Replicability of the EC-Earth3 Earth system model under a change in computing environment
Tóm tắt
Từ khóa
Tài liệu tham khảo
Acosta, M., Yepes, X., Massonnet, F., and Menegoz, M.: Reproducibility of an Earth System Model under a change in computing environment: Test Case, https://doi.org/10.23728/b2share.1931aca743f74dcb859de6f37dfad281, 2019. a
Añel, J. A.: The importance of reviewing the code, Commun. ACM, 5, 40, https://doi.org/10.1145/1941487.1941502, 2011. a
Añel, J. A.: Comment on “Most computational hydrology is not reproducible, so is it really science?” by Christopher Hutton et al., Water Resour. Res., 53, 2572–2574, https://doi.org/10.1002/2016wr020190, 2017. a
Baker, A. H., Hammerling, D. M., Levy, M. N., Xu, H., Dennis, J. M., Eaton, B. E., Edwards, J., Hannay, C., Mickelson, S. A., Neale, R. B., Nychka, D., Shollenberger, J., Tribbia, J., Vertenstein, M., and Williamson, D.: A new ensemble-based consistency test for the Community Earth System Model (pyCECT v1.0), Geosci. Model Dev., 8, 2829–2840, https://doi.org/10.5194/gmd-8-2829-2015, 2015. a, b, c, d, e
Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., van den Hurk, B., Hirschi, M., and Betts, A. K.: A revised hydrology for the ECMWF model: Verification from field site to terrestrial water storage and impact in the Integrated Forecast System, J. Hydrometeorol., 10, 623–643, 2009. a
Beckmann, A. and Döscher, R.: A Method for Improved Representation of Dense Water Spreading over Topography in Geopotential-Coordinate Models, J. Phys. Oceanogr., 27, 581–591, https://doi.org/10.1175/1520-0485(1997)027<0581:amfiro>2.0.co;2, 1997. a
Berg, J.: Progress on reproducibility, Science, 359, 9–9, https://doi.org/10.1126/science.aar8654, 2018. a
Blanke, B. and Delecluse, P.: Variability of the Tropical Atlantic Ocean Simulated by a General Circulation Model with Two Different Mixed-Layer Physics, J. Phys. Oceanogr., 23, 1363–1388, https://doi.org/10.1175/1520-0485(1993)023<1363:vottao>2.0.co;2, 1993. a
Corden, M. J. and Kreitzer, M.: Consistency of Floating-Point Results using the Intel Compiler or Why doesn't my application always give the same answer?, available at: https://software.intel.com/en-us/articles/consistency-of-floating-point-results-using-the-intel-compiler (last access: 8 March 2019), Tech. rep., 2015. a
Donahue, A. S. and Caldwell, P. M.: Impact of Physics Parameterization Ordering in a Global Atmosphere Model, J. Adv. Model. Earth Syst., 10, 481–499, https://doi.org/10.1002/2017ms001067, 2018. a
Forbes, R., Tompkins, A., and Untch, A.: A new prognostic bulk microphysics scheme for the IFS, https://doi.org/10.21957/bf6vjvxk, available at: https://www.ecmwf.int/node/9441 (last access: 10 March 2020), 2011. a
Gent, P. R. and McWilliams, J. C.: Isopycnal Mixing in Ocean Circulation Models, J. Phys. Oceanogr., 20, 150–155, https://doi.org/10.1175/1520-0485(1990)020<0150:imiocm>2.0.co;2, 1990. a
Gurvan, M., Bourdallé-Badie, R., Pierre-Antoine Bouttier, Bricaud, C., Bruciaferri, D., Calvert, D., Chanut, J., Clementi, E., Coward, A., Delrosso, D., Ethé, C., Flavoni, S., Graham, T., Harle, J., Doroteaciro Iovino, Lea, D., Lévy, C., Lovato, T., Martin, N., Masson, S., Mocavero, S., Paul, J., Rousset, C., Storkey, D., Storto, A., and Vancoppenolle, M.: Nemo Ocean Engine, https://doi.org/10.5281/zenodo.1472492, 2017. a
Hawkins, E. and Sutton, R.: The Potential to Narrow Uncertainty in Regional Climate Predictions, B. Am. Meteorol. Soc., 90, 1095–1108, https://doi.org/10.1175/2009bams2607.1, 2009. a
Hawkins, E., Smith, R. S., Gregory, J. M., and Stainforth, D. A.: Irreducible uncertainty in near-term climate projections, Clim. Dynam., 46, 3807–3819, https://doi.org/10.1007/s00382-015-2806-8, 2015. a
Hazeleger, W., Wang, X., Severijns, C., Ştefănescu, S., Bintanja, R., Sterl, A., Wyser, K., Semmler, T., Yang, S., van den Hurk, B., van Noije, T., van der Linden, E., and van der Wiel, K.: EC-Earth V2.2: description and validation of a new seamless earth system prediction model, Clim. Dynam., 39, 2611–2629, https://doi.org/10.1007/s00382-011-1228-5, 2011. a, b
Hong, S.-Y., Koo, M.-S., Jang, J., Kim, J.-E. E., Park, H., Joh, M.-S., Kang, J.-H., and Oh, T.-J.: An Evaluation of the Software System Dependency of a Global Atmospheric Model, Mon. Weather Rev., 141, 4165–4172, https://doi.org/10.1175/mwr-d-12-00352.1, 2013. a
IPCC: IPCC, 2013: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Tech. Rep., 2013. a
Kjellsson, J., Holland, P. R., Marshall, G. J., Mathiot, P., Aksenov, Y., Coward, A. C., Bacon, S., Megann, A. P., and Ridley, J.: Model sensitivity of the Weddell and Ross seas, Antarctica, to vertical mixing and freshwater forcing, Ocean Model., 94, 141–152, https://doi.org/10.1016/j.ocemod.2015.08.003, 2015. a
Knight, C. G., Knight, S. H. E., Massey, N., Aina, T., Christensen, C., Frame, D. J., Kettleborough, J. A., Martin, A., Pascoe, S., Sanderson, B., Stainforth, D. A., and Allen, M. R.: Association of parameter, software, and hardware variation with large-scale behavior across climate models, P. Natl. Acad. Sci. USA, 104, 12259–12264, https://doi.org/10.1073/pnas.0608144104, 2007. a
Le Sager, P.: Suite of processing tools for EC-Earth3 output, available at: https://github.com/plesager/ece3-postproc, last access: 10 March 2020. a
Le Sager, P., Tourigny, E., Davini, P., and Ramos, A.: plesager/ece3-postproc: CMIP6-ready (Version 1.0.0), Zenodo, https://doi.org/10.5281/zenodo.3474777, 2019. a
Lorenz, E. N.: Deterministic Nonperiodic Flow, J. Atmos. Sci., 20, 130–141, https://doi.org/10.1175/1520-0469(1963)020<0130:dnf>2.0.co;2, 1963. a
Manubens-Gil, D., Vegas-Regidor, J., Prodhomme, C., Mula-Valls, O., and Doblas-Reyes, F. J.: Seamless management of ensemble climate prediction experiments on HPC platforms, in: 2016 International Conference on High Performance Computing & Simulation (HPCS), IEEE, https://doi.org/10.1109/hpcsim.2016.7568429, 2016. a
McArthur, S. L.: Repeatability, Reproducibility, and Replicability: Tackling the 3R challenge in biointerface science and engineering, Biointerphases, 14, 020201, https://doi.org/10.1116/1.5093621, 2019. a
Morcrette, J.-J., Barker, H. W., Cole, J. N. S., Iacono, M. J., and Pincus, R.: Impact of a New Radiation Package, McRad, in the ECMWF Integrated Forecasting System, Mon. Weather Rev., 136, 4773–4798, https://doi.org/10.1175/2008mwr2363.1, 2008. a
Plesser, H. E.: Reproducibility vs. Replicability: A Brief History of a Confused Terminology, Front. Neuroinf., 11, 76, https://doi.org/10.3389/fninf.2017.00076, 2018. a
Reichler, T. and Kim, J.: How Well Do Coupled Models Simulate Today's Climate?, B. Am. Meteorol. Soc., 89, 303–312, https://doi.org/10.1175/bams-89-3-303, 2008. a, b, c, d
Rosinski, J. M. and Williamson, D. L.: The Accumulation of Rounding Errors and Port Validation for Global Atmospheric Models, SIAM J. Sci. Comput., 18, 552–564, https://doi.org/10.1137/s1064827594275534, 1997. a
Servonnat, J., Foujols, M. A., Hourdin, F., Caubel, A., Terray, P., and Marti, O.: Comparaison du climat préindustriel du modèle IPSL-CM5A-LR sur différents calculateurs utilisés à l'IPSL, Bulletin d'Information ORAP 77, available at: http://orap.irisa.fr/wp-content/uploads/2016/03/Biorap-77.pdf (last access: 8 March 2019), Tech. rep., 2013. a
Thomas, S. J., Hacker, J. P., Desgagné, M., and Stull, R. B.: An Ensemble Analysis of Forecast Errors Related to Floating Point Performance, Weather Forecast., 17, 898–906, https://doi.org/10.1175/1520-0434(2002)017<0898:aeaofe>2.0.co;2, 2002. a
Valcke, S.: The OASIS3 coupler: a European climate modelling community software, Geosci. Model Dev., 6, 373–388, https://doi.org/10.5194/gmd-6-373-2013, 2013. a
Vancoppenolle, M., Fichefet, T., Goosse, H., Bouillon, S., Madec, G., and Maqueda, M. A. M.: Simulating the mass balance and salinity of Arctic and Antarctic sea ice. 1. Model description and validation, Ocean Model., 27, 33–53, https://doi.org/10.1016/j.ocemod.2008.10.005, 2009. a
van den Hurk, B., Viterbo, P., Beljaars, A., and Betts, A.: Offline validation of the ERA40 surface scheme, https://doi.org/10.21957/9aoaspz8, available at: https://www.ecmwf.int/node/12900 (last access: 10 March 2020), 2000. a