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  Kilometer-scale climate models: Prospects and challenges

Schär, C., Fuhrer, O., Arteaga, A., Ban, N., Charpilloz, C., Di Girolamo, S., et al. (2020). Kilometer-scale climate models: Prospects and challenges. Bulletin of the American Meteorological Society, 101, E567-E587. doi:10.1175/BAMS-D-18-0167.1.

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 Creators:
Schär, Christoph1, Author
Fuhrer, Oliver, Author
Arteaga, Andrea, Author
Ban, Nikolina, Author
Charpilloz, Christophe, Author
Di Girolamo, Salvatore, Author
Hentgen, Laureline, Author
Hoefler, Torsten, Author
Lapillonne, Xavier, Author
Leutwyler, David2, Author           
Osterried, Katherine, Author
Panosetti, Davide, Author
Rüdisühli, Stefan, Author
Schlemmer, Linda, Author
Schulthess, Thomas C., Author
Sprenger, Michael, Author
Ubbiali, Stefano, Author
Wernli, Heini, Author
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1External Organizations, ou_persistent22              
2Precipitating Convection, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society, ou_3001851              

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 Abstract: Currently major efforts are underway toward refining the horizontal resolution (or grid spacing) of climate models to about 1 km, using both global and regional climate models (GCMs and RCMs). Several groups have succeeded in conducting kilometer-scale multiweek GCM simulations and decadelong continental-scale RCM simulations. There is the well-founded hope that this increase in resolution represents a quantum jump in climate modeling, as it enables replacing the parameterization of moist convection by an explicit treatment. It is expected that this will improve the simulation of the water cycle and extreme events and reduce uncertainties in climate change projections. While kilometer-scale resolution is commonly employed in limited-area numerical weather prediction, enabling it on global scales for extended climate simulations requires a concerted effort. In this paper, we exploit an RCM that runs entirely on graphics processing units (GPUs) and show examples that highlight the prospects of this approach. A particular challenge addressed in this paper relates to the growth in output volumes. It is argued that the data avalanche of high-resolution simulations will make it impractical or impossible to store the data. Rather, repeating the simulation and conducting online analysis will become more efficient. A prototype of this methodology is presented. It makes use of a bit-reproducible model version that ensures reproducible simulations across hardware architectures, in conjunction with a data virtualization layer as a common interface for output analyses. An assessment of the potential of these novel approaches will be provided.

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Language(s): eng - English
 Dates: 2020-06
 Publication Status: Issued
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 Rev. Type: Peer
 Identifiers: DOI: 10.1175/BAMS-D-18-0167.1
BibTex Citekey: 10.1175/BAMS-D-18-0167.1
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Title: Bulletin of the American Meteorological Society
Source Genre: Journal
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Pages: - Volume / Issue: 101 Sequence Number: - Start / End Page: E567 - E587 Identifier: ISSN: 0003-0007