COSIMA offers PhD Top-up Scholarships for Ocean and Sea Ice Modelling valued $7,500 per year

PhD Top-up Scholarships for Ocean and Sea Ice Modelling 

Are you interested in understanding ocean physics, and do you have skills in computational/mathematical modelling?  

The Consortium for Ocean-Sea Ice Modelling in Australia is providing opportunities for PhD students to work at the intersection of high-performance computing and ocean-climate dynamics. Projects are available focusing on a wide range of topics, including: 

  1. The role of sea ice in the climate system; 
  2. Modelling biogeochemical cycles in the global ocean; 
  3. Coupling between surface waves and large-scale currents; 
  4. Antarctic ice shelves and their interaction with the Southern Ocean; and 
  5. The sensitivity of ocean dynamics to vertical coordinate systems in ocean models. 

These scholarships are valued at $7,500 per year for 3.5 years. Successful applicants will also need to be successful in receiving a Research Training Program (RTP) scholarship, or equivalent primary scholarship, at a COSIMA partner university (ANU, UNSW, UTas, USyd, UniMelb or U Adelaide). 

 

To Apply, you should submit a package to Ms Alina Bryleva Alina.Bryleva@anu.edu.au including: 

  • A half-page statement explaining your research interests and your planned work with COSIMA. 
  • Your CV and academic transcripts. 
  • Provide amount and source of any existing scholarships, both top-ups and a primary stipend. 

These top-up scholarships are intended primarily for new students, however existing students working on one of the COSIMA models will also be considered. Preference will be given to competitive applicants who do not already receive a top-up scholarship from another source.   

Enquiries: Please contact Professor Andrew Hogg Andy.Hogg@anu.edu.au 
Closing date: 30 November 2021 

Data available: 0.1° 1958-2018 ACCESS-OM2 IAF runs

Announcement (updated 17 June 2021):

140TB of model output data from three consecutive 61-year (1958-2018) runs with COSIMA’s ACCESS-OM2-01 0.1-degree global coupled ocean – sea ice model is now available for anyone to use (see conditions below).

We recommend using the COSIMA Cookbook to access and analyse this data, which is all catalogued in the default cookbook database. A good place to start is the data explorer, which will give an overview of the data available.

Alternatively, the data can be directly accessed at NCI, mostly from
/g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v140_iaf*
and with a few fields (see details below) from
/g/data/ik11/outputs/access-om2-01/01deg_jra55v140_iaf_cycle3

You will need to be a member of the cj50 and ik11 groups to access this data directly or via the cookbook – apply at https://my.nci.org.au/mancini/project-search if needed.

The cj50 subset of the data (111TB) can be downloaded from here for those not on NCI.

The first cycle (01deg_jra55v140_iaf) was run under interannually-varying JRA55-do v1.4.0 forcing from 1 Jan 1958 to 31 Dec 2018, starting from rest with World Ocean Atlas 2013 v2 climatological temperature and salinity. The run configuration history is in the 01deg_jra55v140_iaf branch in the 01deg_jra55_iaf repository. It is based on that used for Kiss et al. (2020) but has many improvements to the forcing, initial conditions, parameters and code which will be documented soon. Summary details of each submitted run are tabulated (and searchable) here.

The second cycle (01deg_jra55v140_iaf_cycle2) continues from the end of the first cycle, with an identical configuration except that its initial condition was the final ocean and sea ice state of the first cycle, and some differences in the output variables. The run configuration history is in the 01deg_jra55v140_iaf_cycle2 branch and summary details of each submitted run are here.

Similarly, the third cycle (01deg_jra55v140_iaf_cycle3) continues from the end of cycle 2, with different output variables. The run configuration history is in the 01deg_jra55v140_iaf_cycle3 branch and summary details of each submitted run are here.

There are many outputs available for the entire run, with additional outputs available only in selected years (see below for details).
MOM5 ocean model outputs are saved under self-explanatory filenames in
/g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v140_iaf*/output*/ocean/*.nc
and CICE5 sea ice model outputs are in
/g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v140_iaf*/output*/ice/OUTPUT/*.nc
(if there are too many files to list with ls, narrow it down, e.g. by including the year, e.g. *2000*.nc)

Annual restarts (on 1 Jan each year) are also available at
/g/data/ik11/restarts/access-om2-01/01deg_jra55v140_iaf*/restart*
for anyone who may wish to re-run a segment with different diagnostics or branch off a perturbation experiment.

Conditions of use:
We request that users of this or other COSIMA model code or output data:

    1. consider citing Kiss et al. (2020) [doi.org/10.5194/gmd-13-401-2020]
    2. include an acknowledgement such as the following:
      The authors thank the Consortium for Ocean-Sea Ice Modelling in Australia (COSIMA; www.cosima.org.au), for making the ACCESS-OM2 suite of models available at github.com/COSIMA/access-om2. Model runs were undertaken with the assistance of resources from the National Computational Infrastructure (NCI), which is supported by the Australian Government.
    3. let us know of any publications which use these models or data so we can add them to our list.

Details of model outputs available

Notes:

  • You may find this partial list of diagnostics useful for decoding the MOM diagnostic names.
  • The ty_trans_int_z diagnostic was incorrect and has therefore been deleted from cycles 1 and 2. Workarounds are given here.
  • surface_temp, temp_surface_ave and bottom_temp are conservative temperature, rather than the potential temperature specified in the OMIP protocol (Griffies et al., 2016) – see this discussion. If you need potential temperature, use pot_temp or surface_pot_temp.
  • Some CICE sea ice data is incorrect – see this issue.

Cycle 1: /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v140_iaf

  • 1 Jan 1958 to 31 Dec 2018
    • MOM ocean data
      • Daily mean 2d bottom_temp, frazil_3d_int_z, mld, pme_river, sea_level, sfc_hflux_coupler, sfc_hflux_from_runoff, sfc_hflux_pme, surface_salt, surface_temp
      • Monthly mean 3d age_global, buoyfreq2_wt, diff_cbt_t, dzt, pot_rho_0, pot_rho_2, pot_temp, salt, temp_xflux_adv, temp_yflux_adv, temp, tx_trans, ty_trans_nrho_submeso, ty_trans_rho, ty_trans_submeso, ty_trans, u, v, vert_pv, wt
      • Monthly mean 2d bmf_u, bmf_v, ekman_we, eta_nonbouss, evap_heat, evap, fprec_melt_heat, fprec, frazil_3d_int_z, lprec, lw_heat, melt, mh_flux, mld, net_sfc_heating, pbot_t, pme_net, pme_river, river, runoff, sea_level_sq, sea_level, sens_heat, sfc_hflux_coupler, sfc_hflux_from_runoff, sfc_hflux_pme, sfc_salt_flux_coupler, sfc_salt_flux_ice, sfc_salt_flux_restore, surface_salt, surface_temp, swflx, tau_x, tau_y, temp_int_rhodz, temp_xflux_adv_int_z, temp_yflux_adv_int_z, tx_trans_int_z, wfiform, wfimelt
      • Monthly mean squared 3d u, v
      • Monthly max 2d mld
      • Monthly min 2d surface_temp
      • Daily snapshot scalar eta_global, ke_tot, pe_tot, rhoave, salt_global_ave, salt_surface_ave, temp_global_ave, temp_surface_ave, total_net_sfc_heating, total_ocean_evap_heat, total_ocean_evap, total_ocean_fprec_melt_heat, total_ocean_fprec, total_ocean_heat, total_ocean_hflux_coupler, total_ocean_hflux_evap, total_ocean_hflux_prec, total_ocean_lprec, total_ocean_lw_heat, total_ocean_melt, total_ocean_mh_flux, total_ocean_pme_river, total_ocean_river_heat, total_ocean_river, total_ocean_runoff_heat, total_ocean_runoff, total_ocean_salt, total_ocean_sens_heat, total_ocean_sfc_salt_flux_coupler, total_ocean_swflx_vis, total_ocean_swflx
    • CICE sea ice data
      • Daily mean 2d aice, congel, dvidtd, dvidtt, frazil, frzmlt, hi, hs, snoice, uvel, vvel
      • Monthly mean 2d aice, alvl, ardg, congel, daidtd, daidtt, divu, dvidtd, dvidtt, flatn_ai, fmeltt_ai, frazil, frzmlt, fsalt, fsalt_ai, hi, hs, iage, opening, shear, snoice, strairx, strairy, strength, tsfc, uvel, vvel
  • 1 Jan 1987 to 31 Dec 2018 only
    • MOM ocean data
      • monthly mean 3d bih_fric_u, bih_fric_v, u_dot_grad_vert_pv
      • daily mean 3d salt, temp, u, v, wt
    • CICE sea ice data
      • daily mean 2d aicen, vicen
  • 1 Jan 2012 to 31 Dec 2018 only
    • MOM ocean data
      • monthly snapshot 2d sea_level
      • monthly snapshot 3d salt, temp, u, v, vert_pv and vorticity_z

Cycle 2: /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v140_iaf_cycle2

  • 1 Jan 1958 to 31 Dec 2018
    • MOM ocean data
      • Daily mean 2d bottom_temp, frazil_3d_int_z, mld, pme_river, sea_level, sfc_hflux_coupler, sfc_hflux_from_runoff, sfc_hflux_pme, surface_salt, surface_temp
      • Monthly mean 3d age_global, bih_fric_u, bih_fric_v, buoyfreq2_wt, diff_cbt_t, dzt, pot_rho_0, pot_rho_2, pot_temp, salt, temp_xflux_adv, temp_yflux_adv, temp, tx_trans, ty_trans_nrho_submeso, ty_trans_rho, ty_trans_submeso, ty_trans, u_dot_grad_vert_pv, u, v, vert_pv, wt
      • Monthly mean 2d bmf_u, bmf_v, ekman_we, eta_nonbouss, evap_heat, evap, fprec_melt_heat, fprec, frazil_3d_int_z, lprec, lw_heat, melt, mh_flux, mld, net_sfc_heating, pbot_t, pme_net, pme_river, river, runoff, sea_level_sq, sea_level, sens_heat, sfc_hflux_coupler, sfc_hflux_from_runoff, sfc_hflux_pme, sfc_salt_flux_coupler, sfc_salt_flux_ice, sfc_salt_flux_restore, surface_salt, surface_temp, swflx, tau_x, tau_y, temp_int_rhodz, temp_xflux_adv_int_z, temp_yflux_adv_int_z, tx_trans_int_z, wfiform, wfimelt
      • Monthly mean squared 3d u, v
      • Monthly max 2d mld
      • Monthly min 2d surface_temp
      • Daily snapshot scalar eta_global, ke_tot, pe_tot, rhoave, salt_global_ave, salt_surface_ave, temp_global_ave, temp_surface_ave, total_net_sfc_heating, total_ocean_evap_heat, total_ocean_evap, total_ocean_fprec_melt_heat, total_ocean_fprec, total_ocean_heat, total_ocean_hflux_coupler, total_ocean_hflux_evap, total_ocean_hflux_prec, total_ocean_lprec, total_ocean_lw_heat, total_ocean_melt, total_ocean_mh_flux, total_ocean_pme_river, total_ocean_river_heat, total_ocean_river, total_ocean_runoff_heat, total_ocean_runoff, total_ocean_salt, total_ocean_sens_heat, total_ocean_sfc_salt_flux_coupler, total_ocean_swflx_vis, total_ocean_swflx
    • CICE sea ice data
      • Daily mean 2d aice, congel, dvidtd, dvidtt, frazil, frzmlt, hi, hs, snoice, uvel, vvel
      • Monthly mean 2d aice, aicen, alvl, ardg, congel, daidtd, daidtt, divu, dvidtd, dvidtt, flatn_ai, fmeltt_ai, frazil, frzmlt, fsalt, fsalt_ai, hi, hs, iage, opening, shear, snoice, strairx, strairy, strength, tsfc, uvel, vvel, vicen
  • 1 April 1971 to 31 Dec 2018 only
    • CICE sea ice data
      • Daily mean 2d fcondtop_ai, fsurf_ai, meltb, melts, meltt, daidtd, daidtt
      • Monthly mean 2d fcondtop_ai, fsurf_ai, meltb, melts, meltt, fresh, dvirdgdt
  • 1 April 1989 to 31 Dec 2018 only
    • CICE sea ice data
      • Daily mean 2d aicen, vicen
  • 1 Oct 1989 to 31 Dec 2018 only
    • MOM ocean data
      • Daily max 2d surface_temp, bottom_temp, sea_level
      • Daily min 2d surface_temp
  • 1 April 1990 to 31 Dec 2018 only
    • MOM ocean data
      • Daily mean 2d usurf, vsurf
  • 1 January 2014 to 31 Dec 2018 only
    • MOM ocean data
      • Daily mean, min, max 2d surface_pot_temp
      • Monthly mean, min 2d surface_pot_temp
    • CICE sea ice data
      • Daily mean 2d sinz, tinz, divu
      • Monthly mean 2d sinz, tinz, strocnx, strocny

Cycle 3: mostly in /g/data/cj50/access-om2/raw-output/access-om2-01/01deg_jra55v140_iaf_cycle3 but with some (marked in italics) in /g/data/ik11/outputs/access-om2-01/01deg_jra55v140_iaf_cycle3

  • 1 Jan 1958 to 31 Dec 2018
    • MOM ocean data
      • Daily mean 3d salt, temp, uhrho_et, vhrho_nt (all but temp are at reduced precision and restricted to south of 60S)
      • Daily mean 2d bottom_temp, frazil_3d_int_z, mld, pme_river, sea_level, sfc_hflux_coupler, sfc_hflux_from_runoff, sfc_hflux_pme, surface_pot_temp, surface_salt, usurf, vsurf
      • Monthly mean 3d age_global, buoyfreq2_wt, diff_cbt_t, dzt, passive_adelie, passive_prydz, passive_ross, passive_weddell, pot_rho_0, pot_rho_2, pot_temp, salt_xflux_adv, salt_yflux_adv, salt, temp_xflux_adv, temp_yflux_adv, temp, tx_trans_rho, tx_trans, ty_trans_nrho_submeso, ty_trans_rho, ty_trans_submeso, ty_trans, u, v, vert_pv, wt
      • Monthly mean 2d bmf_u, bmf_v, ekman_we, eta_nonbouss, evap_heat, evap, fprec_melt_heat, fprec, frazil_3d_int_z, lprec, lw_heat, melt, mh_flux, mld, net_sfc_heating, pbot_t, pme_net, pme_river, river, runoff, sea_level_sq, sea_level, sens_heat, sfc_hflux_coupler, sfc_hflux_from_runoff, sfc_hflux_pme, sfc_salt_flux_coupler, sfc_salt_flux_ice, sfc_salt_flux_restore, surface_pot_temp, surface_salt, swflx, tau_x, tau_y, temp_int_rhodz, temp_xflux_adv_int_z, temp_yflux_adv_int_z, tx_trans_int_z, ty_trans_int_z, wfiform, wfimelt
      • Monthly mean squared 3d u, v
      • Daily max 2d bottom_temp, sea_level, surface_pot_temp
      • Daily min 2d surface_pot_temp
      • Monthly max 2d mld
      • Monthly min 2d surface_pot_temp
      • Daily snapshot scalar eta_global, ke_tot, pe_tot, rhoave, salt_global_ave, salt_surface_ave, temp_global_ave, temp_surface_ave, total_net_sfc_heating, total_ocean_evap_heat, total_ocean_evap, total_ocean_fprec_melt_heat, total_ocean_fprec, total_ocean_heat, total_ocean_hflux_coupler, total_ocean_hflux_evap, total_ocean_hflux_prec, total_ocean_lprec, total_ocean_lw_heat, total_ocean_melt, total_ocean_mh_flux, total_ocean_pme_river, total_ocean_river_heat, total_ocean_river, total_ocean_runoff_heat, total_ocean_runoff, total_ocean_salt, total_ocean_sens_heat, total_ocean_sfc_salt_flux_coupler, total_ocean_swflx_vis, total_ocean_swflx
    • CICE sea ice data
      • Daily mean 2d aice, congel, daidtd, daidtt, divu, dvidtd, dvidtt, fcondtop_ai, frazil, frzmlt, fsurf_ai, hi, hs, meltb, melts, meltt, sinz, snoice, tinz, uvel, vvel
      • Monthly mean 2d aice, aicen, alvl, ardg, congel, daidtd, daidtt, divu, dvidtd, dvidtt, dvirdgdt, fcondtop_ai, flatn_ai, fmeltt_ai, frazil, fresh, frzmlt, fsalt, fsalt_ai, fsurf_ai, hi, hs, iage, meltb, melts, meltt, opening, shear, sinz, snoice, strairx, strairy, strength, strocnx, strocny, tinz, tsfc, uvel, vvel, vicen
  • 1 Jan 1959 to 31 Mar 1963 only
    • MOM ocean data
      • Daily mean 3d passive_adelie, passive_prydz, passive_ross, passive_weddell
  • 1 Jan 2005 to 31 Dec 2018 only
    • MOM ocean data
      • Monthly mean 3d salt_xflux_adv, salt_yflux_adv
  • 1 July 2009 to 31 Dec 2018 only
    • MOM ocean data
      • Monthly mean 3d tx_trans_rho

SAMx paper submitted

The Southern Ocean has accounted for the vast majority of the global ocean heat uptake since the early 2000s. The atmospheric winds over the Southern Ocean play a leading role in its ability to uptake heat, by way of driving much of the Southern Ocean circulation. Observations of these winds indicate that they have been steadily changing over the past few decades, and hence, so too is the Southern Ocean heat uptake. However, despite recent research efforts, the details of the Southern Ocean’s response to these changing winds remain uncertain.

In a recently submitted paper, we introduce a novel methodology to examine the Southern Ocean’s response to changing winds. We perform numerical simulations with the COSIMA model suite at all three resolutions and driven by realistic atmospheric forcing conditions. Our novel approach requires us to characterise the dynamical differences between our various realistic forcing conditions, which we do so with a new simple diagnostic. This new diagnostic proves robust in predicting the rapid response of the Southern Ocean circulation to the changing winds.

Response of the Southern Ocean overturning circulation to extreme Southern Annular Mode conditions“; Stewart, Hogg, England & Waugh, Submitted to Geophysical Research Letters.

Figure: a) Three-monthly SAM index calculated from the JRA55-do dataset; solid bars indicate the Austral summer quarters (September-February, inclusive). The four SAMx periods are shaded, as well as the RYF9091. For comparison, the equivalent observation station-based SAM index of Marshall (2003) is included in black. b) Zonal average zonal winds for the SAMx and RYF9091 periods, with the location of the respective peaks indicated by the circles. Also included is the 1980–2010 average of the JRA55-do dataset (dashed cyan), and all remaining May–April periods between 1980–2015 coloured blue–red by their respective SAM index. c) Timeseries of the zonal average temperatures between 200–500m depth for 45–50S (upper) and 55–60S (lower); these latitudinal bands are selected to lie either side of the zonal wind speed maximum evident in (b). Distributions of the Year 5 temperature anomalies from the ACCESS-OM2-01 for (d) SAM+9899, (e) SAM+1011, (f) SAM-9192 and (g) SAM-0203 simulations. The black and dashed green contours represent the SAMx and RYF9091 isopycnals at 0.5kg/m3 intervals, respectively, with the cyan and dashed magenta contours representing the respective mixed-layer depths.

Updated COSIMA Cookbook default database

The COSIMA Cookbook is the recommended, and supported, method for finding and accessing COSIMA datasets.

Currently COSIMA datasets are located in temporary storage under the hh5 project on the /g/data filesystem at NCI. The default COSIMA Cookbook database (/g/data/hh5/tmp/cosima/database/access-om2.db) indexes data in this location.

The COSIMA datasets are being moved to a new project, ik11: dedicated storage provided by an ARC LIEF grant. As part of this transition the default database will change to:

/g/data/ik11/databases/cosima_master.db

and will index all data in /g/data/ik11/outputs/. The database is updated daily.

This change will take place from Wednesday the 1st of July. To access the old database pass an argument to create_session:

session = cc.database.create_session(db='/g/data/hh5/tmp/cosima/database/access-om2.db')

or set the COSIMA_COOKBOOK_DB environment variable, e.g. for bash

export set COSIMA_COOKBOOK_DB=/g/data/hh5/tmp/cosima/database/access-om2.db

In the same way the new ik11 database can be accessed by using the path to it (/g/data/ik11/databases/cosima_master.db) in the same manner as above.