Editorial Type:
Article
Article Type:
Research Article

The Impact of Multispectral GOES-8 Wind Information on Atlantic Tropical Cyclone Track Forecasts in 1995. Part I: Dataset Methodology, Description, and Case Analysis

Christopher S. Velden Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin—Madison, Madison, Wisconsin

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Timothy L. Olander Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin—Madison, Madison, Wisconsin

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Steve Wanzong Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin—Madison, Madison, Wisconsin

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Print Publication:
01 May 1998
DOI:
https://doi.org/10.1175/1520-0493(1998)126<1202:TIOMGW>2.0.CO;2
Page(s):
1202–1218
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Abstract

Satellite-based remote sensing has long been recognized as an important method to reconnoiter oceanic tropical cyclones due to the scarcity of in situ observations. Beyond the standard qualitative applications offered by imagery, algorithms are being developed to process the information-wealthy imagery into quantitative parameters necessary to positively impact objective analyses on which numerical track predictions are initialized. Techniques developed at the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies enable the automated extraction of displacement vectors from animated imagery featuring sequential geostationary satellite multispectral observations of clouds and water vapor. Recent upgrades to these algorithms and a focused processing strategy directed toward optimizing the retrieved wind vector coverage are discussed. In combination with advanced sensing technology afforded by the National Oceanic and Atmospheric Administration’s latest generation of geostationary meteorological satellites, GOES-8, superior vector yield and quality are being realized.

In this set of two papers, datasets produced during the 1995 Atlantic hurricane season are examined for their impact on tropical cyclone analyses and numerical track forecasts. In Part I, the wind retrieval methodology and data characteristics are described, along with a brief discussion of the tropical cyclones selected for study. Part II addresses the input of the GOES-8 wind information into a global data assimilation system, and the resultant impact on numerical track predictions.

Corresponding author address: Christopher Velden, UW CIMSS, 1225 West Dayton St., Madison, WI 53706.

Abstract

Satellite-based remote sensing has long been recognized as an important method to reconnoiter oceanic tropical cyclones due to the scarcity of in situ observations. Beyond the standard qualitative applications offered by imagery, algorithms are being developed to process the information-wealthy imagery into quantitative parameters necessary to positively impact objective analyses on which numerical track predictions are initialized. Techniques developed at the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies enable the automated extraction of displacement vectors from animated imagery featuring sequential geostationary satellite multispectral observations of clouds and water vapor. Recent upgrades to these algorithms and a focused processing strategy directed toward optimizing the retrieved wind vector coverage are discussed. In combination with advanced sensing technology afforded by the National Oceanic and Atmospheric Administration’s latest generation of geostationary meteorological satellites, GOES-8, superior vector yield and quality are being realized.

In this set of two papers, datasets produced during the 1995 Atlantic hurricane season are examined for their impact on tropical cyclone analyses and numerical track forecasts. In Part I, the wind retrieval methodology and data characteristics are described, along with a brief discussion of the tropical cyclones selected for study. Part II addresses the input of the GOES-8 wind information into a global data assimilation system, and the resultant impact on numerical track predictions.

Corresponding author address: Christopher Velden, UW CIMSS, 1225 West Dayton St., Madison, WI 53706.

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  • Coakley, J., and F. Bretherton, 1982: Cloud cover from high resolution scanner data: Detecting and allowing for partially filled fields of view. J. Geophys. Res.,87, 4917–4932.

  • Derber, J., and W.-S. Wu, 1996: Use of cloud-cleared radiances in the NCEP SSI analysis system. Preprints, 11th Conf. on Numerical Weather Prediction, Norfolk, VA, Amer. Meteor. Soc., 236–237.

  • Fiorino, M., and R. L. Elsberry, 1989: Some aspects of vortex structure in tropical cyclone motion. J. Atmos. Sci.,46, 979–990.

  • Franklin, J. L., and M. DeMaria, 1992: The impact of Omega dropwindsonde observations on barotropic hurricane track forecasts. Mon. Wea. Rev.,120, 381–391.

  • Goerss, J. S., and R. A. Jeffries, 1994: Assimilation of synthetic tropical cyclone observations into the Navy Operational Global Atmospheric Prediction System. Wea. Forecasting,9, 557–576.

  • ——, C. S. Velden, and J. D. Hawkins, 1998: The impact of multispectral GOES-8 wind information on Atlantic tropical cyclone track forecasts in 1995. Part II: NOGAPS forecasts. Mon. Wea. Rev.,126, 1219–1227.

  • Gross, J. M., and M. B. Lawrence, 1996: 1995 National Hurricane Center forecast verification. Proc. 50th Interdepartmental Hurricane Conference, Miami, FL, NOAA OFCM, B10–B28.

  • Hayden, C. M., and R. J. Purser, 1986: Applications of a recursive filter, objective analysis in the processing and presentation of VAS data. Preprints, Second Conf. on Satellite Meteorology, Williamsburg, VA, Amer. Meteor. Soc., 82–87.

  • ——, and C. S. Velden, 1991: Quality control and assimilation experiments with satellite derived wind estimates. Preprints, Ninth Conf. on Numerical Weather Prediction, Denver, CO, Amer. Meteor. Soc., 19–23.

  • ——, and R. J. Purser, 1995: Recursive filter objective analysis of meteorological fields: Applications to NESDIS operational processing. J. Appl. Meteor.,34, 3–15.

  • LeMarshall, J., L. M. Leslie, and A. F. Bennett, 1996: Tropical Cyclone Beti—An example of the benefits of assimilating hourly satellite data. Aust. Meteor. Mag.,45, 275–279.

  • Menzel, W. P., and J. F. W. Purdom, 1994: Introducing GOES-I: The first of a new generation of geostationary operational environmental satellites. Bull. Amer. Meteor. Soc.,75, 757–780.

  • ——, W. L. Smith, and T. R. Stewart, 1983: Improved cloud motion vector and altitude assignment using VAS. J. Climate Appl. Meteor.,22, 377–384.

  • Merrill, R. T., W. P. Menzel, W. Baker, J. Lynch, and E. Legg, 1991:A report on the recent demonstration of NOAA’s upgraded capability to derive cloud motion satellite winds. Bull. Amer. Meteor. Soc.,72, 372–376.

  • Nieman, S. J., J. Schmetz, and W. P. Menzel, 1993: A comparison of several techniques to assign heights to cloud tracers. J. Appl. Meteor.,32, 1559–1568.

  • ——, W. P. Menzel, C. M. Hayden, S. Wanzong, and C. S. Velden, 1996: Upgrades to the NOAA/NESDIS automated cloud-motion vector system. Preprints, Eighth Conf. on Satellite Meteorology and Oceanography, Atlanta, GA, Amer. Meteor. Soc., 1–4.

  • ——, ——, ——, D. Gray, S. Wanzong, C. S. Velden, and J. Daniels, 1997: Fully automated cloud-drift winds in NESDIS operations. Bull. Amer. Meteor. Soc.,78, 1121–1134.

  • Purser, R. J., and R. McQuigg, 1982: A successive correction analysis scheme using recursive numerical filters. Met. O 11 Tech. Note 154, British Meteor. Service, 17 pp.

  • Santek, D., T. Whittaker, J. T. Young, and W. Hibbard, 1991: The implementation plan for McIDAS-AIX. Preprints, Seventh International Conf. on Interactive Information and Processing Systems for Meteorology, Oceanography and Hydrology, New Orleans, LA, Amer. Meteor. Soc., 177–179.

  • Schmetz, J., K. Holmlund, J. Hoffman, and B. Strauss, 1993: Operational cloud-motion winds from Meteosat images. J. Appl. Meteor.,32, 1207–1225.

  • Velden, C. S., 1996: Winds derived from geostationary satellite moisture channel observations: Applications and impact on numerical weather prediction. Meteor. Atmos. Physics,60, 37–46.

  • ——, and S. Goldenberg, 1987: The inclusion of high density satellite wind information in a barotropic hurricane-track forecast model. Preprints, 17th Conf. on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., 90–93.

  • ——, C. M. Hayden, W. P. Menzel, J. L. Franklin, and J. Lynch, 1992: The impact of satellite-derived winds on numerical hurricane track forecasting. Wea. Forecasting,7, 107–118.

  • ——, ——, S. J. Nieman, W. P. Menzel, S. Wanzong, and J. S. Goerss, 1997: Upper-tropospheric winds derived from geostationary satellite water vapor observations. Bull. Amer. Meteor. Soc.,78, 173–195.

  • Weldon, R. B., and S. J. Holmes, 1991: Water vapor imagery: Interpretation and applications to weather analysis and forecasting. NOAA Tech. Rep. NESDIS 67, 213 pp. [Available from NOAA/NESDIS, 5200 Auth Rd., Washington, DC 20233.].

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