Impact of Stochastic Convection on Ensemble Forecasts of Tropical Cyclone Development

Andrew Snyder Department of Atmospheric Sciences, University of Utah, Salt Lake City, Utah

Search for other papers by Andrew Snyder in
Current site
Google Scholar
PubMed
Close
,
Zhaoxia Pu Department of Atmospheric Sciences, University of Utah, Salt Lake City, Utah

Search for other papers by Zhaoxia Pu in
Current site
Google Scholar
PubMed
Close
, and
Carolyn A. Reynolds Naval Research Laboratory, Monterey, California

Search for other papers by Carolyn A. Reynolds in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Two versions of the Navy Operational Global Atmospheric Prediction System (NOGAPS) global ensemble, with and without a stochastic convection scheme, are compared regarding their performance in predicting the development and evolution of tropical cyclones. Forecasts of four typhoons, one tropical storm, and two selected nondeveloping tropical systems from The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign and Tropical Cyclone Structure 2008 (T-PARC/TCS-08) field program during August and September 2008 are evaluated. It is found that stochastic convection substantially increases the spread in ensemble storm tracks and in the vorticity and height fields in the vicinity of the storm. Stochastic convection also has an impact on the number of ensemble members predicting genesis. One day prior to the system being declared a tropical depression, on average, 31% of the ensemble members predict storm development when the ensemble includes initial perturbations only. When stochastic convection is included, this percentage increases to 50%, but the number of “false alarms” for two nondeveloping systems also increases. However, the increase in false alarms is smaller than the increase in correct development predictions, indicating that stochastic convection may have the potential for improving tropical cyclone forecasting.

Corresponding author address: Dr. Zhaoxia Pu, Department of Atmospheric Sciences, University of Utah, 135 S. 1460 E., Rm. 819, Salt Lake City, UT 84112. Email: zhaoxia.pu@utah.edu

Abstract

Two versions of the Navy Operational Global Atmospheric Prediction System (NOGAPS) global ensemble, with and without a stochastic convection scheme, are compared regarding their performance in predicting the development and evolution of tropical cyclones. Forecasts of four typhoons, one tropical storm, and two selected nondeveloping tropical systems from The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign and Tropical Cyclone Structure 2008 (T-PARC/TCS-08) field program during August and September 2008 are evaluated. It is found that stochastic convection substantially increases the spread in ensemble storm tracks and in the vorticity and height fields in the vicinity of the storm. Stochastic convection also has an impact on the number of ensemble members predicting genesis. One day prior to the system being declared a tropical depression, on average, 31% of the ensemble members predict storm development when the ensemble includes initial perturbations only. When stochastic convection is included, this percentage increases to 50%, but the number of “false alarms” for two nondeveloping systems also increases. However, the increase in false alarms is smaller than the increase in correct development predictions, indicating that stochastic convection may have the potential for improving tropical cyclone forecasting.

Corresponding author address: Dr. Zhaoxia Pu, Department of Atmospheric Sciences, University of Utah, 135 S. 1460 E., Rm. 819, Salt Lake City, UT 84112. Email: zhaoxia.pu@utah.edu

Save
  • Cheung, K. K. W. , and R. L. Elsberry , 2002: Tropical cyclone formations over the western North Pacific in the Navy Operational Global Atmospheric Prediction System forecasts. Wea. Forecasting, 17 , 800820.

    • Search Google Scholar
    • Export Citation
  • Goerss, J. S. , and C. A. Reynolds , 2008: Impact of stochastic cumulus on the NOGAPS ET ensemble forecasting system. Part II: Tropical cyclone track forecast performance. Preprints, 28th Conf. on Hurricanes and Tropical Meteorology, Orlando, FL, Amer. Meteor. Soc., 5A.3. [Available online at http://ams.confex.com/ams/28Hurricanes/techprogram/paper_137869.htm].

    • Search Google Scholar
    • Export Citation
  • McLay, J. G. , C. H. Bishop , and C. A. Reynolds , 2008: Evaluation of the ensemble transform analysis perturbation scheme at NRL. Mon. Wea. Rev., 136 , 10931108.

    • Search Google Scholar
    • Export Citation
  • Peng, M. S. , J. A. Ridout , and T. F. Hogan , 2004: Recent modifications of the Emanuel convective scheme in the Navy Operational Global Atmospheric Prediction System. Mon. Wea. Rev., 132 , 12541268.

    • Search Google Scholar
    • Export Citation
  • Puri, K. , J. Barkmeijer , and T. N. Palmer , 2001: Ensemble prediction of tropical cyclones using targeted diabatic singular vectors. Quart. J. Roy. Meteor. Soc., 127 , 709731.

    • Search Google Scholar
    • Export Citation
  • Reynolds, C. A. , J. Teixeira , and J. G. McLay , 2008: Impact of stochastic convection on the ensemble transform. Mon. Wea. Rev., 136 , 45174526.

    • Search Google Scholar
    • Export Citation
  • Rogers, R. , and Coauthors , 2006: The intensity forecasting experiment: A NOAA multiyear field program for improving tropical cyclone intensity forecasts. Bull. Amer. Meteor. Soc., 87 , 15231537.

    • Search Google Scholar
    • Export Citation
  • Snyder, A. , Z. Pu , and Y. Zhu , 2010: Tracking and verification of the east Atlantic tropical cyclone genesis in NCEP global ensemble: Case studies during NASA African monsoon multi-disciplinary analyses. Wea. Forecasting, 25 , 13971411.

    • Search Google Scholar
    • Export Citation
  • Teixeira, J. , and C. A. Reynolds , 2008: Stochastic nature of physical parameterizations in ensemble prediction: A stochastic convection approach. Mon. Wea. Rev., 136 , 483496.

    • Search Google Scholar
    • Export Citation
  • Toth, Z. , and E. Kalnay , 1997: Ensemble forecasting at NCEP and the breeding method. Mon. Wea. Rev., 125 , 32973319.

  • Wei, M. , Z. Toth , R. Wobus , and Y. Zhu , 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
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 230 107 29
PDF Downloads 190 121 2