An Evaluation of Advanced Dvorak Technique–Derived Tropical Cyclone Intensity Estimates during Extratropical Transition Using Synthetic Satellite Imagery

Alexander Manion Atmospheric Science Program, Department of Mathematical Sciences, University of Wisconsin–Milwaukee, Milwaukee, Wisconsin

Search for other papers by Alexander Manion in
Current site
Google Scholar
PubMed
Close
,
Clark Evans Atmospheric Science Program, Department of Mathematical Sciences, University of Wisconsin–Milwaukee, Milwaukee, Wisconsin

Search for other papers by Clark Evans in
Current site
Google Scholar
PubMed
Close
,
Timothy L. Olander Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, Madison, Wisconsin

Search for other papers by Timothy L. Olander in
Current site
Google Scholar
PubMed
Close
,
Christopher S. Velden Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, Madison, Wisconsin

Search for other papers by Christopher S. Velden in
Current site
Google Scholar
PubMed
Close
, and
Lewis D. Grasso Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, Colorado

Search for other papers by Lewis D. Grasso in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

It is known that both Dvorak technique and advanced Dvorak technique–derived intensity estimates for tropical cyclones during extratropical transition are less reliable because the empirical relationships between cloud patterns and cyclone intensity underlying each technique are primarily tropical in nature and thus less robust during extratropical transition. However, as direct observations of cyclone intensity during extratropical transition are rare, the precise extent to which such remotely sensed intensity estimates are in error is uncertain. To address this uncertainty and provide insight into how advanced Dvorak technique–derived intensity estimates during extratropical transition may be improved, the advanced Dvorak technique is applied to synthetic satellite imagery derived from 25 numerical simulations of Atlantic basin tropical cyclones—five cases, five microphysical parameterizations—during extratropical transition. From this, an internally consistent evaluation between model-derived and advanced Dvorak technique–derived cyclone intensity estimates is conducted. Intensity estimate error and bias peak at the beginning of extratropical transition and decline thereafter for maximum sustained surface wind. On average, synthetic advanced Dvorak technique–derived estimates of maximum sustained surface wind asymptote toward or remain near their weakest-possible values after extratropical transition begins. Minimum sea level pressure estimates exhibit minimal bias, although this result is sensitive to microphysical parameterization. Such sensitivity to microphysical parameterization, particularly with respect to cloud radiative properties, suggests that only qualitative insight regarding advanced Dvorak technique–derived intensity estimate error during extratropical transition may be obtained utilizing synthetic satellite imagery. Implications toward developing improved intensity estimates during extratropical transition are discussed.

Corresponding author address: Dr. Clark Evans, Atmospheric Science Program, Dept. of Mathematical Sciences, University of Wisconsin–Milwaukee, P.O. Box 413, Milwaukee, WI 53201. E-mail: evans36@uwm.edu

Abstract

It is known that both Dvorak technique and advanced Dvorak technique–derived intensity estimates for tropical cyclones during extratropical transition are less reliable because the empirical relationships between cloud patterns and cyclone intensity underlying each technique are primarily tropical in nature and thus less robust during extratropical transition. However, as direct observations of cyclone intensity during extratropical transition are rare, the precise extent to which such remotely sensed intensity estimates are in error is uncertain. To address this uncertainty and provide insight into how advanced Dvorak technique–derived intensity estimates during extratropical transition may be improved, the advanced Dvorak technique is applied to synthetic satellite imagery derived from 25 numerical simulations of Atlantic basin tropical cyclones—five cases, five microphysical parameterizations—during extratropical transition. From this, an internally consistent evaluation between model-derived and advanced Dvorak technique–derived cyclone intensity estimates is conducted. Intensity estimate error and bias peak at the beginning of extratropical transition and decline thereafter for maximum sustained surface wind. On average, synthetic advanced Dvorak technique–derived estimates of maximum sustained surface wind asymptote toward or remain near their weakest-possible values after extratropical transition begins. Minimum sea level pressure estimates exhibit minimal bias, although this result is sensitive to microphysical parameterization. Such sensitivity to microphysical parameterization, particularly with respect to cloud radiative properties, suggests that only qualitative insight regarding advanced Dvorak technique–derived intensity estimate error during extratropical transition may be obtained utilizing synthetic satellite imagery. Implications toward developing improved intensity estimates during extratropical transition are discussed.

Corresponding author address: Dr. Clark Evans, Atmospheric Science Program, Dept. of Mathematical Sciences, University of Wisconsin–Milwaukee, P.O. Box 413, Milwaukee, WI 53201. E-mail: evans36@uwm.edu
Save
  • Avila, L. A., and Stewart S. R. , 2013: Atlantic hurricane season of 2011. Mon. Wea. Rev., 141, 25772596, doi:10.1175/MWR-D-12-00230.1.

    • Search Google Scholar
    • Export Citation
  • Beven, J. L., 2000: Subtropical storm tropical cyclone report. NHC, 8 pp. [Available online at http://www.nhc.noaa.gov/data/tcr/AL192000_Subtropical.pdf.]

  • Beven, J. L., Stewart S. R. , Lawrence M. B. , Avila L. A. , Franklin J. L. , and Pasch R. J. , 2003: Atlantic hurricane season of 2001. Mon. Wea. Rev., 131, 14541484, doi:10.1175/1520-0493(2003)131<1454:ASHSO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Bikos, D., and Coauthors, 2012: Synthetic satellite imagery for real-time high-resolution model evaluation. Wea. Forecasting, 27, 784795, doi:10.1175/WAF-D-11-00130.1.

    • Search Google Scholar
    • Export Citation
  • Brennan, M. J., Knabb R. D. , Mainelli M. , and Kimberlain T. B. , 2009: Atlantic hurricane season of 2007. Mon. Wea. Rev., 137, 40614088, doi:10.1175/2009MWR2995.1.

    • Search Google Scholar
    • Export Citation
  • Brown, D. B., and Franklin J. L. , 2004: Dvorak TC wind speed biases determined from reconnaissance-based best track data (1997–2003). Preprints, 26th Conf. on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., 3D.5. [Available online at https://ams.confex.com/ams/pdfpapers/75193.pdf.]

  • Browning, K. A., 1990: Organization of clouds and precipitation in extratropical cyclones. Extratropical Cyclones: The Erik Palmén Memorial Volume, C. W. Newton and E. O. Holopainen, Eds., Amer. Meteor. Soc., 129–165.

  • Carlson, T. N., 1980: Airflow through midlatitude cyclones and the comma cloud pattern. Mon. Wea. Rev., 108, 14981509, doi:10.1175/1520-0493(1980)108<1498:ATMCAT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Chen, F., and Dudhia J. , 2001: Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model description and implementation. Mon. Wea. Rev., 129, 569585, doi:10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Cintineo, R., Otkin J. A. , Xue M. , and Kong F. , 2014: Evaluating the performance of planetary boundary layer and cloud microphysical parameterization schemes in convection-permitting ensemble forecasts using synthetic GOES-13 satellite observations. Mon. Wea. Rev., 142, 163182, doi:10.1175/MWR-D-13-00143.1.

    • Search Google Scholar
    • Export Citation
  • Courtney, J., and Knaff J. A. , 2009: Adapting the Knaff and Zehr wind-pressure relationship for operational use in tropical cyclone warning centres. Aust. Meteor. Oceanogr. J., 58, 167179.

    • Search Google Scholar
    • Export Citation
  • Davis, C., and Coauthors, 2008: Prediction of landfalling hurricanes with the advanced Hurricane WRF model. Mon. Wea. Rev., 136, 19902005, doi:10.1175/2007MWR2085.1.

    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, doi:10.1002/qj.828.

    • Search Google Scholar
    • Export Citation
  • Dillon, C. P., and Andrews M. J. , 1998: Joint Typhoon Warning Center 1997 annual tropical cyclone report. JTWC, 216 pp. [Available online at http://www.usno.navy.mil/NOOC/nmfc- ph/RSS/jtwc/atcr/1997atcr.pdf.]

  • Dvorak, V., 1984: Tropical cyclone intensity analysis using satellite data. NOAA Tech. Rep. NESDIS11, 47 pp. [Available from NOAA/NESDIS, 5200 Auth Rd., Washington, DC 20233.]

  • Evans, C., and Hart R. E. , 2008: Analysis of the wind field evolution associated with the extratropical transition of Bonnie (1998). Mon. Wea. Rev., 136, 20472065, doi:10.1175/2007MWR2051.1.

    • Search Google Scholar
    • Export Citation
  • Evans, J. L., and Hart R. E. , 2003: Objective indicators of the life cycle evolution of extratropical transition for Atlantic tropical cyclones. Mon. Wea. Rev., 131, 909925, doi:10.1175/1520-0493(2003)131<0909:OIOTLC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Garratt, J. R., 1992: The Atmospheric Boundary Layer. Cambridge University Press, 316 pp.

  • Grasso, L., Lindsey D. T. , Lim K.-S. S. , Clark A. , Bikos D. , and Dembek S. R. , 2014: Evaluation of and suggested improvements to the WSM6 microphysics in WRF-ARW using synthetic and observed GOES-13 imagery. Mon. Wea. Rev., 142, 36353650, doi:10.1175/MWR-D-14-00005.1.

    • Search Google Scholar
    • Export Citation
  • Han, Y., van Delst P. , Liu Q. , Weng F. , Yan B. , Treadon R. , and Derber J. , 2006: JCSDA Community Radiative Transfer Model (CRTM)—Version 1. NOAA Tech. Rep. NESDIS 122, 40 pp.

  • Hart, R. E., 2003: A cyclone phase space derived from thermal wind and thermal asymmetry. Mon. Wea. Rev., 131, 585616, doi:10.1175/1520-0493(2003)131<0585:ACPSDF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hart, R. E., Evans J. L. , and Evans C. , 2006: Synoptic composites of the extratropical transition life cycle of North Atlantic tropical cyclones: Factors determining posttransition evolution. Mon. Wea. Rev., 134, 553578, doi:10.1175/MWR3082.1.

    • Search Google Scholar
    • Export Citation
  • Hebert, P. H., and Poteat K. O. , 1975: A satellite classification technique for subtropical cyclones. NOAA Tech. Memo. NWS SR-83, 25 pp.

  • Hong, S.-Y., and Lim J.-O. J. , 2006: The WRF single-moment 6-class microphysics scheme (WSM6). J. Korean Meteor. Soc., 42, 129151.

  • Hong, S.-Y., Noh Y. , and Dudhia J. , 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 23182341, doi:10.1175/MWR3199.1.

    • Search Google Scholar
    • Export Citation
  • Iacono, M. J., Delamere J. S. , Mlawer E. J. , Shephard M. W. , Clough S. A. , and Collins W. D. , 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103, doi:10.1029/2008JD009944.

    • Search Google Scholar
    • Export Citation
  • Jankov, I., and Coauthors, 2011: An evaluation of five ARW-WRF microphysics schemes using synthetic GOES imagery for an atmospheric river event affecting the California coast. J. Hydrometeor., 12, 618633, doi:10.1175/2010JHM1282.1.

    • Search Google Scholar
    • Export Citation
  • Jarvinen, B. R., Neumann C. J. , and Davis M. A. S. , 1984: A tropical cyclone data tape for the North Atlantic basin, 1886–1983: Contents, limitations, and uses. NOAA Tech. Memo. NWS NHC-22, Coral Gables, FL, 21 pp.

  • Jimenez, P. A., Dudhia J. , Gonzalez-Rouco J. F. , Navarro J. , Montavez J. P. , and Garcia-Bustamante E. , 2012: A revised scheme for the WRF surface layer formulation. Mon. Wea. Rev., 140, 898918, doi:10.1175/MWR-D-11-00056.1.

    • Search Google Scholar
    • Export Citation
  • Jin, Y., and Coauthors, 2014: The impact of ice phase cloud parameterizations on tropical cyclone prediction. Mon. Wea. Rev., 142, 606625, doi:10.1175/MWR-D-13-00058.1.

    • Search Google Scholar
    • Export Citation
  • Jones, S. C., and Coauthors, 2003: The extratropical transition of tropical cyclones: Forecast challenges, current understanding, and future directions. Wea. Forecasting, 18, 10521092, doi:10.1175/1520-0434(2003)018<1052:TETOTC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Klein, P. M., Harr P. A. , and Elsberry R. L. , 2000: Extratropical transition of western North Pacific tropical cyclones: An overview and conceptual model of the transformation stage. Wea. Forecasting, 15, 373395, doi:10.1175/1520-0434(2000)015<0373:ETOWNP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Knaff, J. A., and Zehr R. M. , 2007: Reexamination of tropical cyclone wind–pressure relationships. Wea. Forecasting, 22, 7188, doi:10.1175/WAF965.1.

    • Search Google Scholar
    • Export Citation
  • Kossin, J. P., and Velden C. S. , 2004: A pronounced bias in tropical cyclone minimum sea level pressure estimation based on the Dvorak technique. Mon. Wea. Rev., 132, 165173, doi:10.1175/1520-0493(2004)132<0165:APBITC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Landsea, C. W., and Franklin J. L. , 2013: Atlantic hurricane database uncertainty and presentation of a new database format. Mon. Wea. Rev., 141, 35763592, doi:10.1175/MWR-D-12-00254.1.

    • Search Google Scholar
    • Export Citation
  • Lim, K.-S. S., and Hong S.-Y. , 2010: Development of an effective double-moment cloud microphysics scheme with prognostic cloud condensation nuclei (CCN) for weather and climate models. Mon. Wea. Rev., 138, 15871612, doi:10.1175/2009MWR2968.1.

    • Search Google Scholar
    • Export Citation
  • Milbrandt, J. A., and Yau M. K. , 2005: A multimoment bulk microphysics parameterization. Part II: A proposed three-moment closure and scheme description. J. Atmos. Sci., 62, 30653081, doi:10.1175/JAS3535.1.

    • Search Google Scholar
    • Export Citation
  • Miller, D. W., and Lander M. A. , 1997: Intensity estimation of tropical cyclones during extratropical transition. JTWC Rep. JTWC/SATOPS/TN-97/002, 9 pp.

  • Morrison, H., Thompson G. , and Tatarskii V. , 2009: Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes. Mon. Wea. Rev., 137, 9911007, doi:10.1175/2008MWR2556.1.

    • Search Google Scholar
    • Export Citation
  • Olander, T. L., and Velden C. S. , 2007: The advanced Dvorak technique: Continued development of an objective scheme to estimate tropical cyclone intensity using geostationary infrared satellite imagery. Wea. Forecasting, 22, 287298, doi:10.1175/WAF975.1.

    • Search Google Scholar
    • Export Citation
  • Olander, T. L., and Velden C. S. , 2013: ADT—Advanced Dvorak technique users’ guide (McIDAS version 8.1.4). Cooperative Institute for Meteorological Satellite Studies and Space Science and Engineering Center, University of Wisconsin–Madison, 70 pp. [Available online at http://tropic.ssec.wisc.edu/misc/adt/guides/ADTV8.1.4_Guide.pdf.]

  • Otkin, J. A., and Greenwald T. J. , 2008: Comparison of WRF model-simulated and MODIS- derived cloud data. Mon. Wea. Rev., 136, 19571970, doi:10.1175/2007MWR2293.1.

    • Search Google Scholar
    • Export Citation
  • Otkin, J. A., Greenwald T. J. , Sieglaff J. , and Huang H.-L. , 2009: Validation of a large-scale simulated brightness temperature dataset using SEVIRI satellite observations. J. Appl. Meteor. Climatol., 48, 16131626, doi:10.1175/2009JAMC2142.1.

    • Search Google Scholar
    • Export Citation
  • Pasch, R. J., and Avila L. A. , 1999: Atlantic hurricane season of 1996. Mon. Wea. Rev., 127, 581610, doi:10.1175/1520-0493(1999)127<0581:AHSO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Seemann, S. W., Borbas E. E. , Knuteson R. O. , Stephenson G. R. , and Huang H.-L. , 2008: Development of a global infrared land surface emissivity database for application to clear sky sounding retrievals from multispectral satellite radiance measurements. J. Appl. Meteor. Climatol., 47, 108123, doi:10.1175/2007JAMC1590.1.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., 2004: Evaluating mesoscale NWP models utilizing kinetic energy spectra. Mon. Wea. Rev., 132, 30193032, doi:10.1175/MWR2830.1.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., and Coauthors, 2008: A description of the advanced Research WRF version 3. NCAR Tech. Note NCAR/TN–475+STR, 125 pp. [Available online at http://www2.mmm.ucar.edu/wrf/users/docs/arw_v3.pdf.]

  • Stewart, S. R., 2013: Tropical cyclone report: Hurricane Leslie (AL122012). NHC, 19 pp. [Available online at http://www.nhc.noaa.gov/data/tcr/AL122012_Leslie.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, 50955115, doi:10.1175/2008MWR2387.1.

    • Search Google Scholar
    • Export Citation
  • Van Weverberg, K., and Coauthors, 2013: The role of cloud microphysics parameterization in the simulation of mesoscale convective system clouds and precipitation in the tropical western Pacific. J. Atmos. Sci., 70, 11041128, doi:10.1175/JAS-D-12-0104.1.

    • Search Google Scholar
    • Export Citation
  • Velden, C., and Coauthors, 2006: The Dvorak tropical cyclone intensity estimation technique: A satellite-based method that has endured for over 30 years. Bull. Amer. Meteor. Soc., 87, 11951210, doi:10.1175/BAMS-87-9-1195.

    • Search Google Scholar
    • Export Citation
  • Zhu, T., and Zhang D.-L. , 2006: Numerical simulation of Hurricane Bonnie (1998). Part II: Sensitivity to varying cloud microphysical processes. J. Atmos. Sci., 63, 109127, doi:10.1175/JAS3599.1.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 296 129 13
PDF Downloads 176 67 18