Sensitivity of Idealized Hurricane Intensity and Structures under Varying Background Flows and Initial Vortex Intensities to Different Vertical Resolutions in HWRF

Da-Lin Zhang Department of Atmospheric and Oceanic Science and Center for Scientific Computation and Mathematical Modeling, University of Maryland, College Park, College Park, Maryland

Search for other papers by Da-Lin Zhang in
Current site
Google Scholar
PubMed
Close
,
Lin Zhu Department of Atmospheric and Oceanic Science and Center for Scientific Computation and Mathematical Modeling, University of Maryland, College Park, College Park, Maryland

Search for other papers by Lin Zhu in
Current site
Google Scholar
PubMed
Close
,
Xuejin Zhang Cooperative Institute for Marine and Atmospheric Studies, University of Miami, and NOAA/Atlantic Oceanographic and Meteorological Laboratory, Miami, Florida

Search for other papers by Xuejin Zhang in
Current site
Google Scholar
PubMed
Close
, and
Vijay Tallapragada NOAA/NCEP/Environmental Modeling Center, College Park, Maryland

Search for other papers by Vijay Tallapragada in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

A series of 5-day numerical simulations of idealized hurricane vortices under the influence of different background flows is performed by varying vertical grid resolution (VGR) in different portions of the atmosphere with the operational version of the Hurricane Weather Research and Forecasting Model in order to study the sensitivity of hurricane intensity forecasts to different distributions of VGR. Increasing VGR from 21 to 43 levels produces stronger hurricanes, whereas increasing it further to 64 levels does not intensify the storms further, but intensity fluctuations are much reduced. Moreover, increasing the lower-level VGRs generates stronger storms, but the opposite is true for increased upper-level VGRs. On average, adding mean flow increases intensity fluctuations and variability (between the strongest and weakest hurricanes), whereas adding vertical wind shear (VWS) delays hurricane intensification and then causes more rapid growth in intensity variability. The stronger the VWS, the larger intensity variability and bifurcation rate occur at later stages. These intensity differences are found to be closely related to inner-core structural changes, and they are attributable to how much latent heat could be released in higher-VGR layers, followed by how much moisture content in nearby layers is converged. Hurricane intensity with higher VGRs is shown to be much less sensitive to varying background flows, and stronger hurricane vortices at the model initial time are less sensitive to the vertical distribution of VGR; the opposite is true for relatively uniform VGRs or weaker hurricane vortices. Results reveal that higher VGRs with a near-parabolic or Ω shape tend to produce smoother intensity variations and more typical inner-core structures.

Corresponding author address: Dr. Da-Lin Zhang, Department of Atmospheric and Oceanic Science, University of Maryland, College Park, 2419 CSS Bldg., College Park, MD 20742-2425. E-mail: dalin@atmos.umd.edu

Abstract

A series of 5-day numerical simulations of idealized hurricane vortices under the influence of different background flows is performed by varying vertical grid resolution (VGR) in different portions of the atmosphere with the operational version of the Hurricane Weather Research and Forecasting Model in order to study the sensitivity of hurricane intensity forecasts to different distributions of VGR. Increasing VGR from 21 to 43 levels produces stronger hurricanes, whereas increasing it further to 64 levels does not intensify the storms further, but intensity fluctuations are much reduced. Moreover, increasing the lower-level VGRs generates stronger storms, but the opposite is true for increased upper-level VGRs. On average, adding mean flow increases intensity fluctuations and variability (between the strongest and weakest hurricanes), whereas adding vertical wind shear (VWS) delays hurricane intensification and then causes more rapid growth in intensity variability. The stronger the VWS, the larger intensity variability and bifurcation rate occur at later stages. These intensity differences are found to be closely related to inner-core structural changes, and they are attributable to how much latent heat could be released in higher-VGR layers, followed by how much moisture content in nearby layers is converged. Hurricane intensity with higher VGRs is shown to be much less sensitive to varying background flows, and stronger hurricane vortices at the model initial time are less sensitive to the vertical distribution of VGR; the opposite is true for relatively uniform VGRs or weaker hurricane vortices. Results reveal that higher VGRs with a near-parabolic or Ω shape tend to produce smoother intensity variations and more typical inner-core structures.

Corresponding author address: Dr. Da-Lin Zhang, Department of Atmospheric and Oceanic Science, University of Maryland, College Park, 2419 CSS Bldg., College Park, MD 20742-2425. E-mail: dalin@atmos.umd.edu
Save
  • Anthes, R. A., and D. Keyser, 1979: Tests of a fine-mesh model over Europe and United States. Mon. Wea. Rev., 107, 963984, doi:10.1175/1520-0493(1979)107<0963:TOAFMM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Arakawa, A., and V. Lamb, 1977: Computational design of the basic dynamical process of the UCLA general circulation model. Methods Comput. Phys., 17, 173265.

    • Search Google Scholar
    • Export Citation
  • Bao, J.-W., S. G. Gopalakrishnan, S. A. Michelson, F. D. Marks Jr., and M. T. Montgomery, 2012: Impact of physics representations in the HWRFX on simulated hurricane structure and pressure–wind relationships. Mon. Wea. Rev., 140, 32783299, doi:10.1175/MWR-D-11-00332.1.

    • Search Google Scholar
    • Export Citation
  • Black, M. L., J. F. Gamache, F. D. Marks Jr., C. E. Samsury, and H. E. Willoughby, 2002: Eastern Pacific Hurricanes Jimena of 1991 and Olivia of 1994: The effect of vertical shear on structure and intensity. Mon. Wea. Rev., 130, 22912312, doi:10.1175/1520-0493(2002)130<2291:EPHJOA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Chen, H., and D.-L. Zhang, 2013: On the rapid intensification of Hurricane Wilma (2005). Part II: Convective bursts and the upper-level warm core. J. Atmos. Sci., 70, 146172, doi:10.1175/JAS-D-12-062.1.

    • Search Google Scholar
    • Export Citation
  • Chen, H., D.-L. Zhang, J. Carton, and R. Atlas, 2011: On the rapid intensification of Hurricane Wilma (2005). Part I: Model prediction and structural changes. Wea. Forecasting, 26, 885901, doi:10.1175/WAF-D-11-00001.1.

    • Search Google Scholar
    • Export Citation
  • Davis, C., W. Wang, J. Dudhia, and R. Torn, 2010: Does increased horizontal resolution improve hurricane wind forecasts? Wea. Forecasting, 25, 18261841, doi:10.1175/2010WAF2222423.1.

    • Search Google Scholar
    • Export Citation
  • Eckermann, S., 2009: Hybrid σp coordinate choices for a global model. Mon. Wea. Rev., 137, 224245, doi:10.1175/2008MWR2537.1.

  • Ferrier, B. S., 1994: A double-moment multiple-phase four-class bulk ice scheme. Part I: Description. J. Atmos. Sci., 51, 249280, doi:10.1175/1520-0469(1994)051<0249:ADMMPF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Ferrier, B. S., 2005: An efficient mixed-phase cloud and precipitation scheme for use in operational NWP models. Spring Meeting 2005, San Francisco, CA, Amer. Geophys. Union, Abstract A42A-02.

  • Fierro, A. O., R. F. Rogers, F. D. Marks, and D. S. Nolan, 2009: The impact of horizontal grid spacing on the microphysical and kinematic structures of strong tropical cyclones simulated with the WRF-ARW model. Mon. Wea. Rev., 137, 37173743, doi:10.1175/2009MWR2946.1.

    • Search Google Scholar
    • Export Citation
  • Frank, W. M., and E. A. Ritchie, 1999: Effects of environmental flow upon tropical cyclone structure. Mon. Wea. Rev., 127, 20442061, doi:10.1175/1520-0493(1999)127<2044:EOEFUT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Frank, W. M., and E. A. Ritchie, 2001: Effects of vertical wind shear on hurricane intensity and structure. Mon. Wea. Rev., 129, 22492269, doi:10.1175/1520-0493(2001)129<2249:EOVWSO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Gopalakrishnan, S. G., F. D. Marks Jr., X. Zhang, J.-W. Bao, K.-S. Yeh, and R. Atlas, 2011: The experimental HWRF system: A study on the influence of horizontal resolution on the structure and intensity changes in tropical cyclones using an idealized framework. Mon. Wea. Rev., 139, 17621784, doi:10.1175/2010MWR3535.1.

    • Search Google Scholar
    • Export Citation
  • Gopalakrishnan, S. G., F. D. Marks Jr., J. A. Zhang, X. Zhang, J.-W. Bao, and V. Tallapragada, 2013: A study of the impacts of vertical diffusion on the structure and intensity of the tropical cyclones using the high-resolution HWRF system. J. Atmos. Sci., 70, 524541, doi:10.1175/JAS-D-11-0340.1.

    • Search Google Scholar
    • Export Citation
  • Gray, W. M., E. Ruprecht, and R. Phelps, 1975: Relative humidity in tropical weather systems. Mon. Wea. Rev., 103, 685690, doi:10.1175/1520-0493(1975)103<0685:RHITWS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Han, J., and H.-L. Pan, 2006: Sensitivity of hurricane intensity forecasts to convective momentum transport parameterization. Mon. Wea. Rev., 134, 664674, doi:10.1175/MWR3090.1.

    • Search Google Scholar
    • Export Citation
  • Hong, S.-Y., and H.-L. Pan, 1996: Nonlocal boundary layer vertical diffusion in a medium-range forecast model. Mon. Wea. Rev., 124, 23222339, doi:10.1175/1520-0493(1996)124<2322:NBLVDI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Janjić, Z. I., 2003: A nonhydrostatic model based on a new approach. Meteor. Atmos. Phys., 82, 271285, doi:10.1007/s00703-001-0587-6.

    • Search Google Scholar
    • Export Citation
  • Janjić, Z. I., J. P. Gerrity, and S. Nickovic, 2001: An alternative approach to nonhydrostatic modeling. Mon. Wea. Rev., 129, 11641178, doi:10.1175/1520-0493(2001)129<1164:AAATNM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Janjić, Z. I., R. Gall, and M. E. Pyle, 2010: Scientific documentation for the NMM solver. NCAR Tech. Note NCAR/TN-477+STR, doi:10.5065/D6MW2F3Z, 54 pp. [Available online at http://opensky.library.ucar.edu/collections/TECH-NOTE-000-000-000-845.]

  • Kimball, S. K., and F. C. Dougherty, 2006: The sensitivity of idealized hurricane structure and development to the distribution of vertical levels in MM5. Mon. Wea. Rev., 134, 19872008, doi:10.1175/MWR3171.1.

    • Search Google Scholar
    • Export Citation
  • Kwon, Y. C., S. Lord, B. Lapenta, V. Tallapragada, Q. Liu, and Z. Zhang, 2010: Sensitivity of air-sea exchange coefficients (Cd and Ch) on hurricane intensity. 29th Conf. on Hurricanes and Tropical Meteorology, Tucson, AZ, Amer. Meteor. Soc., 13C.1. [Available online at https://ams.confex.com/ams/29Hurricanes/techprogram/paper_167760.htm.]

  • Lacis, A. A., and J. E. Hansen, 1974: A parameterization for the absorption of solar radiation in the earth’s atmosphere. J. Atmos. Sci., 31, 118133, doi:10.1175/1520-0469(1974)031<0118:APFTAO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Lindzen, R. S., and M. Fox-Rabinovitz, 1989: Consistent vertical and horizontal resolution. Mon. Wea. Rev., 117, 25752583, doi:10.1175/1520-0493(1989)117<2575:CVAHR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Liu, Y., D.-L. Zhang, and M. K. Yau, 1997: A multiscale numerical study of Hurricane Andrew (1992). Part I: An explicit simulation. Mon. Wea. Rev., 125, 30733093, doi:10.1175/1520-0493(1997)125<3073:AMNSOH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Peng, M. S., B. F. Jeng, and R. T. Williams, 1999: A numerical study on tropical cyclone intensification. Part I: Beta effect and mean flow effect. J. Atmos. Sci., 56, 14041423, doi:10.1175/1520-0469(1999)056<1404:ANSOTC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Powell, M. D., 1990: Boundary layer structure and dynamics in outer hurricane rainbands. Part II: Downdraft modification and mixed layer recovery. Mon. Wea. Rev., 118, 918938, doi:10.1175/1520-0493(1990)118<0918:BLSADI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Schwarzkopf, M. D., and S. Fels, 1991: The simplified exchange method revisited: An accurate, rapid method for computation of infrared cooling rates and fluxes. J. Geophys. Res., 96, 90759096, doi:10.1029/89JD01598.

    • Search Google Scholar
    • Export Citation
  • Tallapragada, V., and Coauthors, 2013: Hurricane Weather Research and Forecasting (HWRF) Model: 2013 scientific documentation. Developmental Testbed Center, 99 pp. [Available from http://www.dtcenter.org/HurrWRF/users/docs/.]

  • Tracton, M. S., 1973: The role of cumulus convection in the development of extratropical cyclones. Mon. Wea. Rev., 101, 573592, doi:10.1175/1520-0493(1973)101<0573:TROCCI>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wang, Y., and G. J. Holland, 1996: Tropical cyclone motion and evolution in vertical shear. J. Atmos. Sci., 53, 33133332, doi:10.1175/1520-0469(1996)053<3313:TCMAEI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Yau, M. K., Y. Liu, D.-L. Zhang, and Y. Chen, 2004: A multiscale numerical study of Hurricane Andrew (1992). Part VI: Small-scale inner-core structures and wind streaks. Mon. Wea. Rev., 132, 14101433, doi:10.1175/1520-0493(2004)132<1410:AMNSOH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Yeh, K.-S., X. Zhang, S. Gopalakrishnan, S. Aberson, R. Rogers, F. Marks, and R. Atlas, 2012: Performance of the experimental HWRF in the 2008 hurricane season. Nat. Hazards, 63, 1439–1449, doi:10.1007/s11069-011-9787-7.

    • Search Google Scholar
    • Export Citation
  • Zhang, D.-L., and J. M. Fritsch, 1988: Numerical sensitivity experiments of varying model physics on the structure, evolution, and dynamics of two mesoscale convective systems. J. Atmos. Sci., 45, 261293, doi:10.1175/1520-0469(1988)045<0261:NSEOVM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zhang, D.-L., and X. Wang, 2003: Dependence of hurricane intensity and structures on vertical resolution and time-step size. Adv. Atmos. Sci., 20, 711725, doi:10.1007/BF02915397.

    • Search Google Scholar
    • Export Citation
  • Zhang, D.-L., and C. Q. Kieu, 2006: Potential vorticity diagnosis of a simulated hurricane. Part II: Quasi-balanced contributions to forced secondary circulations. J. Atmos. Sci., 63, 28982914, doi:10.1175/JAS3790.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, F., and D. Tao, 2013: Impacts of vertical wind shear on the predictability of tropical cyclones. J. Atmos. Sci., 70, 975983, doi:10.1175/JAS-D-12-0133.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, X., K.-S. Yeh, T. S. Quirino, S. G. Gopalakrishnan, F. D. Marks, S. B. Goldenberg, and S. Aberson, 2011: HWRFx: Improving hurricane forecasts with high-resolution modeling. Comput. Sci. Eng., 13,1321, doi:10.1109/MCSE.2010.121.

    • Search Google Scholar
    • Export Citation
  • Zhu, T., D.-L. Zhang, and F. Weng, 2004: Numerical simulation of Hurricane Bonnie (1998). Part I: Eyewall evolution and intensity changes. Mon. Wea. Rev., 132, 225241, doi:10.1175/1520-0493(2004)132<0225:NSOHBP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 513 244 19
PDF Downloads 163 70 7