Article Type:
Research Article

Assimilation of Tropical Cyclone Advisory Minimum Sea Level Pressure in the NCEP Global Data Assimilation System

Daryl T. Kleist Environmental Modeling Center, National Centers for Environmental Prediction, Camp Springs, Maryland

Search for other papers by Daryl T. Kleist in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Dec 2011
DOI:
https://doi.org/10.1175/WAF-D-11-00045.1
Page(s):
1085–1091
Restricted access

Abstract

The assimilation of official advisory minimum sea level pressure observations has been developed and tested in the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS) to address forecaster concerns regarding some tropical systems being far too weak in operational Global Forecast System (GFS) analyses. The assimilation of these observations has been operational in the GFS since December 2009. Using the T574 version of the NCEP GFS model, it is demonstrated that the assimilation of these observations results in a substantial reduction in the initial intensity bias for tropical systems, resulting in improved track and intensity guidance for lead times out to 5 days.

Additional affiliation: I. M. Systems Group, Camp Springs, Maryland.

Corresponding author address: Daryl T. Kleist, NOAA Science Center, No. 207, 5200 Auth Rd., Camp Springs, MD 20746-4304. E-mail: daryl.kleist@noaa.gov

Abstract

The assimilation of official advisory minimum sea level pressure observations has been developed and tested in the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS) to address forecaster concerns regarding some tropical systems being far too weak in operational Global Forecast System (GFS) analyses. The assimilation of these observations has been operational in the GFS since December 2009. Using the T574 version of the NCEP GFS model, it is demonstrated that the assimilation of these observations results in a substantial reduction in the initial intensity bias for tropical systems, resulting in improved track and intensity guidance for lead times out to 5 days.

Additional affiliation: I. M. Systems Group, Camp Springs, Maryland.

Corresponding author address: Daryl T. Kleist, NOAA Science Center, No. 207, 5200 Auth Rd., Camp Springs, MD 20746-4304. E-mail: daryl.kleist@noaa.gov
Save
Cover Weather and Forecasting
Weather and Forecasting

  • Aberson, S. D., 2008: Large forecast degradations due to synoptic surveillance during the 2004 and 2005 hurricane seasons. Mon. Wea. Rev., 136, 3138–3150.

    • Search Google Scholar
    • Export Citation

  • Chen, Y., and Snyder C. , 2007: Assimilating vortex position with an ensemble Kalman filter. Mon. Wea. Rev., 135, 1828–1845.

  • Dvorak, V. F., 1975: Tropical cyclone intensity analysis and forecasting from satellite imagery. Mon. Wea. Rev., 103, 420–430.

  • Dvorak, V. F., 1984: Tropical cyclone intensity analysis using satellite data. NOAA Tech. Rep. NESDIS 11, 47 pp.

  • Guard, C. P., Carr L. E. , Wells F. H. , Jeffries R. A. , Gural N. D. , and Edson D. K. , 1992: Joint Typhoon Warning Center and the challenges of multibasin tropical cyclone forecasting. Wea. Forecasting, 7, 328–352.

    • Search Google Scholar
    • Export Citation

  • Hamill, T. M., Whitaker J. S. , Fiorino M. , and Benjamin S. G. , 2011: 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

  • 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, 1046–1060.

    • Search Google Scholar
    • Export Citation

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

    • Search Google Scholar
    • Export Citation

  • Krishnamurti, T. N., Correa-Torres R. , Rohaly G. , and Oosterhof D. , 1997: Physical initialization and hurricane ensemble forecasts. Wea. Forecasting, 12, 503–514.

    • Search Google Scholar
    • Export Citation

  • Liu, Q., Marchok T. , Pan H.-L. , Bender M. , and Lord S. J. , 2000: Improvements in hurricane initialization and forecasting at NCEP with global and regional (GFDL) models. NWS Tech. Procedures Bull. 472, 7 pp. [Available online at http://www.nws.noaa.gov/om/tpb/472.htm.]

    • Search Google Scholar
    • Export Citation

  • Lord, S. J., 1991: A bogusing system for vortex circulations in the National Meteorological Center Global Forecast Model. Preprints, 19th Conf. on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., 328–330.

    • Search Google Scholar
    • Export Citation

  • Pu, Z., and Braun S. A. , 2001: Evaluation of bogus vortex techniques with four-dimensional variational data assimilation. Mon. Wea. Rev., 129, 2023–2039.

    • Search Google Scholar
    • Export Citation

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

  • Serrano, E., and Undén P. , 1994: Evaluation of a tropical cyclone bogusing method in data assimilation and forecasting. Mon. Wea. Rev., 122, 1523–1547.

    • Search Google Scholar
    • Export Citation

  • Torn, R. D., 2010: Performance of a mesoscale ensemble Kalman filter (EnKF) during the NOAA High-Resolution Hurricane Test. Mon. Wea. Rev., 138, 4375–4392.

    • Search Google Scholar
    • Export Citation

  • Wu, C.-C., Lien G.-Y. , Chen J.-H. , and Zhang F. , 2010: Assimilation of tropical cyclone track and structure based on the ensemble Kalman filter (EnKF). J. Atmos. Sci., 67, 3806–3822.

    • Search Google Scholar
    • Export Citation

  • Wu, W.-S., Parrish D. F. , and Purser R. J. , 2002: Three-dimensional variational analysis with spatially inhomogeneous covariances. Mon. Wea. Rev., 130, 2905–2916.

    • Search Google Scholar
    • Export Citation

  • Zou, X., and Xiao Q. , 2000: Studies on the initialization and simulation of a mature hurricane using a variational bogus data assimilation scheme. J. Atmos. Sci., 57, 836–860.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 197 70 3
PDF Downloads 218 40 1