Verification of Rapid Refresh and High-Resolution Rapid Refresh Model Variables in Tornadic Tropical Cyclones

Leland M. MacDonald aTexas A &M University, College Station, Texas

Search for other papers by Leland M. MacDonald in
Current site
Google Scholar
PubMed
Close
and
Christopher J. Nowotarski aTexas A &M University, College Station, Texas

Search for other papers by Christopher J. Nowotarski in
Current site
Google Scholar
PubMed
Close
https://orcid.org/0000-0003-4739-7810
Restricted access

Abstract

Tropical cyclone tornadoes (TCTORs) are a hazard to life and property during landfalling tropical cyclones (TCs). The threat is often spread over a wide area within the TC envelope and must be continually evaluated as the TC moves inland and dissipates. To anticipate the risk of TCTORs, forecasters may use high-resolution, rapidly updating model analyses and short-range forecasts such as the Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR), and an ingredients-based approach similar to that used for forecasting continental midlatitude tornadoes. Though RAP and HRRR errors have been identified in typical midlatitude convective environments, this study evaluates the performance of the RAP and the HRRR within the TC envelope, with particular attention given to sounding-derived parameters previously identified as useful for TCTOR forecasting. A sample of 1730 observed upper-air soundings is sourced from 13 TCs that made landfall along the U.S. coastline between 2017 and 2019. The observed soundings are paired with their corresponding model gridpoint soundings from the RAP analysis, RAP 12-h forecast, and HRRR 12-h forecast. Model errors are calculated for both the raw sounding variables of temperature, dewpoint, and wind speed, as well as for the selected sounding-derived parameters. Results show a moist bias that worsens with height across all model runs. There are also statistically significant underpredictions in stability-related parameters such as convective available potential energy (CAPE) and kinematic parameters such as vertical wind shear.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Christopher J. Nowotarski, cjnowotarski@tamu.edu

Abstract

Tropical cyclone tornadoes (TCTORs) are a hazard to life and property during landfalling tropical cyclones (TCs). The threat is often spread over a wide area within the TC envelope and must be continually evaluated as the TC moves inland and dissipates. To anticipate the risk of TCTORs, forecasters may use high-resolution, rapidly updating model analyses and short-range forecasts such as the Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR), and an ingredients-based approach similar to that used for forecasting continental midlatitude tornadoes. Though RAP and HRRR errors have been identified in typical midlatitude convective environments, this study evaluates the performance of the RAP and the HRRR within the TC envelope, with particular attention given to sounding-derived parameters previously identified as useful for TCTOR forecasting. A sample of 1730 observed upper-air soundings is sourced from 13 TCs that made landfall along the U.S. coastline between 2017 and 2019. The observed soundings are paired with their corresponding model gridpoint soundings from the RAP analysis, RAP 12-h forecast, and HRRR 12-h forecast. Model errors are calculated for both the raw sounding variables of temperature, dewpoint, and wind speed, as well as for the selected sounding-derived parameters. Results show a moist bias that worsens with height across all model runs. There are also statistically significant underpredictions in stability-related parameters such as convective available potential energy (CAPE) and kinematic parameters such as vertical wind shear.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Christopher J. Nowotarski, cjnowotarski@tamu.edu

Supplementary Materials

    • Supplemental Materials (ZIP 514 KB)
Save
  • Benjamin, S. G., and Coauthors, 2016: A North American hourly assimilation and model forecast cycle: The Rapid Refresh. Mon. Wea. Rev., 144, 16691694, https://doi.org/10.1175/MWR-D-15-0242.1.

    • Search Google Scholar
    • Export Citation
  • Blumberg, W. G., K. T. Halbert, T. A. Supinie, P. T. Marsh, R. L. Thompson, and J. A. Hart, 2017: SHARPpy: An open source sounding analysis toolkit for the atmospheric sciences. Bull. Amer. Meteor. Soc., 98, 16251636, https://doi.org/10.1175/BAMS-D-15-00309.1.

    • Search Google Scholar
    • Export Citation
  • Bunkers, M. J., B. A. Klimowski, J. W. Zeitler, R. L. Thompson, and M. L. Weisman, 2000: Predicting supercell motion using a new hodograph technique. Wea. Forecasting, 15, 6179, https://doi.org/10.1175/1520-0434(2000)015<0061:PSMUAN>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Bunkers, M. J., D. A. Barber, R. L. Thompson, R. Edwards, and J. Garner, 2014: Choosing a universal mean wind for supercell motion prediction. J. Oper. Meteor., 2, 115129, https://doi.org/10.15191/nwajom.2014.0211.

    • Search Google Scholar
    • Export Citation
  • Curtis, L., 2004: Midlevel dry intrusions as a factor in tornado outbreaks associated with landfalling tropical cyclones from the Atlantic and Gulf of Mexico. Wea. Forecasting, 19, 411427, https://doi.org/10.1175/1520-0434(2004)019<0411:MDIAAF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Davies, J. M., 2006: Hurricane and tropical cyclone tornado environments from RUC proximity soundings. 23rd Conf. on Severe Local Storms, St. Louis, MO, Amer. Meteor. Soc., P8.1, https://ams.confex.com/ams/pdfpapers/115483.pdf.

  • De Pondeca, M. S. F. V., and Coauthors, 2011: The real-time mesoscale analysis at NOAA’s National Centers for Environmental Prediction: Current status and development. Wea. Forecasting, 26, 593612, https://doi.org/10.1175/WAF-D-10-05037.1.

    • Search Google Scholar
    • Export Citation
  • Edwards, R., 2010: Tropical cyclone tornado records for the modernized NWS era. Preprints, 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., P3.1, https://ams.confex.com/ams/pdfpapers/175269.pdf.

  • Edwards, R., 2012: Tropical cyclone tornadoes: A review of knowledge in research and prediction. Electron. J. Severe Storms Meteor., 7 (6), https://ejssm.com/ojs/index.php/site/article/view/42/41.

    • Search Google Scholar
    • Export Citation
  • Edwards, R., and R. M. Mosier, 2022: Over a quarter century of TCTOR: Tropical cyclone tornadoes in the WSR-88D ERA. 30th Conf. Severe Local Storms, Santa Fe, NM, Amer. Meteor. Soc., P171, https://ams.confex.com/ams/30SLS/meetingapp.cgi/Paper/407018.

  • Edwards, R., A. R. Dean, R. L. Thompson, and B. T. Smith, 2012: Convective modes for significant severe thunderstorms in the contiguous United States. Part III: Tropical cyclone tornadoes. Wea. Forecasting, 27, 15071519, https://doi.org/10.1175/WAF-D-11-00117.1.

    • Search Google Scholar
    • Export Citation
  • Evans, C., S. J. Weiss, I. L. Jirak, A. R. Dean, and D. S. Nevius, 2018: An evaluation of paired regional/convection-allowing forecast vertical thermodynamic profiles in warm-season, thunderstorm-supporting environments. Wea. Forecasting, 33, 15471566, https://doi.org/10.1175/WAF-D-18-0124.1.

    • Search Google Scholar
    • Export Citation
  • Fovell, R. G., and A. Gallagher, 2020: Boundary layer and surface verification of the High-Resolution Rapid Refresh, version 3. Wea. Forecasting, 35, 22552278, https://doi.org/10.1175/WAF-D-20-0101.1.

    • Search Google Scholar
    • Export Citation
  • Gentry, R. C., 1983: Genesis of tornadoes associated with hurricanes. Mon. Wea. Rev., 111, 17931805, https://doi.org/10.1175/1520-0493(1983)111<1793:GOTAWH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Laflin, J. M., 2013: Verification of RAP model soundings in preconvective environments. J. Oper. Meteor., 1, 6670, https://doi.org/10.15191/nwajom.2013.0106.

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

    • Search Google Scholar
    • Export Citation
  • McCaul, E. W., Jr., 1991: Buoyancy and shear characteristics of hurricane–tornado environments. Mon. Wea. Rev., 119, 19541978, https://doi.org/10.1175/1520-0493(1991)119<1954:BASCOH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Molinari, J., and D. Vollaro, 2010: Distribution of helicity, CAPE, and shear in tropical cyclones. J. Atmos. Sci., 67, 274284, https://doi.org/10.1175/2009JAS3090.1.

    • Search Google Scholar
    • Export Citation
  • Molinari, J., D. M. Romps, D. Vollaro, and L. Nguyen, 2012: CAPE in tropical cyclones. J. Atmos. Sci., 69, 24522463, https://doi.org/10.1175/JAS-D-11-0254.1.

    • Search Google Scholar
    • Export Citation
  • NOAA/Global Systems Laboratory, 2020: Rapid Refresh (RAP). NOAA, accessed 22 April 2021, https://rapidrefresh.noaa.gov/.

  • NOAA/National Centers for Environmental Information, 2020: Rapid Refresh (RAP). NOAA, accessed 17 April 2023, https://www.ncei.noaa.gov/products/weather-climate-models/rapid-refresh-update.

  • Nowotarski, C. J., J. Spotts, R. Edwards, S. Overpeck, and G. R. Woodall, 2021: Tornadoes in Hurricane Harvey. Wea. Forecasting, 36, 15891609, https://doi.org/10.1175/WAF-D-20-0196.1.

    • Search Google Scholar
    • Export Citation
  • Paredes, M., B. A. Schenkel, R. Edwards, and M. Coniglio, 2021: Tropical cyclone outer size impacts the number and location of tornadoes. Geophys. Res. Lett., 48, e2021GL095922, https://doi.org/10.1029/2021GL095922.

    • Search Google Scholar
    • Export Citation
  • Schenkel, B. A., R. Edwards, and M. Coniglio, 2020: A climatological analysis of ambient deep-tropospheric vertical wind shear impacts upon tornadoes in tropical cyclones. Wea. Forecasting, 35, 20332059, https://doi.org/10.1175/WAF-D-19-0220.1.

    • Search Google Scholar
    • Export Citation
  • Schultz, L. A., and D. J. Cecil, 2009: Tropical cyclone tornadoes, 1950–2007. Mon. Wea. Rev., 137, 34713484, https://doi.org/10.1175/2009MWR2896.1.

    • Search Google Scholar
    • Export Citation
  • Sinnott, R. W., 1984: Virtues of the haversine. Sky Telescope, 68, 158159.

  • Smith, T. L., S. G. Benjamin, J. M. Brown, S. S. Weygandt, T. Smirnova, and B. Schwartz, 2008: Convection forecasts from the hourly updated, 3-km High Resolution Rapid Refresh (HRRR) model. 24th Conf. on Severe Local Storms, Savannah, GA, Amer. Meteor. Soc., 11.1, https://ams.confex.com/ams/24SLS/techprogram/paper_142055.htm.

  • Spratt, S. M., D. W. Sharp, P. Welsh, A. C. Sandrik, F. Alsheimer, and C. Paxton, 1997: A WSR-88D assessment of tropical cyclone outer rainband tornadoes. Wea. Forecasting, 12, 479501, https://doi.org/10.1175/1520-0434(1997)012<0479:AWAOTC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Storm Prediction Center, 2016: SPC mesoscale analysis pages. NOAA, accessed 22 April 2021, https://www.spc.noaa.gov/exper/mesoanalysis/.

  • Sueki, K., and H. Niino, 2016: Toward better assessment of tornado potential in typhoons: Significance of considering entrainment effects for CAPE. Geophys. Res. Lett., 43, 12 59712 604, https://doi.org/10.1002/2016GL070349.

    • Search Google Scholar
    • Export Citation
  • Thompson, R. L., R. Edwards, J. A. Hart, K. L. Elmore, and P. Markowski, 2003: Close proximity soundings within supercell environments obtained from the Rapid Update Cycle. Wea. Forecasting, 18, 12431261, https://doi.org/10.1175/1520-0434(2003)018<1243:CPSWSE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Thompson, R. L., B. T. Smith, J. S. Grams, A. R. Dean, and C. Broyles, 2012: Convective modes for significant severe thunderstorms in the contiguous United States. Part II: Supercell and QLCS tornado environments. Wea. Forecasting, 27, 11361154, https://doi.org/10.1175/WAF-D-11-00116.1.

    • Search Google Scholar
    • Export Citation
  • University of Wyoming, 2020: Upper air soundings. University of Wyoming, accessed 22 January 2020, http://weather.uwyo.edu/upperair/sounding.html.

  • Verbout, S. M., D. M. Schultz, L. M. Leslie, H. E. Brooks, D. J. Karoly, and K. L. Elmore, 2007: Tornado outbreaks associated with landfalling hurricanes in the North Atlantic Basin: 1954–2004. Meteor. Atmos. Phys., 97, 255271, https://doi.org/10.1007/s00703-006-0256-x.

    • Search Google Scholar
    • Export Citation
  • Wilcoxon, F., 1945: Individual comparisons by ranking methods. Biom. Bull., 1, 8083, https://doi.org/10.2307/3001968.

  • Wilks, D. S., 2011: Statistical Methods in the Atmospheric Sciences. 3rd ed. International Geophysics Series, Vol. 100, Academic Press, 704 pp.

All Time Past Year Past 30 Days
Abstract Views 337 337 9
Full Text Views 264 264 10
PDF Downloads 237 237 10