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How Does Riming Affect Snowfall?
Published: April 12, 2017
Posted: July 11, 2017

Observations from an Atmospheric Radiation Measurement (ARM) field campaign are used to quantify the impacts of riming on snowfall.

The Science  
In high latitudes, most precipitation originates from snow. Understanding the microphysical processes governing the growth of snow particles is important for improving model forecasts of snow amount. Riming, or the collection of supercooled water droplets onto an ice surface, is an important microphysical process in snow formation given that a large percentage of cold cloud systems contain supercooled liquid water. In this study, scientists used observations from the Biogenic Aerosols Effects on Clouds and Climate (BAECC) field campaign, which occurred in Finland during the winter of 2014–2015, to quantify the effect of riming on snowfall.

The Impact
Using observations of 22 snowfall events, scientists determined that riming is responsible for 5% to 40% of the precipitation mass. Additionally, a comparison of dual-polarization radar observations and retrieved snowflake microphysical properties was carried out to test the validity of conceptual riming models. The analysis determined that the connection between dual-polarization radar observations and riming is more complex than currently expected. In some cases, the observed differential reflectivity from the radar will increase when the particle is rimed, while in other cases it will decrease, depending on initial particle sizes. The analysis indicates that care should be taken when making conclusions about riming presence from the analysis of dual-polarization radar measurements, since riming growth of aggregates could produce the opposite of the expected pattern.

Researchers used ground-based observations of ice particle size distribution and ensemble mean density to quantify the effect of riming on snowfall. The rime mass fraction is derived from these measurements by following the approach used in a single ice-phase category microphysical scheme proposed for use in numerical weather prediction models. One of the proposed scheme’s characteristics is that the prefactor of a power law relation that links mass and size of ice particles is determined by the rime mass fraction, while the exponent does not change. To derive the rime mass fraction, a mass-dimensional relation representative of unrimed snow also is determined. To check the validity of the proposed retrieval method, the derived rime mass fraction is converted to the effective liquid water path that is compared to microwave radiometer observations. Since dual-polarization radar observations are often used to detect riming, the impact of riming on dual-polarization radar variables is studied for differential reflectivity measurements. The study shows that the relation between rime mass fraction and differential reflectivity is ambiguous; other factors such as change in median volume diameter also need to be considered. Given the current interest on sensitivity of precipitation to aerosol pollution, which could inhibit riming, the researchers investigated the importance of riming for surface snow accumulation. They found that riming is responsible for 5% to 40% of snowfall mass. The study is based on data collected at the University of Helsinki field station in Hyytiälä during the U.S. Department of Energy (DOE) Biogenic Aerosols Effects on Clouds and Climate (BAECC) field campaign in the winter of 2014–2015. In total, 22 winter storms were analyzed and detailed analysis of two events is presented to illustrate the study.

Contacts (BER PM)
Sally McFarlane
ARM Program Manager

(PI Contact)
Dmitri Moisseev
University of Helsinki

The research of J.T. and D.M. was supported by the Academy of Finland (grant 305175) and Academy of Finland Finnish Center of Excellence program (grant 3073314). A.v.L. was funded by a grant of the Vilho, Yrjö and Kalle Väisälä Foundation and by the SESAR Joint Undertaking Horizon 2020 grant agreement 699221 (PNOWWA). The instrumentation used in this study was supported by the National Aeronautics and Space Administration’s Global Precipitation Measurement Mission ground validation program and DOE’s Office of Science, Office of Biological and Environmental Research, ARM program.

Moisseev, D., A. von Lerber, and J. Tiira. 2017. “Quantifying the Effect of Riming on Snowfall Using Ground-Based Observations,” Journal of Geophysical Research: Atmospheres 122, 4019-37. DOI: 10.1002/2016JD026272. (Reference link)

Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling
  • Research Area: Atmospheric System Research
  • Facility: DOE ARM User Facility

Division: SC-33.1 Earth and Environmental Sciences Division, BER


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