NAHosMIP data

• Main Authors: Jackson, Laura, Alastue de Asenjo, Eduardo, Bellomo, Katinka, Danabasoglu, Gokhan, Hu, Aixue, Jungclaus, Johann, Lee, Warren, Meccia, Virna, Saenko, Oleg, Shao, Andrew, Swingedouw, Didier
• Format: Other/Unknown Material
• Language: unknown
• Published: Zenodo 2022
• Subjects: NAHosMIP; Greenland; North Atlantic; Sea ice
• Online Access: https://doi.org/10.5281/zenodo.6786568

This package is of data and code from the publicationJackson et al, (2022), Understanding AMOC stability: the North Atlantic Hosing Model Intercomparison Project. GMD [Full reference to come] This is the initial paper ofthe North Atlantic Hosing Model Intercomparison Project (NAHosMIP). See https://www.tipes.dk/na-hosing-mip/ Data included is from several experiments: Priority u03-hos Uniform hosing of 0.3Sv in the North Atlantic Priority u03-r20 Initialised 20yrs into u03-hos with no additional hosing Priority u03-r50 Initialised 50yrs into u03-hos with no additional hosing u03-r70 Initialised 70yrs into u03-hos with no additional hosing u03-r100 Initialised 100yrs into u03-hos with no additional hosing Priority g01-hos Hosing around Greenland of 0.1Sv Priority g01-r50 Initialised 50yrs into g01-hos with no additional hosing g01-r100 Initialised 100yrs into g01-hos with no additional hosing The models that have run this protocol are: CESM2, CanESM5, EC-Earth3, HadGEM3-GC3-1LL, HadGEM3-GC3-1MM, IPSL-CM6A-LR, MPI-ESM1-2-HR, MPI-ESM1-2-LR. Not all of these experiments are conducted with all models. Also MPI-ESM1-2-LR has the same experiments repeated with 0.5Sv uniform hosing (u05) and 0.3Sv hosing around Greenland (g03). Annual mean data for the AMOC streamfunction in depth and latitude space in all experiments is available in the files MODEL_msftmz.tar and MODEL msftyz.tar. MLD.tar contain March mixed layer depth from u03-hos for all models. SST.tar andSSS.tar containannual mean sea surface temperature and salinity, and SICE.tar contains march sea ice concentrationfrom u03-hos for all models. FOV.tar contains data for Fov from the controls (mostly as netcdf, but in a some cases as a python pickle file). For some models this is output as a standard diagnostic, but for other models it has been calculated offline using monthly mean meridional velocity and salinity files. The script for calculating Fov is listed below as calc_fov.py Con_MLD.tar shows March mixed layer depth from the controls for all modelsand ...