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Greenland ice sheet rainfall climatology, extremes and atmospheric river rapids

Authors :
Jason E. Box
Kristian P. Nielsen
Xiaohua Yang
Masashi Niwano
Adrien Wehrlé
Dirk van As
Xavier Fettweis
Morten A. Ø. Køltzow
Bolli Palmason
Robert S. Fausto
Michiel R. van den Broeke
Baojuan Huai
Andreas P. Ahlstrøm
Kirsty Langley
Armin Dachauer
Brice Noël
Source :
Meteorological Applications, Vol 30, Iss 4, Pp n/a-n/a (2023)
Publication Year :
2023
Publisher :
Wiley, 2023.

Abstract

Abstract Greenland rainfall has come into focus as a climate change indicator and from a variety of emerging cryospheric impacts. This study first evaluates rainfall in five state‐of‐the‐art numerical prediction systems (NPSs) (CARRA, ERA5, NHM‐SMAP, RACMO, MAR) using in situ rainfall data from two regions spanning from land onto the ice sheet. The new EU Copernicus Climate Change Service (C3S) Arctic Regional ReAnalysis (CARRA), with a relatively fine (2.5 km) horizontal grid spacing and extensive within‐model‐domain observational initialization, has the lowest average bias and highest explained variance relative to the field data. ERA5 inland wet bias versus CARRA is consistent with the field data and other research and is presumably due to more ERA5 topographic smoothing. A CARRA climatology 1991–2021 has rainfall increasing by more than one‐third for the ice sheet and its peripheral ice masses. CARRA and in situ data illuminate extreme (above 300 mm per day) local rainfall episodes. A detailed examination CARRA data reveals the interplay of mass conservation that splits flow around southern Greenland and condensational buoyancy generation that maintains along‐flow updraft ‘rapids’ 2 km above sea level, which produce rain bands within an atmospheric river interacting with Greenland. CARRA resolves gravity wave oscillations that initiate as a result of buoyancy offshore, which then amplify from terrain‐forced uplift. In a detailed case study, CARRA resolves orographic intensification of rainfall by up to a factor of four, which is consistent with the field data.

Details

Language :
English
ISSN :
14698080 and 13504827
Volume :
30
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Meteorological Applications
Publication Type :
Academic Journal
Accession number :
edsdoj.6e6a9449f0f44a43a921d783b25c9514
Document Type :
article
Full Text :
https://doi.org/10.1002/met.2134