Early Development and Tuning of a Global Coupled Cloud Resolving Model, and its Fast Response to Increasing CO2
References
- Amdahl, GM. 1967. Validity of single processor approach to achieving large scale computing capabilities. AFIPS Conference Proceedings, 30: 483–485.
- Armour, KC, Bitz, CM and Roe, GH. 2013. Time-Varying Climate Sensitivity from Regional Feedbacks. Journal of Climate, 26(13): 4518–4534. DOI: 10.1175/JCLI-D-12-00544.1
- Balaji, V, et al. 2022. Are GCMs obsolete? Manuscript submitted.
- Baldauf, M, Seifert, A, Foerstner, J, Majewski, D, Raschendorfer, M and Reinhardt, T. 2011. Operational convective-scale numerical weather prediction with the COSMO model: Description and sensitivities. Monthly Weather Review, 139(12): 3887–3905. DOI: 10.1175/MWR-D-10-05013.1
- Bjerknes, V. 1904. Das Problem der Wettervorhersage, betrachtet vom Standpunkte der Mechanik und der Physik. Meteorol. Z., 21: 1–7.
- Bolin, B. 1955. Numerical forecasting with the barotropic model. Tellus, 7: 27–49. DOI: 10.3402/tellusa.v7i1.8770
- Bony, S, Bellon, G, Klocke, D, et al. 2013. Robust direct effect of carbon dioxide on tropical circulation and regional precipitation. Nature Geosci, 6: 447–451. DOI: 10.1038/ngeo1799
- Bony, S, Stevens, B, Ament, F, et al. 2017. EUREC4A: A Field Campaign to Elucidate the Couplings Between Clouds, Convection and Circulation. Surv Geophys, 38: 1529–1568. DOI: 10.1007/s10712-017-9428-0
- Charney, JG, Fjörtoft, R and von Neumann, J. 1950. Numerical integration of the barotropic vorticity equation. Tellus, 2(4): 237–254. DOI: 10.3402/tellusa.v2i4.8607
- Deardorff, J. 1970. A numerical study of three-dimensional turbulent channel flow at large Reynolds numbers. Journal of Fluid Mechanics, 41(2): 453–480. DOI: 10.1017/S0022112070000691
- Dipankar, A, Stevens, B, Heinze, R, Moseley, C, Zängl, G, Giorgetta, M and Brdar, S. 2015. Large eddy simulation using the general circulation model ICON. J. Adv. Model. Earth Syst., 7: 963–986. DOI: 10.1002/2015MS000431
- Fiedler, S, Crueger, T, D’Agostino, R, et al. 2020. Simulated Tropical Precipitation Assessed across Three Major Phases of the Coupled Model Intercomparison Project (CMIP). Mon. Wea. Rev., 148: 3653–3680. DOI: 10.1175/MWR-D-19-0404.1
- Flynn, C and Mauritsen, T. 2020. On the climate sensitivity and historical warming evolution in recentcoupled model ensembles. Atmos. Chem. Phys., 20: 7829–7842. DOI: 10.5194/acp-20-7829-2020
- Fuhrer, O, Chadha, T, Hoefler, T, Kwasniewski, G, Lapillonne, X, Leutwyler, D, Lüthi, D, Osuna, C, Schär, C, Schulthess, TC and Vogt, H. 2018. Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0. Geosci. Model Dev., 11: 1665–1681. DOI: 10.5194/gmd-11-1665-2018
- Giorgetta, MA, Brokopf, R, Crueger, T, Esch, M, Fiedler, S, Helmert, J, Hohenegger, C, Kornblueh, L, Köhler, M, Manzini, E, Mauritsen, T, Nam, C, Raddatz, T, Rast, S, Reinert, D, Sakradzija, M, Schmidt, H, Schneck, R, Schnur, R, Silvers, L, Wan, H, Zängl, G and Stevens, B. 2018. ICON-A, the atmosphere component of the ICON Earth system model: I. Model description. Journal of Advances in Modeling Earth Systems, 10: 1613–1637. DOI: 10.1029/2017MS001242
- Gregory, JM, Ingram, WJ, Palmer, MA, Jones, GS, Stott, PA, Thorpe, RB, Lowe, JA, Johns, TC and Williams, KD. 2004. A new method for diagnosing radiative forcing and climate sensitivity. Geophys. Res. Lett., 31: L03205. DOI: 10.1029/2003GL018747
- Hanke, M and Redler, R. 2019. New features with YAC 1.5.0. Reports on ICON, No 3. DOI: 10.5676/DWD_pub/nwv/icon_003
- Hanke, M, Redler, R, Holfeld, T and Yastremsky, M. 2016. YAC 1.2.0: new aspects for coupling software in Earth system modelling. Geosci. Model Dev., 9: 2755–2769. DOI: 10.5194/gmd-9-2755-2016
- Heikes, RH and Randall, DA. 1995a. Numerical integration of the shallow- water equations on a twisted icosahedral grid. Part I: Basic design and results of tests. Mon. Wea. Rev., 123: 1862–1880. DOI: 10.1175/1520-0493(1995)123<;1862:NIOTSW>2.0.CO;2
- Heikes, RH and Randall, DA. 1995b. Numerical integration of the shallow- water equations on a twisted icosahedral grid. Part II: A detailed description of the grid and analysis of numerical accuracy. Mon. Wea. Rev., 123: 1881–1887. DOI: 10.1175/1520-0493(1995)123<;1881:NIOTSW>2.0.CO;2
- Heinze, R, Dipankar, A, Henken, CC, Moseley, C, Sourdeval, O, Trömel, S, Xie, X, Adamidis, P, Ament, F, Baars, H, Barthlott, C, Behrendt, A, Blahak, U, Bley, S, Brdar, S, Brueck, M, Crewell, S, Deneke, H, Di Girolamo, P, Evaristo, R, Fischer, J, Frank, C, Friederichs, P, Göcke, T, Gorges, K, Hande, L, Hanke, M, Hansen, A, Hege, H-C, Hoose, C, Jahns, T, Kalthoff, N, Klocke, D, Kneifel, S, Knippertz, P, Kuhn, A, van Laar, T, Macke, A, Maurer, V, Mayer, B, Meyer, CI, Muppa, SK, Neggers, RAJ, Orlandi, E, Pantillon, F, Pospichal, B, Röber, N, Scheck, L, Seifert, A, Seifert, P, Senf, F, Siligam, P, Simmer, C, Steinke, S, Stevens, B, Wapler, K, Weniger, M, Wulfmeyer, V, Zängl, G, Zhang, D and Quaas, J. 2017. Large-eddy simulations over Germany using ICON: a comprehensive evaluation. Q.J.R. Meteorol. Soc., 143: 69–100. DOI: 10.1002/qj.2947
- Held, IM, Winton, M, Takahashi, K, Delworth, T, Zeng, F and Vallis, GK. 2010. Probing the Fast and Slow Components of Global Warming by Returning Abruptly to Preindustrial Forcing. Journal of Climate, 23(9): 2418–2427. DOI: 10.1175/2009JCLI3466.1
- Hohenegger, C, Kornblueh, L, Klocke, D, Becker, T, Cioni, G, Engels, JF, Schulzweida, U and Stevens, B. 2020. Climate statistics in global simulations of the atmosphere, from 80 to 2.5 km grid spacing. J. Meteorol. Society Japan, 98: 73–91. DOI: 10.2151/jmsj.2020-005
- Hohenegger, C, Korn, P, Linardakis, L, Redler, R, Schnur, R, Adamidis, P, Bao, J, Bastin, S, Behravesh, M, Bergemann, M, Biercamp, J, Bockelmann, H, Brokopf, R, Bruggemann, N, Esch, M, George, G, Giorgetta, MA, Gutjahr, O, Haak, H, Hanke, M, Jahns, T, Jungclaus, J, Kern, M, Klocke, D, Kluft, L, Kornblueh, L, Kosukhin, SS, Kroll, C, Lee, J, Luschow, V, Mauritsen, T, Müller, R, Naumann, AK, Paccini, L, Panos, S, Praturi, D, Putrasahan, D, Rast, S, Riddick, T, Roeber, N, Schmidt, H, Schulzweida, U, Segura, H, Shevchenko, R, Singh, V, Specht, MS, Stephan, C, von Storch, J-S, Vogel, R, Wengel, C, Winkler, M, Ziemen, F and Stevens, B. 2022. The ICON Sapphire model: a climate modeling system designed for applications at kilo- and subkilometer scales. In preparation.
- Hohenegger, C and Stevens, B. 2018. The role of the permanent wilting point in controlling the spatial distribution of precipitation. Proc. Natl. Acad. Sci., 115: 5692–5697. DOI: 10.1073/pnas.1718842115
- Hourdin, F, Mauritsen, T, Gettelman, A, Golaz, J, Balaji, V, Duan, Q, Folini, D, Ji, D, Klocke, D, Qian, Y, Rauser, F, Rio, C, Tomassini, L, Watanabe, M and Williamson, D. 2017. The Art and Science of Climate Model Tuning. Bulletin of the American Meteorological Society, 98(3): 589–602. DOI: 10.1175/BAMS-D-15-00135.1
- Hyder, P, Edwards, J, Allan, RP, et al. 2018. Critical Southern Ocean climate model biases traced to atmospheric model cloud errors. Nature Communication, 9: 3625. DOI: 10.1038/s41467-018-05634-2
- Jungclaus, JH, et al. 2021. The ICON Earth System Model Version 1.0. Earth and Space Science Open Archive. DOI: 10.1002/essoar.10507989.1
- Klemp, JB and Wilhelmson, RB. 1978. The Simulation of Three-Dimensional Convective Storm Dynamics. Journal of Atmospheric Sciences, 35(6): 1070–1096. DOI: 10.1175/1520-0469(1978)035<;1070:TSOTDC>2.0.CO;2
- Korn, P and Linardakis, L. 2018. A conservative discretization of the shallow-water equations on triangular grid. J. Comp. Phys., 375: 871–900. DOI: 10.1016/j.jcp.2018.09.002
- Loeb, NG, Doelling, DR, Wang, H, Su, W, Nguyen, C, Corbett, JG, Liang, L, Mitrescu, C, Rose, FG and Kato, S. 2018. Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) Edition-4.0 Data Product. J. Climate, 31: 895–918. DOI: 10.1175/JCLI-D-17-0208.1
- Lorenz, EN. 1969. The predictability of a flow which possesses manyscales of motion. Tellus, 21(3): 289–307. DOI: 10.3402/tellusa.v21i3.10086
- Lott, F. 1999. Alleviation of stationary biases in a GCM through a mountain drag parameterization scheme and a simple representation of mountain lift forces. Mon. Wea. Rev., 127: 788–801. DOI: 10.1175/1520-0493(1999)127<;0788:AOSBIA>2.0.CO;2
- Manabe, S and Bryan, K. 1969. Climate calculations with a combined ocean-atmosphere model. Journal of Atmospheric Sciences, 26(4): 786–789. DOI: 10.1175/1520-0469(1969)026<;0786:CCWACO>2.0.CO;2
- Manabe, S, Smagorinski, J and Strickler, RF. 1965. Simulated climatology of a general circulation model with a hydrological cycle. Monthly Weather Review, 93(12): 769–798. DOI: 10.1175/1520-0493(1965)093<;0769:SCOAGC>2.3.CO;2
- Mauritsen, T, et al. 2012. Tuning the climate of a global model. J. Adv. Model. Earth Syst., 4:
M00A01 . DOI: 10.1029/2012MS000154 - Mauritsen, T, Bader, J, Becker, T, Behrens, J, Bittner, M, Brokopf, R, et al. 2019. Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1.2) and its response to increasing CO2. Journal of Advances in Modeling Earth Systems, 11: 998–1038. DOI: 10.1029/2018MS001400
- Moore, GE. 1965. Cramming more components onto integrated circuits. Electronics Magazine, 38.
- Morice, CP, Kennedy, JJ, Rayner, NA, Winn, JP, Hogan, E, Killick, RE, Dunn, RJH, Osborn, TJ, Jones, PD and Simpson, IR. 2021. An updated assessment of near-surface temperature change from 1850: the HadCRUT5 dataset. Journal of Geophysical Research. DOI: 10.1029/2019JD032361
- Palmer, T and Stevens, B. 2019. The scientific challenge of understanding and estimating climate change. Proc. Natl. Acad. Sci., 116(49): 24390–24395. DOI: 10.1073/pnas.1906691116
- Phillips, NA. 1956. The general circulation of the atmosphere: A numerical experiment. Q.J.R. Meteorol. Soc., 82: 123–164. DOI: 10.1002/qj.49708235202
- Pithan, F, Angevine, W and Mauritsen, T. 2015. Improving a global model from the boundary layer: Total turbulent energy and the neutral limit Prandtl number. J. Adv. Model. Earth Syst., 7. DOI: 10.1002/2014MS000382
- Radtke, J, Mauritsen, T and Hohenegger, C. 2021. Shallow cumulus cloud feedback in large eddy simulations – bridging the gap to storm-resolving models. Atmos. Chem. Phys., 21: 3275–3288. DOI: 10.5194/acp-21-3275-2021
- Retsch, MH, Mauritsen, T and Hohenegger, C. 2019. Climate change feedbacks in aquaplanet experiments with explicit and parametrized convection for horizontal resolutions of 2,525 up to 5 km. Journal of Advances in Modeling Earth Systems, 11: 2070–2088. DOI: 10.1029/2019MS001677
- Richardson, LF. 1922.
Weather prediction by numerical process . Cambridge University Press, 258 pp. - Satoh, M. 2014.
Atmospheric Circulation Dynamics and General Circulation Models . Heidelberg: Springer Verlag. DOI: 10.1007/978-3-642-13574-3 - Schneider, T, Lan, S, Stuart, A and Teixeira, J. 2017. Earth system modeling 2.0: A blueprint for models that learn from observations and targeted high-resolution simulations. Geophysical Research Letters, 44: 12396–12417. DOI: 10.1002/2017GL076101
- Shepherd, T. 2014. Atmospheric circulation as a source of uncertainty in climate change projections. Nature Geosci, 7: 703–708. DOI: 10.1038/ngeo2253
- Smith, RD, Maltrud, ME, Bryan, F and Hecht, MW. 2000. Numerical simulation of the North Atlantic Ocean at 1/10°. Journal of Physical Oceanography, 30: 1532–1561. DOI: 10.1175/1520-0485(2000)030<;1532:NSOTNA>2.0.CO;2
- Stevens, B, et al. 2021. EUREC4A. Earth Syst. Sci. Data, 13: 4067–4119. DOI: 10.5194/essd-13-4067-2021
- Stevens, B, Satoh, M, Auger, L, et al. 2019. DYAMOND: the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains. Prog Earth Planet Sci., 6: 61. DOI: 10.1186/s40645-019-0304-z
- Sundqvist, H, Berge, E and Kristjánsson, JE. 1989. Condensation and Cloud Parameterization Studies with a Mesoscale Numerical Weather Prediction Model. Monthly Weather Review, 117(8): 1641–1657. DOI: 10.1175/1520-0493(1989)117<;1641:CACPSW>2.0.CO;2
- Tiedtke, M. 1989. A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Wea. Rev., 117: 1779–1800. DOI: 10.1175/1520-0493(1989)117<;1779:ACMFSF>2.0.CO;2
- Tomita, H, Miura, H, Iga, S, Nasuno, T and Satoh, M. 2005. A global cloud-resolving simulation: Preliminary results from an aqua planet experiment. Geophys. Res. Lett., 32(8): 3283. DOI: 10.1029/2005GL022459
- Tomita, H, Satoh, M and Goto, K. 2002. An optimization of icosahedral grid modified by spring dynamics. J. Comp. Phys., 183: 307–331. DOI: 10.1006/jcph.2002.7193
- Tomita, H, Tsugawa, M, Satoh, M and Goto, K. 2001. Shallow water model on a modified icosahedral geodesic grid by using spring dynamics. J. Comp. Phys., 174: 579–613. DOI: 10.1006/jcph.2001.6897
- Uribe, A, Vial, J and Mauritsen, T. 2021. Sensitivity of tropical extreme precipitation to surface warming in aquaplanet experiments using a global nonhydrostatic model. Geophysical Research Letters, 48:
e2020GL091371 . DOI: 10.1029/2020GL091371 - Wan, H, Rasch, PJ, Zhang, K, Qian, Y, Yan, H and Zhao, C. 2014. Short ensembles: an efficient method for discerning climate-relevant sensitivities in atmospheric general circulation models. Geosci. Model Dev., 7: 1961–1977. DOI: 10.5194/gmd-7-1961-2014
- Wang, C, Zhang, L, Lee, SK, Wu, L and Mechoso, CR. 2014. A global perspective on CMIP5 climate model biases. Nature Climate Change, 4: 201–205. DOI: 10.1038/nclimate2118
- Washington, WM, Buja, L and Craig, A. 2008. The computational future for climate and Earth system models: on the path to petaflop and beyond. Phil. Trans. R. Soc. A., 367833–846. DOI: 10.1098/rsta.2008.0219
- Weller, H, Weller, HG and Fournier, A. 2009. Voronoi, Delaunay, and Block-Structured Mesh Refinement for Solution of the Shallow-Water Equations on the Sphere. Mon. Wea. Rev., 137: 4208–4224. DOI: 10.1175/2009MWR2917.1
- Williams, KD, Bodas-Salcedo, A, Déqué, M, Fermepin, S, Medeiros, B, Watanabe, M, Jakob, C, Klein, SA, Senior, CA and Williamson, DL. 2013. The Transpose-AMIP II Experiment and Its Application to the Understanding of Southern Ocean Cloud Biases in Climate Models. Journal of Climate, 26(10): 3258–3274. DOI: 10.1175/JCLI-D-12-00429.1
- Winton, M, Takahashi, K and Held, IM. 2010. Importance of Ocean Heat Uptake Efficacy to Transient Climate Change. Journal of Climate, 23(9): 2333–2344. DOI: 10.1175/2009JCLI3139.1
- Yashiro, H, Terai, M, Yoshida, R, Iga, S-I, Minami, K and Tomita, H. 2016.
Performance Analysis and Optimization of Nonhydrostatic ICosahedral Atmospheric Model (NICAM) on the K Computer and TSUBAME2.5 . In: Proceedings of the Platform for Advanced Scientific Computing Conference on ZZZ – PASC’16. ACM Press. DOI: 10.1145/2929908.2929911 - Zelinka, MD, Myers, TA, McCoy, DT, Po-Chedley, S, Caldwell, PM, Ceppi, P, et al. 2020. Causes of higher climate sensitivity in CMIP6 models. Geophysical Research Letters, 47:
e2019GL085782 . DOI: 10.1029/2019GL085782 - Zhou, C, Zelinka, M and Klein, S. 2016. Impact of decadal cloud variations on the Earth’s energy budget. Nature Geosci, 9: 871–874. DOI: 10.1038/ngeo2828
- Zuidema, P, Chang, P, Medeiros, B, Kirtman, BP, Mechoso, R, Schneider, EK, Toniazzo, T, Richter, I, Small, RJ, Bellomo, K, Brandt, P, de Szoeke, S, Farrar, JT, Jung, E, Kato, S, Li, M, Patricola, C, Wang, Z, Wood, R and Xu, Z. 2016. Challenges and Prospects for Reducing Coupled Climate Model SST Biases in the Eastern Tropical Atlantic and Pacific Oceans: The U.S. CLIVAR Eastern Tropical Oceans Synthesis Working Group. Bulletin of the American Meteorological Society, 97(12): 2305–2328. DOI: 10.1175/BAMS-D-15-00274.1
DOI: https://doi.org/10.16993/tellusa.54 | Journal eISSN: 3035-9554
Language: English
Page range: 346 - 363
Submitted on: Apr 22, 2022
Accepted on: Aug 16, 2022
Published on: Sep 2, 2022
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services
Keywords:
© 2022 Thorsten Mauritsen, Rene Redler, Monika Esch, Bjorn Stevens, Cathy Hohenegger, Daniel Klocke, Renate Brokopf, Helmuth Haak, Leonidas Linardakis, Niklas Röber, Reiner Schnur, published by Stockholm University Press
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