• Atkins, N. T., and R. M. Wakimoto, 1991: Wet microburst activity over the southeastern United States: Implications for forecasting. Wea. Forecasting,6, 470–482.

    • Crossref
    • Export Citation
  • Brown, J. M., K. Knupp, and F. Caracena, 1982: Destructive winds from shallow, high-based cumulonimbi. Preprints, 12th Conf. on Severe Local Storms, San Antonio, TX, Amer. Meteor. Soc., 272–275.

  • Byers, H. R., and R. R. Braham, 1949: The Thunderstorm: Report of the Thunderstorm Project. U.S. Dept. of Commerce, 287 pp.

  • Caracena, F., J. McCarthy, and J. Flueck, 1983: Forecasting the likelihood of microbursts along the Front Range of Colorado. Preprints, 13th Conf. on Severe Local Storms, Tulsa, OK, Amer. Meteor. Soc., 261–264.

  • Darkow, G. L., 1968: The total energy environment of severe storms. J. Appl. Meteor.,7, 199–205.

    • Crossref
    • Export Citation
  • Dickerson, S., 2000: Review of two microburst prediction indices and the introduction of a new microburst potential index for the Kennedy Space Center and Cape Canaveral Air Station. M.S. thesis, Reference No. AFIT/GM/ENP/00M-06, Air Force Institute of Technology, Wright-Patterson Air Force Base, OH, 112 pp.

  • Dodge, J., J. Arnold, G. Wilson, J. Evans, and T. Fujita, 1986: The Cooperative Huntsvile Meteorological Experiment (COHMEX). Bull. Amer. Meteor. Soc.,67, 417–419.

  • Eilts, M. D., J. T. Johnson, E. D. Mitchell, R. J. Lynn, P. Spencer, S. Cobb, and T. M. Smith, 1996: Damaging downburst prediction and detection algorithm for the WSR-88D. Preprints, 18th Conf. on Severe Local Storms, San Francisco, CA, Amer. Meteor. Soc., 541–543.

  • Ellrod, G. P., 1989: Environmental conditions associated with the Dallas microburst storm determined from satellite soundings. Wea. Forecasting,4, 469–484.

    • Crossref
    • Export Citation
  • ——, 1990: The assessment of microburst potential using GOES-VAS sounder data. Preprints, 16th Conf. on Severe Local Storms, Kananaskis Park, AB, Canada, Amer. Meteor. Soc., 161–166.

  • ——, and J. P. Nelson III, 1998: Experimental microburst image products derived from GOES sounder data. Preprints, 16th Conf. on Weather Analysis and Forecasting, Phoenix, AZ, Amer. Meteor. Soc., 43–45.

  • Emmanuel, K., 1981: A similarity theory for unsaturated downdrafts within clouds. J. Atmos. Sci.,38, 1541–1557.

    • Crossref
    • Export Citation
  • Fujita, T. T., 1976: Spearhead echo and downburst near the approach end of a John F. Kennedy Airport runway, New York City. Satellite Meteorology Research Project (SMRP) Research Paper 137, University of Chicago, 51 pp. [Available from Dept. of Geophysical Sciences, University of Chicago, Chicago, IL 60637.].

  • ——, 1983: Andrews AFB microburst. SMRP Research Paper Number 205, University of Chicago, 38 pp. [Available from Dept. of Geophysical Sciences, University of Chicago, Chicago, IL 60637.].

  • ——, 1985: The downburst, microburst and macroburst. SMRP Research Paper Number 210, University of Chicago, 122 pp. [Available from Dept. of Geophysical Sciences, University of Chicago, Chicago, IL 60637.].

  • Haro, J. A., and G. D. Green, 1996: The southern Arizona severe weather outbreak of 14 August 1996: An initial assessment. Western Region Technical Attachment No. 96-27, 23 pp. [Available from National Weather Service Western Region Headquarters, Federal Building, 125 S. State St., Salt Lake City, UT 84138-1102.].

  • Lanier, R. C., M. R. Witiw, L. Bottos, C. Cook-Gauthier, G. P. Ellrod, and W. P. Roeder, 1999: The human factors and errors in aviation decision making: Integrating satellite weather imagery for improved aviation safety. Preprints, Third Human Error, Safety, and System Development Workshop, Liege, Belgium, Belgian Office for Scientific, Technical and Cultural Affairs and Fonds National de la Recherche Scientific, 17 pp.

  • Ma, X. L., T. J. Schmit, and W. L. Smith, 1999: A nonlinear physical retrieval algorithm—Its application to the GOES-8/9 sounder. J. Appl. Meteor.,38, 501–510.

    • Crossref
    • Export Citation
  • Maddox, R., K. Howard, C. Dempsey, C. Wallace, and J. J. Gourley, 1996: SWAMP 1996—Operational field plan. National Severe Storms Laboratory, Norman, OK. [Available online at http://www.nssl.noaa.gov/projects/swamp/1996/index.html.].

  • McCann, D. W., 1994: WINDEX—A new index for forecasting microburst potential. Wea. Forecasting,9, 532–541.

    • Crossref
    • Export Citation
  • 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, 757–781.

    • Crossref
    • Export Citation
  • ——, F. C. Holt, T. J. Schmit, R. M. Aune, A. J. Schreiner, G. S. Wade, and D. G. Wade, 1998: Application of GOES-8/9 soundings to weather forecasting and nowcasting. Bull. Amer. Meteor. Soc.,79, 2059–2077.

    • Crossref
    • Export Citation
  • Montgomery, H. E., and L. W. Uccellini, Eds., 1985: VAS demonstration: (VISSR Atmospheric Sounder) Description and final report. NASA Ref. Publ. 1151, 170 pp. [Available from National Aeronautics and Space Administration, Code NIT-3, Washington, DC 20546-0001.].

  • Mostek, A., L. W. Uccellini, R. A. Petersen, and D. Chesters, 1986:Assessment of VAS soundings in the analysis of a preconvective environment. Mon. Wea. Rev.,114, 62–87.

    • Crossref
    • Export Citation
  • National Climatic Data Center, 1998: Storm Data. Vol. 40, No. 6, 183–187.

  • Nelson, J. P., III, and G. P. Ellrod, 1997: Recent developments in a microburst risk image product derived from GOES I–M satellite sounder data. Preprints, Seventh Conf. on Aviation, Range, and Aerospace Meteorology, Long Beach, CA, Amer. Meteor. Soc., 262–267.

  • Proctor, F. H., 1989: Numerical simulations of an isolated microburst. Part II: Sensitivity experiments. J. Atmos. Sci.,46, 2143–2165.

  • Rao, P. A., and H. E. Fuelberg, 1998: An evaluation of GOES-8 retrievals. J. Appl Meteor.,37, 1577–1587.

  • Rodi, A. R., K. L. Elmore, and W. P. Mahoney, 1983: Aircraft and Doppler air motion comparisons in a JAWS microburst. Preprints, 21st Conf. on Radar Meteorology, Zurich, Switzerland, Amer. Meteor. Soc., 624–629.

  • Sanger, N., 1999: CCAS microburst climatology, M.S. thesis, Dept. of Meteorology, Texas A&M University, College Station, TX. [Available from College of Geoscience, Texas A&M University, College Station, TX 77843-3148.].

  • Schmidlin, F. J., 1988: WMO international radiosonde comparison. Phase II Final Report. 1985. WMO Tech. Document WMO/TD312, World Meteorological Organization, Geneva, Switzerland, 113 pp.

  • Schreiner, A. J., D. Unger, W. P. Menzel, G. P. Ellrod, K. I. Strabala, and J. L. Pellet, 1993: A comparison of ground and satellite observations of cloud cover. Bull. Amer. Meteor. Soc.,74, 1851–1861.

    • Crossref
    • Export Citation
  • Srivastava, R. C., 1985: A simple model of evaporatively driven down draft: Application to microburst downdraft. J. Atmos. Sci.,42, 1004–1023.

    • Crossref
    • Export Citation
  • ——, 1987: A model of intense downdrafts driven by the melting and evaporation of precipitation. J. Atmos. Sci.,44, 1752–1773.

    • Crossref
    • Export Citation
  • Wade, C. G., 1994: An evaluation of problems affecting measurement of low relative humidity on the United States radiosonde. J. Atmos. Oceanic Technol.,11, 687–700.

    • Crossref
    • Export Citation
  • Wakimoto, R. M., 1985: Forecasting dry microburst activity over the high plains. Mon. Wea. Rev.,113, 1131–1143.

    • Crossref
    • Export Citation
  • Wheeler, M., 1996: Verification and Implementation of Microburst Day Potential Index (MDPI) and Wind Index (WINDEX) forecasting tools at Cape Canaveral Air Station. NASA Contractor Rep. CR-201354, 24 pp. [Available from ENSCO, Inc., 445 Pineda Court, Melbourne, FL 32940.].

  • ——, 1997: 1997 MDPI results. Applied Meteorology Unit Memo., ENSCO, Cape Canaveral, FL, 4 pp. [Available from ENSCO, Inc., 445 Pineda Court, Melbourne, FL 32940.].

  • ——, and W. P. Roeder, 1996: Forecasting wet microbursts on the central Florida Atlantic coast in support of the United States Space Program, 1996. Preprints, 18th Conf. on Severe Local Storms, San Francisco, CA, Amer. Meteor. Soc., 654–658.

  • Wolfson, M. M., 1990: Understanding and predicting microbursts. Preprints, 16th Conf. on Severe Local Storms, Kananaskis Park, AB, Canada, Amer. Meteor. Soc., 340–351.

  • ——, R. L. Delanoy, B. E. Forman, R. G. Hallowell, M. L. Pawlak, and P. D. Smith, 1994: Automated microburst wind-shear prediction. Lincoln Lab. J.,7, 399–426.

  • Zehr, R. M., J. F. W. Purdom, J. F. Weaver, and R. N. Green, 1988: Use of VAS data to diagnose the mesoscale environment of convective storms. Wea. Forecasting,3, 33–49.

    • Crossref
    • Export Citation
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Experimental GOES Sounder Products for the Assessment of Downburst Potential

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  • 1 Office of Research and Applications, NESDIS/NOAA, Washington, D.C.
  • | 2 Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin—Madison, Madison, Wisconsin
  • | 3 Florida Institute of Technology, Melbourne, Florida
  • | 4 45th Weather Squadron, Patrick Air Force Base, Florida
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Abstract

Several experimental products derived from Geostationary Operational Environmental Satellite (GOES) Sounder retrievals (vertical profiles of temperature and moisture) have been developed to assist weather forecasters in assessing the potential for convective downbursts. The product suite currently includes the wind index (WINDEX), a dry microburst index, and the maximum difference in equivalent potential temperature (θe) from the surface to 300 hPa. The products are displayed as color-coded boxes or numerical values, superimposed on GOES visible, infrared, or water vapor imagery, and are available hourly, day and night, via the Internet. After two full summers of evaluation, the products have been shown to be useful in the assessment of atmospheric conditions that may lead to strong, gusty surface winds from thunderstorms. Two case studies are presented: 1) a severe downburst storm in southern Arizona that produced historic surface wind speeds and damage, and 2) multiple dry and wet downbursts in western Kansas that resulted in minor damage. Verification involved comparing the parameters with radiosonde data, numerical model first guess data, or surface wind reports from airports, mesonetworks, or storm spotters. Mean absolute WINDEX from the GOES retrievals differed from the mean surface wind gust reports by <2 kt (1 m s−1) for 82 events, but underestimated wind gusts for 7 nighttime events by 22 kt (11 m s−1). GOES WINDEX was also slightly better than that derived from the concurrent National Centers for Environmental Prediction’s Eta Model first guess. There are plans to incorporate these downburst parameters into a future upgrade of the National Weather Service’s Advanced Weather Interactive Processing System, with the option to derive them from either GOES Sounder data, radiosondes, or numerical model forecast data.

Corresponding author address: Gary P. Ellrod, E/RA2, Room 601, WWBG, NOAA, 5200 Auth Road, Camp Springs, MD 20746-4304.

Email: gellrod@nesdis.noaa.gov

Abstract

Several experimental products derived from Geostationary Operational Environmental Satellite (GOES) Sounder retrievals (vertical profiles of temperature and moisture) have been developed to assist weather forecasters in assessing the potential for convective downbursts. The product suite currently includes the wind index (WINDEX), a dry microburst index, and the maximum difference in equivalent potential temperature (θe) from the surface to 300 hPa. The products are displayed as color-coded boxes or numerical values, superimposed on GOES visible, infrared, or water vapor imagery, and are available hourly, day and night, via the Internet. After two full summers of evaluation, the products have been shown to be useful in the assessment of atmospheric conditions that may lead to strong, gusty surface winds from thunderstorms. Two case studies are presented: 1) a severe downburst storm in southern Arizona that produced historic surface wind speeds and damage, and 2) multiple dry and wet downbursts in western Kansas that resulted in minor damage. Verification involved comparing the parameters with radiosonde data, numerical model first guess data, or surface wind reports from airports, mesonetworks, or storm spotters. Mean absolute WINDEX from the GOES retrievals differed from the mean surface wind gust reports by <2 kt (1 m s−1) for 82 events, but underestimated wind gusts for 7 nighttime events by 22 kt (11 m s−1). GOES WINDEX was also slightly better than that derived from the concurrent National Centers for Environmental Prediction’s Eta Model first guess. There are plans to incorporate these downburst parameters into a future upgrade of the National Weather Service’s Advanced Weather Interactive Processing System, with the option to derive them from either GOES Sounder data, radiosondes, or numerical model forecast data.

Corresponding author address: Gary P. Ellrod, E/RA2, Room 601, WWBG, NOAA, 5200 Auth Road, Camp Springs, MD 20746-4304.

Email: gellrod@nesdis.noaa.gov

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