• Adams, R. J., W. F. Perger, W. I. Rose, and A. Kostinski, 1996: Measurements of the complex dielectric constant of volcanic ash from 4 to 9 GHz. J. Geophys. Res., 101, 81758185, https://doi.org/10.1029/96JB00193.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Banta, R. M., L. D. Olivier, E. T. Holloway, R. A. Kropfli, B. W. Bartram, R. E. Cupp, and M. J. Post, 1992: Smoke-column observations from two forest fires using Doppler lidar and Doppler radar. J. Appl. Meteor., 31, 13281349, https://doi.org/10.1175/1520-0450(1992)031<1328:SCOFTF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baum, T. C., L. Thompson, and K. Ghorbani, 2015: The nature of fire ash particles: Microwave material properties, dynamic behavior, and temperature correlation. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 8, 480492, https://doi.org/10.1109/JSTARS.2014.2386394.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bluestein, H. B., 1999: A history of severe-storm-intercept field programs. Wea. Forecasting, 14, 558577, https://doi.org/10.1175/1520-0434(1999)014<0558:AHOSSI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bryan, S., A. Clarke, L. Vanderkluysen, C. Groppi, S. Paine, and D. W. Bliss, 2017: Measuring water vapor and ash in volcanic eruptions with a millimeter-wave radar/imager. IEEE Trans. Geosci. Remote Sens., 55, 31773185, https://doi.org/10.1109/TGRS.2017.2663381.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cal Fire, 2019a: Incidents-Briceburg Fire. Accessed 20 March 2019, https://fire.ca.gov/incidents/2019/10/6/briceburg-fire/.

  • Cal Fire, 2019b: Incidents-Kincade Fire. Accessed 23 March 2019, https://www.fire.ca.gov/incidents/2019/10/23/kincade-fire/.

  • Cal Fire, 2019c: Incidents-Camp Fire. Accessed 1 September 20, https://www.fire.ca.gov/incidents/2018/11/8/camp-fire/.

  • Charland, A. M., and C. B. Clements, 2013: Kinematic structure of a wildland fire plume observed by Doppler lidar. J. Geophys. Res. Atmos., 118, 32003212, https://doi.org/10.1002/jgrd.50308.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clements, C. B., and A. J. Oliphant, 2014: The California State University Mobile Atmospheric Profiling System: A facility for research and education in boundary layer meteorology. Bull. Amer. Meteor. Soc., 95, 1713–1724, https://doi.org/10.1175/BAMS-D-13-00179.1.

    • Crossref
    • Export Citation
  • Clements, C. B., and et al. , 2007: Observing the dynamics of wildland grass fires: FireFlux—A field validation experiment. Bull. Amer. Meteor. Soc., 88, 13691382, https://doi.org/10.1175/BAMS-88-9-1369.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clements, C. B., and et al. , 2015: Fire weather conditions and fire–atmosphere interactions observed during low-intensity prescribed fires—RxCADRE 2012. Int. J. Wildland Fire, 25, 90101, https://doi.org/10.1071/WF14173.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clements, C. B., N. P. Lareau, D. E. Kingsmill, C. L. Bowers, C. P. Camacho, R. Bagley and B. Davis, 2018: The Rapid Deployments to Wildfires Experiment (RaDFIRE): Observations from the fire zone. Bull. Amer. Meteor. Soc., 99, 25392559, https://doi.org/10.1175/BAMS-D-17-0230.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cruz, M. G., A. L. Sullivan, J. S. Gould, N. C. Sims, A. J. Bannister, J. J. Hollis, and R. J. Hurley, 2012: Anatomy of a catastrophic wildfire: The Black Saturday Kilmore East fire in Victoria, Australia. For. Ecol. Manage., 284, 269285, https://doi.org/10.1016/j.foreco.2012.02.035.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dempsey, F., 2013: Forest fire effects on air quality in Ontario: Evaluation of several recent examples. Bull. Amer. Meteor. Soc., 94, 10591064, https://doi.org/10.1175/BAMS-D-11-00202.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fromm, M., A. Tupper, D. Rosenfeld, R. Servranckx, and R. McRae, 2006: Violent pyro-convective storm devastates Australia’s capital and pollutes the stratosphere. Geophys. Res. Lett., 33, L05815, https://doi.org/10.1029/2005GL025161.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fromm, M., R. H. D. McRae, J. J. Sharples, and G. P. Kablick III, 2012: Pyrocumulonimbus pair in Wollemi and Blue Mountains National Parks, 22 November 2006. Aust. Meteor. Oceanogr. J., 62, 117126, https://doi.org/10.22499/2.6203.001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Helmus, J. J., and S. M. Collis, 2016: The Python ARM Radar Toolkit (Py-ART), a library for working with weather radar data in the Python programming language. J. Open Res. Software, 4, e25, https://doi.org/10.5334/jors.119.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jones, T. A., and S. A. Christopher, 2009: Injection heights of biomass burning debris estimated from WSR-88D radar observations. IEEE Trans. Geosci. Remote Sens., 47, 25992605, https://doi.org/10.1109/TGRS.2009.2014225.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jones, T. A., and S. A. Christopher, 2010: Satellite and radar remote sensing of southern plains grass fires: A case study. J. Appl. Meteor. Climatol., 49, 21332146, https://doi.org/10.1175/2010JAMC2472.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jones, T. A., S. A. Christopher, and W. Petersen, 2009: Dual-polarization radar characteristics of an apartment fire. J. Atmos. Oceanic Technol., 26, 22572269, https://doi.org/10.1175/2009JTECHA1290.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koo, E., P. J. Pagni, D. R. Weise, and J. P. Woycheese, 2010: Firebrands and spotting ignition in large-scale fires. Int. J. Wildland Fire, 19, 818843, https://doi.org/10.1071/WF07119.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lang, T. J., S. A. Rutledge, B. Dolan, P. Krehbiel, W. Rison, and D. T. Lindsey, 2014: Lightning in wildfire smoke plumes observed in Colorado during summer 2012. Mon. Wea. Rev., 142, 489507, https://doi.org/10.1175/MWR-D-13-00184.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lareau, N. P., and C. B. Clements, 2015: Cold smoke: Smoke-induced density currents cause unexpected smoke transport near large wildfires. Atmos. Chem. Phys.,15, 11 513–11 520, https://doi.org/10.5194/acp-15-11513-2015.

    • Crossref
    • Export Citation
  • Lareau, N. P., and C. B. Clements, 2016: Environmental controls on pyrocumulus and pyrocumulonimbus initiation and development. Atmos. Chem. Phys., 16, 40054022, https://doi.org/10.5194/acp-16-4005-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lareau, N. P., and C. B. Clements, 2017: The mean and turbulent properties of a wildfire convective plume. J. Appl. Meteor. Climatol., 56, 22892299, https://doi.org/10.1175/JAMC-D-16-0384.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lareau, N. P., N. J. Nauslar, and J. T. Abatzoglou, 2018: The Carr Fire vortex: A case of pyrotornadogenesis? Geophys. Res. Lett., 45, 13 10713 115, https://doi.org/10.1029/2018GL080667.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • LaRoche, K. T., and T. J. Lang, 2017: Observations of ash, ice, and lightning within pyrocumulus clouds using polarimetric NEXRAD radars and the national lightning detection network. Mon. Wea. Rev., 145, 48994910, https://doi.org/10.1175/MWR-D-17-0253.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Maesaka, T., K. Iwanami, and M. Maki, 2012: Non-negative KDP estimation by monotone increasing ΦDP assumption below melting layer. Seventh European Conf. on Radar Meteorology and Hydrology (ERAD 2012), Toulouse, France, Météo-France, http://www.meteo.fr/cic/meetings/2012/ERAD/extended_abs/QPE_233_ext_abs.pdf.

  • McCarthy, N., H. McGowan, A. Guyot, and A. Dowdy, 2018: Mobile X-Pol radar: A new tool for investigating pyroconvection and associated wildfire meteorology. Bull. Amer. Meteor. Soc., 99, 11771195, https://doi.org/10.1175/BAMS-D-16-0118.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McCarthy, N., A. Guyot, A. Dowdy, and H. McGowan, 2019: Wildfire and weather radar: A review. J. Geophys. Res. Atmos., 124, 266286, https://doi.org/10.1029/2018JD029285.

    • Search Google Scholar
    • Export Citation
  • McRae, R., J. J. Sharples, and M. Fromm, 2015: Linking local wildfire dynamics to pyroCb development. Nat. Hazards Earth Syst. Sci., 15, 417428, https://doi.org/10.5194/nhess-15-417-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Melnikov, V. M., D. S. Zrnić, R. M. Rabin, and P. Zhang, 2008: Radar polarimetric signatures of fire plumes in Oklahoma. Geophys. Res. Lett., 35, L14815, https://doi.org/10.1029/2008GL034311.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Melnikov, V. M., D. S. Zrnić, and R. M. Rabin, 2009: Polarimetric radar properties of smoke plumes: A model. J. Geophys. Res., 114, D21204, https://doi.org/10.1029/2009JD012647.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Penner, J. E., R. E. Dickinson, and C. S. O’Neill, 1992: Effects of aerosol from biomass burning on the global radiation budget. Science, 256, 1432–1434, https://doi.org/10.1126/science.256.5062.1432.

    • Crossref
    • Export Citation
  • Price, O. E., B. Horsey, and N. Jiang, 2016: Local and regional smoke impacts from prescribed fires. Nat. Hazards Earth Syst. Sci., 16, 22472257, https://doi.org/10.5194/nhess-16-2247-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Prichard, S. J., and et al. , 2019: The Fire and Smoke Model Evaluation Experiment—A plan for integrated, large fire-atmosphere field campaigns. Atmosphere, 10, 66, https://doi.org/10.3390/atmos10020066.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • ProSensing, 2019: Ka-band Scanning Polarimetric Radar (KASPR). Accessed 1 April 2019, https://www.prosensing.com/crb-product/ka-band-scanning-polarimetric-radar-kaspr/.

  • Rauber, R. M., and S. W. Nesbitt, 2018: Radar Meteorology: A First Course. John Wiley and Sons, 461 pp.

    • Crossref
    • Export Citation
  • Rodriguez, B., N. P. Lareau, D. E. Kingsmill, and C. B. Clements, 2020: Extreme pyroconvective updrafts during a megafire. Geophys. Res. Lett., 47, e2020GL089001, https://doi.org/10.1029/2020GL089001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schneebeli, M., J. Grazioli, and A. Berne, 2014: Improved estimation of the specific differential phase shift using a compilation of Kalman filter ensembles. IEEE Trans. Geosci. Remote Sens., 52, 51375149, https://doi.org/10.1109/TGRS.2013.2287017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vulpiani, G., M. Montopoli, L. D. Passeri, A. G. Gioia, P. Giordano, and F. S. Marzano, 2012: On the use of dual-polarized C-band radar for operational rainfall retrieval in mountainous areas. J. Appl. Meteor. Climatol., 51, 405425, https://doi.org/10.1175/JAMC-D-10-05024.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zrnić, D., P. Zhang, V. Melnikov, and D. Mirkovic, 2020: Of fire and smoke plumes, polarimetric radar characteristics. Atmosphere, 11, 363, https://doi.org/10.3390/atmos11040363.

    • Crossref
    • Search Google Scholar
    • Export Citation
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Mobile Ka-Band Polarimetric Doppler Radar Observations of Wildfire Smoke Plumes

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  • 1 Fire Weather Research Laboratory, Department of Meteorology and Climate Science, San José State University, San José, California
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ABSTRACT

Remote sensing techniques have been used to study and track wildfire smoke plume structure and evolution; however, knowledge gaps remain because of the limited availability of observational datasets aimed at understanding fine-scale fire–atmosphere interactions and plume microphysics. Meteorological radars have been used to investigate the evolution of plume rise in time and space, but highly resolved plume observations are limited. In this study, we present a new mobile millimeter-wave (Ka band) Doppler radar system acquired to sample the fine-scale kinematics and microphysical properties of active wildfire smoke plumes from both wildfires and large prescribed fires. Four field deployments were conducted in autumn of 2019 during two wildfires in California and one prescribed burn in Utah. Radar parameters investigated in this study include reflectivity, radial velocity, Doppler spectrum width, differential reflectivity ZDR, and copolarized correlation coefficient ρHV. Observed radar reflectivity ranged between −15 and 20 dBZ in plume, and radial velocity ranged from 0 to 16 m s−1. Dual-polarimetric observations revealed that scattering sources within wildfire plumes are primarily nonspherical and oblate-shaped targets as indicated by ZDR values measuring above 0 and ρHV values below 0.8 within the plume. Doppler spectrum width maxima were located near the updraft core region and were associated with radar reflectivity maxima.

© 2021 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: Craig B Clements, craig.clements@sjsu.edu

ABSTRACT

Remote sensing techniques have been used to study and track wildfire smoke plume structure and evolution; however, knowledge gaps remain because of the limited availability of observational datasets aimed at understanding fine-scale fire–atmosphere interactions and plume microphysics. Meteorological radars have been used to investigate the evolution of plume rise in time and space, but highly resolved plume observations are limited. In this study, we present a new mobile millimeter-wave (Ka band) Doppler radar system acquired to sample the fine-scale kinematics and microphysical properties of active wildfire smoke plumes from both wildfires and large prescribed fires. Four field deployments were conducted in autumn of 2019 during two wildfires in California and one prescribed burn in Utah. Radar parameters investigated in this study include reflectivity, radial velocity, Doppler spectrum width, differential reflectivity ZDR, and copolarized correlation coefficient ρHV. Observed radar reflectivity ranged between −15 and 20 dBZ in plume, and radial velocity ranged from 0 to 16 m s−1. Dual-polarimetric observations revealed that scattering sources within wildfire plumes are primarily nonspherical and oblate-shaped targets as indicated by ZDR values measuring above 0 and ρHV values below 0.8 within the plume. Doppler spectrum width maxima were located near the updraft core region and were associated with radar reflectivity maxima.

© 2021 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: Craig B Clements, craig.clements@sjsu.edu
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