{ "cells": [ { "cell_type": "markdown", "id": "b5853c5b-5a7c-4c54-baaa-1e6848125fb4", "metadata": {}, "source": [ "# Barotropic Streamfunction (MOM6-only)\n", " \n", "This recipe demonstrates how to compute and plot the barotropic streamfunction ($\\psi$) from MOM6 output.\n", "\n", "The workflow is,\n", "1. Load the MOM6 depth-integrated zonal mass transport (`umo_2d`).\n", "2. Convert it to volume transport in Sverdrups (`Sv`).\n", "3. Integrate meridionally (cumulative sum along latitude) to obtain the barotropic streamfunction ($\\psi$).\n", "4. Plot a circumpolar map with a circular boundary and land mask.\n", "\n", "## Physical background\n", "\n", "The barotropic streamfunction ($\\psi$) is obtained from the integration of the velocity field starting from a physical boundary at which we know the transport is zero. The difference between to streamlines is a measure of the transport between them. \n", "\n", "There are different ways to calculate it depending on your choice of boundary for the integration. This notebook calculates it integrating in the meridional space, starting from the Antarctic continent using the zonal velocity field:\n", "\n", "$$\n", "\\psi = \\int_{y_{\\rm Antarctica}}^{y} U \\, \\mathrm{d}y ,\n", "$$\n", "\n", "where $U = \\int u \\, \\mathrm{dz}$ is the depth-integrated $u$-velocity.\n", "\n", "### MOM6 settings\n", "\n", "```python\n", "expt = \"panant-01-zstar-v13\"\n", "transport_var = \"umo_2d\" # zonal mass transport\n", "bathy_var = \"deptho\" # bathymetry\n", "```\n", "with,\n", "- coordinates: `yh` (latitude) and `xh` (longitude)\n", "- land mask: `deptho` is NaN over land.\n", "\n", "### MOM5 settings\n", "To adapt this recipe for MOM5 output, update the variables as follows,\n", "```python\n", "expt = \"01deg_jra55v13_ryf9091\"\n", "transport_var = \"tx_trans_int_z\" # zonal mass transport\n", "bathy_var = \"ht\" # bathymetry\n", "```\n", "with,\n", "- coordinates: `yt_ocean` (latitude) and `xt_ocean` (longitude)\n", "- land mask: `ht` is NaN over land." ] }, { "cell_type": "code", "execution_count": 1, "id": "73aeb9e5-5d66-40b5-8cb7-4fd3f62b3fc5", "metadata": {}, "outputs": [], "source": [ "import warnings\n", "import numpy as np\n", "import xarray as xr\n", "import matplotlib.path as mpath\n", "import matplotlib.pyplot as plt\n", "import cartopy.crs as ccrs\n", "import cmocean\n", "import dask.distributed as dask\n", "import intake\n", "warnings.simplefilter(action=\"ignore\", category=UserWarning)" ] }, { "cell_type": "code", "execution_count": 2, "id": "61285a8a-1b9e-4021-a92d-8bd7b5d00cc9", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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modeldescriptionrealmfrequencyvariable
name
01deg_jra55_ryf_Control{ACCESS-OM2-01}{0.1° ACCESS-OM2 repeat year forcing control run for the simulations performed in Huguenin et al. (2024, GRL)}{ocean, seaIce}{1mon, fx}{geolon_t, sss_m, total_ocean_sens_heat, aice_m, temp_advection, neutral, strength_m, fswup_m, temp_eta_smooth_on_nrho, time, time_bnds, scalar_axis, evap, strairx_m, total_net_sfc_heating, eta_gl...
01deg_jra55_ryf_ENFull{ACCESS-OM2}{0.1° ACCESS-OM2 El Níño run for the simulations performed in Huguenin et al. (2024, GRL)}{ocean, seaIce}{1mon, fx}{geolon_t, sss_m, total_ocean_sens_heat, aice_m, temp_advection, neutral, strength_m, fswup_m, time, time_bnds, scalar_axis, evap, strairx_m, total_net_sfc_heating, eta_global, sw_edges_ocean, pot...
01deg_jra55_ryf_LNFull{ACCESS-OM2}{0.1° ACCESS-OM2 La Níña run for the simulations performed in Huguenin et al. (2024, GRL)}{ocean, seaIce}{1mon, fx}{geolon_t, sss_m, total_ocean_sens_heat, aice_m, temp_advection, neutral, strength_m, fswup_m, time, time_bnds, scalar_axis, evap, strairx_m, total_net_sfc_heating, eta_global, sw_edges_ocean, pot...
01deg_jra55v13_ryf9091{ACCESS-OM2-01}{0.1 degree ACCESS-OM2 global model configuration with JRA55-do v1.3 RYF9091 repeat year forcing (May 1990 to Apr 1991)}{ocean, seaIce}{1mon, 3hr, 1day, 3mon, fx}{yu_ocean_sub02, geolon_t, sss_m, total_ocean_sens_heat, aice_m, temp_advection, neutral, strength_m, fswup_m, rho, time, yt_ocean_sub01, scalar_axis, evap, strairx_m, total_net_sfc_heating, eta_g...
01deg_jra55v13_ryf9091_easterlies_down10{ACCESS-OM2-01}{0.1 degree ACCESS-OM2 global model configuration with JRA55-do v1.3 RYF9091 repeat year forcing (May 1990 to Apr 1991) and zonal/meridional wind speed around Antarctica decreased by 10%.}{ocean, seaIce}{1mon, fx, 1day}{geolon_t, sss_m, total_ocean_sens_heat, aice_m, neutral, strength_m, fswup_m, time, scalar_axis, evap, strairx_m, eta_global, sw_edges_ocean, potrho, pot_rho_0, TLON, total_ocean_river, average_T...
01deg_jra55v13_ryf9091_easterlies_up10{ACCESS-OM2-01}{0.1 degree ACCESS-OM2 global model configuration with JRA55-do v1.3 RYF9091 repeat year forcing (May 1990 to Apr 1991) and zonal/meridional wind speed around Antarctica increased by 10%.}{ocean, seaIce}{1mon, fx, 1day}{geolon_t, sss_m, total_ocean_sens_heat, aice_m, neutral, strength_m, fswup_m, time, scalar_axis, evap, strairx_m, eta_global, sw_edges_ocean, potrho, pot_rho_0, TLON, total_ocean_river, average_T...
01deg_jra55v13_ryf9091_easterlies_up10_meridional{ACCESS-OM2-01}{0.1 degree ACCESS-OM2 global model configuration with JRA55-do v1.3 RYF9091 repeat year forcing (May 1990 to Apr 1991) and meridional wind speed around Antarctica increased by 10%.}{ocean, seaIce}{1mon, fx, 1day}{geolon_t, sss_m, total_ocean_sens_heat, aice_m, neutral, strength_m, fswup_m, time, scalar_axis, evap, strairx_m, eta_global, sw_edges_ocean, potrho, pot_rho_0, TLON, total_ocean_river, average_T...
01deg_jra55v13_ryf9091_easterlies_up10_zonal{ACCESS-OM2-01}{0.1 degree ACCESS-OM2 global model configuration with JRA55-do v1.3 RYF9091 repeat year forcing (May 1990 to Apr 1991) and zonal wind speed around Antarctica increased by 10%.}{ocean, seaIce}{1mon, fx, 1day}{geolon_t, sss_m, total_ocean_sens_heat, aice_m, neutral, strength_m, fswup_m, time, scalar_axis, evap, strairx_m, eta_global, sw_edges_ocean, potrho, pot_rho_0, TLON, total_ocean_river, average_T...
01deg_jra55v13_ryf9091_qian_wthmp{ACCESS-OM2}{Future perturbations with wind, thermal and meltwater forcing, branching off 01deg_jra55v13_ryf9091, as described in Li et al. 2023, https://www.nature.com/articles/s41586-023-05762-w}{ocean, seaIce}{1mon, fx}{geolon_t, sss_m, total_ocean_sens_heat, aice_m, temp_advection, strength_m, fswup_m, time, scalar_axis, evap, strairx_m, eta_global, sw_edges_ocean, potrho, pot_rho_0, TLON, total_ocean_river, av...
01deg_jra55v13_ryf9091_qian_wthp{ACCESS-OM2}{Future perturbation with wind and thermal forcing, branching off 01deg_jra55v13_ryf9091, as described in Li et al. 2023, https://www.nature.com/articles/s41586-023-05762-w}{ocean, seaIce}{1mon, fx}{geolon_t, sss_m, total_ocean_sens_heat, aice_m, temp_advection, strength_m, fswup_m, time, scalar_axis, evap, strairx_m, eta_global, sw_edges_ocean, potrho, pot_rho_0, TLON, total_ocean_river, av...
01deg_jra55v13_ryf9091_weddell_down2{ACCESS-OM2-01}{Weddell Sea decreased meltwater perturbation experiment, branched off 01deg_jra55v13_ryf9091. }{ocean, seaIce}{1mon, fx, 1day}{geolon_t, sss_m, total_ocean_sens_heat, aice_m, neutral, strength_m, fswup_m, time, scalar_axis, evap, strairx_m, eta_global, sw_edges_ocean, potrho, pot_rho_0, TLON, total_ocean_river, average_T...
01deg_jra55v13_ryf9091_weddell_up1{ACCESS-OM2-01}{Weddell Sea increased meltwater perturbation experiment, branched off 01deg_jra55v13_ryf9091. }{ocean, seaIce}{1mon, fx, 1day}{geolon_t, sss_m, total_ocean_sens_heat, aice_m, neutral, strength_m, fswup_m, time, scalar_axis, evap, strairx_m, eta_global, sw_edges_ocean, potrho, pot_rho_0, TLON, total_ocean_river, average_T...
01deg_jra55v140_iaf{ACCESS-OM2-01}{Cycle 1 of 0.1 degree ACCESS-OM2 global model configuration with JRA55-do v1.4.0 OMIP2 interannual forcing}{ocean, seaIce}{1mon, fx, 1day}{geolon_t, total_ocean_sens_heat, frazil, aice_m, uvel, neutral, strength_m, fswup_m, time, vvel, scalar_axis, evap, eta_nonbouss, hs, total_net_sfc_heating, strairx_m, eta_global, sw_edges_ocean,...
01deg_jra55v140_iaf_cycle2{ACCESS-OM2-01}{Cycle 2 of 0.1 degree ACCESS-OM2 global model configuration with JRA55-do v1.4.0 OMIP2 interannual forcing}{ocean, seaIce}{1mon, fx, 1day}{geolon_t, total_ocean_sens_heat, frazil, surface_temp_max, dvirdgdt_m, aice_m, VGRDi, uvel, neutral, strength_m, fswup_m, time, vvel, scalar_axis, evap, eta_nonbouss, hs, total_net_sfc_heating, s...
01deg_jra55v140_iaf_cycle3{ACCESS-OM2-01}{Cycle 3 of 0.1 degree ACCESS-OM2 global model configuration with JRA55-do v1.4.0 OMIP2 interannual forcing}{ocean, seaIce}{1mon, fx, 1day}{geolon_t, total_ocean_sens_heat, frazil, dvirdgdt_m, aice_m, VGRDi, uvel, neutral, strength_m, fswup_m, time, vvel, scalar_axis, evap, eta_nonbouss, hs, total_net_sfc_heating, strairx_m, eta_glob...
01deg_jra55v140_iaf_cycle4{ACCESS-OM2-01}{Cycle 4 of 0.1 degree ACCESS-OM2 global model configuration with JRA55-do v1.4.0 OMIP2 interannual forcing}{ocean, seaIce}{1mon, 3hr, 1day, 6hr, fx}{dvirdgdt_m, uvel, fNO_ai_m, radbio_intmld, strocny_m, frzmlt, TLON, no3_int100, phy_intmld, grid_xu_ocean, ke_tot, ht, Tinz, river, vvel_h, sea_level_sq, caco3, alidf_ai_m, fswabs_ai_m, fsurf_ai_...
01deg_jra55v140_iaf_cycle4_jra55v150_extension{ACCESS-OM2-01}{Extensions of cycle 4 of 0.1 degree ACCESS-OM2 + WOMBAT BGC global model configuration with JRA55-do v1.5.0 and v1.5.0.1 interannual forcing}{ocean, seaIce}{subhr, 1mon, fx, 1day}{dvirdgdt_m, uvel, fNO_ai_m, radbio_intmld, strocny_m, frzmlt, TLON, no3_int100, phy_intmld, grid_xu_ocean, ke_tot, ht, river, sea_level_sq, caco3, alidf_ai_m, fswabs_ai_m, fsurf_ai_m, fsalt_m, dv...
01deg_jra55v150_iaf_cycle1{ACCESS-OM2}{Cycle 1 of 0.1 degree ACCESS-OM2 global model configuration with JRA55-do v1.5.0 OMIP2 interannual forcing}{ocean, seaIce}{1mon, fx, 1day}{geolon_t, aice_m, neutral, time, time_bnds, eta_nonbouss, evap, potrho, TLON, average_T2, sfc_salt_flux_restore, ty_trans_submeso, ht, river, potrho_edges, ULON, neutralrho_edges, sea_level_sq, a...
025deg_era5_iaf{ACCESS-OM2}{0.25 degree ACCESS-OM2 global model configuration with ERA5 interannual\\nforcing (1980-2021)}{ocean, seaIce}{1mon, fx, 1day}{geolon_t, sice_m, total_ocean_sens_heat, frazil, aice_m, temp_yflux_submeso_int_z, uvel, neutral, strength_m, fswup_m, flwup_ai_m, time, vvel, time_bnds, scalar_axis, eta_nonbouss, evap, hs, tota...
025deg_era5_ryf{ACCESS-OM2}{0.25 degree ACCESS-OM2 global model configuration with ERA5 RYF9091 repeat\\nyear forcing (May 1990 to Apr 1991)}{ocean, seaIce}{1mon, fx, 1day}{geolon_t, sice_m, total_ocean_sens_heat, frazil, aice_m, temp_yflux_submeso_int_z, uvel, neutral, strength_m, fswup_m, flwup_ai_m, time, vvel, time_bnds, scalar_axis, evap, eta_nonbouss, hs, tota...
025deg_jra55_iaf_era5comparison{ACCESS-OM2}{0.25 degree ACCESS-OM2 global model configuration with JRA55-do v1.5.0\\ninterannual forcing (1980-2019)}{ocean, seaIce}{1mon, fx, 1day}{geolon_t, sice_m, total_ocean_sens_heat, frazil, aice_m, temp_yflux_submeso_int_z, uvel, neutral, strength_m, fswup_m, flwup_ai_m, time, vvel, time_bnds, scalar_axis, eta_nonbouss, evap, hs, tota...
025deg_jra55_iaf_omip2_cycle1{ACCESS-OM2}{Cycle 1/6 of 0.25 degree ACCESS-OM2 physics-only global configuration with JRA55-do v1.4 OMIP2 interannual forcing (1958-2019)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{dvirdgdt_m, uvel, strocny_m, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, diff_cbt_s, sea_level_sq, sw_heat, alidf_ai_m, fswabs_ai_m, fsurf_ai_m, fsalt_m, dvidtt_m, divu_m, temp_xflu...
025deg_jra55_iaf_omip2_cycle2{ACCESS-OM2}{Cycle 1/6 of 0.25 degree ACCESS-OM2 physics-only global configuration with JRA55-do v1.4 OMIP2 interannual forcing (1958-2019)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{dvirdgdt_m, uvel, strocny_m, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, diff_cbt_s, sea_level_sq, sw_heat, alidf_ai_m, fswabs_ai_m, fsurf_ai_m, fsalt_m, dvidtt_m, divu_m, temp_xflu...
025deg_jra55_iaf_omip2_cycle3{ACCESS-OM2}{Cycle 3/6 of 0.25 degree ACCESS-OM2 physics-only global configuration with JRA55-do v1.4 OMIP2 interannual forcing (1958-2019)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{dvirdgdt_m, uvel, strocny_m, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, diff_cbt_s, sea_level_sq, sw_heat, alidf_ai_m, fswabs_ai_m, fsurf_ai_m, fsalt_m, dvidtt_m, divu_m, temp_xflu...
025deg_jra55_iaf_omip2_cycle4{ACCESS-OM2}{Cycle 4/6 of 0.25 degree ACCESS-OM2 physics-only global configuration with JRA55-do v1.4 OMIP2 interannual forcing (1958-2019)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{dvirdgdt_m, uvel, strocny_m, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, diff_cbt_s, sea_level_sq, sw_heat, alidf_ai_m, fswabs_ai_m, fsurf_ai_m, fsalt_m, dvidtt_m, divu_m, temp_xflu...
025deg_jra55_iaf_omip2_cycle5{ACCESS-OM2}{Cycle 5/6 of 0.25 degree ACCESS-OM2 physics-only global configuration with JRA55-do v1.4 OMIP2 interannual forcing (1958-2019)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{dvirdgdt_m, uvel, strocny_m, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, diff_cbt_s, sea_level_sq, sw_heat, alidf_ai_m, fswabs_ai_m, fsurf_ai_m, fsalt_m, dvidtt_m, divu_m, temp_xflu...
025deg_jra55_iaf_omip2_cycle6{ACCESS-OM2}{Cycle 6/6 of 0.25 degree ACCESS-OM2 physics-only global configuration with JRA55-do v1.4 OMIP2 interannual forcing (1958-2019)}{ocean, seaIce}{1mon, fx, 1day}{dvirdgdt_m, uvel, strocny_m, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, diff_cbt_s, sea_level_sq, sw_heat, alidf_ai_m, fswabs_ai_m, fsurf_ai_m, fsalt_m, dvidtt_m, divu_m, temp_xflu...
025deg_jra55_ryf9091_gadi{ACCESS-OM2}{0.25 degree ACCESS-OM2 physics-only global configuration with JRA55-do v1.3 RYF9091 repeat year forcing (May 1990 to Apr 1991)}{ocean, seaIce}{1mon, fx, 1yr}{geolon_t, sice_m, total_ocean_sens_heat, sss_m, aice_m, strength_m, fswup_m, flwup_ai_m, time, scalar_axis, strairx_m, strocny_m, eta_global, sw_edges_ocean, potrho, pot_rho_0, TLON, total_ocean_...
025deg_jra55_ryf_era5comparison{ACCESS-OM2}{0.25 degree ACCESS-OM2 global model configuration with JRA55-do v1.4.0\\nRYF9091 repeat year forcing (May 1990 to Apr 1991)}{ocean, seaIce}{1mon, fx, 1day}{geolon_t, sice_m, total_ocean_sens_heat, frazil, aice_m, temp_yflux_submeso_int_z, uvel, neutral, strength_m, fswup_m, flwup_ai_m, time, vvel, scalar_axis, evap, eta_nonbouss, hs, total_net_sfc_h...
1deg_era5_iaf{ACCESS-OM2}{1 degree ACCESS-OM2 global model configuration with ERA5 interannual\\nforcing (1960-2019)}{ocean, seaIce}{1mon, fx, 1day}{geolon_t, sice_m, total_ocean_sens_heat, frazil, aice_m, temp_yflux_submeso_int_z, uvel, neutral, strength_m, fswup_m, flwup_ai_m, time, vvel, time_bnds, scalar_axis, evap, eta_nonbouss, hs, tota...
1deg_era5_ryf{ACCESS-OM2}{1 degree ACCESS-OM2 global model configuration with ERA5 RYF9091 repeat\\nyear forcing (May 1990 to Apr 1991)}{ocean, seaIce}{1mon, fx, 1day}{geolon_t, sice_m, total_ocean_sens_heat, frazil, aice_m, temp_yflux_submeso_int_z, uvel, strength_m, fswup_m, flwup_ai_m, time, vvel, time_bnds, scalar_axis, eta_nonbouss, evap, hs, total_net_sfc...
1deg_jra55_iaf_era5comparison{ACCESS-OM2}{1 degree ACCESS-OM2 global model configuration with JRA55-do v1.4.0\\ninterannual forcing (1960-2019)}{ocean, seaIce}{1mon, fx, 1day}{geolon_t, sice_m, total_ocean_sens_heat, frazil, aice_m, temp_yflux_submeso_int_z, uvel, neutral, strength_m, fswup_m, flwup_ai_m, time, vvel, scalar_axis, evap, eta_nonbouss, hs, total_net_sfc_h...
1deg_jra55_iaf_omip2_cycle1{ACCESS-OM2}{Cycle 1/6 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{uvel, strocny_m, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, diff_cbt_s, sea_level_sq, caco3, sw_heat, alidf_ai_m, fswabs_ai_m, fsalt_m, dvidtt_m, fgco2_raw, divu_m, temp_xflux_ndif...
1deg_jra55_iaf_omip2_cycle2{ACCESS-OM2}{Cycle 2/6 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{uvel, strocny_m, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, diff_cbt_s, sea_level_sq, caco3, sw_heat, alidf_ai_m, fswabs_ai_m, fsalt_m, dvidtt_m, fgco2_raw, divu_m, temp_xflux_ndif...
1deg_jra55_iaf_omip2_cycle3{ACCESS-OM2}{Cycle 3/6 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{uvel, strocny_m, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, diff_cbt_s, sea_level_sq, caco3, sw_heat, alidf_ai_m, fswabs_ai_m, fsalt_m, dvidtt_m, fgco2_raw, divu_m, temp_xflux_ndif...
1deg_jra55_iaf_omip2_cycle4{ACCESS-OM2}{Cycle 4/6 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{uvel, strocny_m, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, diff_cbt_s, sea_level_sq, caco3, sw_heat, alidf_ai_m, fswabs_ai_m, fsalt_m, dvidtt_m, fgco2_raw, divu_m, temp_xflux_ndif...
1deg_jra55_iaf_omip2_cycle5{ACCESS-OM2}{Cycle 5/6 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{uvel, strocny_m, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, diff_cbt_s, sea_level_sq, caco3, sw_heat, alidf_ai_m, fswabs_ai_m, fsalt_m, dvidtt_m, fgco2_raw, divu_m, temp_xflux_ndif...
1deg_jra55_iaf_omip2_cycle6{ACCESS-OM2}{Cycle 6/6 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{uvel, strocny_m, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, diff_cbt_s, sea_level_sq, caco3, sw_heat, alidf_ai_m, fswabs_ai_m, fsalt_m, dvidtt_m, fgco2_raw, divu_m, temp_xflux_ndif...
1deg_jra55_iaf_omip2spunup_cycle1{ACCESS-OM2}{Cycle 1/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{uvel, strocny_m, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, diff_cbt_s, sea_level_sq, caco3, sw_heat, alidf_ai_m, fswabs_ai_m, fsalt_m, dvidtt_m, fgco2_raw, divu_m, temp_xflux_ndif...
1deg_jra55_iaf_omip2spunup_cycle10{ACCESS-OM2}{Cycle 10/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle11{ACCESS-OM2}{Cycle 11/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle12{ACCESS-OM2}{Cycle 12/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle13{ACCESS-OM2}{Cycle 13/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle14{ACCESS-OM2}{Cycle 14/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle15{ACCESS-OM2}{Cycle 15/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle16{ACCESS-OM2}{Cycle 16/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle17{ACCESS-OM2}{Cycle 17/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle18{ACCESS-OM2}{Cycle 18/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle19{ACCESS-OM2}{Cycle 19/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle2{ACCESS-OM2}{Cycle 2/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{uvel, strocny_m, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, diff_cbt_s, sea_level_sq, caco3, sw_heat, alidf_ai_m, fswabs_ai_m, fsalt_m, dvidtt_m, fgco2_raw, divu_m, temp_xflux_ndif...
1deg_jra55_iaf_omip2spunup_cycle20{ACCESS-OM2}{Cycle 20/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle21{ACCESS-OM2}{Cycle 21/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle22{ACCESS-OM2}{Cycle 22/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle23{ACCESS-OM2}{Cycle 23/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle24{ACCESS-OM2}{Cycle 24/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle25{ACCESS-OM2}{Cycle 25/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle26{ACCESS-OM2}{Cycle 26/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle27{ACCESS-OM2}{Cycle 27/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle28{ACCESS-OM2}{Cycle 28/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle29{ACCESS-OM2}{Cycle 29/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle3{ACCESS-OM2}{Cycle 3/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{uvel, strocny_m, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, diff_cbt_s, sea_level_sq, caco3, sw_heat, alidf_ai_m, fswabs_ai_m, fsalt_m, dvidtt_m, fgco2_raw, divu_m, temp_xflux_ndif...
1deg_jra55_iaf_omip2spunup_cycle30{ACCESS-OM2}{Cycle 30/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle31{ACCESS-OM2}{Cycle 31/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle32{ACCESS-OM2}{Cycle 32/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle33{ACCESS-OM2}{Cycle 33/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle34{ACCESS-OM2}{Cycle 34/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{geolon_t, salt_eta_smooth, total_ocean_sens_heat, aice_m, temp_yflux_submeso_int_z, hblt_max, alk, temp_advection, neutral, vsq, ULAT, fswup_m, rho, time, sss_sq, aiso_bih, scalar_axis, evap, tot...
1deg_jra55_iaf_omip2spunup_cycle35{ACCESS-OM2}{Cycle 35/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{geolon_t, salt_eta_smooth, total_ocean_sens_heat, aice_m, temp_yflux_submeso_int_z, hblt_max, alk, temp_advection, neutral, vsq, ULAT, fswup_m, rho, time, sss_sq, aiso_bih, scalar_axis, evap, tot...
1deg_jra55_iaf_omip2spunup_cycle36{ACCESS-OM2}{Cycle 36/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{geolon_t, salt_eta_smooth, total_ocean_sens_heat, aice_m, temp_yflux_submeso_int_z, hblt_max, alk, temp_advection, neutral, vsq, ULAT, fswup_m, rho, time, sss_sq, aiso_bih, scalar_axis, evap, tot...
1deg_jra55_iaf_omip2spunup_cycle37{ACCESS-OM2}{Cycle 37/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{geolon_t, salt_eta_smooth, total_ocean_sens_heat, aice_m, temp_yflux_submeso_int_z, hblt_max, alk, temp_advection, neutral, vsq, ULAT, fswup_m, rho, time, sss_sq, aiso_bih, scalar_axis, evap, tot...
1deg_jra55_iaf_omip2spunup_cycle38{ACCESS-OM2}{Cycle 38/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{geolon_t, salt_eta_smooth, total_ocean_sens_heat, aice_m, temp_yflux_submeso_int_z, hblt_max, alk, temp_advection, neutral, vsq, ULAT, fswup_m, rho, time, sss_sq, aiso_bih, scalar_axis, evap, tot...
1deg_jra55_iaf_omip2spunup_cycle39{ACCESS-OM2}{Cycle 39/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{geolon_t, salt_eta_smooth, total_ocean_sens_heat, aice_m, temp_yflux_submeso_int_z, hblt_max, alk, temp_advection, neutral, vsq, ULAT, fswup_m, rho, time, sss_sq, aiso_bih, scalar_axis, evap, tot...
1deg_jra55_iaf_omip2spunup_cycle4{ACCESS-OM2}{Cycle 4/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{uvel, strocny_m, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, diff_cbt_s, sea_level_sq, caco3, sw_heat, alidf_ai_m, fswabs_ai_m, fsalt_m, dvidtt_m, fgco2_raw, divu_m, temp_xflux_ndif...
1deg_jra55_iaf_omip2spunup_cycle40{ACCESS-OM2}{Cycle 40/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle41{ACCESS-OM2}{Cycle 41/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle42{ACCESS-OM2}{Cycle 42/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle43{ACCESS-OM2}{Cycle 43/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle44{ACCESS-OM2}{Cycle 44/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle45{ACCESS-OM2}{Cycle 45/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle5{ACCESS-OM2}{Cycle 5/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{geolon_t, salt_eta_smooth, total_ocean_sens_heat, aice_m, temp_yflux_submeso_int_z, hblt_max, alk, temp_advection, neutral, vsq, ULAT, fswup_m, rho, time, sss_sq, aiso_bih, scalar_axis, evap, tot...
1deg_jra55_iaf_omip2spunup_cycle6{ACCESS-OM2}{Cycle 6/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1yr, 1mon, fx, 1day}{geolon_t, salt_eta_smooth, total_ocean_sens_heat, aice_m, temp_yflux_submeso_int_z, hblt_max, alk, temp_advection, neutral, vsq, ULAT, fswup_m, rho, time, sss_sq, aiso_bih, scalar_axis, evap, tot...
1deg_jra55_iaf_omip2spunup_cycle7{ACCESS-OM2}{Cycle 7/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1day, 1mon, 1yr}{sice_m, frazil, aice_m, alk, uvel, strength_m, fswup_m, flwup_ai_m, time, vvel, scalar_axis, strairx_m, hs, strocny_m, eta_global, frzmlt, TLON, average_T2, vvel_m, ULON, HTN, total_mass_seawater...
1deg_jra55_iaf_omip2spunup_cycle8{ACCESS-OM2}{Cycle 8/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_iaf_omip2spunup_cycle9{ACCESS-OM2}{Cycle 9/45 of 1 degree ACCESS-OM2-BGC global configuration with JRA55-do v1.4 OMIP2 spunup interannual forcing (1958-2018)}{ocean, seaIce}{1mon, 1yr}{aice_m, alk, yt_ocean, fswup_m, st_ocean, nv, no3, ANGLET, tarea, phy, uatm_m, time_bounds, uarea, time, hi_m, st_edges_ocean, scalar_axis, fe, alidr_ai_m, eta_global, aicen_m, average_DT, NCAT, ...
1deg_jra55_ryf9091_gadi{ACCESS-OM2}{1 degree ACCESS-OM2 physics-only global configuration with JRA55-do v1.3 RYF9091 repeat year forcing (May 1990 to Apr 1991)}{ocean, seaIce}{1mon, fx, 1yr}{geolon_t, sice_m, total_ocean_sens_heat, sss_m, temp_yflux_adv_on_nrho, aice_m, temp_advection, temp_yflux_gm_on_nrho, neutral, temp_advection_on_nrho, strength_m, fswup_m, temp_eta_smooth_on_nrh...
1deg_jra55v14_ryf{ACCESS-OM2}{1 degree ACCESS-OM2 global model configuration with JRA55-do v1.4.0 RYF9091\\nrepeat year forcing (May 1990 to Apr 1991)}{ocean, seaIce}{1mon, fx, 1day}{geolon_t, sice_m, total_ocean_sens_heat, frazil, aice_m, temp_yflux_submeso_int_z, uvel, strength_m, fswup_m, flwup_ai_m, time, vvel, scalar_axis, eta_nonbouss, evap, hs, total_net_sfc_heating, s...
HI_CN_05{ACCESS-ESM1-5}{Historical run using same configuration as CMIP6 ACCESS-ESM1.5 historical r1i1p1f1, but with phosphorus limitation disabled within CASA-CNP}{atmos, ocean, seaIce}{1mon, 3hr, 1day, 1yr, 6hr}{fld_s03i876, fld_s00i113, frazil_2d, uvel, fld_s30i225, stf10, conv_rho_ud_t, fld_s02i295, TLON, fld_s03i870, grid_xu_ocean, ke_tot, fld_s03i898, ht, ty_trans_rho_gm, fld_s03i812, river, fld_s00i...
HI_C_05_r1{ACCESS-ESM1-5}{Historical run using same configuration as CMIP6 ACCESS-ESM1.5 historical r1i1p1f1, but with nitrogen and phosphorus limitations disabled within CASA-CNP}{atmos, ocean, seaIce}{1yr, 1mon, 1day}{fld_s03i876, fld_s00i113, frazil_2d, uvel, fld_s30i225, stf10, conv_rho_ud_t, fld_s02i295, TLON, fld_s03i870, grid_xu_ocean, ke_tot, fld_s03i898, ht, ty_trans_rho_gm, fld_s03i812, river, fld_s00i...
HI_nl_C_05_r1{ACCESS-ESM1-5}{Historical run using same configuration as CMIP6 ACCESS-ESM1.5 historical r1i1p1f1, but with nitrogen and phosphorus limitations disabled within CASA-CNP, and land-use change disabled}{atmos, ocean, seaIce}{1yr, 1mon, 1day}{fld_s03i876, fld_s00i113, frazil_2d, uvel, fld_s30i225, stf10, conv_rho_ud_t, fld_s02i295, TLON, fld_s03i870, grid_xu_ocean, ke_tot, fld_s03i898, ht, ty_trans_rho_gm, fld_s03i812, river, fld_s00i...
HI_noluc_CN_05{ACCESS-ESM1-5}{Historical run using same configuration as CMIP6 ACCESS-ESM1.5 historical r1i1p1f1, but with phosphorus limitation disabled within CASA-CNP, and land-use change disabled}{atmos, ocean, seaIce}{1mon, 3hr, 1day, 1yr, 6hr}{fld_s03i876, fld_s00i113, frazil_2d, uvel, fld_s30i225, stf10, conv_rho_ud_t, fld_s02i295, TLON, fld_s03i870, grid_xu_ocean, ke_tot, fld_s03i898, ht, ty_trans_rho_gm, fld_s03i812, river, fld_s00i...
OM4_025.JRA_RYF{SIS2, MOM6}{0.25 degree GFDL-OM4 (MOM6+SIS2) global model configuration under 1990-1991 JRA55-do repeat year forcing.}{ocean, seaIce}{1yr, 1mon, fx, 1day}{rlntds, pbo, vo, wet_u, friver, geolat_u, so_xyave, sob, tosmin, ficeberg, pso, areacello, time, time_bnds, scalar_axis, heat_content_massout, uh, dyCu, T_adx, geolon, average_T2, sftof, thetaoga...
PI_GWL_B2035{ACCESS-ESM1-5}{Climate stabilization run at different global warming levels with zero C02 emissions and pre-industrial aerosols, starting in 2035 }{atmos, ocean, seaIce}{1yr, 1mon, 1day}{fld_s03i876, fld_s00i113, frazil_2d, uvel, fld_s30i225, stf10, conv_rho_ud_t, fld_s02i295, TLON, fld_s03i870, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, fld_s03i812, river, fld_s00i116, fld_s03i...
PI_GWL_B2040{ACCESS-ESM1-5}{Climate stabilization run at different global warming levels with zero C02 emissions and pre-industrial aerosols, starting in 2040}{atmos, ocean, seaIce}{1yr, 1mon, 1day}{fld_s03i876, fld_s00i113, frazil_2d, uvel, fld_s30i225, stf10, conv_rho_ud_t, fld_s02i295, TLON, fld_s03i870, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, fld_s03i812, river, fld_s00i116, fld_s03i...
PI_GWL_B2045{ACCESS-ESM1-5}{Climate stabilization run at different global warming levels with zero C02 emissions and pre-industrial aerosols, starting in 2045}{atmos, ocean, seaIce}{1yr, 1mon, 1day}{fld_s03i876, fld_s00i113, frazil_2d, uvel, fld_s30i225, stf10, conv_rho_ud_t, fld_s02i295, TLON, fld_s03i870, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, fld_s03i812, river, fld_s00i116, fld_s03i...
PI_GWL_B2050{ACCESS-ESM1-5}{Climate stabilization run at different global warming levels with zero C02 emissions and pre-industrial aerosols, starting in 2050}{atmos, ocean, seaIce}{1yr, 1mon, 1day}{fld_s03i876, fld_s00i113, frazil_2d, uvel, fld_s30i225, stf10, conv_rho_ud_t, fld_s02i295, TLON, fld_s03i870, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, fld_s03i812, river, fld_s00i116, fld_s03i...
PI_GWL_B2055{ACCESS-ESM1-5}{Climate stabilization run at different global warming levels with zero C02 emissions and pre-industrial aerosols, starting in 2055}{atmos, ocean, seaIce}{1yr, 1mon, 1day}{fld_s03i876, fld_s00i113, frazil_2d, uvel, fld_s30i225, stf10, conv_rho_ud_t, fld_s02i295, TLON, fld_s03i870, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, fld_s03i812, river, fld_s00i116, fld_s03i...
PI_GWL_B2060{ACCESS-ESM1-5}{Climate stabilization run at different global warming levels with zero C02 emissions and pre-industrial aerosols, starting in 2060}{atmos, ocean, seaIce}{1yr, 1mon, 1day}{fld_s03i876, fld_s00i113, frazil_2d, uvel, fld_s30i225, stf10, conv_rho_ud_t, fld_s02i295, TLON, fld_s03i870, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, fld_s03i812, river, fld_s00i116, fld_s03i...
WOA-13{World Ocean Atlas 2013}{2013 World Ocean Atlas (WOA-13), regridded to various model grids.}{ocean}{fx}{GRID_X_T, ZT, temp, salt, GRID_Y_T, time}
barpa_py18{BARPA-R, BARPA-C, BARPA-R1-NN}{Bureau of Meteorology Atmospheric Regional Projections for Australia (BARPA)}{none}{1mon, 3hr, 6hr, 1day, subhr, 1hr, fx}{wap800, va100m, wa950, wap150, hus750, va750, hus950, wap10, va850, zg400, ta100, ztp, MLCIN, helicity, ua20, hus50, MLLCL, rsut, hus500, twisomax, ua200, helicitymax, hus600, hus700, DCP, wap70,...
bx944{ACCESS-CM2}{Standard CMIP6 historical simulation, control experiment for by473 pacemaker experiment (948d8676-2c56-49db-8ea1-b80572b074c8)}{atmos, ocean, seaIce}{1mon, 1day}{frazil_2d, uvel, fld_s30i225, fld_s38i437, sig2, fld_s03i328, fld_s30i298, conv_rho_ud_t, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, fld_s34i071, fld_s03i812, river, fld_s17i257, f...
by473{ACCESS-CM2}{Pacemaker variation of CMIP6 historical simulation, Topical Atlantic region replaced with fixed SSTs from observations}{atmos, ocean, seaIce}{1mon, 1day}{frazil_2d, uvel, fld_s30i225, fld_s38i437, sig2, fld_s03i328, fld_s30i298, conv_rho_ud_t, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, fld_s34i071, fld_s03i812, river, fld_s17i257, f...
by578{ACCESS-CM2}{Pacemaker variation of CMIP6 ssp245 simulation with Tropical Atlantic region replaced with fixed SSTs from observations}{atmos, ocean, seaIce}{1mon, 1day}{frazil_2d, uvel, fld_s30i225, fld_s38i437, sig2, fld_s03i328, fld_s30i298, conv_rho_ud_t, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, fld_s34i071, fld_s03i812, river, fld_s17i257, f...
by647{ACCESS-CM2}{Standard CMIP6 ssp245 simulation, control experiment for by578 pacemaker experiment (1fd9e682-d393-4b17-a9cd-934c3a48a1f8)}{atmos, ocean, seaIce}{1mon, 1day}{frazil_2d, uvel, fld_s30i225, fld_s38i437, sig2, fld_s03i328, fld_s30i298, conv_rho_ud_t, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, fld_s34i071, fld_s03i812, river, fld_s17i257, f...
bz687{ACCESS-CM2}{ACCESS-CM2 CMIP6 with 1 degree ocean. Present day atmospheric forcing with 1985-2014 mean GHG, aerosol emissions etc.}{atmos, ocean, seaIce}{1mon, 1day}{frazil_2d, uvel, fld_s30i225, fld_s38i437, sig2, fld_s03i328, fld_s30i298, conv_rho_ud_t, frzmlt, TLON, grid_xu_ocean, ke_tot, ht, ty_trans_rho_gm, fld_s34i071, fld_s03i812, river, fld_s17i257, f...
cj877{ACCESS-CM2}{ACCESS-CM2 with COSIMA OM2 0.25 degree ocean configuration. Present day atmospheric forcing with 1985-2014 mean GHG, aerosol emissions etc.}{atmos, ocean, seaIce}{1mon, fx, 1day}{uvel, fld_s30i225, fld_s38i437, sig2, fld_s03i328, fld_s30i298, frzmlt, TLON, ke_tot, ht, ty_trans_rho_gm, fld_s34i071, fld_s03i812, river, fld_s17i257, fld_s03i821, sea_level_sq, fld_s03i814, ap...
cmip-forcing-qv56{ImperialCollege-1-1, UoM-GCAM4-ssp434-1-2-0, MRI-JRA55-do-1-4-0, UReading-CCMI-ssp119-1-0, CERES-EBAF_Surface, NCAR-CCMI-ssp245-2-0, UofMD-landState-high-2-1-h, CESM2-ssp585-1-0, CCSM4-rcp85-1-0,...{Earth System Grid (ESGF) Reference Datasets for Climate Model Analysis/Forcing}{none, landIce, atmos, land, ocean, seaIce}{1mon, 3hr, 1day, 1yr, 1hr, fx}{CO2-em-biomassburning, COsmoothedpercentageAGRI, VOC01-alcohols-em-speciated-VOC-anthro, HOCH2CHOpercentageSAVA, C3H8percentageTEMF, CH3COCHOpercentageDEFO, NOx-percentage-SAVA-em-biomassburning,...
cmip5_al33{RACMO22E, CESM1-CAM5, CanAM4, WRF331F, GEOS-5, CFSv2-2011, CCLM5-0-15, WRF341I, CESM1-WACCM, GFDL-HIRAM-C360, RegCM4-4, fio-esm, CNRM-CM5-2, NorESM1-ME, CESM1-BGC, HadGEM2-AO, bcc-csm1-1, ALADIN5...{Replicated CMIP5-era datasets catalogued by NCI}{none, landIce, atmos, land, ocnBgchem, ocean, aerosol, seaIce}{1mon, 3hr, 1day, subhr, 1yr, 6hr, fx}{hfxdiff, masscello, calc, tnhusmp, va, hfsithermds, dems, ficeberg, zo2min, phydiaz, hus600, hus700, prveg, intpbsi, ta850, epsi100, rsdcs, tnsccw, grLateral, concnh4, basin, tnhusa, co3satcalc, ...
cmip5_rr3{CSIRO-Mk3L-1-2, ACCESS1-0, CSIRO-CCAM-1704, CSIRO-Mk3-6-0, UNSW-WRF360K, CSIRO-CCAM, UQ-DES-CCAM, ACCESS1-3, UNSW-WRF360L, UNSW-WRF360J, BOM-SDMa-NRM, CSIRO-CCAM-2008}{Australian CMIP5-era datasets catalogued by NCI}{none, landIce, aerosol, atmos, land, ocean, seaIce}{1mon, 3hr, 1day, 3mon, 6hr, fx, 1hr}{pbo, vo, hfxdiff, friver, masscello, cldncl, va, va850, omlmax, zg400, hus, loadss, hfxba, pso, vsi, loadpoa, concdust, areacello, mrsofc, ta, divice, concdms, drydust, rsut, sconcsoa, ua200, str...
cmip6_fs38{ACCESS-ESM1-5, ACCESS-CM2, ACCESS-OM2-025, ACCESS-OM2}{Australian CMIP6-era datasets catalogued by NCI}{landIce, aerosol, atmos, land, ocnBgchem, ocean, seaIce}{1mon, 3hr, 1day, 1yr, 6hr, fx}{rlntds, masscello, va, rv850, mmraerh2o, hursmin, nwdFracLut, sivols, siextents, basin, po4os, wap, orog, mc, ocontemppadvect, rh, nLitter, thetao, epc100, sftgif, prc, pctisccp, sftlf, mmroa, hf...
cmip6_oi10{EC-Earth3, IPSL-CM5A2-INCA, NorCPM1, E3SM-2-0, CNRM-CM6-1, UKESM1-1-LL, AWI-ESM-1-1-LR, GISS-E2-1-G-CC, EC-Earth3-Veg-LR, ECMWF-IFS-HR, HadGEM3-GC31-MM, EC-Earth3-CC, MIROC-ES2H, GFDL-OM4p5B, Tai...{Replicated CMIP6-era datasets catalogued by NCI}{landIce, atmosChem, atmos, land, ocnBgchem, ocean, aerosol, seaIce}{1mon, 3hr, 1day, subhr, 1yr, 6hr, fx, 1hr}{masscello, va, rv850, ficeberg, nStem, hursmin, prveg, ta850, fracOutLut, opottemprmadvect, basin, po4os, ch4, fDeforestToAtmos, sisali, wap, mlotstsq, ph, orog, cfc11, rh, nLitter, phos, thetao,...
cordex_ig45{ACCESS-ESM1-5, CMCC-ESM2, MRI-ESM2-0, EC-Earth3, MPI-ESM1-2-LR, CNRM-CM6-1-HR, ACCESS-CM2, GFDL-ESM4, FGOALS-g3, GISS-E2-1-G, ERA5, NorESM2-MM}{20km regional projections for CORDEX-CMIP6 from the Queensland Future Climate Science Program}{none}{1hr, 1mon, fx, 1day}{va100m, va850, zg400, rsut, hus500, ua200, hus600, hus700, rsdt, va400, ta850, ua250, tasmax, hus250, va600, prhmax, va1000, psl, zg925, ta925, clh, ua400, snw, cll, sftlaf, orog, mrros, hus200, ...
era5_rt52{era5t, era5-preliminary, era5-derived, era5, era5-1}{ERA5 fifth generation model reanalysis of global climate from ECMWF}{none}{1hr, 1mon, 1day}{vo, mcpr, o3, bfi, metss, licd, tcw, ltlt, slhf, lict, istl2, tcc, msnswrfcs, lshf, tcwv, lsm, w, dndzn, mwp1, 10si, ci, mdts, msdwswrf, vithen, msdrswrf, msmr, tciw, msr, mser, mtnswrfcs, strdc,...
esmvaltool-obs-ct11{ERA-Interim-Land, CALIOP, ESRL, CFSR, OSI-450-sh, CRU, AGCD, ISCCP-FH, HadCRUT5, ISCCP, NOAA-ERSSTv3b, GHCN-CAMS, BerkeleyEarth, Landschuetzer2020, ghgcci, CERES-EBAF, CowtanWay, AIRS-2-0, MODIS-...{Replicated observational datasets for ESMValTool CT11}{none, landIce, aerosol, atmos, land, ocean}{1yr, 1mon, fx, 1day}{cltStderr, va, spco2, dos, hus, clrcalipso, areacello, ta, rsut, tdps, talk, rsdt, tasa, tasmax, clw, tsn, prwErr, ch4, shrubFrac, psl, wap, burntArea, od550lt1aer, ph, cltisccp, baresoilFrac, do...
narclim2_zz63{ACCESS-ESM1-5, UKESM1-0-LL, MPI-ESM1-2-HR, EC-Earth3-Veg, NorESM2-MM}{NARCliM2.0 climate pojections, downscaled from ACCESS-ESM1-5 over Australasia at ~18km resolution.}{atmos}{1mon, 3hr, 1day, 1yr, 1hr, fx}{va100m, hus750, va750, SPI03, va850, zg400, hus50m, ta100, TXgt50p, HWA, DTR, R10mm, SDII, rsut, hus500, ua200, hus600, hus700, rsdt, va400, mrfsos, ta850, TN90p, ua250, tasmax, hus250, va200m, v...
panant-0025-zstar-ACCESSyr2{SIS2, MOM6}{0.025 degree (MOM6+SIS2) Pan-Antarctic regional model configuration under 1990-1991 JRA55-do repeat year forcing.}{ocean, seaIce}{1mon, fx, 1day}{vo, wet_u, geolat_u, net_melt, sob, areacello, time, time_bnds, dyCu, T_adx, geolon, average_T2, FA_X, salt_flux_added, yq, rho2_l, rho2_i, tob, dxCv, yTe, z_l_sub01, yT, geolat_c, thetao, geolon...
panant-005-zstar-ACCESSyr2{SIS2, MOM6}{0.05 degree (MOM6+SIS2) Pan-Antarctic regional model configuration under 1990-1991 JRA55-do repeat year forcing.}{ocean, seaIce}{1mon, fx, 1day}{vo, wet_u, geolat_u, net_melt, sob, areacello, time, time_bnds, dyCu, T_adx, geolon, average_T2, FA_X, salt_flux_added, yq, rho2_l, rho2_i, tob, dxCv, yTe, z_l_sub01, yT, geolat_c, thetao, geolon...
panant-01-hycom1-v13{SIS2, MOM6}{0.1 degree (MOM6+SIS2) Pan-Antarctic regional model configuration under 1990-1991 JRA55-do repeat year forcing with a hybrid (HYCOM1) vertical coordinate..}{ocean, seaIce}{1mon, fx, 1day}{vo, wet_u, geolat_v, friver, umo_2d, thetao, vmo, geolat_u, geolon_v, sithick, xT, mlotst, sob, wet, nv, zos, wet_c, wfo, tauvo, time, z_i, geolat, areacello_bu, time_bnds, areacello, areacello_c...
panant-01-zstar-ACCESSyr2{SIS2, MOM6}{0.1 degree (MOM6+SIS2) Pan-Antarctic regional model configuration under 1990-1991 JRA55-do repeat year forcing.}{ocean, seaIce}{1mon, fx, 1day}{vo, wet_u, geolat_u, net_melt, T_adx_2d, Kd_BBL, IY_TRANS, sob, dudt, Kd_shear, areacello, time, time_bnds, hf_dvdt_2d, col_height, Kd_ePBL, T_adx, dyCu, geolon, average_T2, intz_gKEv_2d, salt_fl...
panant-01-zstar-v13{SIS2, MOM6}{0.1 degree (MOM6+SIS2) Pan-Antarctic regional model configuration under 1990-1991 JRA55-do repeat year forcing.}{ocean, seaIce}{1mon, fx, 1day}{vo, wet_u, friver, geolat_u, sob, areacello, time, time_bnds, col_height, hf_dvdt_2d, dyCu, geolon, average_T2, intz_gKEv_2d, yq, rho2_l, rho2_i, tob, PRCmE, dxCv, yTe, yT, intz_CAu_2d, geolat_c,...
rcm_ccam_hq89{ACCESS-ESM1-5, CMCC-ESM2, EC-Earth3, CESM2, ACCESS-CM2, CNRM-ESM2-1, ERA5, NorESM2-MM}{CMIP6 Regional Climate Model Data from CCAM for Australian Climate Service}{none}{1mon, 6hr, 1day, 1hr, fx}{va100m, va850, zg400, rsut, hus500, ua200, hus600, hus700, rsdt, va400, mrfsos, ta850, ua250, tasmax, hus250, va200m, va600, prhmax, va1000, z0, psl, zg925, wa1000, ta925, clh, ua400, snw, wa850,...
shackleton_v4_jk72{ROMSIceShelf}{Shackleton/Denman Ice Shelf-ocean model application built with ROMSIceShelf}{seaIce}{5day}{rho, ndefHIS, w, LwSrc, dtfast, Tobc_out, Zob, zice, Tcline, x_rho, LsshCLM, rdrg, nl_tnu2, sustr, lon_psi, Tnudg, lon_u, u, nAVG, AKv, LnudgeTCLM, ocean_time, rho0, theta_s, Znudg, ntsAVG, LuvSp...
\n", "
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "cat = intake.cat.access_nri\n", "cat" ] }, { "cell_type": "code", "execution_count": 4, "id": "c01e897c-a078-4122-83c5-d11079ee85d4", "metadata": {}, "outputs": [], "source": [ "expt = \"panant-01-zstar-v13\"\n", "transport_var = \"umo_2d\"\n", "bathy_var = \"deptho\"\n", "freq = \"1mon\"\n", "start_date_regex = r\"203[5-9].*|204[0-9].*\"\n", "start_date = \"2035-01-01\"\n", "end_date = \"2050-01-01\"\n", "rho0 = 1035 #kg/m3\n", "lat = \"yh\"\n", "lon = \"xq\"" ] }, { "cell_type": "code", "execution_count": 5, "id": "b628cedb-85d3-4bdc-86a8-8d1c3a105bcb", "metadata": {}, "outputs": [], "source": [ "def load_mom6_zonal_mass_transport(transport_var: str, rho0: int|float) -> xr.DataArray:\n", " \"\"\"\n", " Load mom6 zonal mass transport, and convert it to Sverdrups\n", " \"\"\"\n", " mass_transport = (\n", " cat[expt]\n", " .search(variable=transport_var,\n", " start_date=start_date_regex,\n", " frequency=freq)\n", " .to_dask(xarray_open_kwargs={\n", " \"chunks\":{\"time\": 3},\n", " \"decode_timedelta\": False})[transport_var]\n", " .sel(time=slice(start_date, end_date))\n", " )\n", "\n", " # convert to volume transport (m^3/s)\n", " volume_transport = mass_transport / rho0\n", "\n", " # convert to Sverdrups\n", " volume_transport = volume_transport / 1e6\n", " volume_transport.attrs[\"units\"] = \"Sv\"\n", " return volume_transport\n", "\n", "def get_land_mask(bathy_var: str)-> xr.DataArray:\n", " \"\"\"\n", " 1 = ocean, Nan = land\n", " \"\"\"\n", " mask = (\n", " cat[expt]\n", " .search(variable=bathy_var)\n", " .to_dask(xarray_open_kwargs={\n", " \"chunks\":{\"time\": 3}})[bathy_var]\n", " )\n", " return xr.where(np.isnan(mask), 1, np.nan).rename(\"land_mask\")\n", "\n", "def calculate_streamfunction(transport_var, rho0, lat) -> xr.DataArray:\n", " \"\"\"\n", " Compute barotropic streamfunction (Sv)\n", " \"\"\"\n", " volume_transport = load_mom6_zonal_mass_transport(transport_var, rho0)\n", " psi = volume_transport.cumsum(dim=lat)\n", " psi.name = \"psi\"\n", " psi.attrs[\"standard_name\"] = \"Barotropic streamfunction\"\n", " psi.attrs[\"units\"] = \"Sv\"\n", " return psi\n", "\n", "def circumpolar_map():\n", " \"\"\"\n", " Set up South Polar Stereo map with circular boundary.\n", " \"\"\"\n", " fig = plt.figure(figsize=(12, 8))\n", " ax = plt.axes(projection=ccrs.SouthPolarStereo())\n", " ax.set_extent([-180, 180, -80, -40], crs=ccrs.PlateCarree())\n", " ax.set_facecolor(\"lightgrey\")\n", "\n", " # Map the plot boundaries to a circle\n", " theta = np.linspace(0, 2 * np.pi, 100)\n", " center, radius = [0.5, 0.5], 0.5\n", " verts = np.vstack([np.sin(theta), np.cos(theta)]).T\n", " circle = mpath.Path(verts * radius + center)\n", " ax.set_boundary(circle, transform=ax.transAxes)\n", "\n", " return fig, ax" ] }, { "cell_type": "code", "execution_count": 6, "id": "740c798a-3e89-4335-86e2-9219ebf2fa84", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.05/lib/python3.11/site-packages/intake_esm/core.py:259: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", " records = grouped.get_group(internal_key).to_dict(orient='records')\n", "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.05/lib/python3.11/site-packages/intake_esm/core.py:259: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", " records = grouped.get_group(internal_key).to_dict(orient='records')\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "psi = calculate_streamfunction(transport_var, rho0, lat)\n", "psi_mean = psi.mean(dim=\"time\").load()\n", "land_mask = get_land_mask(bathy_var)\n", "\n", "fig, ax = circumpolar_map()\n", "levels = np.arange(-50, 150, 10) # levels used in contour plots\n", "\n", "psi_mean.plot.contourf(\n", " ax=ax,\n", " x=lon,\n", " y=lat,\n", " transform=ccrs.PlateCarree(),\n", " levels=levels,\n", " extend=\"both\",\n", " cmap=cmocean.cm.speed,\n", " cbar_kwargs={\"label\": r\"$\\psi$ (Sv)\"},\n", ")\n", "\n", "land_mask.plot.contourf(\n", " ax=ax,\n", " colors=\"lightgrey\",\n", " add_colorbar=False,\n", " zorder=2,\n", " transform=ccrs.PlateCarree(),\n", ")\n", "\n", "plt.title(\"Barotropic streamfunction (MOM6)\")\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "id": "cf97e1b0-9847-47a1-b823-38daed57860d", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python [conda env:analysis3-25.05]", "language": "python", "name": "conda-env-analysis3-25.05-py" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.12" } }, "nbformat": 4, "nbformat_minor": 5 }