Track and Intensity Forecasting of Hurricanes: Impact of Convection-Permitting Resolution and Global Ensemble Kalman Filter Analysis on 2010 Atlantic Season Forecasts

Ming Xue Center for Analysis and Prediction of Storms, and School of Meteorology, University of Oklahoma, Norman, Oklahoma

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Jordan Schleif Center for Analysis and Prediction of Storms, and School of Meteorology, University of Oklahoma, Norman, Oklahoma

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Fanyou Kong Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

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Kevin W. Thomas Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

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Yunheng Wang Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

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Kefeng Zhu Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

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Abstract

Twice-daily 48-h tropical cyclone (TC) forecasts were produced for the fall 2010 Atlantic hurricane season using the Advanced Research core of the Weather Research and Forecasting (WRF-ARW) model on a large 4-km grid covering much of the northern Atlantic. WRF forecasts initialized from operational Global Forecast System (GFS) analyses based on the gridpoint statistical interpolation (GSI) three-dimensional variational data assimilation (3DVAR) system and from experimental global ensemble Kalman filter (EnKF) analyses, and corresponding global GFS forecasts were intercompared. For the track, WRF forecasts show improvement over GFS forecasts using either set of initial conditions (ICs). The EnKF-initialized GFS and WRF are also better than the corresponding GSI-initialized forecasts, but the difference is not always statistically significant. At all lead times, the WRF track errors are comparable to or smaller than the National Hurricane Center (NHC) official track forecast error, with those of the EnKF WRF being smallest. For weaker TCs, more improvement comes from the model (resolution) than from the ICs. For hurricane intensity TCs, EnKF ICs produce better track forecasts than GSI ICs, with the best forecast coming from WRF at most lead times. For intensity, EnKF ICs consistently outperform GSI ICs in both models for weaker TCs. For hurricane-strength TCs, EnKF ICs produce forecasts statistically indistinguishable from GSI ICs in either model. For all TCs combined, WRF produces about half the error of the corresponding GFS simulation beyond 24 h, and at 36 and 48 h, the errors are smaller than those from NHC official forecasts. The improvement is even greater for hurricane-strength TCs. Overall, the WRF forecasts initialized with EnKF ICs have the smallest intensity error, and the difference is statistically significant compared to the GFS forecasts.

Corresponding author address: Dr. Ming Xue, Center for Analysis and Prediction of Storms, University of Oklahoma, 120 David Boren Blvd., Norman, OK 73072. E-mail: mxue@ou.edu

Abstract

Twice-daily 48-h tropical cyclone (TC) forecasts were produced for the fall 2010 Atlantic hurricane season using the Advanced Research core of the Weather Research and Forecasting (WRF-ARW) model on a large 4-km grid covering much of the northern Atlantic. WRF forecasts initialized from operational Global Forecast System (GFS) analyses based on the gridpoint statistical interpolation (GSI) three-dimensional variational data assimilation (3DVAR) system and from experimental global ensemble Kalman filter (EnKF) analyses, and corresponding global GFS forecasts were intercompared. For the track, WRF forecasts show improvement over GFS forecasts using either set of initial conditions (ICs). The EnKF-initialized GFS and WRF are also better than the corresponding GSI-initialized forecasts, but the difference is not always statistically significant. At all lead times, the WRF track errors are comparable to or smaller than the National Hurricane Center (NHC) official track forecast error, with those of the EnKF WRF being smallest. For weaker TCs, more improvement comes from the model (resolution) than from the ICs. For hurricane intensity TCs, EnKF ICs produce better track forecasts than GSI ICs, with the best forecast coming from WRF at most lead times. For intensity, EnKF ICs consistently outperform GSI ICs in both models for weaker TCs. For hurricane-strength TCs, EnKF ICs produce forecasts statistically indistinguishable from GSI ICs in either model. For all TCs combined, WRF produces about half the error of the corresponding GFS simulation beyond 24 h, and at 36 and 48 h, the errors are smaller than those from NHC official forecasts. The improvement is even greater for hurricane-strength TCs. Overall, the WRF forecasts initialized with EnKF ICs have the smallest intensity error, and the difference is statistically significant compared to the GFS forecasts.

Corresponding author address: Dr. Ming Xue, Center for Analysis and Prediction of Storms, University of Oklahoma, 120 David Boren Blvd., Norman, OK 73072. E-mail: mxue@ou.edu
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  • Bender, M. A., Ginis I. , Tuleya R. , Thomas B. , and Marchok T. , 2007: The operational GFDL coupled hurricane–ocean prediction system and a summary of its performance. Mon. Wea. Rev., 135, 45.

    • Search Google Scholar
    • Export Citation
  • Chou, M.-D., and Suarez M. J. , 1999: A shortwave radiation parameterization for atmospheric studies. NASA Tech Rep. NASA/TM-104606, 40 pp.

  • Chou, M.-D., Suarez M. J. , Ho C.-H. , Yan M. M. H. , and Lee K.-T. , 1998: Parameterizations for cloud overlapping and shortwave single-scattering properties for use in general circulation and cloud ensemble models. J. Climate, 11, 202–214.

    • Search Google Scholar
    • Export Citation
  • Clark, A. J., Gallus W. A. Jr., Xue M. , and Kong F. , 2009: A comparison of precipitation forecast skill between small convection-permitting and large convection-parameterizing ensembles. Wea. Forecasting, 24, 1121–1140.

    • Search Google Scholar
    • Export Citation
  • Davis, C., and Coauthors, 2008: Prediction of landfalling hurricanes with the Advanced Hurricane WRF model. Mon. Wea. Rev., 136, 1990–2005.

    • Search Google Scholar
    • Export Citation
  • Davis, C., Wang W. , Dudhia J. , and Torn R. , 2010: Does increased horizontal resolution improve hurricane wind forecasts? Wea. Forecasting, 25, 1826–1841.

    • Search Google Scholar
    • Export Citation
  • DTC, 2009: High-resolution hurricane test final report. Hurricane Forecast Improvement Project, Developmental Testbed Center, 95 pp. [Available online at http://www.dtcenter.org/plots/hrh_test/HRH_Report_30Sept.pdf.]

  • Ek, M. B., Mitchell K. E. , Lin Y. , Grunmann P. , Rogers E. , Gayno G. , Koren V. , and Tarpley J. D. , 2003: Implementation of the upgraded NOAH land-surface model in the NCEP operational mesoscale Eta Model. J. Geophys. Res.,108, 8851, doi:10.1029/2002JD003296.

  • Gopalakrishnan, S. G., Marks F. , Zhang X. , Bao J.-W. , Yeh K.-S. , and Atlas R. , 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, 1762–1784.

    • Search Google Scholar
    • Export Citation
  • Hamill, T. M., Whitaker J. S. , Fiorino M. , and Benjamin S. G. , 2011a: Global ensemble predictions of 2009's tropical cyclones initialized with an ensemble Kalman filter. Mon. Wea. Rev., 139, 668–688.

    • Search Google Scholar
    • Export Citation
  • Hamill, T. M., Whitaker J. S. , Kleist D. T. , Fiorino M. , and Benjamin S. G. , 2011b: Predictions of 2010's tropical cyclones using the GFS and ensemble-based data assimilation methods. Mon. Wea. Rev., 139, 3243–3247.

    • Search Google Scholar
    • Export Citation
  • Hendricks, E. A., Peng M. S. , Ge X. , and Li T. , 2011: Performance of a dynamic initialization scheme in the Coupled Ocean–Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC). Wea. Forecasting, 26, 650–663.

    • Search Google Scholar
    • Export Citation
  • Janjić, Z. I., 1990: The step-mountain coordinate: Physical package. Mon. Wea. Rev., 118, 1429–1443.

  • Kleist, D. T., Parrish D. F. , Derber J. C. , Treadon R. , Wu W.-S. , and Lord S. , 2009: Introduction of the GSI into the NCEP Global Data Assimilation System. Wea. Forecasting, 24, 1691–1705.

    • Search Google Scholar
    • Export Citation
  • Li, Y., Wang X. , and Xue M. , 2012: Assimilation of radar radial velocity data with the WRF ensemble–3DVAR hybrid system for the prediction of Hurricane Ike (2008). Mon. Wea. Rev., 140, 3507–3524.

    • 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. NOAA Tech. Procedures Bull. 472, 7 pp.

  • Mlawer, E. J., Taubman S. J. , Brown P. D. , Iacono M. J. , and Clough S. A. , 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102 (D14), 16 663–16 682.

    • Search Google Scholar
    • Export Citation
  • Parrish, D. F., and Derber J. C. , 1992: The National Meteorological Center's spectral statistical-interpolation analysis system. Mon. Wea. Rev., 120, 1747–1763.

    • Search Google Scholar
    • Export Citation
  • Rappaport, E. N., and Coauthors, 2009: Advances and challenges at the National Hurricane Center. Wea. Forecasting, 24, 395–419.

  • Schwartz, C., and Coauthors, 2009: Next-day convection-allowing WRF model guidance: A second look at 2-km versus 4-km grid spacing. Mon. Wea. Rev., 137, 3351–3372.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., and Weisman M. L. , 2009: The impact of positive-definite moisture transport on NWP precipitation forecasts. Mon. Wea. Rev., 137, 488–494.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Rep. NCAR/TN-475+STR, 113 pp.

  • Thompson, G., Field P. R. , Hall W. D. , and Rasmussen R. M. , 2006: A new bulk microphysical parameterization for WRF (& MM5). WRF User's Workshop, Boulder, CO, NCAR, 5.3. [Available online at http://www.mmm.ucar.edu/wrf/users/workshops/WS2006/abstracts/Session05/5_3_Thompson.pdf.]

  • Thompson, G., Field P. R. , Rasmussen R. M. , and Hall W. D. , 2008: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part II: Implementation of a new snow parameterization. Mon. Wea. Rev., 136, 5095–5115.

    • Search Google Scholar
    • Export Citation
  • Torn, R. D., and Snyder C. , 2012: Uncertainty of tropical cyclone best-track information. Wea. Forecasting, 27, 715–729.

  • Tripoli, G. J., 1992: A nonhydrostatic mesoscale model designed to simulate scale interaction. Mon. Wea. Rev., 120, 1342–1359.

  • Warner, T. T., Peterson R. A. , and Treadon R. E. , 1997: A tutorial on lateral boundary conditions as a basic and potentially serious limitation to regional numerical weather prediction. Bull. Amer. Meteor. Soc., 78, 2599–2617.

    • Search Google Scholar
    • Export Citation
  • Whitaker, J. S., Hamill T. M. , Wei X. , Song Y. , and Toth Z. , 2008: Ensemble data assimilation with the NCEP Global Forecast System. Mon. Wea. Rev., 136, 463–482.

    • Search Google Scholar
    • Export Citation
  • Xue, M., and Coauthors, 2010: CAPS realtime storm scale ensemble and high resolution forecasts for the NOAA Hazardous Weather Testbed 2010 Spring Experiment. Preprints, 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., 7B.3. [Available online at https://ams.confex.com/ams/pdfpapers/176056.pdf.]

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