• Adams-Selin, R. D., and R. H. Johnson, 2010: Mesoscale surface pressure and temperature features associated with bow echoes. Mon. Wea. Rev., 138, 212227, https://doi.org/10.1175/2009MWR2892.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Adams-Selin, R. D., and R. H. Johnson, 2013: Examination of gravity waves associated with the 13 March 2003 bow echo. Mon. Wea. Rev., 141, 37353756, https://doi.org/10.1175/MWR-D-12-00343.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ashley, W. S., and T. L. Mote, 2005: Derecho hazards in the United States. Bull. Amer. Meteor. Soc., 86, 15771592, https://doi.org/10.1175/BAMS-86-11-1577.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Atkins, N. T., C. S. Bouchard, R. W. Przybylinski, R. J. Trapp, and G. Schmocker, 2005: Damaging surface wind mechanism within the 10 June 2003 Saint Louis bow echo during BAMEX. Mon. Wea. Rev., 133, 22752296, https://doi.org/10.1175/MWR2973.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bentley, M. L., and T. L. Mote, 1998: A climatology of derecho-producing mesoscale convective systems in the central and eastern United States, 1986–95. Part I: Temporal and spatial distribution. Bull. Amer. Meteor. Soc., 79, 25272540, https://doi.org/10.1175/1520-0477(1998)079<2527:ACODPM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bernardet, L. R., and W. R. Cotton, 1998: Multiscale evolution of a derecho-producing mesoscale convective system. Mon. Wea. Rev., 126, 29913015, https://doi.org/10.1175/1520-0493(1998)126<2991:MEOADP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bonner, W. D., 1968: Climatology of the low-level jet. Mon. Wea. Rev., 96, 833850, https://doi.org/10.1175/1520-0493(1968)096<0833:COTLLJ>2.0.CO;2.

  • Bothwell, P. D., J. A. Hart, and R. L. Thompson, 2002: An integrated three-dimensional objective analysis scheme in use at the Storm Prediction Center. Preprints, 21st Conf. on Severe Local Storms, San Antonio, TX, Amer. Meteor. Soc., JP3.1, https://ams.confex.com/ams/SLS_WAF_NWP/techprogram/paper_47482.htm.

    • Crossref
    • Export Citation
  • Brooks, H. E., C. A. Doswell III, and J. Cooper, 1994: On the environments of tornadic and nontornadic mesocyclones. Wea. Forecasting, 9, 606618, https://doi.org/10.1175/1520-0434(1994)009<0606:OTEOTA>2.0.CO;2.

    • Crossref
    • 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.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clark, A. J., W. A. Gallus, and T. C. Chen, 2007: Comparison of the diurnal precipitation cycle in convective-resolving and non-convection-resolving mesoscale models. Mon. Wea. Rev., 135, 34563473, https://doi.org/10.1175/MWR3467.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cohen, A. E., M. C. Coniglio, S. F. Corfidi, and S. J. Corfidi, 2007: Discrimination of mesoscale convective system environments using sounding observations. Wea. Forecasting, 22, 10451062, https://doi.org/10.1175/WAF1040.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cohen, A. E., S. M. Cavallo, M. C. Coniglio, and H. E. Brooks, 2015: A review of planetary boundary layer parameterization schemes and their sensitivity in simulating Southeastern U.S. cold season severe weather environments. Wea. Forecasting, 30, 591612, https://doi.org/10.1175/WAF-D-14-00105.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coniglio, M. C., 2012: Verification of RUC 0–1-h forecasts and SPC mesoscale analyses using VORTEX2 soundings. Wea. Forecasting, 27, 667683, https://doi.org/10.1175/WAF-D-11-00096.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coniglio, M. C., D. J. Stensrud, and M. B. Richman, 2004: An observational study of derecho-producing convective systems. Wea. Forecasting, 19, 320337, https://doi.org/10.1175/1520-0434(2004)019<0320:AOSODC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coniglio, M. C., S. F. Corfidi, and J. S. Kain, 2012: Views on applying RKW theory: An illustration using the 8 May 2009 derecho-producing convective system. Mon. Wea. Rev., 140, 10231043, https://doi.org/10.1175/MWR-D-11-00026.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davis, C. A., K. W. Manning, R. E. Carbone, S. B. Trier, and J. D. Tuttle, 2003: Coherence of warm-season continental rainfall in numerical weather prediction models. Mon. Wea. Rev., 131, 26672679, https://doi.org/10.1175/1520-0493(2003)131<2667:COWCRI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davis, C. A., and Coauthors, 2004: The Bow Echo and MCV Experiment: Observations and opportunities. Bull. Amer. Meteor. Soc., 85, 10751094, https://doi.org/10.1175/BAMS-85-8-1075.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doswell, C. A., III, and J. S. Evans, 2003: Proximity sounding analysis for derechos and supercells: An assessment of similarities and differences. Atmos. Res., 67–68, 117133, https://doi.org/10.1016/S0169-8095(03)00047-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doswell, C. A., III, H. E. Brooks, and M. P. Kay, 2005: Climatological estimates of daily local nontornadic severe thunderstorm probability for the United States. Wea. Forecasting, 20, 577595, https://doi.org/10.1175/WAF866.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Edwards, R., J. T. Allen, and G. W. Carbin, 2018: Reliability and climatological impacts of convective wind estimations. J. Appl. Meteor. Climatol., 57, 18251845, https://doi.org/10.1175/JAMC-D-17-0306.1.

    • Search Google Scholar
    • Export Citation
  • Evans, J. S., and C. A. Doswell III, 2001: Examination of derecho environments using proximity soundings. Wea. Forecasting, 16, 329342, https://doi.org/10.1175/1520-0434(2001)016<0329:EODEUP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • French, A. J., and M. D. Parker, 2012: Observations of mergers between squall lines and isolated supercell thunderstorms. Wea. Forecasting, 27, 255278, https://doi.org/10.1175/WAF-D-11-00058.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • French, A. J., and M. D. Parker, 2014: Numerical simulations of bow echo formation following a squall line–supercell merger. Mon. Wea. Rev., 142, 47914822, https://doi.org/10.1175/MWR-D-13-00356.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fujita, T. T., 1978: Manual of downburst identification for project NIMROD. Satellite and Mesometeorology Research Paper 156, 104 pp., http://hdl.handle.net/10605/261961.

    • Crossref
    • Export Citation
  • Fujita, T. T., and R. M. Wakimoto, 1981: Five scales of airflow associated with a series of downbursts of 16 July 1980. Mon. Wea. Rev., 109, 14381456, https://doi.org/10.1175/1520-0493(1981)109<1438:FSOAAW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Gallus, W. A., Jr., N. A. Snook, and E. V. Johnson, 2008: Spring and summer severe weather reports over the Midwest as a function of convective mode: A preliminary study. Wea. Forecasting, 23, 101113, https://doi.org/10.1175/2007WAF2006120.1.

    • Search Google Scholar
    • Export Citation
  • Gebauer, J. G., A. Shapiro, E. Fedorovich, and P. Klein, 2018: Convection initiation caused by heterogeneous low-level jets over the Great Plains. Mon. Wea. Rev., 146, 26152637, https://doi.org/10.1175/MWR-D-18-0002.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guastini, C. T., and L. F. Bosart, 2016: Analysis of a progressive derecho climatology and associated formation environments. Mon. Wea. Rev., 144, 13631382, https://doi.org/10.1175/MWR-D-15-0256.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hampshire, N. L., R. M. Mosier, T. M. Ryan, and D. E. Cavanaugh, 2017: Relationship of low-level instability and tornado damage rating based on observed soundings. J. Oper. Meteor., 6, 112, https://doi.org/10.15191/nwajom.2018.0601.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Heidke, P., 1926: Calculation of the success and goodness of strong wind forecasts in the storm warning service. Geogr. Ann. Stockholm, 8, 301349.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hiris, Z. A., and W. A. Gallus Jr., 2021: On the relationship of cold pool and bulk shear magnitudes on upscale convective growth in the Great Plains of the United States. Atmosphere, 12, 1019, https://doi.org/10.3390/atmos12081019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hitchcock, S. M., R. S. Schumacher, G. R. Herman, M. C. Coniglio, M. D. Parker, and C. L. Ziegler, 2019: Evolution of pre- and postconvective environment profiles from mesoscale convective systems during PECAN. Mon. Wea. Rev., 147, 23292354, https://doi.org/10.1175/MWR-D-18-0231.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • James, R. P., P. M. Markowski, and J. M. Fritsch, 2006: Bow echo sensitivity to ambient moisture and cold pool strength. Mon. Wea. Rev., 134, 950964, https://doi.org/10.1175/MWR3109.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Johns, R. H., 1993: Meteorological conditions associated with bow echo development in convective storms. Wea. Forecasting, 8, 294299, https://doi.org/10.1175/1520-0434(1993)008<0294:MCAWBE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Johns, R. H., and W. D. Hirt, 1987: Derechos: Widespread convectively induced windstorms. Wea. Forecasting, 2, 3249, https://doi.org/10.1175/1520-0434(1987)002<0032:DWCIW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Klimowski, B. A., M. J. Bunkers, M. R. Hjelmfelt, and J. N. Covert, 2003: Severe convective windstorms over the northern high plains of the United States. Wea. Forecasting, 18, 502519, https://doi.org/10.1175/1520-0434(2003)18<502:SCWOTN>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Klimowski, B. A., M. R. Hjelmfelt, and M. J. Bunkers, 2004: Radar observation of the early evolution of bow echoes. Wea. Forecasting, 19, 727734, https://doi.org/10.1175/1520-0434(2004)019<0727:ROOTEE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuchera, E. L., and M. D. Parker, 2006: Severe convective wind environments. Wea. Forecasting, 21, 595612, https://doi.org/10.1175/WAF931.1.

  • Lawson, J., and W. A. Gallus Jr., 2016: On contrasting ensemble simulations of two Great Plains bow echoes. Wea. Forecasting, 31, 787810, https://doi.org/10.1175/WAF-D-15-0060.1.

    • Search Google Scholar
    • Export Citation
  • Mahoney, K. M., and G. M. Lackmann, 2011: The sensitivity of momentum transport and severe surface winds to environmental moisture in idealized simulations of a mesoscale convective system. Mon. Wea. Rev., 139, 13521369, https://doi.org/10.1175/2010MWR3468.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marsham, J. H., S. B. Trier, T. M. Weckwerth, and J. W. Wilson, 2011: Observations of elevated convection initiation leading to a surface based squall line during 13 June IHOP_2002. Mon. Wea. Rev., 139, 247271, https://doi.org/10.1175/2010MWR3422.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mauri, E. L., and W. A. Gallus Jr., 2021: Differences between severe and non-severe warm-season nocturnal bow echo environments. Wea. Forecasting, 36, 5374, https://doi.org/10.1175/WAF-D-20-0137.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mendenhall, W. M., and T. L. Sincich, 2007: Statistics for Engineering and the Sciences. CRC Press, 1072 pp.

    • Crossref
    • Export Citation
  • Parker, M. D., 2008: Response of simulated squall lines to low-level cooling. J. Atmos. Sci., 65, 13231341, https://doi.org/10.1175/2007JAS2507.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Parker, M. D., B. S. Borchardt, R. L. Miller, and C. L. Ziegler, 2020: Simulated evolution and severe wind production by the 25–26 June 2015 nocturnal MCS from PECAN. Mon. Wea. Rev., 148, 183209, https://doi.org/10.1175/MWR-D-19-0072.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Potvin, C. K., K. L. Elmore, and S. J. Weiss, 2010: Assessing the impacts of proximity sounding criteria on the climatology of significant tornado environments. Wea. Forecasting, 25, 921930, https://doi.org/10.1175/2010WAF2222368.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reames, L. J., 2017: Diurnal variations in severe weather forecast parameters of Rapid Update Cycle-2 tornado proximity environments. Wea. Forecasting, 32, 743761, https://doi.org/10.1175/WAF-D-16-0029.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shapiro, A., E. Fedorovich, and S. Rahimi, 2016: A unified theory for the Great Plains nocturnal low-level jet. J. Atmos. Sci., 73, 30373057, https://doi.org/10.1175/JAS-D-15-0307.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, E. N., J. G. Gebauer, P. M. Klein, E. Fedorovich, and J. A. Gibbs, 2019: The Great Plains low-level jet during PECAN: Observed and simulated characteristics. Mon. Wea. Rev., 147, 18451869, https://doi.org/10.1175/MWR-D-18-0293.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stensrud, D. J., 1996: Importance of low-level jets to climate: A review. J. Climate, 9, 16981711, https://doi.org/10.1175/1520-0442(1996)009<1698:IOLLJT>2.0.CO;2.

    • 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.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thompson, R. L., R. Edwards, and C. M. Mead, 2004: An update to the supercell composite and significant tornado parameters. 22nd Conf. on Severe Local Storms, Hyannis, MA, Amer. Meteor. Soc., P8.1, https://ams.confex.com/ams/11aram22sls/techprogram/paper_82100.htm.

    • Crossref
    • Export Citation
  • Thompson, R. L., C. M. Mead, and R. Edwards, 2007: Effective storm-relative helicity and bulk shear in supercell thunderstorm environments. Wea. Forecasting, 22, 102115, https://doi.org/10.1175/WAF969.1.

    • Crossref
    • 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.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tirone, E., W. A. Gallus Jr., S. Pal, S. Dutta, R. Maitra, J. L. Newman, and E. S. Weber, 2020: A machine learning tool to provide probabilities that thunderstorm wind damage reports are due to severe intensity winds. Severe Local Storms Symp., Boston, MA, Amer. Meteor. Soc., 364573, https://ams.confex.com/ams/2020Annual/webprogram/Paper364573.html.

    • Crossref
    • Export Citation
  • Trapp, R. J., D. M. Wheatley, N. T. Atkins, R. W. Przybylinski, and R. Wolf, 2006: Buyer beware: Some words of caution on the use of severe wind reports in postevent assessment and research. Wea. Forecasting, 21, 408415, https://doi.org/10.1175/WAF925.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Uccellini, L. W., 1980: On the role of upper tropospheric jet streaks and leeside cyclogenesis in the development of low-level jet in the Great Plains. Mon. Wea. Rev., 108, 16891696, https://doi.org/10.1175/1520-0493(1980)108<1689:OTROUT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wakimoto, R. M., H. V. Murphey, A. Nester, D. P. Jorgensen, and N. T. Atkins, 2006: High winds generated by bow echoes. Part I: Overview of the Omaha bow echo 5 July 2003 storm during BAMEX. Mon. Wea. Rev., 134, 27932812, https://doi.org/10.1175/MWR3215.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., 1992: The role of convectively generated rear-inflow jets in the evolution of long-lived mesoconvective systems. J. Atmos. Sci., 49, 18261847, https://doi.org/10.1175/1520-0469(1992)049<1826:TROCGR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., 1993: The genesis of severe, long-lived bow echoes. J. Atmos. Sci., 50, 645670, https://doi.org/10.1175/1520-0469(1993)050<0645:TGOSLL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., C. Davis, W. Wang, K. W. Manning, and J. B. Klemp, 2008: Experiences with 0–36-h explicit convective forecasts with the WRF-ARW Model. Wea. Forecasting, 23, 407437, https://doi.org/10.1175/2007WAF2007005.1.

    • Search Google Scholar
    • Export Citation
  • Weiss, S. J., A. J. Hart, and P. R. Janish, 2002: An examination of severe thunderstorm wind report climatology: 1970–1999. Preprints, 21st Conf. Severe Local Storms, San Antonio, TX, Amer. Meteor. Soc., 11B.2, https://ams.confex.com/ams/SLS_WAF_NWP/webprogram/Paper47494.html.

  • Wheatley, D. M., R. J. Trapp, and N. T. Atkins, 2006: Radar and damage analysis of severe bow echoes observed during BAMEX. Mon. Wea. Rev., 134, 791806, https://doi.org/10.1175/MWR3100.1.

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

  • Wilson, J. W., and R. D. Roberts, 2006: Summary of convective storm initiation and evolution during IHOP: Observational and modeling perspective. Mon. Wea. Rev., 134, 2347, https://doi.org/10.1175/MWR3069.1.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 164 164 8
Full Text Views 115 115 5
PDF Downloads 146 146 7

Differences in Near-Storm Parameters Useful for Forecasting Intensity of Nocturnal and Diurnal Bow Echo Winds

William A. Gallus Jr.aDepartment of Geological and Atmospheric Sciences, Iowa State University, Ames, Iowa

Search for other papers by William A. Gallus Jr. in
Current site
Google Scholar
PubMed
Close
https://orcid.org/0000-0001-7024-8341
and
Anna C. DuhachekaDepartment of Geological and Atmospheric Sciences, Iowa State University, Ames, Iowa

Search for other papers by Anna C. Duhachek in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Because bow echoes are often associated with damaging wind, accurate prediction of their severity is important. Recent work by Mauri and Gallus showed that despite increased challenges in forecasting nocturnal bows due to an incomplete understanding of how elevated convection interacts with the nocturnal stable boundary layer, several near-storm environmental parameters worked well to distinguish between bow echoes not producing severe winds (NS), those only producing low-intensity severe winds [LS; 50–55 kt (1 kt ≈ 0.51 m s−1)], and those associated with high-intensity (HS; >70 kt) severe winds. The present study performs a similar comparison for daytime warm-season bow echoes examining the same 43 SPC mesoanalysis parameters for 158 events occurring from 2010 to 2018. Although low-level shear and the meridional component of the wind discriminate well for nocturnal bow severity, they do not significantly differ in daytime bows. CAPE parameters discriminate well between daytime NS events and severe ones, but not between LS and HS, differing from nocturnal events where they discriminate between HS and the other types. The 500–850-hPa layer lapse rate works better to differentiate daytime bow severity, whereas the 500–700-hPa layer works better at night. Composite parameters work well to differentiate between all three severity types for daytime bow echoes, just as they do for nighttime ones, with the derecho composite parameter performing especially well. Heidke skill scores indicate that both individual and pairs of parameters generally are not as skillful at predicting daytime bow echo wind severity as they are at predicting nocturnal bow wind severity.

© 2022 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: William A. Gallus, wgallus@iastate.edu

Abstract

Because bow echoes are often associated with damaging wind, accurate prediction of their severity is important. Recent work by Mauri and Gallus showed that despite increased challenges in forecasting nocturnal bows due to an incomplete understanding of how elevated convection interacts with the nocturnal stable boundary layer, several near-storm environmental parameters worked well to distinguish between bow echoes not producing severe winds (NS), those only producing low-intensity severe winds [LS; 50–55 kt (1 kt ≈ 0.51 m s−1)], and those associated with high-intensity (HS; >70 kt) severe winds. The present study performs a similar comparison for daytime warm-season bow echoes examining the same 43 SPC mesoanalysis parameters for 158 events occurring from 2010 to 2018. Although low-level shear and the meridional component of the wind discriminate well for nocturnal bow severity, they do not significantly differ in daytime bows. CAPE parameters discriminate well between daytime NS events and severe ones, but not between LS and HS, differing from nocturnal events where they discriminate between HS and the other types. The 500–850-hPa layer lapse rate works better to differentiate daytime bow severity, whereas the 500–700-hPa layer works better at night. Composite parameters work well to differentiate between all three severity types for daytime bow echoes, just as they do for nighttime ones, with the derecho composite parameter performing especially well. Heidke skill scores indicate that both individual and pairs of parameters generally are not as skillful at predicting daytime bow echo wind severity as they are at predicting nocturnal bow wind severity.

© 2022 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: William A. Gallus, wgallus@iastate.edu
Save