ACCESS-NRI Intake catalog for loading model output

This tutorial demonstrates how to use the ACCESS-NRI Intake catalog to load model or other output.

⚠️ Membership to project ``xp65`` is required to access the ACCESS-NRI Intake catalog ⚠️

This is a concise version of the longer ACCESS-NRI Intake catalog documentation and related COSIMA training workshop. Users are encouraged to refer to these for more detail and demonstrations.

Requirements: The conda/analysis3 module from /g/data/xp65/public/modules.

Start a dask Client

This is not specific to using the ACCESS-NRI Intake catalog, but it’s useful!

[1]:

from dask.distributed import Client

client = Client(threads_per_worker=1)
client

/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/distributed/node.py:187: UserWarning: Port 8787 is already in use.
Perhaps you already have a cluster running?
Hosting the HTTP server on port 45801 instead
  warnings.warn(

[1]:

Client

Client-b71d431f-bf7b-11f0-9c1e-000003c1fe80

Connection method: Cluster object Cluster type: distributed.LocalCluster
Dashboard: /proxy/45801/status

Cluster Info

Opening and searching the catalog

To use the ACCESS-NRI Intake catalog, we need to import intake

[2]:

import intake

We can open the catalog as follows

[3]:

catalog = intake.cat.access_nri

The returned object catalog is an instance of the ACCESS-NRI Intake catalog that we can use to find and load data.

Printing the catalog object will return a dataframe of experiments that you can browse:

[4]:

catalog

access_nri catalog with 120 source(s) across 2569 rows:

model description realm frequency variable
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} {fx, 1mon} {HTN, st_ocean, nv, mlt_onset_m, grid_yu_ocean, mld, total_ocean_lw_heat, grid_xt_ocean, dzt, tx_trans_nrho_submeso, mass_pmepr_on_nrho, pme_net, kmt, sens_heat, sw_heat_on_nrho, potrho, total_oce...
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} {fx, 1mon} {HTN, st_ocean, nv, mlt_onset_m, grid_yu_ocean, mld, total_ocean_lw_heat, grid_xt_ocean, dzt, pme_net, kmt, sens_heat, potrho, total_ocean_swflx_vis, total_ocean_melt, sfc_hflux_from_runoff, salt_...
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} {fx, 1mon} {HTN, st_ocean, nv, mlt_onset_m, grid_yu_ocean, mld, total_ocean_lw_heat, grid_xt_ocean, dzt, pme_net, kmt, sens_heat, potrho, total_ocean_swflx_vis, total_ocean_melt, sfc_hflux_from_runoff, salt_...
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} {3mon, 3hr, 1day, fx, 1mon} {HTN, st_ocean, nv, mlt_onset_m, mld, grid_yu_ocean, total_ocean_lw_heat, grid_xt_ocean, dzt, eta_t, pme_net, kmt, sens_heat, potrho, total_ocean_swflx_vis, xu_ocean_sub01, total_ocean_melt, sfc_h...
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} {1day, fx, 1mon} {HTN, st_ocean, nv, mlt_onset_m, mld, grid_yu_ocean, total_ocean_lw_heat, grid_xt_ocean, dzt, eta_t, pme_net, kmt, sens_heat, potrho, total_ocean_swflx_vis, total_ocean_melt, sfc_hflux_from_runoff...
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} {1day, fx, 1mon} {HTN, st_ocean, nv, mlt_onset_m, mld, grid_yu_ocean, total_ocean_lw_heat, grid_xt_ocean, dzt, eta_t, pme_net, kmt, sens_heat, potrho, total_ocean_swflx_vis, total_ocean_melt, sfc_hflux_from_runoff...
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} {1day, fx, 1mon} {HTN, st_ocean, nv, mlt_onset_m, mld, grid_yu_ocean, total_ocean_lw_heat, grid_xt_ocean, dzt, eta_t, pme_net, kmt, sens_heat, potrho, total_ocean_swflx_vis, total_ocean_melt, sfc_hflux_from_runoff...
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} {1day, fx, 1mon} {HTN, st_ocean, nv, mlt_onset_m, mld, grid_yu_ocean, total_ocean_lw_heat, grid_xt_ocean, dzt, eta_t, pme_net, kmt, sens_heat, potrho, total_ocean_swflx_vis, total_ocean_melt, sfc_hflux_from_runoff...
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} {fx, 1mon} {HTN, st_ocean, nv, mlt_onset_m, grid_yu_ocean, mld, total_ocean_lw_heat, grid_xt_ocean, dzt, pme_net, kmt, sens_heat, potrho, total_ocean_swflx_vis, total_ocean_melt, sfc_hflux_from_runoff, salt_...
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} {fx, 1mon} {HTN, st_ocean, nv, mlt_onset_m, grid_yu_ocean, mld, total_ocean_lw_heat, grid_xt_ocean, dzt, pme_net, kmt, sens_heat, potrho, total_ocean_swflx_vis, total_ocean_melt, sfc_hflux_from_runoff, salt_...
01deg_jra55v13_ryf9091_weddell_down2 {ACCESS-OM2-01} {Weddell Sea decreased meltwater perturbation experiment, branched off 01deg_jra55v13_ryf9091. } {ocean, seaIce} {1day, fx, 1mon} {HTN, st_ocean, nv, mlt_onset_m, mld, grid_yu_ocean, total_ocean_lw_heat, grid_xt_ocean, dzt, eta_t, pme_net, kmt, sens_heat, potrho, total_ocean_swflx_vis, total_ocean_melt, sfc_hflux_from_runoff...
01deg_jra55v13_ryf9091_weddell_up1 {ACCESS-OM2-01} {Weddell Sea increased meltwater perturbation experiment, branched off 01deg_jra55v13_ryf9091. } {ocean, seaIce} {1day, fx, 1mon} {HTN, st_ocean, nv, mlt_onset_m, mld, grid_yu_ocean, total_ocean_lw_heat, grid_xt_ocean, dzt, eta_t, pme_net, kmt, sens_heat, potrho, total_ocean_swflx_vis, total_ocean_melt, sfc_hflux_from_runoff...
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} {1day, fx, 1mon} {HTN, dvidtt, st_ocean, nv, total_ocean_lw_heat, mld, grid_yu_ocean, grid_xt_ocean, dzt, frazil, pme_net, kmt, sens_heat, frzmlt, potrho, total_ocean_swflx_vis, eta_nonbouss, total_ocean_melt, sfc...
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} {1day, fx, 1mon} {HTN, dvidtt, st_ocean, nv, total_ocean_lw_heat, mld, grid_yu_ocean, grid_xt_ocean, meltb, dzt, frazil, pme_net, kmt, sens_heat, frzmlt, potrho, total_ocean_swflx_vis, eta_nonbouss, total_ocean_me...
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} {1day, fx, 1mon} {HTN, dvidtt, st_ocean, nv, total_ocean_lw_heat, mld, grid_yu_ocean, grid_xt_ocean, meltb, dzt, frazil, pme_net, kmt, sens_heat, frzmlt, potrho, total_ocean_swflx_vis, eta_nonbouss, total_ocean_me...
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} {6hr, 3hr, 1day, fx, 1mon} {HTN, stf07, pme_net, alidf_ai, skl_Nit_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, phy_int100, HTE, frazil_3d_int_z, fmeltt_ai_m, bottom_temp, net_sfc_heating, ml_Nit_m, surface_...
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} {1day, subhr, fx, 1mon} {HTN, stf07, pme_net, skl_Nit_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, phy_int100, HTE, frazil_3d_int_z, fmeltt_ai_m, bottom_temp, net_sfc_heating, ml_Nit_m, surface_salt, surf...
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} {1day, fx, 1mon} {st_ocean, nv, grid_yu_ocean, mld, grid_xt_ocean, dzt, eta_t, pme_net, kmt, sens_heat, potrho, eta_nonbouss, sfc_hflux_from_runoff, TLAT, average_T1, evap, pbot_t, neutralrho_edges, frazil_3d_int_...
025deg_era5_iaf {ACCESS-OM2} {0.25 degree ACCESS-OM2 global model configuration with ERA5 interannual\nforcing (1980-2021)} {ocean, seaIce} {1day, fx, 1mon} {HTN, rain_ai_m, dvidtt, st_ocean, nv, total_ocean_lw_heat, mld, grid_xt_ocean, grid_yu_ocean, flat_ai_m, frazil, pme_net, kmt, sens_heat, frzmlt, potrho, total_ocean_swflx_vis, eta_nonbouss, strc...
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} {1day, fx, 1mon} {HTN, rain_ai_m, dvidtt, st_ocean, nv, total_ocean_lw_heat, mld, grid_yu_ocean, grid_xt_ocean, flat_ai_m, dzt, frazil, pme_net, kmt, sens_heat, frzmlt, potrho, total_ocean_swflx_vis, eta_nonbouss,...
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} {1day, fx, 1mon} {HTN, rain_ai_m, dvidtt, st_ocean, nv, total_ocean_lw_heat, mld, grid_xt_ocean, grid_yu_ocean, flat_ai_m, frazil, pme_net, kmt, sens_heat, frzmlt, potrho, total_ocean_swflx_vis, eta_nonbouss, strc...
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} {1day, 1yr, fx, 1mon} {HTN, rain_ai_m, bv_freq, pme_net, strcorx_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, Tair_m, bih_fric_v, HTE, frazil_3d_int_z, psiu, fmeltt_ai_m, temp_submeso, bottom_temp, net_...
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} {1day, 1yr, fx, 1mon} {HTN, rain_ai_m, bv_freq, pme_net, strcorx_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, Tair_m, bih_fric_v, HTE, frazil_3d_int_z, psiu, fmeltt_ai_m, temp_submeso, bottom_temp, net_...
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} {1day, 1yr, fx, 1mon} {HTN, rain_ai_m, bv_freq, pme_net, strcorx_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, Tair_m, bih_fric_v, HTE, frazil_3d_int_z, psiu, fmeltt_ai_m, temp_submeso, bottom_temp, net_...
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} {1day, 1yr, fx, 1mon} {HTN, rain_ai_m, bv_freq, pme_net, strcorx_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, Tair_m, bih_fric_v, HTE, frazil_3d_int_z, psiu, fmeltt_ai_m, temp_submeso, bottom_temp, net_...
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} {1day, 1yr, fx, 1mon} {HTN, rain_ai_m, bv_freq, pme_net, strcorx_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, Tair_m, bih_fric_v, HTE, frazil_3d_int_z, psiu, fmeltt_ai_m, temp_submeso, bottom_temp, net_...
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} {1day, fx, 1mon} {HTN, rain_ai_m, bv_freq, pme_net, strcorx_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, Tair_m, bih_fric_v, HTE, frazil_3d_int_z, psiu, fmeltt_ai_m, temp_submeso, bottom_temp, net_...
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} {1yr, fx, 1mon} {HTN, rain_ai_m, st_ocean, nv, mlt_onset_m, total_ocean_lw_heat, grid_yu_ocean, grid_xt_ocean, mld, flat_ai_m, dzt, eta_t, kmt, potrho, total_ocean_swflx_vis, strcorx_m, total_ocean_melt, salt_glo...
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} {1day, fx, 1mon} {HTN, rain_ai_m, dvidtt, st_ocean, nv, total_ocean_lw_heat, mld, grid_yu_ocean, grid_xt_ocean, flat_ai_m, dzt, frazil, pme_net, kmt, sens_heat, frzmlt, potrho, total_ocean_swflx_vis, eta_nonbouss,...
1deg_era5_iaf {ACCESS-OM2} {1 degree ACCESS-OM2 global model configuration with ERA5 interannual\nforcing (1960-2019)} {ocean, seaIce} {1day, fx, 1mon} {HTN, rain_ai_m, dvidtt, st_ocean, nv, total_ocean_lw_heat, mld, grid_yu_ocean, grid_xt_ocean, flat_ai_m, dzt, frazil, pme_net, kmt, sens_heat, frzmlt, potrho, total_ocean_swflx_vis, eta_nonbouss,...
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} {1day, fx, 1mon} {HTN, rain_ai_m, dvidtt, st_ocean, nv, total_ocean_lw_heat, mld, flat_ai_m, dzt, frazil, pme_net, kmt, sens_heat, frzmlt, total_ocean_swflx_vis, eta_nonbouss, strcorx_m, total_ocean_melt, sfc_hflu...
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} {1day, fx, 1mon} {HTN, rain_ai_m, dvidtt, st_ocean, nv, total_ocean_lw_heat, mld, grid_yu_ocean, grid_xt_ocean, flat_ai_m, dzt, frazil, pme_net, kmt, sens_heat, frzmlt, potrho, total_ocean_swflx_vis, eta_nonbouss,...
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} {1day, 1yr, fx, 1mon} {HTN, rain_ai_m, stf07, bv_freq, pme_net, strcorx_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, Tair_m, bih_fric_v, HTE, frazil_3d_int_z, psiu, fmeltt_ai_m, temp_submeso, bottom_tem...
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} {1day, 1yr, fx, 1mon} {HTN, rain_ai_m, stf07, bv_freq, pme_net, strcorx_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, Tair_m, bih_fric_v, HTE, frazil_3d_int_z, psiu, fmeltt_ai_m, temp_submeso, bottom_tem...
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} {1day, 1yr, fx, 1mon} {HTN, rain_ai_m, stf07, bv_freq, pme_net, strcorx_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, Tair_m, bih_fric_v, HTE, frazil_3d_int_z, psiu, fmeltt_ai_m, temp_submeso, bottom_tem...
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} {1day, 1yr, fx, 1mon} {HTN, rain_ai_m, stf07, bv_freq, pme_net, strcorx_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, Tair_m, bih_fric_v, HTE, frazil_3d_int_z, psiu, fmeltt_ai_m, temp_submeso, bottom_tem...
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} {1day, 1yr, fx, 1mon} {HTN, rain_ai_m, stf07, bv_freq, pme_net, strcorx_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, Tair_m, bih_fric_v, HTE, frazil_3d_int_z, psiu, fmeltt_ai_m, temp_submeso, bottom_tem...
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} {1day, 1yr, fx, 1mon} {HTN, rain_ai_m, stf07, bv_freq, pme_net, strcorx_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, Tair_m, bih_fric_v, HTE, frazil_3d_int_z, psiu, fmeltt_ai_m, temp_submeso, bottom_tem...
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} {1day, 1yr, fx, 1mon} {HTN, rain_ai_m, stf07, bv_freq, pme_net, strcorx_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, Tair_m, HTE, frazil_3d_int_z, psiu, fmeltt_ai_m, temp_submeso, bottom_temp, net_sfc_h...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1day, 1yr, fx, 1mon} {HTN, rain_ai_m, stf07, bv_freq, pme_net, strcorx_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, Tair_m, HTE, frazil_3d_int_z, psiu, fmeltt_ai_m, temp_submeso, bottom_temp, net_sfc_h...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1day, 1yr, fx, 1mon} {HTN, rain_ai_m, stf07, bv_freq, pme_net, strcorx_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, Tair_m, HTE, frazil_3d_int_z, psiu, fmeltt_ai_m, temp_submeso, bottom_temp, net_sfc_h...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1day, 1yr, fx, 1mon} {salt_nonlocal_KPP, neutral_gm_salt, HTN, st_ocean, stf07, eta_adjust, bv_freq, nv, sfc_hflux_from_water_prec, total_ocean_lw_heat, mld, grid_yu_ocean, grid_xt_ocean, tx_trans_rho_gm, paco2, tx_tr...
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} {1day, 1yr, fx, 1mon} {salt_nonlocal_KPP, neutral_gm_salt, HTN, st_ocean, stf07, eta_adjust, bv_freq, nv, sfc_hflux_from_water_prec, total_ocean_lw_heat, mld, grid_yu_ocean, grid_xt_ocean, tx_trans_rho_gm, paco2, tx_tr...
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} {1day, 1yr, fx, 1mon} {salt_nonlocal_KPP, neutral_gm_salt, HTN, st_ocean, stf07, eta_adjust, bv_freq, nv, sfc_hflux_from_water_prec, total_ocean_lw_heat, mld, grid_yu_ocean, grid_xt_ocean, tx_trans_rho_gm, paco2, tx_tr...
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} {1day, 1yr, fx, 1mon} {salt_nonlocal_KPP, neutral_gm_salt, HTN, st_ocean, stf07, eta_adjust, bv_freq, nv, sfc_hflux_from_water_prec, total_ocean_lw_heat, mld, grid_yu_ocean, grid_xt_ocean, tx_trans_rho_gm, paco2, tx_tr...
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} {1day, 1yr, fx, 1mon} {salt_nonlocal_KPP, neutral_gm_salt, HTN, st_ocean, stf07, eta_adjust, bv_freq, nv, sfc_hflux_from_water_prec, total_ocean_lw_heat, mld, grid_yu_ocean, grid_xt_ocean, tx_trans_rho_gm, paco2, tx_tr...
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} {1day, 1yr, fx, 1mon} {salt_nonlocal_KPP, neutral_gm_salt, HTN, st_ocean, stf07, eta_adjust, bv_freq, nv, sfc_hflux_from_water_prec, total_ocean_lw_heat, mld, grid_yu_ocean, grid_xt_ocean, tx_trans_rho_gm, paco2, tx_tr...
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} {1day, 1yr, fx, 1mon} {HTN, rain_ai_m, stf07, bv_freq, pme_net, strcorx_m, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, Tair_m, HTE, frazil_3d_int_z, psiu, fmeltt_ai_m, temp_submeso, bottom_temp, net_sfc_h...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1day, 1yr, fx, 1mon} {salt_nonlocal_KPP, neutral_gm_salt, HTN, st_ocean, stf07, eta_adjust, bv_freq, nv, sfc_hflux_from_water_prec, total_ocean_lw_heat, mld, grid_yu_ocean, grid_xt_ocean, tx_trans_rho_gm, paco2, tx_tr...
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} {1day, 1yr, fx, 1mon} {salt_nonlocal_KPP, neutral_gm_salt, HTN, st_ocean, stf07, eta_adjust, bv_freq, nv, sfc_hflux_from_water_prec, total_ocean_lw_heat, mld, grid_yu_ocean, grid_xt_ocean, tx_trans_rho_gm, paco2, tx_tr...
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, 1yr, 1mon} {HTN, rain_ai_m, dvidtt, st_ocean, stf07, nv, mld, flat_ai_m, frazil, frzmlt, strcorx_m, salt_global_ave, TLAT, alvdf_ai_m, average_T1, Tair_m, fswabs_ai_m, sst, HTE, fmeltt_ai_m, blkmask, caco3, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, 1mon} {HTN, adic, st_ocean, stf07, temp_global_ave, nv, yt_ocean, tarea, mld, xt_ocean, scalar_axis, TLON, dxu, total_volume_seawater, aice_m, sss, ULAT, ANGLET, dyt, salt_global_ave, TLAT, alvdf_ai_m, ...
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} {1yr, fx, 1mon} {HTN, rain_ai_m, st_ocean, nv, mlt_onset_m, grid_yu_ocean, mld, total_ocean_lw_heat, grid_xt_ocean, temp_xflux_gm_on_nrho, temp_yflux_gm_on_nrho, dzt, neutral_gm_on_nrho_temp, flat_ai_m, tx_trans_...
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} {1day, fx, 1mon} {HTN, rain_ai_m, dvidtt, st_ocean, nv, total_ocean_lw_heat, mld, flat_ai_m, dzt, frazil, pme_net, kmt, sens_heat, frzmlt, total_ocean_swflx_vis, eta_nonbouss, strcorx_m, total_ocean_melt, sfc_hflu...
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} {6hr, 3hr, 1day, 1mon, 1yr} {fld_s03i831, sigma_theta, stf07, bv_freq, fld_s30i111, pseudo_level_2, fld_s02i203, fld_s02i287, drhodsalinity, fld_s03i314, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, temp_merid_f...
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} {1day, 1yr, 1mon} {fld_s03i831, sigma_theta, stf07, bv_freq, pseudo_level_2, fld_s02i203, fld_s02i287, drhodsalinity, fld_s03i314, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, temp_merid_flux_over_atla...
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} {1day, 1yr, 1mon} {fld_s03i831, sigma_theta, stf07, bv_freq, pseudo_level_2, fld_s02i203, fld_s02i287, drhodsalinity, fld_s03i314, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, temp_merid_flux_over_atla...
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} {6hr, 3hr, 1day, 1mon, 1yr} {fld_s03i831, sigma_theta, stf07, bv_freq, fld_s30i111, pseudo_level_2, fld_s02i203, fld_s02i287, drhodsalinity, fld_s03i314, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, temp_merid_f...
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} {1day, 1yr, fx, 1mon} {z_i, tauvo, sob, nv, Heat_PmE, net_massin, wet_c, hfgeou, geolon, heat_content_massin, prsn, areacello_cv, so, average_T1, volcello, rho2_i, so_xyave, tos, evs, sfdsi, fsitherm, hfds, geolon_v, w...
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} {1day, 1yr, 1mon} {fld_s03i831, sigma_theta, stf07, bv_freq, pseudo_level_2, fld_s02i203, fld_s02i287, fld_s00i251, drhodsalinity, fld_s03i314, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, temp_merid_f...
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} {1day, 1yr, 1mon} {fld_s03i831, sigma_theta, stf07, bv_freq, pseudo_level_2, fld_s02i203, fld_s02i287, fld_s00i251, drhodsalinity, fld_s03i314, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, temp_merid_f...
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} {1day, 1yr, 1mon} {fld_s03i831, sigma_theta, stf07, bv_freq, pseudo_level_2, fld_s02i203, fld_s02i287, fld_s00i251, drhodsalinity, fld_s03i314, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, temp_merid_f...
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} {1day, 1yr, 1mon} {fld_s03i831, sigma_theta, stf07, bv_freq, pseudo_level_2, fld_s02i203, fld_s02i287, fld_s00i251, drhodsalinity, fld_s03i314, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, temp_merid_f...
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} {1day, 1yr, 1mon} {fld_s03i831, sigma_theta, stf07, bv_freq, pseudo_level_2, fld_s02i203, fld_s02i287, fld_s00i251, drhodsalinity, fld_s03i314, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, temp_merid_f...
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} {1day, 1yr, 1mon} {fld_s03i831, sigma_theta, stf07, bv_freq, pseudo_level_2, fld_s02i203, fld_s02i287, fld_s00i251, drhodsalinity, fld_s03i314, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, temp_merid_f...
WOA-13 {World Ocean Atlas 2013} {2013 World Ocean Atlas (WOA-13), regridded to various model grids.} {ocean} {fx} {potential_temperature, GRID_X_T, ZT, lat, salt, practical_salinity, GRID_Y_T, temp, time, lon}
WOA23 {World Ocean Atlas 2023} {World Ocean Atlas 2023} {ocean} {fx} {n_an, i_ma, s_ma, p_an, t_gp, p_gp, p_mn, t_se, p_se, p_oa, s_an, n_oa, t_ma, s_sea, o_ma, i_oa, t_dd, s_se, i_an, n_sd, t_mn, t_sdo, t_an, t_sea, o_sea, o_dd, i_mn, n_dd, i_sd, s_gp, o_an, s_mn,...
barpa_py18 {BARPA-R1-NN, BARPA-C, BARPA-R} {Bureau of Meteorology Atmospheric Regional Projections for Australia (BARPA)} {none} {6hr, 3hr, 1day, fx, subhr, 1mon, 1hr} {va30, hus700, tauu, wa250, wap700, wa150, qfluxv, MLCAPE03, prc, zg500, clt, helicity, ua50m, zg400, ua850, throughfall, ta800, zmla, prsn, cw, FZL, ta300, ta30, sic, va150, ua200m, ta400, ta700,...
bx944 {ACCESS-CM2} {Standard CMIP6 historical simulation, control experiment for by473 pacemaker experiment (948d8676-2c56-49db-8ea1-b80572b074c8)} {atmos, ocean, seaIce} {1day, 1mon} {fld_s03i831, sigma_theta, bv_freq, ardg, pseudo_level_2, sisnthick, pme_net, fld_s02i203, alidf_ai, drhodsalinity, fld_s03i314, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, sidmassgr...
by473 {ACCESS-CM2} {Pacemaker variation of CMIP6 historical simulation, Topical Atlantic region replaced with fixed SSTs from observations} {atmos, ocean, seaIce} {1day, 1mon} {fld_s03i831, sigma_theta, bv_freq, ardg, pseudo_level_2, sisnthick, pme_net, fld_s02i203, alidf_ai, drhodsalinity, fld_s03i314, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, sidmassgr...
by578 {ACCESS-CM2} {Pacemaker variation of CMIP6 ssp245 simulation with Tropical Atlantic region replaced with fixed SSTs from observations} {atmos, ocean, seaIce} {1day, 1mon} {fld_s03i831, sigma_theta, bv_freq, ardg, pseudo_level_2, sisnthick, pme_net, fld_s02i203, alidf_ai, drhodsalinity, fld_s03i314, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, sidmassgr...
by647 {ACCESS-CM2} {Standard CMIP6 ssp245 simulation, control experiment for by578 pacemaker experiment (1fd9e682-d393-4b17-a9cd-934c3a48a1f8)} {atmos, ocean, seaIce} {1day, 1mon} {fld_s03i831, sigma_theta, bv_freq, ardg, pseudo_level_2, sisnthick, pme_net, fld_s02i203, alidf_ai, drhodsalinity, fld_s03i314, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, sidmassgr...
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} {1day, 1mon} {fld_s03i831, sigma_theta, bv_freq, ardg, pseudo_level_2, sisnthick, pme_net, fld_s02i203, alidf_ai, drhodsalinity, fld_s03i314, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, sidmassgr...
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} {1day, fx, 1mon} {fld_s03i831, sigma_theta, ardg, pseudo_level_2, sisnthick, pme_net, fld_s02i203, alidf_ai, fld_s03i314, salt_global_ave, total_ocean_fprec_melt_heat, average_T1, sidmassgrowthbot, frazil_3d_int_z...
cmip5_al33 {CMCC-CESM, CNRM-CM5-2, REMO2015, RCA4, CanAM4, CCLM4-8-17-CLM3-5, GFDL-ESM2G, IPSL-CM5B-LR, CNRM-CM5, ALARO-0, HadCM3, MIROC-ESM, CCLM5-0-15, gfdl-esm2m, CFSv2-2011, HadGEM2-AO, CESM1-FASTCHEM, m... {Replicated CMIP5-era datasets catalogued by NCI} {ocnBgchem, seaIce, atmos, none, land, ocean, landIce, aerosol} {6hr, 3hr, 1day, fx, subhr, 1mon, 1yr} {usi, sconcoa, emibc, fddtdife, rsdsdiff, zmicro, grLateral, si, rsd4co2, epcalc100, wetsoa, loadpoa, prcprof, nppWood, hur, hfdsn, rlussi, hfcorr, fsitherm, tso, tnsccwacs, reffclis, gridspec, va...
cmip5_rr3 {ACCESS1-3, UQ-DES-CCAM, BOM-SDMa-NRM, UNSW-WRF360J, CSIRO-CCAM-2008, UNSW-WRF360L, CSIRO-Mk3-6-0, CSIRO-CCAM, UNSW-WRF360K, ACCESS1-0, CSIRO-Mk3L-1-2, CSIRO-CCAM-1704} {Australian CMIP5-era datasets catalogued by NCI} {seaIce, atmos, none, land, ocean, landIce, aerosol} {3mon, 6hr, 3hr, 1day, fx, 1mon, 1hr} {tauvo, strocnx, tauu, usi, sconcoa, hfbasindiff, tauvcorr, emibc, prc, rsdsdiff, zg500, clt, wmo, reffclwtop, ua850, zg400, rhs, divice, hfgeou, zmla, cldnvi, prsn, zg350, so, loadpoa, grassFrac,...
cmip6_fs38 {ACCESS-ESM1-5, ACCESS-OM2, ACCESS-CM2, ACCESS-OM2-025} {Australian CMIP6-era datasets catalogued by NCI} {seaIce, ocnBgchem, atmos, land, ocean, landIce, aerosol} {6hr, 3hr, 1day, fx, 1mon, 1yr} {msftmrho, rsdsdiff, zg500, sisnthick, fNup, sidmassgrowthbot, hfbasinpadv, hur, hfdsn, fNnetmin, fsitherm, sidmassdyn, vegHeight, siu, rsdt, rls, tauv, snw, opottempmint, nLitter, treeFracBdlDcd,...
cmip6_oi10 {CESM1-CAM5-SE-LR, HadGEM3-GC31-LL, INM-CM5-0, CESM1-CAM5-SE-HR, CMCC-CM2-HR4, CESM2, E3SM-1-1-ECA, HadGEM3-GC31-MM, E3SM-2-0-NARRM, HiRAM-SIT-LR, GISS-E2-1-G, NorESM2-MM, ICON-ESM-LR, CAMS-CSM1-0... {Replicated CMIP6-era datasets catalogued by NCI} {seaIce, ocnBgchem, atmos, atmosChem, land, ocean, landIce, aerosol} {6hr, 3hr, 1day, fx, subhr, 1mon, 1yr, 1hr} {t20d, cropFracC4, zg500, thetaot700, sisnthick, si, opottemptend, fNup, sidmassgrowthbot, hur, hfdsn, fNnetmin, hfcorr, fsitherm, sidmassdyn, pastureFracC3, siu, lossch4, rsdt, rls, tauv, snw, op...
cordex_ig45 {ACCESS-ESM1-5, MPI-ESM1-2-LR, FGOALS-g3, GFDL-ESM4, EC-Earth3, CMCC-ESM2, GISS-E2-1-G, MRI-ESM2-0, NorESM2-MM, ERA5, ACCESS-CM2, CNRM-CM6-1-HR} {20km regional projections for CORDEX-CMIP6 from the Queensland Future Climate Science Program} {none} {1day, 1mon, fx, 1hr} {hus700, tauu, prc, zg500, clt, zg400, ua850, zmla, prsn, ta300, ta400, ta700, ta500, ua100m, soilt, mrros, va925, clh, rsdt, hus300, zg300, tauv, clm, snw, hus850, orog, mrro, va600, evspsbl, va5...
era5_rt52 {era5, era5-preliminary, era5t, era5-derived, era5-1} {ERA5 fifth generation model reanalysis of global climate from ECMWF} {none} {1day, 1mon, 1hr} {ttrc, alnip, aluvd, mdww, lai-hv, viked, u10n, csfr, es, inss, aluvp, wmb, rhoao, mtnswrf, vimad, tvl, mwd, sshf, swvl2, fsr, lsp, ttr, vigd, p2ww, t, mer, PSurf, mlspf, slt, wstar, mmtss, vitoe,...
esmvaltool-obs-ct11 {OSI-450-sh, Eppley-VGPM-MODIS, CT2019, ESACCI-AEROSOL, Landschuetzer2020, Landschuetzer2016, ESACCI-SEA-SURFACE-SALINITY, ghgcci, BerkeleyEarth, AIRS-2-0, HadISST, Scripps-CO2-KUM, NCEP-DOE-R2, C... {Replicated observational datasets for ESMValTool CT11} {atmos, none, land, ocean, landIce, aerosol} {1day, 1yr, fx, 1mon} {tauu, clt, cltStddev, si, albisccp, prsn, od550aerStderr, tro3prof, so, grassFrac, sic, smStderr, hur, tos, hfds, taNobs, cttisccp, toz, talkos, fpar, prwFlag, clhcalipso, od870aerStderr, thetao,...
narclim2_zz63 {ACCESS-ESM1-5, EC-Earth3-Veg, NorESM2-MM, MPI-ESM1-2-HR, UKESM1-0-LL} {NARCliM2.0 climate pojections, downscaled from ACCESS-ESM1-5 over Australasia at ~18km resolution.} {atmos} {3hr, 1day, fx, 1mon, 1yr, 1hr} {hus700, tauu, wa250, wa150, TNlt2, prc, zg500, TN10p, clt, zg400, zmla, prsn, ta300, DTR, ta400, ta700, ta500, wa750, TX10p, mrros, zg750, CAPEmax, rsdt, hus300, zg300, tauv, snw, hus850, FFDIgt5...
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} {1day, fx, 1mon} {z_i, tauvo, sob, lrunoff, nv, wet_c, geolon, areacello_cv, so, average_T1, volcello, rho2_i, fsitherm, hfds, geolon_v, wet, yB, thetao, wet_u, FA_X, dyCu, xq, z_l, salt_flux_added, dyCv, dxCu, xT...
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} {1day, fx, 1mon} {z_i, tauvo, sob, lrunoff, nv, wet_c, geolon, areacello_cv, so, average_T1, volcello, rho2_i, fsitherm, hfds, geolon_v, wet, yB, thetao, wet_u, FA_X, dyCu, xq, z_l, salt_flux_added, dyCv, dxCu, xT...
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} {1day, fx, 1mon} {z_i, hmo, tauvo, xq, sob, z_l, areacello_bu, nv, dyCv, umo_2d, dxCu, xT, vmo_2d, geolat, wfo, rho2_l, yh, speed, tob, v, geolat_v, wet_c, geolat_u, areacello, yTe, zos, geolon, friver, areacello_...
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} {1day, fx, 1mon} {z_i, tauvo, Kd_interface, lrunoff, sob, nv, rvxv, T_adx_2d, Kd_ePBL, taux, wet_c, geolon, areacello_cv, so, average_T1, volcello, rho2_i, T_ady_2d, intz_CAv_2d, fsitherm, hfds, geolon_v, wet, hf_...
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} {1day, fx, 1mon} {z_i, tauvo, sob, nv, taux, wet_c, geolon, areacello_cv, so, average_T1, volcello, rho2_i, intz_CAv_2d, tos, hfds, geolon_v, wet, hf_dvdt_2d, thetao, wet_u, intz_diffu_2d, intz_rvxv_2d, dyCu, hmo,...
rcm_ccam_hq89 {ACCESS-ESM1-5, CMCC-ESM2, CNRM-ESM2-1, EC-Earth3, NorESM2-MM, ERA5, CESM2, ACCESS-CM2} {CMIP6 Regional Climate Model Data from CCAM for Australian Climate Service} {none} {6hr, 1day, fx, 1mon, 1hr} {hus700, tauu, wa250, prc, zg500, clt, ua50m, zg400, ua850, zmla, prsn, ta300, ua200m, ta400, ta700, ta500, mrfsos, ua100m, mrros, ua250m, va925, clh, rsdt, hus300, zg300, tauv, wsgsmax, clm, snw,...
shackleton_v4_jk72 {ROMSIceShelf} {Shackleton/Denman Ice Shelf-ocean model application built with ROMSIceShelf} {seaIce} {5day} {Zob, nHIS, lat_v, Sb, Cs_w, pm, Fgamma, lon_v, Akv_bak, ocean_time, m, LnudgeM2CLM, Znudg, zice, FSobc_out, mask_v, dstart, spherical, dtfast, LnudgeM3CLM, ndtfast, rho, nl_tnu2, Vstretching, x_u...

You can also search based on the columns in this dataframe to find experiments that are relevant to you. For example, you might be interested in all ACCESS-OM2 experiments that have the variable "surface_salt" at daily frequency. There are 6 such experiments currently available through the catalog:

[5]:

catalog.search(model="ACCESS-OM2", variable="surface_salt", frequency="1day")

Intake dataframe catalog with 6 source(s) across 6 rows:

model description realm frequency variable
name
025deg_era5_iaf {ACCESS-OM2} {0.25 degree ACCESS-OM2 global model configuration with ERA5 interannual\nforcing (1980-2021)} {ocean} {1day} {surface_salt}
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} {1day} {surface_salt}
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} {1day} {surface_salt}
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} {1day} {surface_salt}
1deg_era5_iaf {ACCESS-OM2} {1 degree ACCESS-OM2 global model configuration with ERA5 interannual\nforcing (1960-2019)} {ocean} {1day} {surface_salt}
1deg_jra55_iaf_era5comparison {ACCESS-OM2} {1 degree ACCESS-OM2 global model configuration with JRA55-do v1.4.0\ninterannual forcing (1960-2019)} {ocean} {1day} {surface_salt}

Opening data

There are multiple ways to open data from the experiments in catalog. Here we’ll demonstrate how to do this when you know the name of the experiment you are interested in, since this typical for COSIMA users.

For example, we can open monthly data for the surface_salt variable in the 01deg_jra55v13_ryf9091 experiment as follows:

[6]:

experiment = "01deg_jra55v13_ryf9091"
variable = "surface_salt"

[7]:

data_ic = catalog[experiment].search(
    variable=variable,
    frequency="1mon"
).to_dask()

/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/intake_esm/core.py:321: 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.
  records = grouped.get_group(internal_key).to_dict(orient='records')

[8]:

data_ic["surface_salt"]

[8]:

<xarray.DataArray 'surface_salt' (time: 3360, yt_ocean: 2700, xt_ocean: 3600)> Size: 131GB
dask.array<concatenate, shape=(3360, 2700, 3600), dtype=float32, chunksize=(1, 675, 900), chunktype=numpy.ndarray>
Coordinates:
  * xt_ocean  (xt_ocean) float64 29kB -279.9 -279.8 -279.7 ... 79.75 79.85 79.95
  * yt_ocean  (yt_ocean) float64 22kB -81.11 -81.07 -81.02 ... 89.89 89.94 89.98
  * time      (time) object 27kB 1900-01-16 12:00:00 ... 2179-12-16 12:00:00
Attributes:
    long_name:      Practical Salinity
    units:          psu
    valid_range:    [-10. 100.]
    cell_methods:   time: mean
    time_avg_info:  average_T1,average_T2,average_DT
    standard_name:  sea_surface_salinity

Some important facts

There are a few important facts in the ACCESS-NRI Intake catalog that users should be aware of.

1. The catalog returns Datasets (not Dataarrays)

This is because with the catalog you can load multiple variables into a single dataset with a single call (when these variables are in the same file). For example,

[9]:

data_ic_multivar = catalog[experiment].search(
    variable=["surface_salt", "surface_temp"],
    frequency="1mon"
).to_dask()

/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/intake_esm/core.py:321: 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.
  records = grouped.get_group(internal_key).to_dict(orient='records')

[10]:

data_ic_multivar

[10]:

<xarray.Dataset> Size: 261GB
Dimensions:       (time: 3360, yt_ocean: 2700, xt_ocean: 3600)
Coordinates:
  * xt_ocean      (xt_ocean) float64 29kB -279.9 -279.8 -279.7 ... 79.85 79.95
  * yt_ocean      (yt_ocean) float64 22kB -81.11 -81.07 -81.02 ... 89.94 89.98
  * time          (time) object 27kB 1900-01-16 12:00:00 ... 2179-12-16 12:00:00
Data variables:
    surface_temp  (time, yt_ocean, xt_ocean) float32 131GB dask.array<chunksize=(1, 675, 900), meta=np.ndarray>
    surface_salt  (time, yt_ocean, xt_ocean) float32 131GB dask.array<chunksize=(1, 675, 900), meta=np.ndarray>
Attributes:
    filename:                        ocean_month.nc
    title:                           ACCESS-OM2-01
    grid_type:                       mosaic
    grid_tile:                       1
    intake_esm_vars:                 ['surface_temp', 'surface_salt']
    intake_esm_attrs:filename:       ocean_month.nc
    intake_esm_attrs:file_id:        ocean.1mon.nv:2.xt_ocean:3600.xu_ocean:3...
    intake_esm_attrs:frequency:      1mon
    intake_esm_attrs:realm:          ocean
    intake_esm_attrs:_data_format_:  netcdf
    intake_esm_dataset_key:          ocean.1mon.nv:2.xt_ocean:3600.xu_ocean:3...

2. The catalog knows which files make up distinct datasets

The catalog knows which files make up distinct datasets and provides methods to open multiple datasets from a single query. We can run the equivalent to the cell above using the catalog, using to_dataset_dict() rather than to_dask(). Doing so returns a dictionary containing Datasets of the variable at all the available frequencies (daily and monthly in this case).

[11]:

data_ic_multifreq = catalog[experiment].search(variable=variable).to_dataset_dict()


--> The keys in the returned dictionary of datasets are constructed as follows:
        'file_id'

/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/intake_esm/core.py:321: 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.
  records = grouped.get_group(internal_key).to_dict(orient='records')
/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/intake_esm/core.py:321: 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.
  records = grouped.get_group(internal_key).to_dict(orient='records')
/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/intake_esm/core.py:321: 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.
  records = grouped.get_group(internal_key).to_dict(orient='records')
100.00% [3/3 00:19<00:00] 
[12]:

data_ic_multifreq

[12]:

{'ocean.1day.nv:2.xt_ocean:3600.xu_ocean:3600.yt_ocean:2700.yu_ocean:2700': <xarray.Dataset> Size: 610GB
 Dimensions:       (time: 15695, yt_ocean: 2700, xt_ocean: 3600)
 Coordinates:
   * xt_ocean      (xt_ocean) float64 29kB -279.9 -279.8 -279.7 ... 79.85 79.95
   * yt_ocean      (yt_ocean) float64 22kB -81.11 -81.07 -81.02 ... 89.94 89.98
   * time          (time) object 126kB 2137-01-01 12:00:00 ... 2179-12-31 12:0...
 Data variables:
     surface_salt  (time, yt_ocean, xt_ocean) float32 610GB dask.array<chunksize=(1, 675, 900), meta=np.ndarray>
 Attributes:
     filename:                        ocean_daily.nc
     title:                           ACCESS-OM2-01
     grid_type:                       mosaic
     grid_tile:                       1
     intake_esm_vars:                 ['surface_salt']
     intake_esm_attrs:filename:       ocean_daily.nc
     intake_esm_attrs:file_id:        ocean.1day.nv:2.xt_ocean:3600.xu_ocean:3...
     intake_esm_attrs:frequency:      1day
     intake_esm_attrs:realm:          ocean
     intake_esm_attrs:_data_format_:  netcdf
     intake_esm_dataset_key:          ocean.1day.nv:2.xt_ocean:3600.xu_ocean:3...,
 'ocean.1day.nv:2.xt_ocean:3600.yt_ocean:2700': <xarray.Dataset> Size: 3TB
 Dimensions:       (time: 65885, yt_ocean: 2700, xt_ocean: 3600)
 Coordinates:
   * xt_ocean      (xt_ocean) float64 29kB -279.9 -279.8 -279.7 ... 79.85 79.95
   * yt_ocean      (yt_ocean) float64 22kB -81.11 -81.07 -81.02 ... 89.94 89.98
   * time          (time) object 527kB 1956-04-01 12:00:00 ... 2136-12-31 12:0...
 Data variables:
     surface_salt  (time, yt_ocean, xt_ocean) float32 3TB dask.array<chunksize=(1, 675, 900), meta=np.ndarray>
 Attributes: (12/14)
     filename:                                ocean_daily.nc
     title:                                   ACCESS-OM2-01
     grid_type:                               mosaic
     grid_tile:                               1
     intake_esm_vars:                         ['surface_salt']
     intake_esm_attrs:filename:               ocean_daily.nc
     ...                                      ...
     intake_esm_attrs:variable:               average_DT,average_T1,average_T2...
     intake_esm_attrs:variable_long_name:     Length of average period,Start t...
     intake_esm_attrs:variable_cell_methods:  ,,,time: mean,time: mean,time: m...
     intake_esm_attrs:realm:                  ocean
     intake_esm_attrs:_data_format_:          netcdf
     intake_esm_dataset_key:                  ocean.1day.nv:2.xt_ocean:3600.yt...,
 'ocean.1mon.nv:2.xt_ocean:3600.xu_ocean:3600.yt_ocean:2700.yu_ocean:2700': <xarray.Dataset> Size: 131GB
 Dimensions:       (time: 3360, yt_ocean: 2700, xt_ocean: 3600)
 Coordinates:
   * xt_ocean      (xt_ocean) float64 29kB -279.9 -279.8 -279.7 ... 79.85 79.95
   * yt_ocean      (yt_ocean) float64 22kB -81.11 -81.07 -81.02 ... 89.94 89.98
   * time          (time) object 27kB 1900-01-16 12:00:00 ... 2179-12-16 12:00:00
 Data variables:
     surface_salt  (time, yt_ocean, xt_ocean) float32 131GB dask.array<chunksize=(1, 675, 900), meta=np.ndarray>
 Attributes:
     filename:                        ocean_month.nc
     title:                           ACCESS-OM2-01
     grid_type:                       mosaic
     grid_tile:                       1
     intake_esm_vars:                 ['surface_salt']
     intake_esm_attrs:filename:       ocean_month.nc
     intake_esm_attrs:file_id:        ocean.1mon.nv:2.xt_ocean:3600.xu_ocean:3...
     intake_esm_attrs:frequency:      1mon
     intake_esm_attrs:realm:          ocean
     intake_esm_attrs:_data_format_:  netcdf
     intake_esm_dataset_key:          ocean.1mon.nv:2.xt_ocean:3600.xu_ocean:3...}

Alternatively, multiple datasets can be opened directly into an xarray-datatree by calling to_datatree rather than to_dataset_dict (in an upcoming release, it will be easier for users to control how the groups are structured in the datatree). For example:

[13]:

data_ic_datatree = catalog[experiment].search(variable=variable).to_datatree()


--> The keys in the returned dictionary of datasets are constructed as follows:
        'file_id'

/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/intake_esm/core.py:321: 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.
  records = grouped.get_group(internal_key).to_dict(orient='records')
/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/intake_esm/core.py:321: 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.
  records = grouped.get_group(internal_key).to_dict(orient='records')
/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/intake_esm/core.py:321: 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.
  records = grouped.get_group(internal_key).to_dict(orient='records')
100.00% [3/3 00:13<00:00] 
[14]:

data_ic_datatree

[14]:

<xarray.DatasetView> Size: 0B
Dimensions:  ()
Data variables:
    *empty*

3. The frequency vocabulary:

In the catalog, frequency follows a standard vocabulary that is very similar to CMIP6:

"fx" # fixed
"subhr" # subhourly
"<int>hr" # hourly
"<int>day" # daily
"<int>mon" # monthly
"<int>yr" # yearly
"<int>dec" # decadal

4. Method for passing keyword arguments

With the catalog, keyword argments for xarray’s open_dataset and combine_by_coords functions are passed separately to to_dask (or to_dataset_dict). For example:

[15]:

xarray_open_kwargs=dict(
    chunks={"xt_ocean": -1, "yt_ocean": -1}
)
xarray_combine_by_coords_kwargs=dict(
    compat="override",
    data_vars="minimal",
    coords="minimal"
)

data_ic_kw = catalog[experiment].search(
    variable=variable,
    frequency="1mon"
).to_dask(
    xarray_open_kwargs=xarray_open_kwargs,
    xarray_combine_by_coords_kwargs=xarray_combine_by_coords_kwargs,
)

/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/intake_esm/core.py:321: 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.
  records = grouped.get_group(internal_key).to_dict(orient='records')

5. Catalog does not allow search by start and end date

It’s not possible to query on a time range with the Intake catalog.

We can always slice the time axis afterwards though. That is, with the catalog you’d just do:

[17]:

data_ic = catalog[experiment].search(
    variable=variable,
    frequency="1mon"
).to_dask()

start_time = "2000-01-01"
end_time = "2180-01-01"

data_ic_times = data_ic.sel(time=slice(start_time, end_time))

/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/intake_esm/core.py:301: 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.
  records = grouped.get_group(internal_key).to_dict(orient='records')

which takes a few seconds longer.

This difference is acceptable because the opening of datasets is a parallelized task that is done lazily, so opening all files and reducing the times using xarray’s sel methods doesn’t add too much overhead. In most cases where the overhead of opening the files seems large, this can be reduced through sensible choices of keyword arguments provided to open_dataset and combine_by_coords - see the xarray documentation on Reading multi-file datasets for details.

6. Applying a preprocessing function

You can use xarray’s preprocess function to apply a function to each dataset prior to intake’s concatenation. In some cases, this can make the loading into memory fast.

For example:

[18]:

def select_region(ds):
    ds = ds.sel(xt_ocean=slice(-230, -180), yt_ocean=slice(-50, -20))
    return ds

data_ic = catalog['01deg_jra55v13_ryf9091'].search(
    variable='surface_temp',
    frequency="1mon"
).to_dask(preprocess=select_region)
data_ic

/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/intake_esm/core.py:321: 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.
  records = grouped.get_group(internal_key).to_dict(orient='records')

[18]:

<xarray.Dataset> Size: 3GB
Dimensions:       (time: 3360, yt_ocean: 375, xt_ocean: 500)
Coordinates:
  * xt_ocean      (xt_ocean) float64 4kB -229.9 -229.8 -229.7 ... -180.1 -180.0
  * yt_ocean      (yt_ocean) float64 3kB -49.96 -49.9 -49.83 ... -20.12 -20.03
  * time          (time) object 27kB 1900-01-16 12:00:00 ... 2179-12-16 12:00:00
Data variables:
    surface_temp  (time, yt_ocean, xt_ocean) float32 3GB dask.array<chunksize=(1, 9, 400), meta=np.ndarray>
Attributes:
    filename:                        ocean_month.nc
    title:                           ACCESS-OM2-01
    grid_type:                       mosaic
    grid_tile:                       1
    intake_esm_vars:                 ['surface_temp']
    intake_esm_attrs:filename:       ocean_month.nc
    intake_esm_attrs:file_id:        ocean.1mon.nv:2.xt_ocean:3600.xu_ocean:3...
    intake_esm_attrs:frequency:      1mon
    intake_esm_attrs:realm:          ocean
    intake_esm_attrs:_data_format_:  netcdf
    intake_esm_dataset_key:          ocean.1mon.nv:2.xt_ocean:3600.xu_ocean:3...

Tips, gotchas and workarounds

1. Speeding up opening your datasets

Try passing the following argument to your to_dask or to_dataset_dict call:

xarray_combine_by_coords_kwargs=dict(
    compat="override",
    data_vars="minimal",
    coords="minimal"
)

See the xarray documentation on Reading multi-file datasets for more details about these arguments.

2. Choosing chunksizes

Correctly choosing chunk sizes when you open datasets will greatly improve the speed of your analysis. Check out the Chunking tutorial in the ACCESS-NRI Intake catalog documentation

3. Loading time-invariant variables

Many COSIMA experiments include multiple repeated files containing the same fixed frequency data (e.g. grid information). You can use the option fx for the frequency argument, otherwise the catalog fails to concatenate these files since they don’t contain clear dimension to concatenate along.

[20]:

data_ic_fixed = catalog[experiment].search(
    variable='area_t',
    frequency='fx'
).to_dask()
data_ic_fixed

/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/intake_esm/core.py:321: 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.
  records = grouped.get_group(internal_key).to_dict(orient='records')
/g/data/xp65/public/apps/med_conda/envs/analysis3-25.09/lib/python3.11/site-packages/intake_esm/source.py:308: ConcatenationWarning: Attempting to concatenate datasets without valid dimension coordinates: retaining only first dataset. Request valid dimension coordinate to silence this warning.
  warnings.warn(

[20]:

<xarray.Dataset> Size: 117MB
Dimensions:   (yt_ocean: 2700, xt_ocean: 3600)
Coordinates:
  * xt_ocean  (xt_ocean) float64 29kB -279.9 -279.8 -279.7 ... 79.75 79.85 79.95
  * yt_ocean  (yt_ocean) float64 22kB -81.11 -81.07 -81.02 ... 89.89 89.94 89.98
    geolon_t  (yt_ocean, xt_ocean) float32 39MB dask.array<chunksize=(675, 900), meta=np.ndarray>
    geolat_t  (yt_ocean, xt_ocean) float32 39MB dask.array<chunksize=(675, 900), meta=np.ndarray>
Data variables:
    area_t    (yt_ocean, xt_ocean) float32 39MB dask.array<chunksize=(675, 900), meta=np.ndarray>
Attributes: (12/19)
    filename:                                 ocean_grid.nc
    title:                                    ACCESS-OM2-01
    grid_type:                                mosaic
    grid_tile:                                1
    intake_esm_vars:                          ['area_t']
    intake_esm_attrs:filename:                ocean_grid.nc
    ...                                       ...
    intake_esm_attrs:variable_standard_name:  ,,,,,,,,,,,sea_floor_depth_belo...
    intake_esm_attrs:variable_cell_methods:   time: point,time: point,time: p...
    intake_esm_attrs:variable_units:          m^2,m^2,dimensionless,m,m,m,m,d...
    intake_esm_attrs:realm:                   ocean
    intake_esm_attrs:_data_format_:           netcdf
    intake_esm_dataset_key:                   ocean.fx.xt_ocean:3600.xu_ocean...

4. Determining what can be searched upon in an experiment

You can see what can be searched on within an experiment with:

[21]:

catalog[experiment].df.columns.tolist()

[21]:

['filename',
 'path',
 'file_id',
 'frequency',
 'start_date',
 'end_date',
 'variable',
 'variable_long_name',
 'variable_standard_name',
 'variable_cell_methods',
 'variable_units',
 'realm']

It can also be helpful sometimes to look at the catalog[experiment].df object itself, which is a dataframe of all of the files in the experiment and their metadata

[22]:

catalog[experiment].df.head()

[22]:
filename path file_id frequency start_date end_date variable variable_long_name variable_standard_name variable_cell_methods variable_units realm
0 iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 (ANGLE, ANGLET, HTE, HTN, NCAT, TLAT, TLON, Tsfc_m, ULAT, ULON, aice_m, aicen_m, alidf_ai_m, alidr_ai_m, alvdf_ai_m, alvdr_ai_m, blkmask, congel_m, divu_m, dxt, dxu, dyt, dyu, flatn_ai_m, fmeltt_a... (angle grid makes with latitude line on U grid, angle grid makes with latitude line on T grid, T cell width on East side, T cell width on North side, category maximum thickness, T grid center lati... (, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ) (, , , , , , , time: mean, , , time: mean, time: mean, time: mean, time: mean, time: mean, time: mean, , time: mean, time: mean, , , , , time: mean, time: mean, time: mean, time: mean, time: mean,... (radians, radians, m, m, m, degrees_north, degrees_east, C, degrees_north, degrees_east, 1, 1, %, %, %, %, , cm/day, %/day, m, m, m, m, W/m^2, W/m^2, W/m^2, cm/day, day of year, kg/m^2/s, kg/m^2/s... seaIce
1 iceh.1900-02.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-02.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-02-01, 00:00:00 1900-03-01, 00:00:00 (ANGLE, ANGLET, HTE, HTN, NCAT, TLAT, TLON, Tsfc_m, ULAT, ULON, aice_m, aicen_m, alidf_ai_m, alidr_ai_m, alvdf_ai_m, alvdr_ai_m, blkmask, congel_m, divu_m, dxt, dxu, dyt, dyu, flatn_ai_m, fmeltt_a... (angle grid makes with latitude line on U grid, angle grid makes with latitude line on T grid, T cell width on East side, T cell width on North side, category maximum thickness, T grid center lati... (, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ) (, , , , , , , time: mean, , , time: mean, time: mean, time: mean, time: mean, time: mean, time: mean, , time: mean, time: mean, , , , , time: mean, time: mean, time: mean, time: mean, time: mean,... (radians, radians, m, m, m, degrees_north, degrees_east, C, degrees_north, degrees_east, 1, 1, %, %, %, %, , cm/day, %/day, m, m, m, m, W/m^2, W/m^2, W/m^2, cm/day, day of year, kg/m^2/s, kg/m^2/s... seaIce
2 iceh.1900-03.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-03.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-03-01, 00:00:00 1900-04-01, 00:00:00 (ANGLE, ANGLET, HTE, HTN, NCAT, TLAT, TLON, Tsfc_m, ULAT, ULON, aice_m, aicen_m, alidf_ai_m, alidr_ai_m, alvdf_ai_m, alvdr_ai_m, blkmask, congel_m, divu_m, dxt, dxu, dyt, dyu, flatn_ai_m, fmeltt_a... (angle grid makes with latitude line on U grid, angle grid makes with latitude line on T grid, T cell width on East side, T cell width on North side, category maximum thickness, T grid center lati... (, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ) (, , , , , , , time: mean, , , time: mean, time: mean, time: mean, time: mean, time: mean, time: mean, , time: mean, time: mean, , , , , time: mean, time: mean, time: mean, time: mean, time: mean,... (radians, radians, m, m, m, degrees_north, degrees_east, C, degrees_north, degrees_east, 1, 1, %, %, %, %, , cm/day, %/day, m, m, m, m, W/m^2, W/m^2, W/m^2, cm/day, day of year, kg/m^2/s, kg/m^2/s... seaIce
3 ocean.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ocean/ocean.nc ocean.3mon.grid_xt_ocean:3600.grid_xu_ocean:3600.grid_yt_ocean:2700.grid_yu_ocean:2700.neutral:80.neutralrho_edges:81.nv:2.potrho:80.potrho_edges:81.st_edges_ocean:76.st_ocean:75.sw_edges_ocean:76... 3mon 1900-01-01, 00:00:00 1900-04-01, 00:00:00 (age_global, average_DT, average_T1, average_T2, dzt, grid_xt_ocean, grid_xu_ocean, grid_yt_ocean, grid_yu_ocean, neutral, neutralrho_edges, nv, pot_rho_0, pot_temp, potrho, potrho_edges, rho, sal... (Age (global), Length of average period, Start time for average period, End time for average period, t-cell thickness, tcell longitude, ucell longitude, tcell latitude, ucell latitude, neutral den... (sea_water_age_since_surface_contact, , , , cell_thickness, , , , , , , , sea_water_potential_density, sea_water_potential_temperature, , , , sea_water_salinity, , , , , , , , , , ocean_mass_x_tra... (time: mean, , , , time: mean, , , , , , , , time: mean, time: mean, , , time: mean, time: mean, , , , , time: mean, time: mean, time: mean, , , time: mean, time: mean, time: mean, time: mean, tim... (yr, days, days since 1900-01-01 00:00:00, days since 1900-01-01 00:00:00, m, degrees_E, degrees_E, degrees_N, degrees_N, kg/m^3, kg/m^3, none, kg/m^3, degrees K, kg/m^3, kg/m^3, kg/m^3, psu, mete... ocean
4 ocean_grid.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ocean/ocean_grid.nc ocean.fx.xt_ocean:3600.xu_ocean:3600.yt_ocean:2700.yu_ocean:2700 fx 1900-04-01, 00:00:00 1900-04-01, 00:00:00 (area_t, area_u, drag_coeff, dxt, dxu, dyt, dyu, geolat_c, geolat_t, geolon_c, geolon_t, ht, hu, kmt, kmu, time, xt_ocean, xu_ocean, yt_ocean, yu_ocean) (tracer cell area, velocity cell area, Dimensionless bottom drag coefficient, ocean dxt on t-cells, ocean dxu on u-cells, ocean dyt on t-cells, ocean dyu on u-cells, uv latitude, tracer latitude, ... (, , , , , , , , , , , sea_floor_depth_below_geoid, , , , , , , , ) (time: point, time: point, time: point, time: point, time: point, time: point, time: point, time: point, time: point, time: point, time: point, time: point, time: point, time: point, time: point, ... (m^2, m^2, dimensionless, m, m, m, m, degrees_N, degrees_N, degrees_E, degrees_E, m, m, dimensionless, dimensionless, days since 1900-01-01 00:00:00, degrees_E, degrees_E, degrees_N, degrees_N) ocean

5. Finding all variables in an experiment

You can get a list of all available variable names from an experiment with:

[23]:

variables = catalog.search(name=experiment).unique().variable
print(variables)

['HTN', 'st_ocean', 'nv', 'mlt_onset_m', 'mld', 'grid_yu_ocean', 'total_ocean_lw_heat', 'grid_xt_ocean', 'dzt', 'eta_t', 'pme_net', 'kmt', 'sens_heat', 'potrho', 'total_ocean_swflx_vis', 'xu_ocean_sub01', 'total_ocean_melt', 'sfc_hflux_from_runoff', 'salt_global_ave', 'TLAT', 'total_ocean_fprec_melt_heat', 'alvdf_ai_m', 'average_T1', 'evap', 'yu_ocean_sub02', 'pbot_t', 'bih_fric_v', 'neutralrho_edges', 'yt_ocean_sub01', 'HTE', 'frazil_3d_int_z', 'fmeltt_ai_m', 'fprec_melt_heat', 'blkmask', 'vocn_m', 'temp_submeso', 'shear_m', 'alidf_ai_m', 'aicen_m', 'temp_surface_ave', 'tx_trans', 'eta_global', 'yu_ocean_sub01', 'total_ocean_hflux_prec', 'vhrho_nt', 'tx_trans_submeso', 'xu_ocean', 'salt_surface_ave', 'usurf', 'net_sfc_heating', 'total_ocean_hflux_evap', 'ULON', 'geolon_t', 'fswup_m', 'surface_salt', 'ke_tot', 'rho', 'river', 'ANGLE', 'temp_xflux_adv', 'vvel_m', 'pot_rho_1', 'sw_heat', 'yt_ocean', 'potrho_edges', 'total_ocean_runoff_heat', 'tx_trans_rho', 'xt_ocean', 'sfc_salt_flux_coupler', 'total_ocean_calving_heat', 'strairx_m', 'dxu', 'aice_m', 'total_ocean_fprec', 'temp_rivermix', 'ULAT', 'passive_weddell', 'fprec', 'xu_ocean_sub02', 'melt', 'total_ocean_sfc_salt_flux_coupler', 'fsalt_m', 'vsurf', 'pot_rho_2', 'drag_coeff', 'swflx', 'total_ocean_heat', 'pot_rho_0', 'average_DT', 'sss_m', 'uarea', 'geolat_c', 'sst_m', 'area_u', 'total_ocean_calving', 'passive_prydz', 'buoyfreq2_wt', 'uhrho_et', 'flatn_ai_m', 'salt', 'temp_vdiffuse_diff_cbt_conv', 'temp_tendency', 'uatm_m', 'fmelttn_ai_m', 'strairy_m', 'bih_fric_u', 'ty_trans_rho', 'geolat_t', 'yt_ocean_sub02', 'vert_pv', 'vicen_m', 'xt_ocean_sub02', 'temp_global_ave', 'ht', 'kmu', 'TLON', 'opening_m', 'wfimelt', 'sfc_salt_flux_restore', 'pe_tot', 'fsalt_ai_m', 'evap_heat', 'ANGLET', 'neutral', 'total_ocean_evap', 'yu_ocean', 'age_global', 'lw_heat', 'tau_x', 'sw_edges_ocean', 'ty_trans_nrho_submeso', 'temp_yflux_adv', 'strength_m', 'Tsfc_m', 'total_ocean_calving_melt_heat', 'ty_trans', 'divu_m', 'geolon_c', 'alidr_ai_m', 'passive_adelie', 'total_net_sfc_heating', 'time_bounds', 'hs_m', 'pot_temp', 'frz_onset_m', 'average_T2', 'congel_m', 'total_ocean_sens_heat', 'sfc_hflux_coupler', 'sea_level', 'tau_y', 'total_ocean_salt', 'sea_levelsq', 'lprec', 'total_ocean_river', 'dxt', 'xt_ocean_sub01', 'vatm_m', 'total_ocean_swflx', 'runoff', 'temp_advection', 'tarea', 'uvel_m', 'grid_xu_ocean', 'total_ocean_runoff', 'total_ocean_evap_heat', 'ty_trans_submeso', 'hu', 'scalar_axis', 'wfiform', 'v', 'total_ocean_lprec', 'dyt', 'sfc_hflux_pme', 'ty_trans_int_z', 'sig1_m', 'tmask', 'u_dot_grad_vert_pv', 'temp', 'total_ocean_hflux_coupler', 'uocn_m', 'temp_nonlocal_KPP', 'wt', 'rhoave', 'sfc_salt_flux_ice', 'NCAT', 'frazil_3d', 'sw_ocean', 'passive_ross', 'grid_yt_ocean', 'area_t', 'frazil_m', 'tx_trans_int_z', 'st_edges_ocean', 'total_ocean_pme_river', 'dyu', 'hi_m', 'alvdr_ai_m', 'surface_temp', 'total_ocean_river_heat', 'u', 'sig2_m', 'temp_vdiffuse_impl', 'time', 'pme_river']

We could similarly filter for any of the keys in our catalog - see the intake dataframe catalog below

[24]:

catalog.search(name=experiment)

Intake dataframe catalog with 1 source(s) across 6 rows:

model description realm frequency variable
name
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} {3mon, 3hr, 1day, fx, 1mon} {HTN, st_ocean, nv, mlt_onset_m, mld, grid_yu_ocean, total_ocean_lw_heat, grid_xt_ocean, dzt, eta_t, pme_net, kmt, sens_heat, potrho, total_ocean_swflx_vis, xu_ocean_sub01, total_ocean_melt, sfc_h... 
[25]:

catalog.search(name=experiment, realm = 'ocean')

Intake dataframe catalog with 1 source(s) across 5 rows:

model description realm frequency variable
name
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} {3mon, 3hr, 1day, fx, 1mon} {st_ocean, nv, mld, grid_yu_ocean, total_ocean_lw_heat, grid_xt_ocean, dzt, eta_t, pme_net, kmt, sens_heat, potrho, total_ocean_swflx_vis, xu_ocean_sub01, total_ocean_melt, sfc_hflux_from_runoff, ... 
[26]:

# Lets pull out all the unique frequencies, just like we did for variable above
catalog.search(name=experiment, realm='ocean').unique().frequency

[26]:

['3mon', '3hr', '1day', 'fx', '1mon']

We could also open the experiment (using square brackets) to search for variables, frequencies, etc. - but this opens the datastore: see how the output of the cell below is displayed differently.

If we open the datastore:

  1. It is slower - opening datastores requires extra work

  2. The items we can search on might change - the datastore below contains no model field, for example.

The opened datastore can contain extra information, eg. variable_long_name below - so sometimes you might want to open it to search the datastore. In general, try to use catalog.search(name='xyz',...) before you use catalog['xyz'].search(...), though.

[27]:

catalog[experiment]

01deg_jra55v13_ryf9091 catalog with 22 dataset(s) from 11947 asset(s):

unique
filename 3469
path 11947
file_id 22
frequency 5
start_date 3361
end_date 3360
variable 205
variable_long_name 197
variable_standard_name 36
variable_cell_methods 3
variable_units 52
realm 2
derived_variable 0

For more information about the available variables, you can use the following command function - just copy and paste it in where you need it:

[28]:

from intake_esm.utils import MinimalExploder

def get_detailed_variable_info(intake_catalog, experiment_name : str, variable : str | None = None) -> "pd.Dataframe":
    """
    Get detailed information about all the variables available in an experiment contained within the catalog.

    If a specific variable is passed, then the returned dataframe will be filtered to include only information
    about that variable

    Returns a pandas dataframe, reorganised to use the variable as the index.

    Parameters:
    -----------
    intake_catalog:
        The variable holding the intake catalog. If you have opened the catalog using
        `cat = intake.cat.access_nri`, then `intake_catalog=cat`, etc.
    experiment_name: str
        The name of the experiment you are interested in. Eg. `experiment = "01deg_jra55v13_ryf9091"`
    variable: str | None
        If you want detailed information about just a single variable, then pass it here. For
        example, if you only want information about potential temperature, pass `variable='pot_temp'`
    """


    expt_ds = intake_catalog[experiment_name]
    df = MinimalExploder(expt_ds.esmcat.pl_df)()

    df = df.unique('variable').sort('variable')

    df = df.to_pandas().set_index("variable")

    return df

To get detailed info about all variables:

[29]:

df = get_detailed_variable_info(catalog, experiment)
df.head(10)

[29]:
filename path file_id frequency start_date end_date variable_long_name variable_standard_name variable_cell_methods variable_units realm
variable
ANGLE iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 angle grid makes with latitude line on U grid radians seaIce
ANGLET iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 angle grid makes with latitude line on T grid radians seaIce
HTE iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 T cell width on East side m seaIce
HTN iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 T cell width on North side m seaIce
NCAT iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 category maximum thickness m seaIce
TLAT iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 T grid center latitude degrees_north seaIce
TLON iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 T grid center longitude degrees_east seaIce
Tsfc_m iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 snow/ice surface temperature time: mean C seaIce
ULAT iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 U grid center latitude degrees_north seaIce
ULON iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 U grid center longitude degrees_east seaIce

Say we are only interested in zonal wind stress, tau_x:

[30]:

df = get_detailed_variable_info(catalog, experiment, 'tau_x')
df.head(10)

[30]:
filename path file_id frequency start_date end_date variable_long_name variable_standard_name variable_cell_methods variable_units realm
variable
ANGLE iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 angle grid makes with latitude line on U grid radians seaIce
ANGLET iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 angle grid makes with latitude line on T grid radians seaIce
HTE iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 T cell width on East side m seaIce
HTN iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 T cell width on North side m seaIce
NCAT iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 category maximum thickness m seaIce
TLAT iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 T grid center latitude degrees_north seaIce
TLON iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 T grid center longitude degrees_east seaIce
Tsfc_m iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 snow/ice surface temperature time: mean C seaIce
ULAT iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 U grid center latitude degrees_north seaIce
ULON iceh.1900-01.nc /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v13_ryf9091/output000/ice/OUTPUT/iceh.1900-01.nc seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700 1mon 1900-01-01, 00:00:00 1900-02-01, 00:00:00 U grid center longitude degrees_east seaIce

If you have any further questions after reading this notebook and the documentation linked from this notebook, please open an issue in the ACCESS-NRI Intake catalog Github repo or open topic on the ACCESS-Hive forum.

[ ]:

client.close()

[ ]: