Configuration and spin-up of ACCESS-CM2, the new generation Australian Community Climate and Earth System Simulator Coupled Model
Daohua Bi A I , Martin Dix A , Simon Marsland A B C , Siobhan O’Farrell A , Arnold Sullivan A , Roger Bodman D , Rachel Law A , Ian Harman E , Jhan Srbinovsky A , Harun A. Rashid A , Peter Dobrohotoff A , Chloe Mackallah A , Hailin Yan F , Anthony Hirst F , Abhishek Savita A B C , Fabio Boeira Dias A B C , Matthew Woodhouse A , Russell Fiedler G and Aidan Heerdegen C H
+ Author Affiliations
- Author Affiliations
A CSIRO Oceans and Atmosphere, 107–121 Station Street, Aspendale, Vic. 3195, Australia.
B Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Australia.
C ARC Centre of Excellence for Climate Extremes, Sydney, Australia.
D University of Melbourne, Melbourne, Australia.
E CSIRO Oceans and Atmosphere, Canberra, Australia.
F Bureau of Meteorology, Melbourne, Australia.
G CSIRO Oceans and Atmosphere, Hobart, Australia.
H Australian National University, Canberra, Australia.
I Corresponding author. Email: Dave.Bi@csiro.au
Journal of Southern Hemisphere Earth Systems Science 70(1) 225-251 https://doi.org/10.1071/ES19040
Submitted: 20 December 2019 Accepted: 29 June 2020 Published: 8 October 2020
Journal Compilation © BoM 2020 Open Access CC BY-NC-ND
Abstract
A new version of the Australian Community Climate and Earth System Simulator coupled model, ACCESS-CM2, has been developed for a wide range of climate modelling research and applications. In particular, ACCESS-CM2 is one of Australia’s contributions to the World Climate Research Programme’s Coupled Model Intercomparison Project Phase 6 (CMIP6). Compared with the ACCESS1.3 model used for our CMIP5 submission, all model components have been upgraded as well as the coupling framework (OASIS3-MCT) and experiment control system (Rose/Cylc). The component models are: UM10.6 GA7.1 for the atmosphere, CABLE2.5 for the land surface, MOM5 for the ocean, and CICE5.1.2 for the sea ice. This paper describes the model configuration of ACCESS-CM2, documents the experimental set up, and assesses the model performance for the preindustrial spin-up simulation in comparison against (reconstructed) observations and ACCESS1.3 results. While the performance of the two generations of the ACCESS coupled model is largely comparable, ACCESS-CM2 shows better global hydrological balance, more realistic ocean water properties (in terms of spatial distribution) and meridional overturning circulation in the Southern Ocean but a poorer simulation of the Antarctic sea ice and a larger energy imbalance at the top of atmosphere. This energy imbalance reflects a noticeable warming trend of the global ocean over the spin-up period.
Keywords: ACCESS-CM2, climate change, climate simulation, CMIP6, coupled climate model, evaluation, greenhouse gases, physical configuration, preindustrial spin-up, tuning and debugging.
References
Adcroft, A., and Campin, J.-M. (2004). Rescaled height coordinates for accurate representation of free-surface flows in ocean circulation models. Ocean Modell 7, 269–284.| Rescaled height coordinates for accurate representation of free-surface flows in ocean circulation models.Crossref | GoogleScholarGoogle Scholar |
Adler, R. F., Sapiano, M. R. P., Huffman, G. J., Wang, J.-J., Gu, G., Bolvin, D., Chiu, L., Schneider, U., Becker, A., Nelkin, E., Xie, P., Ferraro, R., and Shin, D.-B. (2018). The Global Precipitation Climatology Project (GPCP) Monthly Analysis (New Version 2.3) and a Review of 2017 Global Precipitation. Atmosphere 9, 138.
| The Global Precipitation Climatology Project (GPCP) Monthly Analysis (New Version 2.3) and a Review of 2017 Global Precipitation.Crossref | GoogleScholarGoogle Scholar | 30013797PubMed |
Allan, R. P., Liu, C., Loeb, N. G., Palmer, M. D., Roberts, M., Smith, D., and Vidale, P. L. (2014). Changes in global net radiative imbalance 1985–2012. Geophys. Res. Lett. 41, 5588–5597.
| Changes in global net radiative imbalance 1985–2012.Crossref | GoogleScholarGoogle Scholar | 25821270PubMed |
Antonov, J. I., Locarnini, R. A., Boyer, T. P., Mishonov, A. V. and Garcia, H. E. (2006). ‘World Ocean Atlas 2005, Vol. 2: Salinity. NOAA Atlas NESDIS 62.’ (Ed. S. Levitus.) (U.S. Government Printing Office: Washington, D.C.)
Antonov, J. I., Seidov, D., Boyer, T. P., Locarnini, R. A., Mishonov, A. V., Garcia, H. E., Baranova, O. K., Zweng, M. M. and Johnson, D. R. (2010). ‘World Ocean Atlas 2009, Vol. 2: Salinity. NOAA Atlas NESDIS 69.’ (Ed. S. Levitus.), (U.S. Government Printing Office: Washington, D.C.)
Arakawa, A. and Lamb, V. R. (1977). Computational design and the basic dynamical processes of the UCLA general circulation Model. In ‘Methods in Computational Physics: Advances in Research and Applications, Vol. 17’. (Ed. J. Chang.) pp. 173–265. (Elsevier.)
Arribas, A., Glover, M., Maidens, A., Peterson, K., Gordon, M., MacLachlan, C., Cusack, S., and Scaife, A. (2011). The GloSea4 ensemble prediction system for seasonal forecasting. Mon. Wea. Rev. 139, 1891–1910.
| The GloSea4 ensemble prediction system for seasonal forecasting.Crossref | GoogleScholarGoogle Scholar |
Bacon, S. (1997). Circulation and fluxes in the North Atlantic between Greenland and Ireland. J. Phys. Oceanogr. 27, 1420–1435.
| Circulation and fluxes in the North Atlantic between Greenland and Ireland.Crossref | GoogleScholarGoogle Scholar |
Bellouin, N., Rae, J., Jones, A., Johnson, C., Haywood, J., and Boucher, O. (2011). Aerosol forcing in the Climate Model Intercomparison Project (CMIP5) simulations by HadGEM2‐ES and the role of ammonium nitrate. J. Geophys. Res. 116, D20206.
| Aerosol forcing in the Climate Model Intercomparison Project (CMIP5) simulations by HadGEM2‐ES and the role of ammonium nitrate.Crossref | GoogleScholarGoogle Scholar |
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J. (2011). The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes. Geosci. Model Dev. 4, 677–699.
| The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes.Crossref | GoogleScholarGoogle Scholar |
Bi, D. and Marsland, S. J. (2010). Australian Climate Ocean Model (AusCOM) Users Guide. CAWCR Technical Report No. 027. The Centre for Australian Weather and Climate Research, a partnership between CSIRO and the Bureau of Meteorology.
Bi, D., Budd, W. F., Hirst, A. C., and Wu, X. (2002). Response of the Antarctic Circumpolar Current to global warming forcing in the CSIRO coupled model. Geophys. Res. Lett. 29, 2173.
| Response of the Antarctic Circumpolar Current to global warming forcing in the CSIRO coupled model.Crossref | GoogleScholarGoogle Scholar |
Bi, D., Marsland, S. J., Uotila, P., O’Farrell, S., Fiedler, R., Sullivan, A., Griffies, S. M., Zhou, X., and Hirst, A. C. (2013a). ACCESSOM: the ocean and sea-ice core of the ACCESS coupled model. Aust. Meteor. Oceanogr. J. 63, 213–232.
| ACCESSOM: the ocean and sea-ice core of the ACCESS coupled model.Crossref | GoogleScholarGoogle Scholar |
Bi, D., Dix, M., Marsland, S. J., O’Farrell, S., Rashid, H. A., Uotila, P., Hirst, A. C., Kowalczyk, E., Golebiewski, M., Sullivan, A., Yan, H., Hannah, N., Franklin, C., Sun, Z., Vohralik, P., Watterson, I., Zhou, X., Fiedler, R., Collier, M., Ma, Y., Noonan, J., Stevens, L., Uhe, P., Zhu, H., Griffies, S. M., Hill, R., Harris, C., and Puri, K. (2013b). The ACCESS coupled model: description, control climate and evaluation. Aust. Meteor. Oceanogr. J. 63, 41–64.
| The ACCESS coupled model: description, control climate and evaluation.Crossref | GoogleScholarGoogle Scholar |
Bellenger, H., Guilyardi, E., Leloup, J., Lengaigne, J., and Vialard, J. (2014). ENSO representation in climate models: from CMIP3 to CMIP5. Climate Dyn. 42, 1999–2018.
| ENSO representation in climate models: from CMIP3 to CMIP5.Crossref | GoogleScholarGoogle Scholar |
Bitz, C. M., and Lipscomb, W. H. (1999). An energy-conserving thermodynamic model of sea ice. J. Geophys. Res.-Oceans 104, 15669–15677.
| An energy-conserving thermodynamic model of sea ice.Crossref | GoogleScholarGoogle Scholar |
Brown, A. R., Beare, R. J., Edwards, J. M., Lock, A. P., Keogh, S. J., Milton, S. F., and Walters, D. N. (2008). Upgrades to the boundary-layer scheme in the Met Office numerical weather prediction model. Bound.-Lay. Meteorol. 128, 117–132.
| Upgrades to the boundary-layer scheme in the Met Office numerical weather prediction model.Crossref | GoogleScholarGoogle Scholar |
Boutle, I. A., and Morcrette, C. J. (2010). Parametrization of area cloud fraction. Atmos. Sci. Lett. 11, 283–289.
| Parametrization of area cloud fraction.Crossref | GoogleScholarGoogle Scholar |
Boyer, T., Locarnini, R. A., Zweng, M. M.,. Mishonov, A. V. Reagan, J. R., Antonov, J. I. Garcia, H. E., Baranova, O. K., Johnson, D. R., Seidov, D., Biddle, M. M. and Hamilton, M. (2015). ‘Changes to calculations of the World Ocean Atlas 2013 for version 2.’ (National Oceanographic Data Center: Silver Spring.)
Cavalieri, D. J., Parkinson, C. L., Gloersen, P., Comiso, J. C., and Zwally, H. J. (1999). Deriving long‐term time series of sea ice cover from satellite passive‐microwave multisensor data sets. J. Geophys. Res. 104, 15803–15814.
| Deriving long‐term time series of sea ice cover from satellite passive‐microwave multisensor data sets.Crossref | GoogleScholarGoogle Scholar |
Charney, J. G., and Phillips, N. A. (1953). Numerical integration of the quasi-geostrophic equations for barotropic and simple baroclinic flows. J. Meteor. 10, 71–99.
| Numerical integration of the quasi-geostrophic equations for barotropic and simple baroclinic flows.Crossref | GoogleScholarGoogle Scholar |
Cinquini, L., Crichton, D., Mattmann, C., Harney, J., Shipman, G., Wang, F., Ananthakrishnan, R., Miller, N., Denvil, S., Morgan, M., Pobre, Z., Bell, G. M., Doutriaux, C., Drach, R., Williams, D., Kershaw, P., Pascoe, S., Gonzalez, E., Fiore, S., and Schweitzer, R. (2014). The Earth System Grid Federation: An open infrastructure for access to distributed geospatial data. Future Gener. Comp. Syst. 36, 400–417.
| The Earth System Grid Federation: An open infrastructure for access to distributed geospatial data.Crossref | GoogleScholarGoogle Scholar |
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, , Boucher, O., Cox, P. M., and Harding, R. J. (2011). The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation. Geosci. Model Dev. 4, 701–722.
| The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation.Crossref | GoogleScholarGoogle Scholar |
Clarke, R. A. (1984). Transport through the Cape Farewell–Flemish Cap section. Rapp. P.-V. Reun.- Cons. Int. Explor. Mer. 185, 120–130.
Colin de Verdière, A., and Ollitrault, M. (2016). A direct determination of the World Ocean barotropic circulation. J. Phys. Oceanogr. 46, 255–273.
| A direct determination of the World Ocean barotropic circulation.Crossref | GoogleScholarGoogle Scholar |
Collins, M., Booth, B. B. B., Bhaskaran, B., Harris, G. R., Murphy, J. M., Sexton, D. M. H., and Webb, M. J. (2010). Climate model errors, feedbacks and forcings: A comparison of perturbed physics and multi-model ensembles. Climate Dyn. 36, 1737–1766.
| Climate model errors, feedbacks and forcings: A comparison of perturbed physics and multi-model ensembles.Crossref | GoogleScholarGoogle Scholar |
Comiso, J. (2012). Large Decadal Decline of the Multi-year ice cover. J. Climate 25, 1176–1193.
| Large Decadal Decline of the Multi-year ice cover.Crossref | GoogleScholarGoogle Scholar |
Cracknell, A. P., Newcombe, S. K., Black, A. F., and Kirby, N. E. (2001). The ABDMAP (Algal Bloom Detection, Monitoring and Prediction) Concerted Action. Int. J. Remote Sens. 22, 205–247.
| The ABDMAP (Algal Bloom Detection, Monitoring and Prediction) Concerted Action.Crossref | GoogleScholarGoogle Scholar |
Craig, A., Valcke, S., and Coquart, L. (2017). Development and performance of a new version of the OASIS coupler, OASIS3-MCT_3.0. Geosci. Model Dev. 10, 3297–3308.
| Development and performance of a new version of the OASIS coupler, OASIS3-MCT_3.0.Crossref | GoogleScholarGoogle Scholar |
Danabasoglu, G., Yeager, S. G., Bailey, D., Behrens, E., Bentsen, M., Bi, D., Biastoch, A., Böning, C., Bozec, A., Canuto, V. M., Cassou, C., Chassignet, E., Coward, A. C., Danilov, S., Diansky, N., Drange, H., Farneti, R., Fernandez, E., Fogli, P. G., Forget, G., Fujii, Y., Griffies, S. M., Gusev, A., Heimbach, P., Howard, A., Jung, T., Kelley, M., Large, W. G., Leboissetier, A., Lu, J., Madec, G., Marsland, S. J., Masina, S., Navarra, A., Nurser, A. J. G., Pirani, A., Salas y Mélia, D., Samuels, B. L., Scheinert, M., Sidorenko, D., Treguier, A.-M., Tsujino, H., Uotila, P., Valcke, S., Voldoire, A., and Wang, Q. (2014). North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part I: Mean states. Ocean Model 73, 76–107.
| North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part I: Mean states.Crossref | GoogleScholarGoogle Scholar |
Davies, T., Cullen, M. J. P., Malcolm, A. J., Mawson, M. H., Staniforth, A., White, A. A., and Wood, N. (2005). A new dynamical core for the Met Office’s global and regional modelling of the atmosphere. Quart. J. Roy. Meteor. Soc 131, 1759–1782.
| A new dynamical core for the Met Office’s global and regional modelling of the atmosphere.Crossref | GoogleScholarGoogle Scholar |
Dix, M., Vohralik, P., Bi, D., Rashid, H., Marsland, S., O’Farrell, S., Uotila, P., Hirst, T., Kowalczyk, E., Sullivan, A., Yan, H., Franklin, C., Sun, Z., Watterson, I., Collier, M., Noonan, J., Rotstayn, L., Stevens, L., Uhe, P., and Puri, K. (2013). The ACCESS coupled model: documentation of core CMIP5 simulations and initial results. Aust. Meteor. Oceanogr. J. 63, 83–99.
| The ACCESS coupled model: documentation of core CMIP5 simulations and initial results.Crossref | GoogleScholarGoogle Scholar |
Donohue, K. A., Tracey, K. L., Watts, D. R., Chidichimo, M. P., and Chereskin, T. K. (2016). Mean Antarctic circumpolar current transport measured in Drake passage. Geophys. Res. Lett. 43, 11760–11767.
| Mean Antarctic circumpolar current transport measured in Drake passage.Crossref | GoogleScholarGoogle Scholar |
Doos, K., and Webb, D. J. (1994). The Deacon Cell and other meridional cells of the Southern Ocean. J. Phys. Ocean 24, 429442.
Downes, S. M., Farneti, R., Uotila, P., Griffies, S. M., Marsland, S. J., Bailey, D., Behrens, E., Bentsen, M., Bi, D. H., Biastoch, A., Boning, C., Bozec, A., Canuto, V. M., Chassignet, E., Danabasoglu, G., Danilov, S., Diansky, N., Drange, H., Fogli, P. G., Gusev, A., Howard, A., Ilicak, M., Jung, T., Kelley, M., Large, W. G., Leboissetier, A., Long, M., Lu, J. H., Masina, S., Mishra, A., Navarra, A., Nurser, A. J. G., Patara, L., Samuels, B. L., Sidorenko, D., Spence, P., Tsujino, H., Wang, Q., and Yeager, S. G. (2015). An assessment of Southern Ocean water masses and sea ice during 1988–2007 in a suite of interannual CORE-II simulations. Ocean Model 94, 67–94.
| An assessment of Southern Ocean water masses and sea ice during 1988–2007 in a suite of interannual CORE-II simulations.Crossref | GoogleScholarGoogle Scholar |
Edwards, J. M., and Slingo, A. (1996). Studies with a flexible new radiation code. I: Choosing a configuration for a large-scale model. Quart. J. Roy. Meteor. Soc. 122, 689–719.
| Studies with a flexible new radiation code. I: Choosing a configuration for a large-scale model.Crossref | GoogleScholarGoogle Scholar |
Eyring, V., Bony, S., Meehl, G. A., Senior, C., Stevens, B., Stouffer, R. J., and Taylor, K. E. (2016). Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organisation. Geosci. Model Dev. 9, 1937–1958.
| Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organisation.Crossref | GoogleScholarGoogle Scholar |
Fairall, C. W., Bradley, E. F., Hare, J. E., Grachev, A. A., and Edson, J. B. (2003). Bulk parameterization of air-sea fluxes: updates and verification for the COARE algorithm. J. Climate 16, 571–591.
| Bulk parameterization of air-sea fluxes: updates and verification for the COARE algorithm.Crossref | GoogleScholarGoogle Scholar |
Ferrari, R., Griffies, S. M., Nurser, A. J. G., and Vallis, G. K. (2010). A boundary-value problem for the parameterized mesoscale eddy transport. Ocean Model 32, 143–156.
| A boundary-value problem for the parameterized mesoscale eddy transport.Crossref | GoogleScholarGoogle Scholar |
Fetterer, F., Knowles, K., Meier, W., Savoie, M., and Windnagel, A. K. (2017). ‘Sea Ice Index, Version 3, Tech. Rep.’ (NSIDC, National Snow and Ice Data Center: Boulder, Colorado, USA.) Available at https://doi.org/10.7265/N5K072F8.
Flato, G., Marotzke, J., Abiodun, B., Braconnot, P., Chou, S. C., Collins, W., Cox, P., Driouech, F., Emori, S., Eyring, V., Forest, C., Gleckler, P., Guilyardi, E., Jakob, C., Kattsov, V., Reason C. and Rummukainen M. (2013). Evaluation of Climate Models. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Eds T.F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley.) pp. 741–866. (Cambridge University Press: Cambridge, UK.)
Flocco, D., Feltham, D. L., and Turner, A. K. (2010). Incorporation of a physically based melt pond scheme into the sea ice component of a climate model. J. Geophys. Res.-Oceans 115, C08012.
| Incorporation of a physically based melt pond scheme into the sea ice component of a climate model.Crossref | GoogleScholarGoogle Scholar |
Flocco, D., Schroeder, D., Feltham, D. L., and Hunke, E. C. (2012). Impact of melt ponds on Arctic sea ice simulations from 1990 to 2007. J. Geophys. Res.-Oceans 117, C09032.
| Impact of melt ponds on Arctic sea ice simulations from 1990 to 2007.Crossref | GoogleScholarGoogle Scholar |
Franklin, C. N., Jakob, C., Dix, M., Protat, A., and Roff, G. (2012). Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP-ICE. Quart. J. Roy. Meteor. Soc. 138, 734–754.
| Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP-ICE.Crossref | GoogleScholarGoogle Scholar |
Ganachaud, A. (2003). Error budget of inverse box models: The North Atlantic. J. Atmos. Oceanic Technol. 20, 1641–1655.
| Error budget of inverse box models: The North Atlantic.Crossref | GoogleScholarGoogle Scholar |
Ganachaud, A., and Wunsch, C. (2000). The oceanic meridional overturning circulation, mixing, bottom water formation and heat transport. Nature 408, 453–457.
| The oceanic meridional overturning circulation, mixing, bottom water formation and heat transport.Crossref | GoogleScholarGoogle Scholar | 11100723PubMed |
Gent, P. R., and McWilliams, J. C. (1990). Isopycnal mixing in ocean circulation models. J. Phys. Oceanogr. 20, 150–155.
| Isopycnal mixing in ocean circulation models.Crossref | GoogleScholarGoogle Scholar |
Gent, P. R., Danabasoglu, G., Donner, L. J., Holland, M. M., Hunke, E. C., Jayne, S. R., Lawrence, D. M., Neale, R. B., Rasch, P. J., Vertenstein, M., Worley, P. H., Yang, Z. L., and Zhang, M. (2011). The Community Climate System Model Version 4. J. Climate 24, 2011.
| The Community Climate System Model Version 4.Crossref | GoogleScholarGoogle Scholar |
Gregory, D., and Rowntree, P. R. (1990). A massflux convection scheme with representation of cloud ensemble characteristics and stability dependent closure. Mon. Wea. Rev. 118, 1483–1506.
| A massflux convection scheme with representation of cloud ensemble characteristics and stability dependent closure.Crossref | GoogleScholarGoogle Scholar |
Gregory, D. and Allen, S. (1991). The effect of convective downdraughts upon NWP and climate simulations. Proceedings of the ninth conference on numerical weather prediction 14–18 October 1991, Denver, Colorado. American Meteorological Society. pp. 122–123.
Gregory, D., Kershaw, R., and Inness, P. M. (1997). Parametrization of momentum transport by convection II: Tests in single-column and general circulation models. Quart. J. Roy. Meteorol. Soc. 123, 1153–1183.
| Parametrization of momentum transport by convection II: Tests in single-column and general circulation models.Crossref | GoogleScholarGoogle Scholar |
Griffies, S. M. (2014). Elements of the Modular Ocean Model (MOM) (2012 release with update). GFDL Ocean Group Technical report No. 7, NOAA/GFDL, 632 + xiii pp.
Griffies, S. M., and Hallberg, R. W. (2000). Biharmonic friction with a Smagorinsky viscosity for use in large-scale eddy-permitting ocean models. Mon. Wea. Rev. 128, 2935–2946.
| Biharmonic friction with a Smagorinsky viscosity for use in large-scale eddy-permitting ocean models.Crossref | GoogleScholarGoogle Scholar |
Griffies, S. M., Biastoch, A. W., Boening, C., Bryan, F., Chassignet, E., England, M., Gerdes, R., Haak, H., Hallberg, R. W., Hazeleger, W., Jungclaus, J., Large, W. G., Madec, G., Samuels, B. L., Scheinert, M., Gupta, A. S., Severijns, C. A., Simmons, H. L., Treguier, A. M., Winton, M., Yeager, S., and Yin, J. (2009). Coordinated ocean-ice reference experiments (COREs). Ocean Model 26, 1–46.
| Coordinated ocean-ice reference experiments (COREs).Crossref | GoogleScholarGoogle Scholar |
Griffies, S. M., Danabasoglu, G., Durack, P. J., Adcroft, A. J., Balaji, V., Böning, C. W., Chassignet, E. P., Curchitser, E., Deshayes, J., Drange, H., Fox-Kemper, B., Gleckler, P. J., Gregory, J. M., Haak, H., Hallberg, R. W., Heimbach, P., Hewitt, H. T., Holland, D. M., Ilyina, T., Jungclaus, J. H., Komuro, Y., Krasting, J. P., Large, W. G., Marsland, S. J., Masina, S., McDougall, T. J., Nurser, A. J. G., Orr, J. C., Pirani, A., Qiao, F., Stouffer, R. J., Taylor, K. E., Treguier, A. M., Tsujino, H., Uotila, P., Valdivieso, M., Wang, Q., Winton, M., and Yeager, S. G. (2016). OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project. Geosci. Model Dev. 9, 3231–3296.
| OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project.Crossref | GoogleScholarGoogle Scholar |
Harman, I., Bodman, R., Dix, M. and Srbinovsky, J. (2019). CABLE within ACCESS-CM2. CSIRO client report. Available at https://trac.nci.org.au/trac/cable/attachment/wiki/CableDocuments/Harman_2019_CoE_final_report_revised.pdf.
Hewitt, H. T., Copsey, D., Culverwell, I. D., Harris, C. M., Hill, R. S. R., Keen, A. B., McLaren, A. J., and Hunke, E. C. (2011). Design and implementation of the infrastructure of HadGEM3: the next-generation Met Office climate modelling system. Geosci. Model Dev. 4, 223–253.
| Design and implementation of the infrastructure of HadGEM3: the next-generation Met Office climate modelling system.Crossref | GoogleScholarGoogle Scholar |
Hirst, A. C., Jackett, D. R., and McDougall, T. J. (1996). The meridional overturning cells of a world ocean model in neutral surface coordinates. J. Phys. Ocean 26, 775–791.
| The meridional overturning cells of a world ocean model in neutral surface coordinates.Crossref | GoogleScholarGoogle Scholar |
Hunke, E. C., and Dukowicz, J. K. (1997). An Elastic–Viscous–Plastic Model for Sea ice Dynamics. J. Phys. Oceanogr 27, 1849–1867.
| An Elastic–Viscous–Plastic Model for Sea ice Dynamics.Crossref | GoogleScholarGoogle Scholar |
Hunke, E. C., Lipscomb, W. H., Turner, A. K., Jeffery, N. and Elliott, S. (2015). CICE: the Los Alamos Sea Ice Model Documentation and Software User’s Manual Version 5.1, LA-CC-06-012, Los Alamos National Laboratory, Los Alamos, NM, 2015.
Jochum, M. (2009). Impact of latitudinal variations in vertical diffusivity on climate simulations. J. Geophys. Res. 114, C01010.
| Impact of latitudinal variations in vertical diffusivity on climate simulations.Crossref | GoogleScholarGoogle Scholar |
Jones, P. W. (1997). A User’s Guide for SCRIP: A spherical coordinate remapping and interpolation package. LA-CC- 98-45, Los Alamos National Laboratory, N.M.
Kiss, A. E., Hogg, A. McC., Hannah, N., Boeira Dias, F., Brassington, G. B., Chamberlain, M. A., Chapman, C., Dobrohotoff, P., Domingues, C. M., Duran, E. R., England, M. H., Fiedler, R., Griffies, S. M., Heerdegen, A., Heil, P., Holmes, R. M., Klocker, A., Marsland, S. J., Morrison, A. K., Munroe, J., Nikurashin, M., Oke, P. R., Pilo, G. S., Richet, O., Savita, A., Spence, P., Stewart, K. D., Ward, M. L., Wu, F., and Zhang, X. (2020). ACCESS-OM2 v1.0: a global ocean–sea ice model at three resolutions. Geosci. Model Dev. 13, 401–442.
| ACCESS-OM2 v1.0: a global ocean–sea ice model at three resolutions.Crossref | GoogleScholarGoogle Scholar |
Kowalczyk, E. A., Stevens, L., Law, R. M., Dix, M., Wang, Y. P., Harman, I. N., Hayens, K., Srbinovsky, J., Pak, B., and Zhien, T. (2013). The land surface model component of ACCESS: description and impact on the simulated surface climatology. Aust. Met. Oceanog. J. 63, 65–82.
| The land surface model component of ACCESS: description and impact on the simulated surface climatology.Crossref | GoogleScholarGoogle Scholar |
Kuhlbrodt, T., Jones, C. G., Sellar, A., Storkey, D., Blockley, E., Stringer, M., et al. (2018). The low-resolution version of HadGEM3 GC3.1: Development and evaluation for global climate. J. Adv. Model. Earth. Syst. 10, 2865–2888.
| The low-resolution version of HadGEM3 GC3.1: Development and evaluation for global climate.Crossref | GoogleScholarGoogle Scholar | 30774751PubMed |
Kwok, R. (2018). Arctic sea ice thickness, volume, and multiyear ice coverage: losses and coupled variability (1958–2018). Environ, Res, Lett. 13, 105005.
| Arctic sea ice thickness, volume, and multiyear ice coverage: losses and coupled variability (1958–2018).Crossref | GoogleScholarGoogle Scholar |
Large, W., McWilliams, J., and Doney, S. (1994). Oceanic vertical mixing: a review and a model with a nonlocal boundary layer parameterization. Rev. Geophys. 32, 363–403.
| Oceanic vertical mixing: a review and a model with a nonlocal boundary layer parameterization.Crossref | GoogleScholarGoogle Scholar |
Law, R. M., Ziehn, T., Matear, R. J., Lenton, A., Chamberlain, M. A., Stevens, L. E., Wang, Y.-P., Srbinovsky, J., Bi, D., Yan, H., and Vohralik, P. F. (2017). The carbon cycle in the Australian Community Climate and Earth System Simulator (ACCESS-ESM1) – Part 1: Model description and pre-industrial simulation. Geosci. Model Dev. 10, 2567–2590.
| The carbon cycle in the Australian Community Climate and Earth System Simulator (ACCESS-ESM1) – Part 1: Model description and pre-industrial simulation.Crossref | GoogleScholarGoogle Scholar |
Lawrence, P. J., Feddema, J. J., Bonan, G. B., Meehl, G. A., O’Neill, B. C., Oleson, K. W., Levis, S., Lawrence, D. M., Kluzek, E., Lindsay, K., and Thorton, P. E. (2012). Simulating the biogeochemical impacts of transient land cover change and wood harvest in the Community Climate System Model (CCSM4) from 1850 to 2100. J Climate 25, 3071–3095.
| Simulating the biogeochemical impacts of transient land cover change and wood harvest in the Community Climate System Model (CCSM4) from 1850 to 2100.Crossref | GoogleScholarGoogle Scholar |
Lee, H.-C., Rosati, A., and Spelman, M. (2006). Barotropic tidal mixing effects in a coupled climate model: Oceanic conditions in the northern Atlantic. Ocean Model 3–4, 464–477.
| Barotropic tidal mixing effects in a coupled climate model: Oceanic conditions in the northern Atlantic.Crossref | GoogleScholarGoogle Scholar |
Leloup, J., Lengaigne, M., and Boulanger, J. (2008). Twentieth century ENSO characteristics in the IPCC database. Climate Dyn. 30, 277C291.
| Twentieth century ENSO characteristics in the IPCC database.Crossref | GoogleScholarGoogle Scholar |
Li, Q., Fox-Kemper, B., Breivikc, Ø., and Webb, A. (2017). Statistical models of global Langmuir mixing. Ocean Model 113, 95–114.
| Statistical models of global Langmuir mixing.Crossref | GoogleScholarGoogle Scholar |
Locarnini, R. A., Mishonov, A. V., Antonov, J. I., Boyer, T. P., Garcia, H. E. (2006). ‘World Ocean Atlas 2005, Vol. 1: Temperature. NOAA Atlas NESDIS 61’. (U.S. Government Printing Office: Washington, DC.)
Locarnini R. A., Mishonov, A. V., Antonov, J. I., Boyer, T. P. and Garcia, H. E. (2010). ‘World Ocean Atlas 2009, Vol. 1: Temperature. NOAA Atlas NESDIS 68’. (U.S. Government Printing Office: Washington DC.)
Lock, A. P. (2001). The numerical representation of entrainment in parametrizations of boundary layer turbulent mixing. Mon. Wea. Rev. 129, 1148–1163.
| The numerical representation of entrainment in parametrizations of boundary layer turbulent mixing.Crossref | GoogleScholarGoogle Scholar |
Lock, A. P., Brown, A. R., Bush, M. R., Martin, G. M., and Smith, R. N. B. (2000). A new boundary layer mixing scheme. Part I: Scheme description and single-column model tests. Mon. Wea. Rev. 128, 3187–3199.
| A new boundary layer mixing scheme. Part I: Scheme description and single-column model tests.Crossref | GoogleScholarGoogle Scholar |
Lumpkin, R., Speer, K., and Koltermann, K. (2008). Transport across 48°N in the Atlantic Ocean. J. Phys. Oceanogr. 38, 733–752.
| Transport across 48°N in the Atlantic Ocean.Crossref | GoogleScholarGoogle Scholar |
Mann, G. W., Carslaw, K. S., Spracklen, D. V., Ridley, D. A., Manktelow, P. T., Chipperfield, M. P., Pickering, S. J., and Johnson, C. E. (2010). Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model. Geosci. Model Dev. 3, 519–551.
| Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model.Crossref | GoogleScholarGoogle Scholar |
Mann, G. W., Carslaw, K. S., Ridley, D. A., Spracklen, D. V., Pringle, K. J., Merikanto, J., Korhonen, S., Schwarz, J. P., Lee, L. A., Manktelow, P. T., Woodhouse, M. T., Schmidt, A., Breider, T. J., Emmerson, K. M., Chipperfield, M. P., and Pickering, S. J. (2012). Intercomparison of modal and sectional aerosol microphysics representations within the same 3-D global chemical transport model. Atmos. Chem. Phys. 12, 4449–4476.
| Intercomparison of modal and sectional aerosol microphysics representations within the same 3-D global chemical transport model.Crossref | GoogleScholarGoogle Scholar |
Manners, J., Edwards, J. M., Hill, P. and Thelen, J.-C. (2015). SOCRATES (Suite Of Community RAdiative Transfer codes based on Edwards and Slingo) Technical Guide, Met Office, UK. Available at https://code.metoffice.gov.uk/trac/socrates (accessed 25 October 2017).
Marsland, S. J., Bi, D., Uotila, P., Fiedler, R., Griffies, S. M., Lorbacher, K., O’Farrell, S., Sullivan, A., Uhe, P., Zhou, X., and Hirst, A. C. (2013). Evaluation of ACCESS climate model ocean diagnostics in CMIP5 simulations. Aust. Meteor. Oceanogr. J. 63, 101–119.
| Evaluation of ACCESS climate model ocean diagnostics in CMIP5 simulations.Crossref | GoogleScholarGoogle Scholar |
McCarthy, G. D., Smeed, D. A., Johns, W. E., Frajka-Williams, E., Moat, B. I., et al. (2015). Measuring the Atlantic meridional overturning circulation at 26°N. Prog. Oceanogr. 130, 91–111.
| Measuring the Atlantic meridional overturning circulation at 26°N.Crossref | GoogleScholarGoogle Scholar |
Morcrette, C. J. (2012). Improvements to a prognostic cloud scheme through changes to its cloud erosion parametrization. Atmos. Sci. Let. 13, 95–102.
| Improvements to a prognostic cloud scheme through changes to its cloud erosion parametrization.Crossref | GoogleScholarGoogle Scholar |
Murray, R. J. (1996). Explicit generation of orthogonal grids for ocean models. J. Comput. Phys. 126, 251–273.
| Explicit generation of orthogonal grids for ocean models.Crossref | GoogleScholarGoogle Scholar |
Naveira Garabato, A. C., McDonagh, E. L., Stevens, D. P., Heywood, K. J., and Sanders, R. J. (2002). On the export of Antarctic BottomWater from the Weddell Sea. Deep-Sea Research II 49, 4715–4742.
| On the export of Antarctic BottomWater from the Weddell Sea.Crossref | GoogleScholarGoogle Scholar |
Oliver, H., Shin, M., Matthews, D., Sanders, O., Bartholomew, S., Clark, A., Fitzpatrick, B., van Haren, R., Hut, R., and Drost, N. (2019). Workflow Automation for Cycling Systems. Comput. Sci. Eng. 21, 7–21.
| Workflow Automation for Cycling Systems.Crossref | GoogleScholarGoogle Scholar |
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V., Rowell, D. P., Kent, E. C., and Kaplan, A. (2003). Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res. 108, 4407.
| Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century.Crossref | GoogleScholarGoogle Scholar |
Redi, M. H. (1982). Oceanic isopycnal mixing by coordinate rotation. J. Phys. Oceanogr. 12, 1154–1158.
| Oceanic isopycnal mixing by coordinate rotation.Crossref | GoogleScholarGoogle Scholar |
Ridley, J. K., Blockley, E. W., Keen, A. B., Rae, J. G. L., West, A. E., and Schroeder, D. (2018). The sea ice model component of HadGEM3-GC3.1. Geosci. Model Dev. 11, 713–723.
| The sea ice model component of HadGEM3-GC3.1.Crossref | GoogleScholarGoogle Scholar |
Samanta, D., Karnauskas, K. B., Goodkin, N. F., Coats, S., Smerdon, J. E., and Zhang, L. (2018). Coupled model biases breed spurious low-frequency variability in the tropical Pacific Ocean. Geophys. Res. Lett. 45, .
| Coupled model biases breed spurious low-frequency variability in the tropical Pacific Ocean.Crossref | GoogleScholarGoogle Scholar |
Shonk, J. K. P., and Hogan, R. J. (2008). Tripleclouds: an efficient method for representing cloud inhomogeneity in 1D radiation schemes by using three regions at each height. J. Climate 21, 2352–2370.
| Tripleclouds: an efficient method for representing cloud inhomogeneity in 1D radiation schemes by using three regions at each height.Crossref | GoogleScholarGoogle Scholar |
Sillmann, J., Kharin, V. V., Zhang, X., Zwiers, F. W., and Bronaugh, D. (2013). Climate extremes indicesin the CMIP5 multimodel ensemble: Part 1. Model evaluation in the present climate. J. Geophys. Res. Atmos. 118, 1716–1733.
| Climate extremes indicesin the CMIP5 multimodel ensemble: Part 1. Model evaluation in the present climate.Crossref | GoogleScholarGoogle Scholar |
Simmons, H. L., Jayne, S. R., St. Laurent, L. C., and Weaver, A. J. (2004). Tidally driven mixing in a numerical model of the ocean general circulation. Ocean Model 6, 245–263.
| Tidally driven mixing in a numerical model of the ocean general circulation.Crossref | GoogleScholarGoogle Scholar |
Smeed, D. A., Josey, S. A., Beaulieu, C., Johns, W. E., Moat, B. I., Frajka-Williams, E., et al. (2018). The North Atlantic Ocean is in a state of reduced overturning. Geophys. Res. Lett. 45, 1527–1533.
| The North Atlantic Ocean is in a state of reduced overturning.Crossref | GoogleScholarGoogle Scholar |
Stephens, G. L., Hakuba, M. Z., Hawcroft, M., Haywood, J. M., Behrangi, A., Kay, J. E., and Webster, P. J. (2016). The curious nature of the hemispheric symmetry of the Earth’s water and energy balances. Curr. Clim. Change Rep. 2, 135–147.
| The curious nature of the hemispheric symmetry of the Earth’s water and energy balances.Crossref | GoogleScholarGoogle Scholar |
Storkey, D., Blaker, A. T., Mathiot, P., Megann, A., Aksenov, Y., Blockley, E. W., Calvert, D., Graham, T., Hewitt, H. T., Hyder, P., Kuhlbrodt, T., Rae, J. G. L., and Sinha, B. (2018). UK Global Ocean GO6 and GO7: a traceable hierarchy of model resolutions. Geosci. Model Dev. 11, 3187–3213.
| UK Global Ocean GO6 and GO7: a traceable hierarchy of model resolutions.Crossref | GoogleScholarGoogle Scholar |
Sun, Z., Franklin, C., Zhou, X., Ma, Y., Okely, P., Bi, D., Dix, M., Hirst, A. C., Shonk, J. K. P., and Puri, K. (2013). Modifications in atmospheric physical parameterization for improving SST simulation in the ACCESS coupled model. Aust. Met. Oceanog. J. 63, 233–247.
| Modifications in atmospheric physical parameterization for improving SST simulation in the ACCESS coupled model.Crossref | GoogleScholarGoogle Scholar |
Taylor, K. E., Stouffer, R. J., and Meehl, G. A. (2012). An Overview of CMIP5 and the Experiment Design. Bull. Am. Met. Soc. 93, 485–498.
| An Overview of CMIP5 and the Experiment Design.Crossref | GoogleScholarGoogle Scholar |
Talley, L. D. (2013). Closure of the Global Overturning Circulation Through the Indian, Pacific, and Southern Oceans: Schematics and Transports. Oceanogr 26, 80–97.
| Closure of the Global Overturning Circulation Through the Indian, Pacific, and Southern Oceans: Schematics and Transports.Crossref | GoogleScholarGoogle Scholar |
Uotila, P., O’Farrell, S., Marsland, S., and Bi, D. (2012). A sea ice sensitivity study with a global ocean-ice model. Ocean Model 51, 1–18.
| A sea ice sensitivity study with a global ocean-ice model.Crossref | GoogleScholarGoogle Scholar |
Valcke, S. (2006). ‘OASIS3 User Guide (prism_2-5), PRISM Support Initiative No. 3.’ (CERFACS: Toulouse, France.)
Valcke, S., Craig, T., and Coquart, L. (2015). ‘OASIS3-MCT User Guide: OASIS3-MCT 3.0, Technical Report, TR/CMGC/15/38.’ (CERFACS: Toulouse, France.)
Walsh, J. E., Fetterer, F., Stewart, J. S., and Chapman, W. L. (2015). A database for depicting Arctic sea ice variations back to 1850. Geog. Rev. 107, 89–107.
| A database for depicting Arctic sea ice variations back to 1850.Crossref | GoogleScholarGoogle Scholar |
Walters, D., Boutle, I., Brooks, M., Melvin, T., Stratton, R., Vosper, S., Wells, H., Williams, K., Wood, N., Allen, T., et al. (2017). The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations. Geosci. Model Dev. 10, 1487–1520.
| The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations.Crossref | GoogleScholarGoogle Scholar |
Walters, D., Baran, A. J., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J., Furtado, K., Hill, P., Lock, A., Manners, J., et al. (2019). The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations. Geosci. Model Dev. 12, 1909–1963.
| The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations.Crossref | GoogleScholarGoogle Scholar |
Watterson, I. W., Hirst, A. C., and Rotstayn, L. D. (2013). A skill-score based evaluation of simulated Australian climate. Aust. Met. Oceanog. J. 63, 181–190.
| A skill-score based evaluation of simulated Australian climate.Crossref | GoogleScholarGoogle Scholar |
West, A. E., McLaren, A. J., Hewitt, H. T., and Best, M. J. (2016). The location of the thermodynamic atmosphere–ice interface in fully coupled models – a case study using JULES and CICE. Geosci. Model Dev. 9, 1125–1141.
| The location of the thermodynamic atmosphere–ice interface in fully coupled models – a case study using JULES and CICE.Crossref | GoogleScholarGoogle Scholar |
Wilson, D. R., Bushell, A. C., Kerr-Munslow, A. M., Price, J. D., and Morcrette, C. J. (2008). PC2: A prognostic cloud fraction and condensation scheme. I: Scheme description. Quart. J. Roy. Meteorol. Soc. 134, 2093–2107.
| PC2: A prognostic cloud fraction and condensation scheme. I: Scheme description. Quart.Crossref | GoogleScholarGoogle Scholar |
Wood, N., Staniforth, A., White, A., Allen, T., Diamantakis, M., Gross, M., Melvin, T., Smith, C., Vosper, S., Zerroukat, M., and Thuburn, J. (2014). An inherently mass-conserving semi-implicit semi-Lagrangian discretization of the deep-atmosphere global non-hydrostatic equations. Quart. J. Roy. Meteorol. Soc. 140, 1505–1520.
| An inherently mass-conserving semi-implicit semi-Lagrangian discretization of the deep-atmosphere global non-hydrostatic equations. Quart.Crossref | GoogleScholarGoogle Scholar |
Woodward, S. (2011). Mineral dust in HadGEM2, Tech. Rep. 87. Hadley Centre, Met Office, Exeter, UK
Yu, Y., Maykut, G. A., and Rothrock, D. A. (2004). Changes in thickness distribution of Arctic sea ice between 1958–1970 and 1993–1997. J. Geophys. Res. 108, C08004.
| Changes in thickness distribution of Arctic sea ice between 1958–1970 and 1993–1997.Crossref | GoogleScholarGoogle Scholar |
Zhou, X., Marsland, S., Fiedler, R., Bi, D., Hirst, A. C., and Oscar, A. (2015). Impact of different solar penetration depths on climate simulations. Tellus A 67, 18.
| Impact of different solar penetration depths on climate simulations.Crossref | GoogleScholarGoogle Scholar |
Ziehn, T., Chamberlain, M. A., Law, R., Lenton, A., Bodman, R. W., Dix, M., Stevens, L., Wang, Y.-P., and Srbinovsky, J. (2020). The Australian Earth System Model: ACCESS-ESM1.5. J. South. Hemisph. Earth Syst. Sci. , .
| The Australian Earth System Model: ACCESS-ESM1.5.Crossref | GoogleScholarGoogle Scholar |
