ARM Campaign Provides Unprecedented Snowfall Dataset
Correctly predicting snowfall properties in numerical models is important not just for weather forecasts, but for long-term climate simulations. Errors in predicting snowflake fall speeds can cause simulated clouds to disappear too quickly or live too long, resulting in further errors in their impact on Earth’s radiation budget. Research and weather radars can observe scattering from snowflakes, but their complex shapes and particles make it difficult to relate observations of radar scattering by snowfall to the physical properties of the snow particles. A recent deployment of the Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility to the University of Helsinki Hyytiälä Forestry Field Station in Finland, combined with the availability of excellent in situ ground-based snow particle measurements, provided an unprecedented snowfall dataset. This dataset provides the first opportunity to relate collocated ground-based triple frequency radar observations with in situ measurements of snowfall at the ground to produce relationships that can be used to characterize snowfall properties in future radar observations.
A team of scientists, including researchers funded by DOE’s Atmospheric System Research program, analyzed three snowfall cases from the campaign. These cases cover light to moderate snowfall rates with transitions from heavily rimed snow to open-structured, low-density snowflakes. The triple-frequency radar measurements show rich temporal and spatial structure throughout the cloud during each of the three cases; these structures often seem to be related to riming and aggregation zones within the cloud. A comparison of the radar signatures from the lowest altitudes with the ground-based in situ measurements reveals that in the presence of large (>5?mm) snow aggregates, the triple-frequency radar observations do not follow the curve of classical spheroid scattering models. Additionally, rimed particles appear along an almost horizontal line in the triple-frequency space, which had not been observed before. Overall, the three case studies indicate a close connection of the triple-frequency radar signatures to snow particle structure, bulk snowfall density, and characteristic size of the snowfall particle size distribution.
Kneifel, S., A. von Lerber, J. Tiira, D. Moisseev, P. Kollias, and J. Leinonen. 2015. “Observed Relations Between Snowfall Microphysics and Triple-Frequency Radar Measurements,” Journal of Geophysical Research: Atmospheres 120(12), 6034-55. DOI: 10.1002/2015JD023156.