Articles | Volume 17, issue 15
https://doi.org/10.5194/amt-17-4581-2024
https://doi.org/10.5194/amt-17-4581-2024
Research article
 | 
01 Aug 2024
Research article |  | 01 Aug 2024

Time-resolved measurements of the densities of individual frozen hydrometeors and fresh snowfall

Dhiraj K. Singh, Eric R. Pardyjak, and Timothy J. Garrett

Related authors

A global analysis of the fractal properties of clouds revealing anisotropy of turbulence across scales
Karlie N. Rees, Timothy J. Garrett, Thomas D. DeWitt, Corey Bois, Steven K. Krueger, and Jérôme C. Riedi
Nonlin. Processes Geophys., 31, 497–513, https://doi.org/10.5194/npg-31-497-2024,https://doi.org/10.5194/npg-31-497-2024, 2024
Short summary
Finite domains cause bias in measured and modeled distributions of cloud sizes
Thomas D. DeWitt and Timothy J. Garrett
Atmos. Chem. Phys., 24, 8457–8472, https://doi.org/10.5194/acp-24-8457-2024,https://doi.org/10.5194/acp-24-8457-2024, 2024
Short summary
Climatologically invariant scale invariance seen in distributions of cloud horizontal sizes
Thomas D. DeWitt, Timothy J. Garrett, Karlie N. Rees, Corey Bois, Steven K. Krueger, and Nicolas Ferlay
Atmos. Chem. Phys., 24, 109–122, https://doi.org/10.5194/acp-24-109-2024,https://doi.org/10.5194/acp-24-109-2024, 2024
Short summary
Lotka's wheel and the long arm of history: how does the distant past determine today's global rate of energy consumption?
Timothy J. Garrett, Matheus R. Grasselli, and Stephen Keen
Earth Syst. Dynam., 13, 1021–1028, https://doi.org/10.5194/esd-13-1021-2022,https://doi.org/10.5194/esd-13-1021-2022, 2022
Short summary
Idealized simulation study of the relationship of disdrometer sampling statistics with the precision of precipitation rate measurement
Karlie N. Rees and Timothy J. Garrett
Atmos. Meas. Tech., 14, 7681–7691, https://doi.org/10.5194/amt-14-7681-2021,https://doi.org/10.5194/amt-14-7681-2021, 2021
Short summary

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: In Situ Measurement | Topic: Validation and Intercomparisons
Uncertainties in temperature statistics and fluxes determined by sonic anemometers due to wind-induced vibrations of mounting arms
Zhongming Gao, Heping Liu, Dan Li, Bai Yang, Von Walden, Lei Li, and Ivan Bogoev
Atmos. Meas. Tech., 17, 4109–4120, https://doi.org/10.5194/amt-17-4109-2024,https://doi.org/10.5194/amt-17-4109-2024, 2024
Short summary
Performance evaluation of MeteoTracker mobile sensor for outdoor applications
Francesco Barbano, Erika Brattich, Carlo Cintolesi, Abdul Ghafoor Nizamani, Silvana Di Sabatino, Massimo Milelli, Esther E. M. Peerlings, Sjoerd Polder, Gert-Jan Steeneveld, and Antonio Parodi
Atmos. Meas. Tech., 17, 3255–3278, https://doi.org/10.5194/amt-17-3255-2024,https://doi.org/10.5194/amt-17-3255-2024, 2024
Short summary
Impacts of anemometer changes, site relocations and processing methods on wind speed trends in China
Yi Liu, Lihong Zhou, Yingzuo Qin, Cesar Azorin-Molina, Cheng Shen, Rongrong Xu, and Zhenzhong Zeng
Atmos. Meas. Tech., 17, 1123–1131, https://doi.org/10.5194/amt-17-1123-2024,https://doi.org/10.5194/amt-17-1123-2024, 2024
Short summary
Validation of Aeolus L2B products over the tropical Atlantic using radiosondes
Maurus Borne, Peter Knippertz, Martin Weissmann, Benjamin Witschas, Cyrille Flamant, Rosimar Rios-Berrios, and Peter Veals
Atmos. Meas. Tech., 17, 561–581, https://doi.org/10.5194/amt-17-561-2024,https://doi.org/10.5194/amt-17-561-2024, 2024
Short summary
Estimating the turbulent kinetic energy dissipation rate from one-dimensional velocity measurements in time
Marcel Schröder, Tobias Bätge, Eberhard Bodenschatz, Michael Wilczek, and Gholamhossein Bagheri
Atmos. Meas. Tech., 17, 627–657, https://doi.org/10.5194/amt-17-627-2024,https://doi.org/10.5194/amt-17-627-2024, 2024
Short summary

Cited articles

Alcott, T. I. and Steenburgh, W. J.: Snow-to-liquid ratio variability and prediction at a high-elevation site in Utah's Wasatch Mountains, Weather Forecast., 25, 323–337, 2010. a, b
Dickinson, R. E.: Land surface processes and climate – Surface albedos and energy balance, Adv. Geophys., 25, 305–353, https://doi.org/10.1016/S0065-2687(08)60176-4, 1983. a
Dunnavan, E. L., Jiang, Z., Harrington, J. Y., Verlinde, J., Fitch, K., and Garrett, T. J.: The shape and density evolution of snow aggregates, J. Atmos. Sci., 76, 3919–3940, 2019. a
Fierz, C., Armstrong, R. L., Durand, Y., Etchevers, P., Greene, E., McClung, D. M., Nishimura, K., Satyawali, P. K., and Sokratov, S. A.: The international classification for seasonal snow on the ground, UNESCO, https://unesdoc.unesco.org/ark:/48223/pf0000186462 (last access: 17 June 2023), 2009. a
Finlon, J. A., McFarquhar, G. M., Nesbitt, S. W., Rauber, R. M., Morrison, H., Wu, W., and Zhang, P.: A novel approach for characterizing the variability in mass–dimension relationships: results from MC3E, Atmos. Chem. Phys., 19, 3621–3643, https://doi.org/10.5194/acp-19-3621-2019, 2019. a
Download
Short summary
Accurate measurements of the properties of snowflakes are challenging to make. We present a new technique for the real-time measurement of the density of freshly fallen individual snowflakes. A new thermal-imaging instrument, the Differential Emissivity Imaging Disdrometer (DEID), is shown to be capable of providing accurate estimates of individual snowflake and bulk snow hydrometeor density. The method exploits the rate of heat transfer during the melting of a snowflake on a hotplate.