An Examination of Model Track Forecast Errors for Hurricane Ike (2008) in the Gulf of Mexico

Michael J. Brennan NOAA/NWS/NCEP/National Hurricane Center, Miami, Florida

Search for other papers by Michael J. Brennan in
Current site
Google Scholar
PubMed
Close
and
Sharanya J. Majumdar Division of Meteorology and Physical Oceanography, Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida

Search for other papers by Sharanya J. Majumdar in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Sources of dynamical model track error for Hurricane Ike (2008) in the Gulf of Mexico are examined. Deterministic and ensemble model output are compared against National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) analyses to identify potential critical features associated with the motion of Ike and its eventual landfall along the upper Texas coast. Several potential critical features were identified, including the subtropical ridge north of Ike and several synoptic-scale short-wave troughs and ridges over central and western North America, and Tropical Storm Lowell in the eastern North Pacific. Using the NCEP Gridpoint Statistical Interpolation (GSI) data assimilation scheme, the operational GSI analysis from the 0000 UTC 9 September 2008 cycle was modified by perturbing each of these features individually, and then integrating the GFS model using the perturbed initial state. The track of Ike from each of the perturbed runs was compared to the operational GFS and it was found that the greatest improvements to the track forecast were associated with weakening the subtropical ridge north of Ike and strengthening a midlevel short-wave trough over California. A GFS run beginning with an analysis where both of these features were perturbed produced a greater track improvement than either did individually. The results suggest that multiple sources of error exist in the initial states of the operational models, and that the correction of these errors in conjunction with reliable ensemble forecasts would lead to improved forecasts of tropical cyclone tracks and their accompanying uncertainty.

Corresponding author address: Dr. Michael J. Brennan, 11691 SW 17th St., Miami, FL 33165. E-mail: michael.j.brennan@noaa.gov

Abstract

Sources of dynamical model track error for Hurricane Ike (2008) in the Gulf of Mexico are examined. Deterministic and ensemble model output are compared against National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) analyses to identify potential critical features associated with the motion of Ike and its eventual landfall along the upper Texas coast. Several potential critical features were identified, including the subtropical ridge north of Ike and several synoptic-scale short-wave troughs and ridges over central and western North America, and Tropical Storm Lowell in the eastern North Pacific. Using the NCEP Gridpoint Statistical Interpolation (GSI) data assimilation scheme, the operational GSI analysis from the 0000 UTC 9 September 2008 cycle was modified by perturbing each of these features individually, and then integrating the GFS model using the perturbed initial state. The track of Ike from each of the perturbed runs was compared to the operational GFS and it was found that the greatest improvements to the track forecast were associated with weakening the subtropical ridge north of Ike and strengthening a midlevel short-wave trough over California. A GFS run beginning with an analysis where both of these features were perturbed produced a greater track improvement than either did individually. The results suggest that multiple sources of error exist in the initial states of the operational models, and that the correction of these errors in conjunction with reliable ensemble forecasts would lead to improved forecasts of tropical cyclone tracks and their accompanying uncertainty.

Corresponding author address: Dr. Michael J. Brennan, 11691 SW 17th St., Miami, FL 33165. E-mail: michael.j.brennan@noaa.gov
Save
  • Berg, R., cited 2011: Tropical cyclone report: Hurricane Ike. [Available online at http://www.nhc.noaa.gov/pdf/TCR-AL092008_Ike_3May10.pdf.]

    • Search Google Scholar
    • Export Citation
  • ECMWF, cited 2011: IFS documentation—Cy33r1 operational implementation 3 June 2008. Part V: Ensemble prediction system. [Available online at http://www.ecmwf.int/research/ifsdocs/CY33r1/ENSEMBLE/IFSPart5.pdf.]

    • Search Google Scholar
    • Export Citation
  • Franklin, J. L., cited 2011: 2009 National Hurricane Center forecast verification report. [Available online at http://www.nhc.noaa.gov/verification/pdfs/Verification_2009.pdf.]

    • Search Google Scholar
    • Export Citation
  • Goerss, J., Sampson C. , and Gross J. , 2004: A history of western North Pacific tropical cyclone track forecast skill. Wea. Forecasting, 19, 633638.

    • Search Google Scholar
    • Export Citation
  • Henderson, J. M., Lackmann G. M. , and Gyakum J. R. , 1999: An analysis of Hurricane Opal’s forecast track errors using quasigeostrophic potential vorticity inversion. Mon. Wea. Rev., 127, 292307.

    • Search Google Scholar
    • Export Citation
  • Hoffman, R. N., 2004: Controlling hurricanes. Sci. Amer., 291, 6875.

  • Kleist, D. T., Parrish D. F. , Derber J. C. , Treadon R. , Errico R. M. , and Yang R. , 2009a: Improving incremental balance in the GSI 3DVAR analysis system. Mon. Wea. Rev., 137, 10461060.

    • Search Google Scholar
    • Export Citation
  • Kleist, D. T., Parrish D. F. , Derber J. C. , Treadon R. , Wu W. S. , and Lord S. , 2009b: Introduction of the GSI into the NCEP Global Data Assimilation System. Wea. Forecasting, 24, 16911705.

    • Search Google Scholar
    • Export Citation
  • Liu, Q., Marchok T. , Pan H.-L. , Bender M. , and Lord S. , 2000: Improvements in hurricane initialization and forecasting at NCEP with global and regional GFDL models. National Weather Service Tech. Procedures Bull. 472, 7 pp. [Available online at http://www.nws.noaa.gov/om/tpb/472.pdf.]

    • Search Google Scholar
    • Export Citation
  • Majumdar, S. J., Chen S.-G. , and Wu C.-C. , 2011: Characteristics of ensemble transform Kalman filter adaptive sampling guidance for tropical cyclones. Quart. J. Roy. Meteor. Soc., 137B, 503520, doi:10.1002/qj.746.

    • Search Google Scholar
    • Export Citation
  • Peng, M. S., and Reynolds C. A. , 2006: Sensitivity of tropical cyclone forecasts as revealed by singular vectors. J. Atmos. Sci., 63, 25082528.

    • Search Google Scholar
    • Export Citation
  • Rappaport, E. N., and Coauthors, 2009: Advances and challenges at the National Hurricane Center. Wea. Forecasting, 24, 395419.

  • Sampson, C. R., and Schrader A. J. , 2000: The Automated Tropical Cyclone Forecasting System (version 3.2). Bull. Amer. Meteor. Soc., 81, 12311240.

    • Search Google Scholar
    • Export Citation
  • Sampson, C. R., Goerss J. S. , and Weber H. C. , 2006: Operational performance of a new barotropic model (WBAR) in the western North Pacific basin. Wea. Forecasting, 21, 656662.

    • Search Google Scholar
    • Export Citation
  • Wei, M., Toth Z. , Wobus R. , and Zhu Y. , 2008: Initial perturbations based on the ensemble transform (ET) technique in the NCEP global operational forecast system. Tellus, 60A, 6279.

    • Search Google Scholar
    • Export Citation
  • Wu, C. C., and Emanuel K. A. , 1995a: Potential vorticity diagnostics of hurricane movement. Part I: A case study of Hurricane Bob (1991). Mon. Wea. Rev., 123, 6992.

    • Search Google Scholar
    • Export Citation
  • Wu, C. C., and Emanuel K. A. , 1995b: Potential vorticity diagnostics of hurricane movement. Part II: Tropical Storm Ana (1991) and Hurricane Andrew (1992). Mon. Wea. Rev., 123, 93109.

    • Search Google Scholar
    • Export Citation
  • Zhang, F., Snyder C. , and Rotunno R. , 2003: Effects of moist convection on mesoscale predictability. J. Atmos. Sci., 60, 11731185.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 199 74 7
PDF Downloads 248 58 8