LongRunMIP -motivation and design for a large collection of millennial-length AO-GCM simulations 2

Maria Rugenstein , Jonah Bloch-Johnson , Ayako Abe-Ouchi (1) , Timothy J. Andrews (2) , Urs Beyerle , Long Cao , Tarun Chadha , Gokhan Danabasoglu (3) , Jean-Louis Dufresne (4) , Lei Duan , Marie-Alice Foujols (5) , Thomas Frölicher , Olivier Geoffroy (6) , Jonathan M Gregory (7) , Reto Knutti (8) , Chao Li (9) , Alice Marzocchi , Thorsten Mauritsen (10) , Matthew Menary , Elisabeth Moyer , Larissa Nazarenko , David Paynter , David Saint-Martin (11) , Gavin Schmidt , Akitomo Yamamoto , Shuting Yang (12)

1 CCSR - Center for Climate System Research [Kashiwa]
2 Department of Psychology [York, UK]
3 NCAR - National Center for Atmospheric Research [Boulder]
4 LMD - Laboratoire de Météorologie Dynamique (UMR 8539)
5 IPSL - Institut Pierre-Simon-Laplace
6 G2ELab - Laboratoire de Génie Electrique de Grenoble
7 UOR - University of Reading
8 IAC - Institute for Atmospheric and Climate Science [Zürich]
9 BUAA - Beihang University
10 MPI-M - Max Planck Institute for Meteorology
11 CNRM - Centre national de recherches météorologiques
12 DMI - Danish Meteorological Institute

Domaines: Océan, Atmosphère

Maria Rugenstein, Jonah Bloch-Johnson, Ayako Abe-Ouchi, Timothy J. Andrews, Urs Beyerle, et al.. LongRunMIP -motivation and design for a large collection of millennial-length AO-GCM simulations 2. Bulletin of the American Meteorological Society, 2019, ⟨10.1175/BAMS-D-19-0068.1⟩. ⟨hal-02385682⟩