Assessing the simulation of snowfall at Dumont d'Urville, Antarctica, during the YOPP‐SH special observing campaign
Abstract The performance of a set of atmospheric models and meteorological reanalyses in the representation of precipitation days in Antarctica is assessed using ground‐based observations such as a precipitation gauge and a Micro Rain Radar during the Year Of Polar Prediction Special Observing Perio...
Published in: | Quarterly Journal of the Royal Meteorological Society |
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Online Access: | http://dx.doi.org/10.1002/qj.4463 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.4463 |
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crwiley:10.1002/qj.4463 2024-06-02T07:57:40+00:00 Assessing the simulation of snowfall at Dumont d'Urville, Antarctica, during the YOPP‐SH special observing campaign Roussel, Marie‐Laure Wiener, Valentin Genthon, Christophe Vignon, Etienne Bazile, Eric Agosta, Cécile Berne, Alexis Durán‐Alarcón, Claudio Dufresne, Jean‐Louis Claud, Chantal Centre National de la Recherche Scientifique Institut Polaire Français Paul Emile Victor 2023 http://dx.doi.org/10.1002/qj.4463 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.4463 en eng Wiley http://creativecommons.org/licenses/by-nc-nd/4.0/ Quarterly Journal of the Royal Meteorological Society volume 149, issue 753, page 1391-1406 ISSN 0035-9009 1477-870X journal-article 2023 crwiley https://doi.org/10.1002/qj.4463 2024-05-03T11:43:52Z Abstract The performance of a set of atmospheric models and meteorological reanalyses in the representation of precipitation days in Antarctica is assessed using ground‐based observations such as a precipitation gauge and a Micro Rain Radar during the Year Of Polar Prediction Special Observing Period at Dumont d'Urville (November 2018–February 2019), East Antarctic coast. The occurrence of precipitation is overall well predicted, but the number of days and intensity with snowfall are overestimated by the models. This is reflected by high values of bias, probability of detection, and false alarm ratios, in particular for reanalyses, due to too frequent simulated precipitating days. The Heidke skill score shows the overall great contribution of the models in the forecasting of precipitating days, and the best performances are achieved by numerical weather prediction models. The chronology is better represented when the models benefit from the data assimilation of in‐situ observations, such as in reanalysis or weather forecasting models. Precipitation amounts at the surface are overestimated by most of the models. In addition, data from a ground‐based radar make it possible to evaluate the representation of the vertical profiles of snowfall rate. We can show that an excessive sublimation in the atmospheric boundary layer can compensate for overly strong precipitation flux in the mid and low troposphere. Therefore, the need to expand the measurement of precipitation across the atmospheric column using radars is highlighted, in particular in Antarctica where the cold cloud microphysics is poorly known and observations are particularly rare. Article in Journal/Newspaper Antarc* Antarctic Antarctica Wiley Online Library Antarctic Dumont d'Urville ENVELOPE(140.017,140.017,-66.667,-66.667) Dumont-d'Urville ENVELOPE(140.013,140.013,-66.667,-66.667) Quarterly Journal of the Royal Meteorological Society 149 753 1391 1406 |
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Open Polar |
collection |
Wiley Online Library |
op_collection_id |
crwiley |
language |
English |
description |
Abstract The performance of a set of atmospheric models and meteorological reanalyses in the representation of precipitation days in Antarctica is assessed using ground‐based observations such as a precipitation gauge and a Micro Rain Radar during the Year Of Polar Prediction Special Observing Period at Dumont d'Urville (November 2018–February 2019), East Antarctic coast. The occurrence of precipitation is overall well predicted, but the number of days and intensity with snowfall are overestimated by the models. This is reflected by high values of bias, probability of detection, and false alarm ratios, in particular for reanalyses, due to too frequent simulated precipitating days. The Heidke skill score shows the overall great contribution of the models in the forecasting of precipitating days, and the best performances are achieved by numerical weather prediction models. The chronology is better represented when the models benefit from the data assimilation of in‐situ observations, such as in reanalysis or weather forecasting models. Precipitation amounts at the surface are overestimated by most of the models. In addition, data from a ground‐based radar make it possible to evaluate the representation of the vertical profiles of snowfall rate. We can show that an excessive sublimation in the atmospheric boundary layer can compensate for overly strong precipitation flux in the mid and low troposphere. Therefore, the need to expand the measurement of precipitation across the atmospheric column using radars is highlighted, in particular in Antarctica where the cold cloud microphysics is poorly known and observations are particularly rare. |
author2 |
Centre National de la Recherche Scientifique Institut Polaire Français Paul Emile Victor |
format |
Article in Journal/Newspaper |
author |
Roussel, Marie‐Laure Wiener, Valentin Genthon, Christophe Vignon, Etienne Bazile, Eric Agosta, Cécile Berne, Alexis Durán‐Alarcón, Claudio Dufresne, Jean‐Louis Claud, Chantal |
spellingShingle |
Roussel, Marie‐Laure Wiener, Valentin Genthon, Christophe Vignon, Etienne Bazile, Eric Agosta, Cécile Berne, Alexis Durán‐Alarcón, Claudio Dufresne, Jean‐Louis Claud, Chantal Assessing the simulation of snowfall at Dumont d'Urville, Antarctica, during the YOPP‐SH special observing campaign |
author_facet |
Roussel, Marie‐Laure Wiener, Valentin Genthon, Christophe Vignon, Etienne Bazile, Eric Agosta, Cécile Berne, Alexis Durán‐Alarcón, Claudio Dufresne, Jean‐Louis Claud, Chantal |
author_sort |
Roussel, Marie‐Laure |
title |
Assessing the simulation of snowfall at Dumont d'Urville, Antarctica, during the YOPP‐SH special observing campaign |
title_short |
Assessing the simulation of snowfall at Dumont d'Urville, Antarctica, during the YOPP‐SH special observing campaign |
title_full |
Assessing the simulation of snowfall at Dumont d'Urville, Antarctica, during the YOPP‐SH special observing campaign |
title_fullStr |
Assessing the simulation of snowfall at Dumont d'Urville, Antarctica, during the YOPP‐SH special observing campaign |
title_full_unstemmed |
Assessing the simulation of snowfall at Dumont d'Urville, Antarctica, during the YOPP‐SH special observing campaign |
title_sort |
assessing the simulation of snowfall at dumont d'urville, antarctica, during the yopp‐sh special observing campaign |
publisher |
Wiley |
publishDate |
2023 |
url |
http://dx.doi.org/10.1002/qj.4463 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.4463 |
long_lat |
ENVELOPE(140.017,140.017,-66.667,-66.667) ENVELOPE(140.013,140.013,-66.667,-66.667) |
geographic |
Antarctic Dumont d'Urville Dumont-d'Urville |
geographic_facet |
Antarctic Dumont d'Urville Dumont-d'Urville |
genre |
Antarc* Antarctic Antarctica |
genre_facet |
Antarc* Antarctic Antarctica |
op_source |
Quarterly Journal of the Royal Meteorological Society volume 149, issue 753, page 1391-1406 ISSN 0035-9009 1477-870X |
op_rights |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
op_doi |
https://doi.org/10.1002/qj.4463 |
container_title |
Quarterly Journal of the Royal Meteorological Society |
container_volume |
149 |
container_issue |
753 |
container_start_page |
1391 |
op_container_end_page |
1406 |
_version_ |
1800740856953569280 |