Titolo | Characterization of snowfall estimated by in situ and ground-based remote-sensing observations at Terra Nova Bay, Victoria Land, Antarctica |
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Tipo di pubblicazione | Articolo su Rivista peer-reviewed |
Anno di Pubblicazione | 2020 |
Autori | Scarchilli, Claudio, Ciardini Virginia, Grigioni P., Iaccarino Antonio, De Silvestri Lorenzo, Proposito Marco, Dolci Stefano, Camporeale Giuseppe, Schioppo Riccardo, Antonelli Adriano, Baldini Luca, Roberto Nicoletta, Argentini Stefania, Bracci Alessandro, and Frezzotti Massimo |
Rivista | Journal of Glaciology |
Volume | 66 |
Issue | 260 |
Paginazione | 1006 - 1023 |
Data di pubblicazione | Jan-12-2020 |
Parole chiave | antarctica, East Antarctica, glacier dynamics, glaciology, mass balance, Remote sensing, Satellite data, satellite imagery, Sea ice, snow cover, Terra Nova Bay |
Abstract | Knowledge 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. Copyright © The Author(s) 2020. |
Note | cited By 5 |
URL | https://www.cambridge.org/core/product/identifier/S0022143020000702/type/journal_articlehttps://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143020000702 |
DOI | 10.1017/jog.2020.70 |
Titolo breve | J. Glaciol. |
Citation Key | 8999 |