Introduction

Particle Flux Analytics collaborates with the University of Utah and customers worldwide to develop for sale pioneering precipitation and weather measurement technologies. Current products include the Multi Angle Snowflake Camera, the Differential Emissivity Image Distrometer, and the SnowPixel.

Multi-Angle Snowflake Camera

The Multi-Angle Snowflake Camera (MASC) takes 10 to 30 micron resolution photographs of hydrometeors from three angles while simultaneously measuring their fallspeed.

The instrument is robust to cold and weather and runs unattended. Calibration is limited to occasional camera alignment and lens focusing using a calibration tool that attaches to the instrument. Software is included for image and fallspeed acquisition and display on PC platforms and for creating a live internet feed from the installation site.

Technical details are available in the specifications PDF.

For more information or to request a quote, please reach out to us at info@particleflux.net.

SnowPixel

The SnowPixel is the most advanced thermodynamic sensor array developed to date. It uses an advanced NanoFab technology developed through DOE Phase I and II SBIR/STTR funding to PFA as a 576-channel 24x24 array of 0.5 mm x 0.5 mm individually, thermostatically, controlled platinum micro-hotplates, each 120 nm thick, with a footprint of just 32 mm x 35 mm. The output is the first high-resolution, high-speed 2D ``video'' of environmental thermodynamic cooling signatures. The SnowPixel can be used in a wide range of applications including simulateneous measurements of hydrometeor mass and cumulative precipitation amount, with ongoing testing of its application as a concurrent wind and turbulence sensor. Further development is aimed at a miniaturized, low-power, fully capable weather station for deployment in high-density meteorological sensor networks aimed at improved societal resilience to weather extremes.

For more information or to request a quote, please reach out to us at info@particleflux.net.

Differential Emissivity Imaging Distrometer

The Differential Emissivity Imaging Distrometer measures the size, shape, mass, and density of individual hydrometeors, as well as cumulative snow and liquid precipitation rates, by exploiting difference in thermal emissivity of metal and water. Hydrometeors that land on a heated metal plate are seen by a thermal camera as seen as bright regions on a blackground. With heat transfer physics the mass and density can of individual hydrometeors can be obtained with unprecendented accuracy from the evaporation time. The DEID has been successfully validated against traditional, very coarse resolution, snow stakes and weighing gauges, and it is currently being used for precipitation measurement and avalanche prediction at a major Utah ski resort.

For more information or to request a quote, please reach out to us at info@particleflux.net.

Media

Images shown below were captured using a MASC in Salt Lake City, UT. Further media coverage.

Our Team

Allan Reaburn, President

Jesse Smith, Senior Engineer

Sanket Deshmukh, Engineer

Advisor

Prof. Tim Garrett, Scientific Advisor

PUBLICATIONS
  • Garrett, T. J. and Yuter, S. E: Observed influence of riming, temperature, and turbulence on the fallspeed of solid precipitation Geophys. Res. Lett. doi:10.1002/2014GL061016
  • Gergely M. and T. J. Garrett, 2016: Impact of the natural variability in snowflake diameter, aspect ratio, and orientation on modeled snowfall radar reflectivity. J. Geophys. Research, doi: 10.1002/2016JD025192
  • Mathias Gergely, Steven J. Cooper, and Timothy J. Garrett, 2017: Using snowflake surface-area-to-volume ratio to model and interpret snowfall triple-frequency radar signatures, Atmos. Chem. Phys., 17, 12011-12030, 2017, doi: 10.5194/acp-17-12011-2017
  • Oue, M., Kollias, P., Ryzhkov, A., & Luke,E. P. (2018). Toward exploring the synergy between cloud radar polarimetry and Doppler spectral analysis in deep cold precipitating systems in the Arctic. Journal of Geophysical Research:Atmospheres, 123. https://doi.org/10.1002/2017JD027717
  • Besic, N., Gehring, J., Praz, C., Figueras i Ventura, J., Grazioli, J., Gabella, M., Germann, U., and Berne, A.: Unraveling hydrometeor mixtures in polarimetric radar measurements, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-58, in review, 2018.
  • Patrick Kennedy, Merhala Thurai, Christophe Praz, V. N. Bringi, Alexis Berne, and Branislav M. Notaroš, 2018: Variations in Snow Crystal Riming and ZDR: A Case Analysis. J. Appl. Met. Clim., doi: 10.1175/JAMC-D-17-0068.1
  • Matrosov, S.Y., C.G. Schmitt, M. Maahn, and G. de Boer, 2017: Atmospheric Ice Particle Shape Estimates from Polarimetric Radar Measurements and In Situ Observations. J. Atmos. Oceanic Technol., 34, 2569–2587, https://doi.org/10.1175/JTECH-D-17-0111.1
  • Huang, G-J, Kleinkort, C. Bringi, and V.N. Notaroš, B.M.: Winter precipitation particle size distribution measurement by Multi-Angle Snowflake Camera. Atmos. Res. doi.org/10.1016/j.atmosres.2017.08.005, 2017
  • Bair EH, Dozier J, Davis RE, Colee MT and Claffey KJ, 2015: CUES—a study site for measuring snowpack energy balance in the Sierra Nevada. Front. Earth Sci. 3:58. doi: 10.3389/feart.2015.00058
  • Praz, C., Roulet, Y.-A., and Berne, A.: Solid hydrometeor classification and riming degree estimation from pictures collected with a Multi-Angle Snowflake Camera, Atmos. Meas. Tech., 10, 1335-1357, https://doi.org/10.5194/amt-10-1335-2017, 2017
  • Cooper, S. J., Wood, N. B. and L’Ecuyer, T. S.: A variational technique to estimate snowfall rate from coincident radar, snowflake, and fall-speed observations, Atmos. Meas. Tech., 10, 2557-2571, 2017, doi:10.5194/amt-10-2557-2017
  • Grazioli, J., Genthon, C., Boudevillain, B., Duran-Alarcon, C., Del Guasta, M., Madeleine, J.-B., and Berne, A.: Measurements of precipitation in Dumont d'Urville, Adélie Land, East Antarctica, The Cryosphere, 11, 1797-1811, https://doi.org/10.5194/tc-11-1797-2017, 2017
  • Garrett, T. J., Yuter, S.E., Fallgatter, C., Shkurko, K., Rhodes, S. R. and Endries, J. L., 2015: Orientations and aspect ratios of falling snow. Geophys. Res. Lett., 42, 4617-4622, doi:10.1002/2015GL06404
  • Garrett, T. J., Fallgatter, C., Shkurko, K., and Howlett, D., 2012: Fallspeed measurement and high-resolution multi-angle photography of hydrometeors in freefall. Atmos. Meas. Tech., 5, 2625-2633, doi:10.5194/amt-5-2625-2012
  • Notaroš, B. M., Bringi, V. N., Kleinkort, C., Kennedy, P., Huang, G. J., Thurai, M., ... & Lee, G., 2016: Accurate characterization of winter precipitation using multi-angle snowflake camera, visual hull, advanced scattering methods and polarimetric radar. Atmosphere, 7(6), 81.
  • C. Kleinkort, G.-J. Huang, V. N. Bringi, and B. M. Notaros, 2016: Visual Hull Method for Realistic 3D Particle Shape Reconstruction Based on High-Resolution Photographs of Snowflakes in Freefall from Multiple Views, Journal of Atmospheric and Oceanic Technology, doi:10.1175/JTECH-D-16-0099.1.
  • V. N. Bringi, P. C. Kennedy, G.-J. Huang, C. Kleinkort, M. Thurai, and B. M. Notaros, 2016: Dual-polarized radar and surface observations of a winter graupel shower with negative Zdr column, Journal of Applied Meteorology and Climatology, doi:10.1175/JAMC-D-16-0197.1

CONTACT

Mailing Address

Particle Flux Analytics Inc.
6300 N. Sagewood Drive
STE. H#623
Park City, UT 84098
United States