Published in

Cambridge University Press, Journal of Glaciology, 260(66), p. 1006-1023, 2020

DOI: 10.1017/jog.2020.70

Links

Tools

Export citation

Search in Google Scholar

Characterization of snowfall estimated by in situ and ground-based remote-sensing observations at Terra Nova Bay, Victoria Land, Antarctica

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

AbstractKnowledge of the precipitation contribution to the Antarctic surface mass balance is essential for defining the ice-sheet contribution to sea-level rise. Observations of precipitation are sparse over Antarctica, due to harsh environmental conditions. Precipitation during the summer months (November–December–January) on four expeditions, 2015–16, 2016–17, 2017–18 and 2018–19, in the Terra Nova Bay area, were monitored using a vertically pointing radar, disdrometer, snow gauge, radiosounding and an automatic weather station installed at the Italian Mario Zucchelli Station. The relationship between radar reflectivity and precipitation rate at the site can be estimated using these instruments jointly. The error in calculated precipitation is up to 40%, mostly dependent on reflectivity variability and disdrometer inability to define the real particle fall velocity. Mean derived summer precipitation is ~55 mm water equivalent but with a large variability. During collocated measurements in 2018–19, corrected snow gauge amounts agree with those derived from the relationship, within the estimated errors. European Centre for the Medium-Range Weather Forecasts (ECMWF) and the Antarctic Mesoscale Prediction System (AMPS) analysis and operational outputs are able to forecast the precipitation timing but do not adequately reproduce quantities during the most intense events, with overestimation for ECMWF and underestimation for AMPS.