Lecturer: Steven J. Cooper (Utah) Date: 2018-05-03 10:00 Place: Aniara
Characterization of Snowfall Properties at Haukeliseter, Norway, through a Combined Radar and In-Situ Microphysical Observation Approach
Steven J. Cooper
University of Utah
We explore the ability of in-situ snowflake microphysical observations to constrain estimates of surface snowfall accumulations derived from co-incident ground-based radar observations. In this work, we exploit results from a recent field campaign in Scandinavia to study high-latitude snowfall processes. Specifically, in Winter 2016-17, we deployed a Micro Rain Radar (MRR), Precipitation Imaging Package (PIP) and Multi-Angle Snow Camera (MASC) to the Haukeliseter Test Site run by the Norwegian Meteorological Institute. This state-of-the-art snowfall measurement station lies at 60Â°N near an elevation of 5000 feet on a plateau in the coastal mountains of Norway and typically receives up to 45 feet of snow per year. The site also houses a double fenced snow gauge, two single fenced snow gauges, and a comprehensive set of basic meteorological observations. In terms of the retrieval work, observations of snowflake particle size distribution, fallspeed, and habit from the PIP and MASC were used as input to a snowfall retrieval algorithm based upon MRR measurements. Retrieved snowfall rates were then compared with snow gauge observations to evaluate retrieval performance. These analyses, as well as descriptions of snow particle size distributions, habits, and fall speeds, will be presented as a function of storm event type and meteorological conditions for the Haukeliseter site. Preliminary results suggest good agreement between the combined retrieval scheme and double fenced snow accumulations for low wind snow events. Agreement is less robust for stronger events such as Extreme Weather Event Urd which occurred over Christmas week 2016. Bulk statistics on snowfall retrieval performance for the season will be presented.
Created 2018-03-20 09:06:57 by Mats HolmstrÃ¶m Last changed 2018-03-20 10:54:04 by Mats HolmstrÃ¶m