C039-01
Working towards a reliable snowfall estimate on Central Arctic sea ice
Friday, 11 December 2020: 05:30
Virtual
David Wagner1,2, Matthew Shupe3,4, Ola P G Persson3,4, Markus M Frey5, Amelie Kirchgaessner5, Ian Raphael6, David Clemens-Sewall6, Chris Polashenski6,7, Julia Regnery8, Stefan Hendricks8, Marc Oggier9, Glen E Liston10, Martin Schneebeli1 and Michael Lehning1,2, (1)WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland, (2)Swiss Federal Institute of Technology Lausanne, CRYOS - School of Architecture, Civil and Environmental Engineering, Lausanne, Switzerland, (3)University of Colorado at Boulder, Cooperative Institute for the Research in Environmental Sciences, Boulder, CO, United States, (4)NOAA, Physical Science Laboratory, Boulder, CO, United States, (5)NERC British Antarctic Survey, Cambridge, United Kingdom, (6)Dartmouth College, Thayer School of Engineering, Hanover, NH, United States, (7)USACE-CRREL, Alaska Projects Office, Ft. Wainwright, AK, United States, (8)Alfred Wegener Institute Helmholtz-Center for Polar and Marine Research Bremerhaven, Bremerhaven, Germany, (9)University of Alaska Fairbanks, International Arctic Research Center, Fairbanks, AK, United States, (10)Colorado State University, Cooperative Institute for Research in the Atmosphere (CIRA), Fort Collins, CO, United States
Abstract:
For the Central Arctic, especially during polar night, little is known about the role of precipitation, blowing snow and snow mass accumulation on the ice. Many research topics regarding Arctic sea ice however depend on reliable snowfall estimations. Blowing snow can quickly reach a vertical extent of several tens of meters, leading to an overestimation of the snowfall rate for sensors that are installed within that range. Apart from that, the harsh conditions may lead to measurement errors or instrument failures. Ze-S relationships exist to derive snowfall rates from radar reflectivity, but these need to be validated for the precipitation processes and atmospheric conditions in winter over the Central Arctic. Furthermore, mass flux estimates of blowing snow are necessary to distinguish it from precipitation in order to calculate snow mass balance.
During MOSAiC, an extensive instrumentation setup was installed on and around research vessel Polarstern in the Central Arctic, including zenith- and scanning cloud radars, different types of precipitation gauges, wind sensors and snow particle counters (SPCs). Apart from that, detailed snow profile measurements, frequent terrestrial laser scans (TLS) and Magnaprobe transects were conducted.
A combination of these datasets allows for a detailed investigation of snowfall and blowing snow estimates for MOSAiC leg 1 (24 Oct – 15 Dec 2019). We present first evaluation results of ice- and ship-based sensors and the capability of remote sensing instruments to derive snowfall rates. At current state, most snowfall estimates from precipitation gauges show large differences between each other. However, we can already demonstrate the ability of the ship-based Ka-band ARM Zenith Radar (KAZR) to estimate snowfall. We also find that the cumulative precipitation sums derived from KAZR and the ship-based Vaisala PWD22 optical precipitation gauge do not show significant differences between them. The findings are particularly noteworthy, as ice dynamics led to partial power cuts of instruments installed on the ice during leg 1, as well as during later legs, while the power supply on the ship was not affected. Furthermore, higher installed instruments are less vulnerable to blowing snow and blowing snow is not considered when deriving precipitation based on radar reflectivity.
