region of primary interest for this research is the SE Gulf of Mexico (GOM) where Lili was located on 2 Oct. Plot courtesy of the National Oceanic and Atmospheric Administration (NOAA) National Hurricane Center (NHC) Hurricane Lili intensity time series in terms of maximum sustained 1-min wind speed. Note the rapid intensification from 2-3 Oct., immediately followed by a rapid weakening. Plot courtesy of the NOAA NHC Locations of the ocean probes deployed prior to the passage of Hurricane Lili used to estimate the initial temperature conditions. AXBTs are identified by ( ), AXCTDs by ( ), and AXCPs by (+). Lili s observed Besttrack is indicated by the solid line, and marked at six-hour intervals. The storm travels from SE to NW. The solid box indicates the analysis region for this research, and the dotted contours identify the 2 m and 1 m isobaths Locations of AXCTDs which measured salinity profiles prior to the passage of Hurricane Lili. Symbols are the same as for Fig xiii

17 2.5 Locations of AXCPs which measured horizontal current profiles prior to the passage of Hurricane Lili. Symbols are the same as for Fig Surface wind speed measured by the SFMR along four segments of the flight track during the 2 October 22 in-storm flight in Lili. In the left panels, the X marks the approximate location of the center of Lili and the open circles/dashed line indicates the storm track and locations of the center at each of the four passes through the eye. Note that a data gap exists from around 45 to 55 UTC. The peak 1-min average wind speed of 49 ms 1 was found on the north side of the storm, which is the right-front quadrant relative to motion direction Locations of temperature (a), salinity (b), and currents (c) from ocean profilers deployed during the the in-storm research flight pattern in Hurricane Lili on 2 October 22. Symbols are the same as in Fig Locations of temperature (a), salinity (b), and currents (c) from ocean profilers deployed during the the post-storm research flight on 4 October 22. Symbols are the same as in Fig Optimal interpolation covariance model ρ (Eqn. 2.1) as a function of dimensional horizontal distance rl ( ), where is L is the horizontal length scale parameter in Table Pre-storm temperature ( C) on Sept. at (a) surface, (b) 1 m, (c) 2 m, and (d) 3 m depth objectively analyzed from observed profiles. Contour interval is 1 C Pre-storm temperature vertical cross sections on Sept. Cross-section locations are identified on the lower-right map panel. Contour interval is 1 C. Lili s track runs from B to B xiv

18 2.12 Pre-storm salinity (ppt) on Sept. at (a) surface, (b) 1 m, (c) 2 m, and (d) 3 m depth objectively analyzed from observed profiles. Contour interval is.2 ppt Pre-storm salinity vertical cross sections on Sept. Cross-section locations are identified on the lower-right map panel. Contour interval is.2 ppt In-storm sea-surface temperature (a) and error estimates (b) on 2 Oct. objectively analyzed from observed profiles. Along- and cross-track distances are normalized by inertial wavelength (Λ) and max. wind radius (R max ), respectively Example temperature profile from AXCTD, showing near-surface warming confined to a shallow later. The blue line corresponds to observed SST, and the red line a true post-storm SST Post-storm temperature ( C) on 4 Oct. at (a) surface, (b) 1, (c) 2, and (d) 3 m depths objectively analyzed from observed profiles. Contour interval is 1 C Post-storm temperature ( C) vertical cross sections on 4 Oct. Cross-section locations are identified on the lower-right map panel. Contour interval is 1 C Post-storm salinity (ppt) on 4 Oct. at (a) surface, (b) 1, (c) 2, and (d) 3 m depths objectively analyzed from observed profiles. Contour interval is.2 ppt Post-storm salinity (ppt) vertical cross sections on 4 Oct. Cross-section locations are identified on the lower-right map panel. Contour interval is.2 ppt Temperature, salinity, and density anomaly profiles plotted as the difference profile 1714 minus profile xv

19 2.21 Pre-storm density (kgm 3 ) on Sept. at (a) surface, (b) 1 m, (c) 2 m, and (d) 3 m depth computed from objectively analyzed temperature and salinity profiles. Contour interval is.2 kgm Pre-storm density (kgm 3 ) vertical cross sections on Sept. computed from objectively analyzed temperature and salinity observations. Section locations are identified on the map at right. Contour interval is.2 kgm Post-storm density (kgm 3 ) on 4 Oct. at (a) surface, (b) 1, (c) 2, and (d) 3-m depth computed from objectively analyzed temperature and salinity profiles. Contour interval is.2 kgm Post-storm density (kgm 3 ) vertical cross sections on 4 Oct. computed from objectively analyzed temperature and salinity observations. Crosssection locations are identified on the map at right. Contour interval is.2 kgm Example of model fits (solid) using the three-layer model of (Sanford et al., 1987) for the east (u) and north (v) velocity (ms 1 ) components in panels a,d and b,e, respectively, compared to observed profile (dots). Panels c and f show differences between observed and model profiles for both velocity components normalized by the estimated surface wave amplitudes (C and S). Also indicated are surface wave period (T ) estimates. Normalized residuals are larger in panel f due to the smaller wave amplitude Pre-storm OML mean current velocity V 1 (ms 1 ), obtained from AXCP fits. Observed currents plotted as red arrows, and analyzed field plotted in black. Analyzed vectors are plotted at 1/3 the resolution of the computed fields for clarity. Contour interval for current speed is.1 ms 1, and speeds <.4ms 1 are not contoured xvi

20 2.27 Pre-storm surface geostrophic velocity V g relative to 75 m. Vectors are plotted at 1/3 the resolution of the computed fields for clarity. Contour interval is.2ms 1, and speeds <.4ms 1 are not contoured Pre-storm geostrophic current speed V g vertical cross section from SE to NW (left to right) at the middle grid row. Note the plot horizontal direction is reversed from the density cross section in Fig. 2.22b, such that the flow direction is out of the page and the storm track is left to right. Density contour interval is.5 kgm HWind surface wind analysis of Hurricane Lili on 2 October 22 at 7 UTC. Isotachs are contoured every 5 ms 1. Data used to generate this analysis include observations from SFMR, GPS dropwindsondes, QuikSCAT scatterometer, and available hourly buoy reports. The storm track is indicated by the line, and the box shows the ocean data analysis region considered for this research Analyses of (a) surface pressure (mb), (b) 1-m temperature ( C), (c) specific humidity (g kg 1 ), and (d) 1-m surface wind analysis (ms 1 ) shown in Figure Plots are rotated such that the y-axis is aligned with the direction of storm motion (indicated by the arrow), and the origin is at the center of the cyclone. Dots represent storm-relative sonde splash locations Scatterplot of observed temperature (panels a and b) and salinity (panels c and d) vs. objectively-analyzed values at the same location. Panels a and c (b and d) are for surface (3 m depth) Scatterplot of observed OML currents vs. objective analyzed currents at the same location Example density (left), temperature (center), and salinity (right) profile illustrating OML depth estimate variability under a number of cited criteria.. 44 xvii

21 2.34 Pre-storm (a) and post-storm (b) OML depth (m), estimated from objectively analyzed temperature fields. Contour interval is 1 m Example density and current profiles illustrating how vertical differences are defined in bulk shear and stratification calculations. In this example obtained in the GCW post-storm, N = s 1, and S = s Thermocline stratification frequency (N, 1 2 s 1 ) for (a) pre-storm, (b) in-storm, and (c) post-storm. Contour interval is s Thermocline current vertical shear (S, 1 2 s 1 ) for (a) pre-storm, (b) instorm, and (c) post-storm. Contour interval is s Logarithm of bulk Richardson number for (a) pre-storm, (b) in-storm, and (c) post-storm. Contour interval is.5 log(ri B ), and log(ri B ) = (i.e., Ri B = 1) is highlighted, indicative of criticality HWIND-analyzed wind stress field for Lili on 2 Oct Surface sensible heat flux (a), latent heat flux (b), and total moist enthalpy flux (c). Units for all panels are Wm 2. The arrow indicates storm motion direction Lili TMI rain rate (mmhr 1 ) distribution (a) and freshwater input (mm) (b) as function of cross-track distance x/r max Lili integrated heat losses (MJm 2 ) due to: (a) Q rain, (b) Q rad and (c) Q k as function of cross-track distance x/r max Along-track initially observed upper-ocean quantities summarizing the horizontal ocean variability encountered by Lili (a) Pre-storm MLT, (b) post-storm MLT, and (c) MLT. Observed cooling is generally < 1 C in the LC and STW, and >2.5 C in the GCW Changes in along-track upper-ocean quantities from initially- observed conditions in Fig xviii

22 3.8 Analyzed OML currents pre-storm (a,d,g), post-storm (b,e,h) and changes (c,f,i) V (a,b,c), V g (d,e,f) and V a (g,h,i). Contour intervals (red) are.2 ms (a) Pre-storm and (b) post-storm OML kinetic energy fields. Values are in units of kj m (a) Pre-storm, (b) post-storm, and (c) change in OML kinetic energy (kj m 2 ) for three analyzed regions as a function of cross-storm track distance (a) Pre-storm and (b) post-storm OML relative vorticity fields (a) Pre-storm, (b) post-storm, and (c) change in OML relative vorticity for three analyzed regions as a function of cross-storm track distance Rio-5 7-year combined MDT (a), 1-day mean SHA centered at year-day 265/22 (b), and (c) dynamic topography (a+b). Values are in m, and contour interval is.2 m. Box represents Lili observational domain Estimated near-surface geostrophic current derived from sea height field (Fig. 3.13c) for 22 year-day 265. Current magnitude, as it defines the LC here, is contoured, and interval is.1 ms 1. Notice the weaker current at the location of rapidly-turning LC ( 25 N), where the geostrophic approximation is underestimating the current Ten-year time series of LC current (mean and standard deviation) through the Lili observation region (a), and one-year record centered at time of Lili s passage (b). Pre- and post-storm V within the LC estimated from the objectively-analyzed fields are plotted for comparison Near-surface relative vorticity derived from sea height field (Fig. 3.13c) for 22 year-day 265. The ζ = line is highlighted xix

23 3.17 Ten-year time series of LC relative vorticity (mean and standard deviation) through the Lili experiment domain (a), and one-year record centered at time of Lili s passage (b). Pre- and post-storm ζ within the LC estimated from the objectively-analyzed density fields are plotted for comparison Normalized power spectrum of LC current magnitude within Lili observational domain. Dashed line is 9% confidence limits on mean spectral estimates Radial distribution of observed azimuthal-mean surface wind speed (ms 1 ). Best-fits from the Willoughby et al. (26) model (WDR) and the Holland (198) are shown Initial geostrophic current (right panel) model top (mixed) layer thickness (left panel). Boxes represent approximate dimensions of the Hurricane Lili experimental domain. Right panel axes are normalized cross-track (r/r max ) and along-track (y/λ) distances. Simulated storm travels from bottom to top along x = r/r max Initial density (kgm 3 ) and geostrophic current (ms 1 ) vertical cross section in the along-storm track/cross-stream direction. Simulated storm travels from left to right, indicated by the arrow, and current flows out of plot. Bottom panel is zoomed on approximate bounds of the Hurricane Lili observation domain to aid in comparison with Fig Initial ocean density (kgm 3 ) vertical structure for the homogeneous test case in which the ocean is at rest. Observed horizontally-averaged density profile is plotted as the solid line, and the fitted model initial condition is indicated by points at layer mid-depths xx

24 4.5 Simulated fields for 3DNL test case at.7 IP after storm passes mid-point of domain (y = ). Fields are: (a) surface wind stress (τ wind, Pa), (b) mixedlayer currents (V 1, ms 1 ), (c) mixed-layer depth (h 1, m); along-track vertical sections of: (d) cross-track current (u, ms 1 ), (e) along-track current (v, ms 1 ), and (f) current magnitude ( V, ms 1 ) Cross-track (u) and along-track (v) current vector components, current speed ( V ) and mixed-layer depth (h) responses for three test cases. Currents are in units of ms 1 and depth is in m OML kinetic energy (left) and relative vorticity (right) responses for test cases OML current shear (left) and bulk Richardson number (right) responses for three test cases Same as Fig. 4.5, but for the pre-existing current case (LC) Same as Fig. 4.6 but for initially horizontally-variable LC case and the initially quiescent 3DNL test case. Also plotted is observed average OML current speed in the LC based on AXCPs deployed in the post-storm experiment OML kinetic energy (left panel) and relative vorticity (right panel) for the initially homogeneous (3DNL) and perturbed ( Current ) simulations. KE values are relative to the initial state, which in the Current case is 16.4 kjm 2. For comparison, observed changes from the in situ data within the LC are plotted at +2 IP OML kinetic energy (K) as a function of normalized cross-track distance (x/r max relative to its initial level at six temporal locations. Dashed lines indicate approximate cross-track limits of experimental observation domain. View is down storm-track, and pre-existing current flows left to right Same as Fig but for relative vorticity (ζ ) xxi

25 4.14 Shear across OML base (left) and bulk Richardson number (right) for homogeneous and perturbed simulations Same as Fig. 4.6 but for different locations in the model domain. The LC case is as before, location STW is on the warm/light side of the current, and GCW is on the cold/heavy side Same as Fig. 4.8 but for different locations in the model domain. The LC case is as before, location STW is on the warm/light side of the current, and GCW is on the cold/heavy side Simulated energy budget for the OML averaged between and +2R max. Budget terms are kinetic energy (KE), potential energy (PE), sea-surface flux (SF), shear stress-induced flux at OML base (BF), pressure work (PW), and advection (ADV). Quantities are scaled by the peak surface energy inputs, 69.4 and 55. kj m 2 for 3DNL and LC cases, respectively Relative vorticity budget for the OML averaged between and +2R max. Budget terms are relative vorticity (RV), vortex stretching (ST), wind-stress curl (SC), stress curl at OML base (BC), and advection (ADV). Quantities are scaled by the peak surface vorticity input, s 1, equal for both cases Non-dimensional response for five initial current jet intensity cases (U g /V s ). Top panels are total current (u,v), and bottom panels are ageostrophic currents (u a,v a ) Current shear response for five initial current jet intensity cases (U g /V s ) Non-dimensional response for five initial current jet intensity cases (U g /V s ). Top panels are total current (u,v), and bottom panels are ageostrophic currents (u a,v a ) Current shear response for five initial current jet intensity cases (U g /V s ) xxii

26 4.23 Non-dimensional ageostrophic current response U a /V s = f(u g /V s ) for (a) varied initial OML current (U g ) and (b) varied storm speed (V s ). In (a), storm speed is fixed at V s = 7. ms 1, and in (b), current speed is fixed at U g =.68 ms xxiii

27 List of Acronyms 1D one dimensional linear 3DL three dimensional quasi-linear 3DNL three dimensional non-linear AXBT Airborne expendable BathyThermograph AXCP Airborne expendable Current Profiler AXCTD Airborne expendable Conductivity-Temperature-Depth CBLAST Coupled Boundary Layer Air-Sea Transfer CFL Courant-Friedrichs-Levy CLS Collecte Localisation Satellites ERS European Remote Sensing Satellite GCW Gulf of Mexico Common Water GFO Geosat Follow-On GOM Gulf of Mexico GPS Global Positioning System xxiv

28 HRD Hurricane Research Division IP inertial period KE kinetic energy LC Loop Current MDT mean dynamic topography ME mechanical energy NASA National Aeronautics and Space Administration NAVOCEANO Naval Oceanographic Office NHC National Hurricane Center NOAA National Oceanic and Atmospheric Administration NRL Naval Research Laboratory NSF National Science Foundation OI optimal interpolation OML ocean mixed layer RANS Reynolds-averaged Navier-Stokes SHA sea-height anomaly SRA Scanning Radar Altimeter SFMR Stepped-Frequency Microwave Radiometer SS Saffir-Simpson SST sea surface temperature xxv

29 STW Caribbean Subtropical Water TC tropical cyclone TMI TRMM satellite microwave imager TOPEX ocean TOPography EXperiment TS tropical storm UTC universal time coordinate WCR warm-core ring xxvi

30 Chapter 1 Introduction 1.1 Motivation Hurricanes, and more generally tropical cyclones (TCs), are among the most intense organized vortical systems observed in the atmosphere. These cyclones derive their energy primarily from the release of latent heat upon condensation of water vapor (Ooyama, 1969). Thus, it is necessary that a large moisture source be present, such as the ocean, and that the ocean surface temperature is sufficiently warm to maintain a moisture flux from the sea to the atmospheric boundary layer, as was first recognized by Palmen (1948). Numerous other studies have examined the relationship between the intensity of TCs and the sea surface temperature (SST). Malkus and Riehl (196) derived a relationship between the decrease in central pressure and the increase in equivalent potential temperature in the eyewall region (due to imported enthalpy from the ocean). Further studies by Emanuel (1986) and Betts and Simpson (1987) confirmed this relationship to be approximately constant. More recent research has studied not only the influence of SST on TC intensity but the relationship between intensity and the upper ocean thermal energy (Shay et al., 2). The early observational study of Leipper (1967) has motivated extensive research of the ocean mixed layer (OML) response to hurricane forcing, with a primary goal to better 1

31 2 understand energy feedback to the storm. Most previous studies have focused on the upper ocean thermal energy response (Price, 1981; Black, 1983; Brooks, 1983). Numerical studies (e.g. O Brien and Reid, 1967; Chang and Anthes, 1978; Greatbatch, 1983; Price, 1983) have provided additional insight into the coupling between the mechanical and thermal energy response, but in general the role of the storm-generated current field on the ocean temperature change could only be verified through comparison with linear solutions (Geisler, 197). Since entrainment of thermocline water into the OML is the dominant cooling mechanism over surface heat flux (Price, 1981), the lack of momentum data prevented a quantitative budgetary closure in most early work. Shay and Elsberry (1987) were able to examine the OML and thermocline current response to Hurricane Frederic (1979) with sufficient resolution to quantify both the vertical flux of energy through the OML as well as the internal wave wake response that is predicted by linear theory. Using a series of Airborne expendable Current Profilers (AXCPs) deployed in Hurricane Gilbert (1988), Shay et al. (1998) isolated the geostrophic and nearinertial current in the vertical structure. With these data, Jacob et al. (2) studied the effect of the pre-existing current field on the advective tendency of OML cooling. In conjunction with this observational effort, Jacob and Shay (23) conducted a series of numerical experiments to examine differences in the simulated ocean response based on the choice of vertical mixing parameterizations. In virtually all previous studies of OML response, sea-surface energy exchanges were assumed known and often unquestioned. Because the underlying ocean significantly modulates TC intensity, much attention has been drawn toward gaining a better understanding of the physical interaction between the atmosphere and ocean during these events. Unfortunately, due to limited observational data at the air-sea interface in high-wind conditions, the understanding has not progressed nearly enough to significantly improve the parameterization of momentum and energy transfer. The relationships of the transfer processes to small-scale roughness (Charnock relation) and surface-layer stability (Monin-Obukhov similarity theory) are fairly well understood under

32 3 low-wind conditions (e.g. Large and Pond, 1981), but additional phenomena not typically observed such as the maturity of the sea state (Donelan et al., 1993), sea spray (Fairall et al., 1994), and boundary layer roll vorticies (Foster, 25), have also been shown to modulate the heat and momentum exchange. These effects have been studied in the field at sub hurricane-force conditions (Katsaros et al., 1987; Donelan et al., 1997), and at high winds in controlled laboratory experiments (Alamaro et al., 22; Donelan et al., 24), but to date have not been field-verified at wind speeds much above the TC wind-speed threshold (32 ms 1 ), and most certainly not in the TC eyewall. The recent Office of Naval Research sponsored Coupled Boundary Layer Air-Sea Transfer (CBLAST) field experiment in was designed to address these issues (Black et al., 27). The various conclusions generally now agree that the bulk enthalpy and momentum exchange coefficients in TCs are not as large as previously assumed (Drennan et al., 27; French et al., 27). Coupled oceanic and atmospheric models that predict hurricane track, intensity, and structure will eventually be used to issue forecasts to the public who increasingly rely on the most advanced weather forecasting systems to prepare for land-falling systems (Marks and Shay, 1998). For such models, it has become increasingly clear over the past decade that oceanic models will have to include realistic conditions to simulate not only the oceanic response to hurricane forcing (Price, 1981; Sanford et al., 1987; Shay et al., 1992; D Asaro, 23), but also to simulate the atmospheric response to oceanic forcing (Hong et al., 2; Shay et al., 2; Lin et al., 25; Walker et al., 25; Shay and Jacob, 26). To improve the models, the observational database will have to be significantly expanded to include many more cases in various locations than currently exists. A particularly interesting region to examine the effects of variable ocean structure on TC intensity is the GOM. The upper ocean s transport from the NW Caribbean Sea and through the Yucatan Straits forms the Loop Current (LC) system which significantly influences GOM circulation patterns. These transports, 24 Sv (1 Sv = 1 6 m 3 s 1 ) through the straits, forces LC variability and modulates warm-core ring (WCR) shedding events

33 4 (Maul, 1977; Sturges and Leben, 2; Leben, 25). The LC transports warm subtropical water with markedly different temperature and salinity structure into the GOM compared to the Gulf of Mexico Common Water (GCW) (Shay et al., 1998). As the LC intrudes north of 25 N, WCRs having diameters of 1 to 2 km separate from the LC at an average interval of 6 to 11 months as determined by radar altimeter-derived sea-height anomaly (SHA) fields (Sturges and Leben, 2). By contrast, when the LC retracts south of 25 N, this time envelope for WCR shedding events increases to an average of more than 17 months (Leben, 25). Regardless of the northward LC penetration, these anticyclonically rotating WCRs propagate westward at speeds of 3 to 5 km d 1 (Elliott, 1982). Both the LC and WCR features contain upper-ocean currents of up to 1.7 m s 1 (Forristall et al., 1992; Oey et al., 25). At any given time, the GOM may have two or three WCRs embedded within its circulation pattern with smaller-scale cold core rings located along their periphery. The anticyclonic circulation around the LC exits the GOM through the Florida Straits between the United States and Cuba to form the Florida Current and eventually the Gulf Stream. Recent studies of Hurricanes Gilbert (Shay et al., 1992) and Opal (Shay et al., 2), Ivan (Walker et al., 25) and Rita (Shay, 28) have demonstrated the potential influence GOM upper-ocean variability can have on TC intensity. As revealed by microwave satellite imagery, SST cooling, indicated by the arrow in Figure 1.1, was associated with Hurricane Lili s (22) passage through the GOM. However, this cooling is clearly confined to a region outside of the LC, which is located in the extreme SE portion of the GOM. While Lili traversed the GOM, it underwent a period of rapid intensification from Saffir-Simpson (SS) category-1 to 4, immediately followed by a weakening back to category-1 intensity, over a 2.5 day period. Particularly relevant to understanding air-sea heat exchange is the interaction of storm-generated near-inertial waves with complex pre-existing circulations (e.g. Kunze, 1985), and the resulting modulation of SST and OML cooling. Underscoring uncertainties in forecasting hurricane intensity in this region is the often complex atmospheric environment which also exerts an influence on intensity (Bosart et al., 2).

34 5 1/4 1/3 1/2 1/1 Figure 1.1: Sea surface temperature on 4 Oct. 22 from microwave imagery, 2 days after Hurricane Lili passed over the SE Gulf of Mexico. Arrow points to area of significant surface cooling, which is sharply delineated from the LC s intrusion into the Gulf. Courtesy of Remote Sensing Systems, Inc. During 22, life cycles of Hurricanes Isidore and Lili in the NW Caribbean Sea and GOM were extensively observed (Shay and Uhlhorn, 28) which indicated deep, warm ocean structures cooled relatively little providing a positive thermal feedback to these storms. This is in contrast to more typical negative feedback on hurricane intensity when shear-induced mixing at the OML base cools and deepens this layer and causes a cold ocean wake where air-sea fluxes decrease (Chang and Anthes, 1978; Price, 1981; Shay et al., 1992; Schade and Emanuel, 1999; Bender and Ginis, 2). These observations raise several relevant questions: What physical mechanisms are responsible for preventing the expected cooling? Can the positive feedback on intensity in terms of enhanced moist enthalpy flux be quantified separately from other controls? Do coupled atmosphere-ocean

35 6 models, when properly initialized based on these observations, yield improved forecasts of TC intensity? 1.2 Scientific objectives In his numerical simulation of the ocean s internal wave wake response to a TC-like storm, Price (1983) used energy and vorticity conservation relations to diagnose model results. In the research presented herein, similar diagnostic methods are applied to highresolution upper-ocean observations of dynamic and thermodynamic structure within the directly-forced region beneath a hurricane. This particular study, on the other hand, differs significantly, in that observations were obtained in a highly dynamic region of the GOM LC system, which presents an additional complexity. In light of the results which are found to contradict previous observational and modeling studies of ocean response, background LC variability is examined using satellite altimetry data. Finally, an evaluation of the important mechanisms in the ocean response in an idealized variable-ocean environment using a numerical model is presented. The primary goal of this research is: To quantify the observed mean kinetic energy (KE) and vorticity response of the LC OML forced by a tropical cyclone. In support of the primary goal, the scientific objectives of this research are: Estimate the mechanical energy (ME) and vorticity response, and associated errors, derived primarily from observed vertical profiles of horizontal currents and thermodynamic variables; Examine LC variability in terms of implied currents using satellite altimetry seaheight topography measurements, and relate these estimates to the in situ observations; and

36 7 Evaluate the simulated ocean response (currents, shear, energy, and vorticity) within an idealized upper-ocean current system using a numerical modeling methodology. Upper-ocean cooling has been shown to relate directly to changes in TC intensity (Cione and Uhlhorn, 23). As this cooling is primarily a function of mechanical processes internal to the OML and upper thermocline, understanding the details of these processes is crucial to ultimately improving coupled model simulations of TCs, and predicting TCintensity changes in general. To address these research objectives, a combined observational and numerical study focusing on Hurricane Lili (22) is presented. As part of the annual NOAA Hurricane Research Division (HRD) field program, a joint National Science Foundation (NSF)/NOAA experiment was designed to measure the evolution of the upper ocean response to a hurricane. The objectives of the experiment were to be met through a series of research aircraft flights by deploying expendable ocean and atmospheric data probes prior to, during, and after passage of the storm. Hurricane Lili provided an ideal situation to meet these objectives. By combining the efforts of three NOAA aircraft, the cyclone and its environment was sampled nearly continuously as it traversed the GOM from western Cuba on its way to landfall in Louisiana. A dense grid of upper-ocean thermal data was measured by Airborne expendable BathyThermograph (AXBT), Airborne expendable Conductivity-Temperature-Depth (AXCTD) profilers and AXCP, AXCTDs measured salinity profiles, and the horizontal current field was sampled using AXCPs. In addition, the long-wave portion of the surface wave directional spectrum was measured within the storm by the National Aeronautics and Space Administration (NASA) Scanning Radar Altimeter (SRA) (Wright et al., 21). Atmospheric near-surface data were provided by over 4 Global Positioning System (GPS) dropwindsondes (Hock and Franklin, 1999) deployed by NOAA WP-3D and Air Force Reserve Command WC-13H aircraft to measure sea surface thermodynamic forcing. Finally,

37 8 a high-resolution wind field was observed directly at the surface by the HRD Stepped- Frequency Microwave Radiometer (SFMR) operated on the NOAA WP-3D (Uhlhorn et al., 27).

38 Chapter 2 Data and analyses 2.1 Hurricane Lili chronology Lili was a tropical wave of Cape Verde origin initially tracked on 16 Sept. 22 (Pasch et al., 24). This wave became a tropical depression on 21 Sept., and as the system moved just west of north at 1 ms 1, initial intensification to tropical storm (TS) status occurred on 23 Sept. The TS subsequently weakened to an open tropical wave on 26 Sept., but as the wave slowed, it redeveloped into a TS late on 27 Sept., with a minimum central pressure of 994 mb. Lili intensified to hurricane status at 12 universal time coordinate (UTC) on 3 Sept. while passing over the Cayman Islands. As Lili tracked along a north-northwest trajectory after emerging off the north Cuba coast (Fig. 2.1), the hurricane intensified to SS category-3 status (51 ms 1 ) over the SE GOM and to category-4 intensity (61 ms 1 ) in the south-central GOM where it reached its minimum central pressure of 938 mb (Fig. 2.2). During this period of rapid intensification, Lili s radius of maximum winds (R max ) decreased from 25 km to 18 km while moving at 7 ms 1. Lili then rapidly weakened to category-1 status due to a combination of enhanced atmospheric shear, dry-air intrusion along the western edge (Pasch et al., 24), and interacting with the shelf water cooled approximately ten days earlier by TS Isidore. Hurricane Lili made landfall at 13 UTC 3 9

39 1 Oct. near Intracoastal City, Louisiana. Lili is notable for its rapid intensification (defined as a maximum surface wind speed increase of at least 35 kt/24 hr (17 ms 1 /24 hr), as well as its subsequent, and equally rapid, weakening (Frederick, 23). Figure 2.1: Hurricane Lili storm track. The geographic region of primary interest for this research is the SE GOM where Lili was located on 2 Oct. Plot courtesy of the NOAA NHC. Of particular relevance here, a NOAA research flight was conducted within the storm on 2 Oct. as Lili was beginning its rapid intensification period in the SE GOM. This flight took place somewhat serendipitously in the area where a large set of vertical ocean profiles were acquired 8-13 days earlier (Shay and Uhlhorn, 28). These expendable probes were deployed in anticipation of Hurricane Isidore s forecasted track, which ultimately passed well south over the Yucatan Straits. 2.2 Data summary During the 22 NOAA HRD hurricane field program, a joint NOAA/NSF experiment was designed to measure both the kinematic and thermodynamic upper-ocean response to a propagating mature tropical cyclone. The experiment consisted of a series of research

40 11 Figure 2.2: Hurricane Lili intensity time series in terms of maximum sustained 1-min wind speed. Note the rapid intensification from 2-3 Oct., immediately followed by a rapid weakening. Plot courtesy of the NOAA NHC. flights, each deploying expendable probes in the same location before, during, and subsequent to the cyclone s passage. A set of pre-storm flights was conducted from Sept. 22, the in-storm flight occurred on 2 Oct., and a final post-storm survey was conducted on 4 Oct. The large set of ocean observations included both in situ and remotely-sensed data. Among the data obtained, relevant oceanic observations included arrays of temperature, salinity, and horizontal current vertical profiles. In conjunction with this ocean data, atmosphere near-surface and lower-tropospheric wind and thermodynamic observations were acquired within the storm environment and at the geographic location of the ocean profiles. GPS dropwindsondes (Hock and Franklin, 1999) were used primarily to measure near-surface atmospheric temperature, pressure, and humidity, while the surface (1-m) wind speed distribution was measured by the NOAA HRD SFMR (Uhlhorn et al., 27) Research flights into Hurricanes Isidore and Lili in 22 are unprecedented in the volume of upper-ocean data collected. Temperature (T ) profiles are measured by all deployed AXBT, AXCP, and AXCTD profiles. Upper-ocean horizontal current (V) profiles are mea-