These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.HighResMIP.AWI.AWI-CM-1-1-LR' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The AWI-CM 1.1 LR climate model, released in 2018, includes the following components: atmos: ECHAM6.3.04p1 (T63L47 native atmosphere T63 gaussian grid; 192 x 96 longitude/latitude; 47 levels; top level 80 km), land: JSBACH 3.20, ocean: FESOM 1.4 (unstructured grid in the horizontal with 126859 wet nodes; 46 levels; top grid cell 0-5 m), seaIce: FESOM 1.4. The model was run by the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany (AWI) in native nominal resolutions: atmos: 250 km, land: 250 km, ocean: 50 km, seaIce: 50 km.
Semmler, Tido; Danilov, Sergey; Rackow, Thomas; Sidorenko, Dmitry; Hegewald, Jan; Sein, Dmitri; Wang, Qiang; Jung, Thomas (2023). IPCC DDC: AWI AWI-CM 1.1 LR model output prepared for CMIP6 HighResMIP. World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/AR6.C6HRAWACL
[1] DOIIntergovernmental Panel on Climate Change (IPCC). (2023). Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. doi:10.1017/9781009157896
Is part of
[1] DOISemmler, Tido; Danilov, Sergey; Rackow, Thomas; Sidorenko, Dmitry; Hegewald, Jan; Sein, Dmitri; Wang, Qiang; Jung, Thomas. (2017). AWI AWI-CM 1.1 LR model output prepared for CMIP6 HighResMIP. doi:10.22033/ESGF/CMIP6.1209
Is referenced by
[1] DOIPonsoni, Leandro; Massonnet, François; Docquier, David; Van Achter, Guillian; Fichefet, Thierry. (2020). Statistical predictability of the Arctic sea ice volume anomaly: identifying predictors and optimal sampling locations. doi:10.5194/tc-14-2409-2020
[2] DOIPonsoni, Leandro; Massonnet, François; Docquier, David; Van Achter, Guillian; Fichefet, Thierry. (2019). Statistical predictability of the Arctic sea ice volume anomaly: identifying predictors and optimal sampling locations. doi:10.5194/tc-2019-257