U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights


ARM Campaign Provides Unprecedented Snowfall Dataset
Published: June 19, 2015
Posted: July 20, 2015

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.

Reference: 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. (Reference link)

Contact: Sally McFarlane, SC-23.1, (301) 903-0943, Shaima Nasiri, SC-23.1, 301-903-0207
Topic Areas:

  • Research Area: Atmospheric System Research
  • Facility: DOE ARM User Facility

Division: SC-23.1 Climate and Environmental Sciences Division, BER

 

BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER

Recent Highlights

May 10, 2019
Quantifying Decision Uncertainty in Water Management via a Coupled Agent-Based Model
Considering risk perception can improve the representation of human decision-making processes in age [more...]

May 09, 2019
Projecting Global Urban Area Growth Through 2100 Based on Historical Time Series Data and Future Scenarios
Study provides country-specific urban area growth models and the first dataset on country-level urba [more...]

May 05, 2019
Calibrating Building Energy Demand Models to Refine Long-Term Energy Planning
A new, flexible calibration approach improved model accuracy in capturing year-to-year changes in bu [more...]

May 03, 2019
Calibration and Uncertainty Analysis of Demeter for Better Downscaling of Global Land Use and Land Cover Projections
Researchers improved the Demeter model’s performance by calibrating key parameters and establi [more...]

Apr 22, 2019
Representation of U.S. Warm Temperature Extremes in Global Climate Model Ensembles
Representation of warm temperature events varies considerably among global climate models, which has [more...]

List all highlights (possible long download time)