Analysis of Debris Signature Characteristics and Evolution in the 24 May 2016 Dodge City, Kansas, Tornadoes

Zachary B. Wienhoff School of Meteorology, University of Oklahoma, Norman, Oklahoma

Search for other papers by Zachary B. Wienhoff in
Current site
Google Scholar
PubMed
Close
,
Howard B. Bluestein School of Meteorology, University of Oklahoma, Norman, Oklahoma

Search for other papers by Howard B. Bluestein in
Current site
Google Scholar
PubMed
Close
,
Dylan W. Reif School of Meteorology, University of Oklahoma, Norman, Oklahoma

Search for other papers by Dylan W. Reif in
Current site
Google Scholar
PubMed
Close
,
Roger M. Wakimoto Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, Los Angeles, California

Search for other papers by Roger M. Wakimoto in
Current site
Google Scholar
PubMed
Close
,
Louis J. Wicker NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma

Search for other papers by Louis J. Wicker in
Current site
Google Scholar
PubMed
Close
, and
James M. Kurdzo Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, Massachusetts

Search for other papers by James M. Kurdzo in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

On 24 May 2016, a supercell that produced 13 tornadoes near Dodge City, Kansas, was documented by a rapid-scanning, X-band, polarimetric, Doppler radar (RaXPol). The anomalous nature of this storm, particularly the significant deviations in storm motion from the mean flow and number of tornadoes produced, is examined and discussed. RaXPol observed nine tornadoes with peak radar-derived intensities (ΔVmax) and durations ranging from weak (~60 m s−1) and short lived (<30 s) to intense (>150 m s−1) and long lived (>25 min). This case builds on previous studies of tornado debris signature (TDS) evolution with continuous near-surface sampling of multiple strong tornadoes. The TDS sizes increased as the tornadoes intensified but lacked direct correspondence to tornado intensity otherwise. The most significant growth of the TDS in both cases was linked to two substantial rear-flank-downdraft surges and subsequent debris ejections, resulting in growth of the TDSs to more than 3 times their original sizes. The TDS was also observed to continue its growth as the tornadoes decayed and lofted debris fell back to the surface. The TDS size and polarimetric composition were also found to correspond closely to the underlying surface cover, which resulted in reductions in ZDR in wheat fields and growth of the TDS in terraced dirt fields as a result of ground scouring. TDS growth with respect to tornado vortex tilt is also discussed.

Current affiliation: Wind Engineering Research Laboratory, Department of Civil and Environmental Engineering, University of Illinois at Urbana–Champaign, Urbana, Illinois.

© 2020 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: Zachary B. Wienhoff, wienhof1@illinois.edu

Abstract

On 24 May 2016, a supercell that produced 13 tornadoes near Dodge City, Kansas, was documented by a rapid-scanning, X-band, polarimetric, Doppler radar (RaXPol). The anomalous nature of this storm, particularly the significant deviations in storm motion from the mean flow and number of tornadoes produced, is examined and discussed. RaXPol observed nine tornadoes with peak radar-derived intensities (ΔVmax) and durations ranging from weak (~60 m s−1) and short lived (<30 s) to intense (>150 m s−1) and long lived (>25 min). This case builds on previous studies of tornado debris signature (TDS) evolution with continuous near-surface sampling of multiple strong tornadoes. The TDS sizes increased as the tornadoes intensified but lacked direct correspondence to tornado intensity otherwise. The most significant growth of the TDS in both cases was linked to two substantial rear-flank-downdraft surges and subsequent debris ejections, resulting in growth of the TDSs to more than 3 times their original sizes. The TDS was also observed to continue its growth as the tornadoes decayed and lofted debris fell back to the surface. The TDS size and polarimetric composition were also found to correspond closely to the underlying surface cover, which resulted in reductions in ZDR in wheat fields and growth of the TDS in terraced dirt fields as a result of ground scouring. TDS growth with respect to tornado vortex tilt is also discussed.

Current affiliation: Wind Engineering Research Laboratory, Department of Civil and Environmental Engineering, University of Illinois at Urbana–Champaign, Urbana, Illinois.

© 2020 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: Zachary B. Wienhoff, wienhof1@illinois.edu
Save
  • Adlerman, E. J., K. K. Droegemeier, and R. Davies-Jones, 1999: A numerical simulation of cyclic mesocyclogenesis. J. Atmos. Sci., 56, 20452069, https://doi.org/10.1175/1520-0469(1999)056<2045:ANSOCM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Alexander, C. R., and J. Wurman, 2005: The 30 May 1998 Spencer, South Dakota, storm. Part I: The structural evolution and environment of the tornadoes. Mon. Wea. Rev., 133, 7297, https://doi.org/10.1175/MWR-2855.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Alexander, C. R., and J. M. Wurman, 2008: Updated mobile radar climatology of supercell tornado structures and dynamics. 24th Conf. on Severe Local Storms, Savannah, GA, Amer. Meteor. Soc., 19.4, https://ams.confex.com/ams/24SLS/techprogram/paper_141821.htm.

  • Barnes, S. L., 1964: A technique for maximizing details in numerical weather map analysis. J. Appl. Meteor. Climatol., 3, 396409, https://doi.org/10.1175/1520-0450(1964)003<0396:ATFMDI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Biggerstaff, M. I., and Coauthors, 2005: The Shared Mobile Atmospheric Research and Teaching radar: A collaboration to enhance research and teaching. Bull. Amer. Meteor. Soc., 86, 12631274, https://doi.org/10.1175/BAMS-86-9-1263.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bluestein, H. B., 2013: Severe Convective Storms and Tornadoes. Springer, 456 pp.

  • Bluestein, H. B., and A. L. Pazmany, 2000: Observations of tornadoes and other convective phenomena with a mobile, 3-mm wavelength, Doppler radar: The spring 1999 field experiment. Bull. Amer. Meteor. Soc., 81, 29392952, https://doi.org/10.1175/1520-0477(2000)081<2939:OOTAOC>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bluestein, H. B., A. L. Pazmany, J. C. Galloway, and R. E. McIntosh, 1995: Studies of the substructure of severe convective storms using a mobile 3-mm-wavelength Doppler radar. Bull. Amer. Meteor., 76, 21552170, https://doi.org/10.1175/1520-0477(1995)076<2155:SOTSOS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bluestein, H. B., M. M. French, R. L. Tanamachi, S. Frasier, K. Hardwick, F. Junyent, and A. L. Pazmany, 2007: Close-range observations of tornadoes in supercells made with a dual-polarization, X-band, mobile Doppler radar. Mon. Wea. Rev., 135, 15221543, https://doi.org/10.1175/MWR3349.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bluestein, H. B., M. M. French, I. PopStefanija, R. T. Bluth, and J. B. Knorr, 2010: A mobile, phased-array Doppler radar for the study of severe convective storms: The MWR-05XP. Bull. Amer. Meteor. Soc., 91, 579600, https://doi.org/10.1175/2009BAMS2914.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bluestein, H. B., K. J. Thiem, J. C. Snyder, and J. B. Houser, 2018: The multiple-vortex structure of the El Reno, Oklahoma, tornado on 31 May 2013. Mon. Wea. Rev., 146, 24832502, https://doi.org/10.1175/MWR-D-18-0073.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bluestein, H. B., K. J. Thiem, J. C. Snyder, and J. B. Houser, 2019: Tornadogenesis and early tornado evolution in the El Reno, Oklahoma, supercell on 31 May 2013. Mon. Wea. Rev., 147, 20452066, https://doi.org/10.1175/MWR-D-18-0338.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bodine, D. J., R. D. Palmer, and G. Zhang, 2014: Dual-wavelength polarimetric radar analyses of tornadic debris signatures. J. Appl. Meteor. Climatol., 53, 242261, https://doi.org/10.1175/JAMC-D-13-0189.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bodine, D. J., T. Maruyama, R. D. Palmer, C. J. Fulton, H. B. Bluestein, and D. C. Lewellen, 2016: Sensitivity of tornado dynamics to soil debris loading. J. Atmos. Sci., 73, 27832801, https://doi.org/10.1175/JAS-D-15-0188.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Burgess, D. W., 1982: Mesocyclone evolution statistics. Preprints, 12th Conf. on Severe Local Storms, San Antonio, TX, Amer. Meteor. Soc., 422–424.

  • French, M. M., H. B. Bluestein, I. PopStefanija, C. A. Baldi, and R. T. Bluth, 2013: Reexamining the vertical development of tornadic vortex signatures in supercells. Mon. Wea. Rev., 141, 45764601, https://doi.org/10.1175/MWR-D-12-00315.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • French, M. M., H. B. Bluestein, I. PopStefanija, C. A. Baldi, and R. T. Bluth, 2014: Mobile, phased-array, Doppler radar observations of tornadoes at X band. Mon. Wea. Rev., 142, 10101036, https://doi.org/10.1175/MWR-D-13-00101.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fujiwara, S., 1943: Report of thunderstorm observation project. Japan Meteorological Agency Rep., 248 pp.

  • Griffin, C. B., D. J. Bodine, and R. D. Palmer, 2017: Kinematic and polarimetric radar observations of the 10 May 2010, Moore–Choctaw, Oklahoma, tornadic debris signature. Mon. Wea. Rev., 145, 27232741, https://doi.org/10.1175/MWR-D-16-0344.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffin, C. B., D. J. Bodine, J. M. Kurdzo, A. Mahre, and R. D. Palmer, 2019: High-temporal resolution observations of the 27 May 2015 Canadian, Texas, tornado using the atmospheric imaging radar. Mon. Wea. Rev., 147, 873891, https://doi.org/10.1175/MWR-D-18-0297.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffin, C. B., D. J. Bodine, and R. Palmer, 2020: Polarimetric radar observations of simultaneous tornadoes on 10 May 2010 near Norman, Oklahoma. Mon. Wea. Rev., 148, 477497, https://doi.org/10.1175/MWR-D-19-0156.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Houser, J. B., 2013: Observations of supercell tornado evolution using a mobile, rapid-scan, X-band radar. Ph.D. thesis, University of Oklahoma, 264 pp. https://shareok.org/handle/11244/319359.

  • Houser, J. L., H. B. Bluestein, and J. C. Snyder, 2015: Rapid-scan, polarimetric, Doppler radar observations of tornadogenesis and tornado dissipation in a tornadic supercell: The “El Reno, Oklahoma” storm of 24 May 2011. Mon. Wea. Rev., 143, 26852710, https://doi.org/10.1175/MWR-D-14-00253.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Houser, J. L., H. B. Bluestein, and J. C. Snyder, 2016: A finescale radar examination of the tornadic debris signature and weak-echo reflectivity band associated with a large, violent tornado. Mon. Wea. Rev., 144, 41014130, https://doi.org/10.1175/MWR-D-15-0408.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Isom, B., and Coauthors, 2013: The Atmospheric Imaging Radar: Simultaneous volumetric observations using a phased array weather radar. J. Atmos. Oceanic Technol., 30, 655675, https://doi.org/10.1175/JTECH-D-12-00063.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koch, S. E., M. desJardins, and P. J. Kocin, 1983: An interactive Barnes objective map analysis scheme for use with satellite and conventional data. J. Climate Appl. Meteor., 22, 14871503, https://doi.org/10.1175/1520-0450(1983)022<1487:AIBOMA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kosiba, K., J. Wurman, Y. Richardson, P. Markowski, P. Robinson, and J. Marquis, 2013: Genesis of the Goshen County, Wyoming, Tornado on 5 June 2009 during VORTEX2. Mon. Wea. Rev., 141, 11571181, https://doi.org/10.1175/MWR-D-12-00056.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumjian, M. R., and A. V. Ryzhkov, 2008: Polarimetric signatures in supercell thunderstorms. J. Appl. Meteor. Climatol., 47, 19401961, https://doi.org/10.1175/2007JAMC1874.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kurdzo, J. M., D. J. Bodine, B. L. Cheong, and R. D. Palmer, 2015: High-temporal resolution polarimetric X-band Doppler radar observations of the 20 May 2013 Moore, Oklahoma, tornado. Mon. Wea. Rev., 143, 27112735, https://doi.org/10.1175/MWR-D-14-00357.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kurdzo, J. M., and Coauthors, 2017: Observations of severe local storms and tornadoes with the atmospheric imaging radar. Bull. Amer. Meteor. Soc., 98, 915935, https://doi.org/10.1175/BAMS-D-15-00266.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lewellen, D. C., B. Gong, and W. S. Lewellen, 2008: Effects of finescale debris on near-surface tornado dynamics. J. Atmos. Sci., 65, 32473262, https://doi.org/10.1175/2008JAS2686.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mahre, A., J. M. Kurdzo, D. J. Bodine, C. B. Griffin, R. D. Palmer, and T.-Y. Yu, 2018: Analysis of the 16 May 2015 Tipton, Oklahoma, EF-3 tornado at high spatiotemporal resolution using the atmospheric imaging radar. Mon. Wea. Rev., 146, 21032124, https://doi.org/10.1175/MWR-D-17-0256.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Majcen, M., P. Markowski, Y. Richardson, D. Dowell, and J. Wurman, 2008: Multipass objective analyses of Doppler radar data. J. Atmos. Oceanic Technol., 25, 18451858, https://doi.org/10.1175/2008JTECHA1089.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oye, R., C. Mueller, and S. Smith, 1995: Software for radar translation, visualization, editing, and interpolation. Preprints, 27th Conf. on Radar Meteorology, Vail, CO, Amer. Meteor. Soc., 359–363.

  • Pauley, P., and X. Wu, 1990: The theoretical, discrete, and actual response of the Barnes objective analysis scheme for one- and two-dimensional fields. Mon. Wea. Rev., 118, 11451164, https://doi.org/10.1175/1520-0493(1990)118<1145:TTDAAR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pazmany, A. L., J. B. Mead, H. B. Bluestein, J. C. Snyder, and J. B. Houser, 2013: A mobile rapid-scanning X-band polarimetric (RaXPol) Doppler radar system. J. Atmos. Oceanic Technol., 30, 13981413, https://doi.org/10.1175/JTECH-D-12-00166.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rotunno, R., and J. B. Klemp, 1982: The influence of the shear-induced pressure gradient on thunderstorm motion. Mon. Wea. Rev., 110, 136151, https://doi.org/10.1175/1520-0493(1982)110<0136:TIOTSI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rotunno, R., and J. Klemp, 1985: On the rotation and propagation of simulated supercell thunderstorms. J. Atmos. Sci., 42, 271292, https://doi.org/10.1175/1520-0469(1985)042<0271:OTRAPO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., D. S. Zrnić, J. C. Hubbert, V. N. Bringi, J. Vivekanandan, and E. A. Brandes, 2002: Polarimetric radar observations and interpretation of co-cross-polar correlation coefficients. J. Atmos. Oceanic Technol., 19, 340354, https://doi.org/10.1175/1520-0426-19.3.340.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., T. J. Schuur, D. W. Burgess, and D. S. Zrnić, 2005: Polarimetric tornado detection. J. Appl. Meteor., 44, 557570, https://doi.org/10.1175/JAM2235.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Salazar-Cerreno, J. L., and Coauthors, 2017: Development of a mobile C-band Polarimetric Atmospheric Imaging Radar (PAIR). Special Symp. on Meteorological Observations and Instrumentation, Seattle, WA, Amer. Meteor. Soc., 1B.1, https://ams.confex.com/ams/97Annual/webprogram/Paper308655.html.

  • Schultz, C. J., W. A. Petersen, and L. D. Carey, 2012: Dual-polarization tornadic debris signatures. Part I: Examples and utility in an operational setting. Electron. J. Oper. Meteor., 13, 120137.

    • Search Google Scholar
    • Export Citation
  • Shapiro, A., K. M. Willingham, and C. K. Potvin, 2010: Spatially variable advection correction of radar data. Part I: Theoretical considerations. J. Atmos. Sci., 67, 34453456, https://doi.org/10.1175/2010JAS3465.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Snyder, J. C., and H. B. Bluestein, 2014: Some considerations for the use of high-resolution mobile radar data in tornado intensity determination. Wea. Forecasting, 29, 799827, https://doi.org/10.1175/WAF-D-14-00026.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Snyder, J. C., H. B. Bluestein, G. Zhang, and S. J. Frasier, 2010: Attenuation correction and hydrometeor classification of high-resolution, X-band, dual-polarized mobile radar measurements in severe convective storms. J. Atmos. Oceanic Technol., 27, 19792001, https://doi.org/10.1175/2010JTECHA1356.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Snyder, J. C., H. B. Bluestein, V. Venkatesh, and S. J. Frasier, 2013: Observations of polarimetric signatures in supercells by an X-band mobile Doppler radar. Mon. Wea. Rev., 141, 329, https://doi.org/10.1175/MWR-D-12-00068.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tanamachi, R. L., H. B. Bluestein, J. B. Houser, S. J. Frasier, and K. M. Hardwick, 2012: Mobile, X-band, polarimetric Doppler radar observations of the 4 May 2007 Greensburg, Kansas, tornadic supercell. Mon. Wea. Rev., 140, 21032125, https://doi.org/10.1175/MWR-D-11-00142.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tanamachi, R. L., H. B. Bluestein, M. Xue, W.-C. Lee, K. A. Orzel, S. J. Frasier, and R. M. Wakimoto, 2013: Near-surface vortex structure in a tornado and in a sub-tornado-strength convective-storm vortex observed by a mobile, W-band radar during VORTEX2. Mon. Wea. Rev., 141, 36613690, https://doi.org/10.1175/MWR-D-12-00331.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thompson, R. L., R. Edwards, and J. A. Hart, 2002: Evaluation and interpretation of the supercell composite and significant tornado parameters at the Storm Prediction Center. Preprints, 21st Conf. on Severe Local Storms, San Antonio, TX, Amer. Meteor. Soc., J3.2, https://ams.confex.com/ams/SLS_WAF_NWP/techprogram/paper_46942.htm.

  • 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
  • Torres, S., and C. Curtis, 2006: Initial implementation of super-resolution data on the NEXRAD network. Preprints, Third European Conf. on Radar Meteorology and Hydrology (ERAD), Barcelona, Spain, Amer. Meteor. Soc., 5B.10, https://ams.confex.com/ams/pdfpapers/116240.pdf.

  • Umeyama, A., B. L. Cheong, S. Torres, and D. Bodine, 2018: Orientation analysis of simulated tornadic debris. J. Atmos. Oceanic Technol., 35, 9931010, https://doi.org/10.1175/JTECH-D-17-0140.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Van Den Broeke, M. S., 2015: Polarimetric tornadic debris signature variability and debris fallout signatures. J. Appl. Meteor. Climatol., 54, 23892405, https://doi.org/10.1175/JAMC-D-15-0077.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Van Den Broeke, M. S., and S. T. Jauernic, 2014: Spatial and temporal characteristics of polarimetric tornadic debris signatures. J. Appl. Meteor. Climatol., 53, 22172231, https://doi.org/10.1175/JAMC-D-14-0094.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wakimoto, R. M., Z. Wienhoff, H. B. Bluestein, and D. Reif, 2018: The Dodge City tornadoes on 24 May 2016: Damage survey, photogrammetric analysis combined with mobile polarimetric radar data. Mon. Wea. Rev., 146, 37353771, https://doi.org/10.1175/MWR-D-18-0125.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wakimoto, R. M., Z. Wienhoff, H. B. Bluestein, D. J. Bodine, and J. M. Kurdzo, 2020: Mobile radar observations of the evolving debris field compared with a damage survey of the Shawnee, Oklahoma, tornado of 19 May 2013. Mon. Wea. Rev., 148, 17791803, https://doi.org/10.1175/MWR-D-19-0215.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wienhoff, Z. B., and Coauthors, 2018: Applications of a spatially variable advection correction technique for temporal correction of dual-Doppler analyses of tornadic supercells. Mon. Wea. Rev., 146, 29492971, https://doi.org/10.1175/MWR-D-17-0360.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wurman, J., and M. Randall, 2001: An inexpensive, mobile, rapid-scan radar. Preprints, 30th Conf. on Radar Meteorology, Munich, Germany, Amer. Meteor. Soc., P3.4, https://ams.confex.com/ams/30radar/techprogram/paper_21577.htm.

  • Wurman, J., J. Straka, E. Rasmussen, M. Randall, and A. Zahrai, 1997: Design and deployment of a portable, pencil-beam, pulsed, 3-cm Doppler radar. J. Atmos. Oceanic Technol., 14, 15021512, https://doi.org/10.1175/1520-0426(1997)014<1502:DADOAP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 498 0 0
Full Text Views 2515 1619 206
PDF Downloads 885 208 37