Articles | Volume 10, issue 5
https://doi.org/10.5194/os-10-837-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/os-10-837-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Evaluation of the eastern equatorial Pacific SST seasonal cycle in CMIP5 models
Z. Y. Song
First Institute of Oceanography, State Oceanic Administration, Qingdao, China
H. L. Liu
Cooperative Institute for Marine and Atmospheric Studies, University of Miami, Miami, FL, USA
Atlantic Oceanographic and Meteorological Laboratory, NOAA, Miami, FL, USA
C. Z. Wang
Atlantic Oceanographic and Meteorological Laboratory, NOAA, Miami, FL, USA
L. P. Zhang
Atmospheric and Oceanic Science, Princeton University, Princeton, NJ, USA
F. L. Qiao
First Institute of Oceanography, State Oceanic Administration, Qingdao, China
Related authors
Xiaole Li, Zhenya Song, Xiongbo Zheng, Zhanpeng Zhuang, Fangli Qiao, Haibin Zhou, and Mingze Ji
EGUsphere, https://doi.org/10.5194/egusphere-2025-2636, https://doi.org/10.5194/egusphere-2025-2636, 2025
Preprint archived
Short summary
Short summary
Based on the variable-limit integration method, this study developed a novel numerical approach for the thermohaline equations in ocean models. This method significantly enhances the simulation accuracy of temperature and salinity, improves model stability, and better simulates seawater overflow dynamics across steep ridges. The variable-limit integral method designed herein for thermohaline equations can be readily applied to other ocean numerical models.
Yaqi Wang, Lanning Wang, Juan Feng, Zhenya Song, Qizhong Wu, and Huaqiong Cheng
Geosci. Model Dev., 16, 6857–6873, https://doi.org/10.5194/gmd-16-6857-2023, https://doi.org/10.5194/gmd-16-6857-2023, 2023
Short summary
Short summary
In this study, to noticeably improve precipitation simulation in steep mountains, we propose a sub-grid parameterization scheme for the topographic vertical motion in CAM5-SE to revise the original vertical velocity by adding the topographic vertical motion. The dynamic lifting effect of topography is extended from the lowest layer to multiple layers, thus improving the positive deviations of precipitation simulation in high-altitude regions and negative deviations in low-altitude regions.
Qi Shu, Qiang Wang, Chuncheng Guo, Zhenya Song, Shizhu Wang, Yan He, and Fangli Qiao
Geosci. Model Dev., 16, 2539–2563, https://doi.org/10.5194/gmd-16-2539-2023, https://doi.org/10.5194/gmd-16-2539-2023, 2023
Short summary
Short summary
Ocean models are often used for scientific studies on the Arctic Ocean. Here the Arctic Ocean simulations by state-of-the-art global ocean–sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) were evaluated. The simulations on Arctic Ocean hydrography, freshwater content, stratification, sea surface height, and gateway transports were assessed and the common biases were detected. The simulations forced by different atmospheric forcing were also evaluated.
Zhanpeng Zhuang, Quanan Zheng, Yongzeng Yang, Zhenya Song, Yeli Yuan, Chaojie Zhou, Xinhua Zhao, Ting Zhang, and Jing Xie
Geosci. Model Dev., 15, 7221–7241, https://doi.org/10.5194/gmd-15-7221-2022, https://doi.org/10.5194/gmd-15-7221-2022, 2022
Short summary
Short summary
We evaluate the impacts of surface waves and internal tides on the upper-ocean mixing in the Indian Ocean. The surface-wave-generated turbulent mixing is dominant if depth is < 30 m, while the internal-tide-induced mixing is larger than surface waves in the ocean interior from 40
to 130 m. The simulated thermal structure, mixed layer depth and surface current are all improved when the mixing schemes are jointly incorporated into the ocean model because of the strengthened vertical mixing.
Yuejin Ye, Zhenya Song, Shengchang Zhou, Yao Liu, Qi Shu, Bingzhuo Wang, Weiguo Liu, Fangli Qiao, and Lanning Wang
Geosci. Model Dev., 15, 5739–5756, https://doi.org/10.5194/gmd-15-5739-2022, https://doi.org/10.5194/gmd-15-5739-2022, 2022
Short summary
Short summary
The swNEMO_v4.0 is developed with ultrahigh scalability through the concepts of hardware–software co-design based on the characteristics of the new Sunway supercomputer and NEMO4. Three breakthroughs, including an adaptive four-level parallelization design, many-core optimization and mixed-precision optimization, are designed. The simulations achieve 71.48 %, 83.40 % and 99.29 % parallel efficiency with resolutions of 2 km, 1 km and 500 m using 27 988 480 cores, respectively.
Xiao Liu, John P. Dunne, Liwei Jia, Charles A. Stock, Xiaosong Yang, Matthew J. Harrison, Liping Zhang, and Anthony Rosati
EGUsphere, https://doi.org/10.5194/egusphere-2026-4194, https://doi.org/10.5194/egusphere-2026-4194, 2026
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
Short summary
Short summary
This study uses NOAA GFDL’s SPEAR model to improve predictions of how the ocean absorbs human emitted CO2. While standard models capture long-term trends, they struggle with yearly fluctuations. Researchers found that "initializing" the model with observed data significantly boosts their prediction accuracy for up to two years. This framework helps separate the predictions of natural variability from human-driven carbon changes, a vital step for verifying future marine carbon removal efforts.
Vimal Koul, Andrew Ross, Charles Stock, Liping Zhang, Andrew Wittenberg, and Thomas Delworth
EGUsphere, https://doi.org/10.5194/egusphere-2026-481, https://doi.org/10.5194/egusphere-2026-481, 2026
Short summary
Short summary
Predicting coastal ocean conditions years ahead has been difficult due to complex regional dynamics. This work shows we can forecast bottom temperature, oxygen, and acidity up to a decade ahead for the Northeast U.S. Shelf. Our forecasts indicate increasing Labrador water may accelerate acidification, threatening shell-forming organisms. This provides a foundation for early warning systems to help communities and fisheries adapt proactively.
Xiaole Li, Zhenya Song, Xiongbo Zheng, Zhanpeng Zhuang, Fangli Qiao, Haibin Zhou, and Mingze Ji
EGUsphere, https://doi.org/10.5194/egusphere-2025-2636, https://doi.org/10.5194/egusphere-2025-2636, 2025
Preprint archived
Short summary
Short summary
Based on the variable-limit integration method, this study developed a novel numerical approach for the thermohaline equations in ocean models. This method significantly enhances the simulation accuracy of temperature and salinity, improves model stability, and better simulates seawater overflow dynamics across steep ridges. The variable-limit integral method designed herein for thermohaline equations can be readily applied to other ocean numerical models.
Yushi Morioka, Liping Zhang, Thomas L. Delworth, Xiaosong Yang, Fanrong Zeng, Masami Nonaka, and Swadhin K. Behera
The Cryosphere, 17, 5219–5240, https://doi.org/10.5194/tc-17-5219-2023, https://doi.org/10.5194/tc-17-5219-2023, 2023
Short summary
Short summary
Antarctic sea ice extent shows multidecadal variations with its decrease in the 1980s and increase after the 2000s until 2015. Here we show that our climate model can predict the sea ice decrease by deep convection in the Southern Ocean and the sea ice increase by the surface wind variability. These results suggest that accurate simulation and prediction of subsurface ocean and atmosphere conditions are important for those of Antarctic sea ice variability on a multidecadal timescale.
Yaqi Wang, Lanning Wang, Juan Feng, Zhenya Song, Qizhong Wu, and Huaqiong Cheng
Geosci. Model Dev., 16, 6857–6873, https://doi.org/10.5194/gmd-16-6857-2023, https://doi.org/10.5194/gmd-16-6857-2023, 2023
Short summary
Short summary
In this study, to noticeably improve precipitation simulation in steep mountains, we propose a sub-grid parameterization scheme for the topographic vertical motion in CAM5-SE to revise the original vertical velocity by adding the topographic vertical motion. The dynamic lifting effect of topography is extended from the lowest layer to multiple layers, thus improving the positive deviations of precipitation simulation in high-altitude regions and negative deviations in low-altitude regions.
Qi Shu, Qiang Wang, Chuncheng Guo, Zhenya Song, Shizhu Wang, Yan He, and Fangli Qiao
Geosci. Model Dev., 16, 2539–2563, https://doi.org/10.5194/gmd-16-2539-2023, https://doi.org/10.5194/gmd-16-2539-2023, 2023
Short summary
Short summary
Ocean models are often used for scientific studies on the Arctic Ocean. Here the Arctic Ocean simulations by state-of-the-art global ocean–sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) were evaluated. The simulations on Arctic Ocean hydrography, freshwater content, stratification, sea surface height, and gateway transports were assessed and the common biases were detected. The simulations forced by different atmospheric forcing were also evaluated.
Bin Xiao, Fangli Qiao, Qi Shu, Xunqiang Yin, Guansuo Wang, and Shihong Wang
Geosci. Model Dev., 16, 1755–1777, https://doi.org/10.5194/gmd-16-1755-2023, https://doi.org/10.5194/gmd-16-1755-2023, 2023
Short summary
Short summary
A new global surface-wave–tide–circulation coupled ocean model (FIO-COM32) with a resolution of 1/32° × 1/32° is developed and validated. Both the promotion of the horizontal resolution and included physical processes are shown to be important contributors to the significant improvements in FIO-COM32 simulations. It is time to merge these separated model components (surface waves, tidal currents and ocean circulation) and start a new generation of ocean model development.
Zhanpeng Zhuang, Quanan Zheng, Yongzeng Yang, Zhenya Song, Yeli Yuan, Chaojie Zhou, Xinhua Zhao, Ting Zhang, and Jing Xie
Geosci. Model Dev., 15, 7221–7241, https://doi.org/10.5194/gmd-15-7221-2022, https://doi.org/10.5194/gmd-15-7221-2022, 2022
Short summary
Short summary
We evaluate the impacts of surface waves and internal tides on the upper-ocean mixing in the Indian Ocean. The surface-wave-generated turbulent mixing is dominant if depth is < 30 m, while the internal-tide-induced mixing is larger than surface waves in the ocean interior from 40
to 130 m. The simulated thermal structure, mixed layer depth and surface current are all improved when the mixing schemes are jointly incorporated into the ocean model because of the strengthened vertical mixing.
Takaya Uchida, Julien Le Sommer, Charles Stern, Ryan P. Abernathey, Chris Holdgraf, Aurélie Albert, Laurent Brodeau, Eric P. Chassignet, Xiaobiao Xu, Jonathan Gula, Guillaume Roullet, Nikolay Koldunov, Sergey Danilov, Qiang Wang, Dimitris Menemenlis, Clément Bricaud, Brian K. Arbic, Jay F. Shriver, Fangli Qiao, Bin Xiao, Arne Biastoch, René Schubert, Baylor Fox-Kemper, William K. Dewar, and Alan Wallcraft
Geosci. Model Dev., 15, 5829–5856, https://doi.org/10.5194/gmd-15-5829-2022, https://doi.org/10.5194/gmd-15-5829-2022, 2022
Short summary
Short summary
Ocean and climate scientists have used numerical simulations as a tool to examine the ocean and climate system since the 1970s. Since then, owing to the continuous increase in computational power and advances in numerical methods, we have been able to simulate increasing complex phenomena. However, the fidelity of the simulations in representing the phenomena remains a core issue in the ocean science community. Here we propose a cloud-based framework to inter-compare and assess such simulations.
Yuejin Ye, Zhenya Song, Shengchang Zhou, Yao Liu, Qi Shu, Bingzhuo Wang, Weiguo Liu, Fangli Qiao, and Lanning Wang
Geosci. Model Dev., 15, 5739–5756, https://doi.org/10.5194/gmd-15-5739-2022, https://doi.org/10.5194/gmd-15-5739-2022, 2022
Short summary
Short summary
The swNEMO_v4.0 is developed with ultrahigh scalability through the concepts of hardware–software co-design based on the characteristics of the new Sunway supercomputer and NEMO4. Three breakthroughs, including an adaptive four-level parallelization design, many-core optimization and mixed-precision optimization, are designed. The simulations achieve 71.48 %, 83.40 % and 99.29 % parallel efficiency with resolutions of 2 km, 1 km and 500 m using 27 988 480 cores, respectively.
Bin Xiao, Fangli Qiao, Qi Shu, Xunqiang Yin, Guansuo Wang, and Shihong Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-52, https://doi.org/10.5194/gmd-2022-52, 2022
Revised manuscript not accepted
Short summary
Short summary
A new global surface wave-tide-circulation coupled ocean model FIO-COM32 with resolution of 1/32° × 1/32° is developed and validated. Both the promotion of the horizontal resolution and included physical processes are proved to be important contributors to the significant improvements of FIO-COM32 simulations. It should be the time to merge these separated model components (surface wave, tidal current and ocean circulation) for new generation ocean model development.
Cited articles
Bentsen, M., Bethke, I., Debernard, J. B., Iversen, T., Kirkevåg, A., Seland, Ø., Drange, H., Roelandt, C., Seierstad, I. A., Hoose, C., and Kristjánsson, J. E.: The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate, Geosci. Model Dev., 6, 687–720, https://doi.org/10.5194/gmd-6-687-2013, 2013.
Chylek, P., Li, J., Dubey, M. K., Wang, M., and Lesins, G.: Observed and model simulated 20th century Arctic temperature variability: Canadian Earth System Model CanESM2, Atmos. Chem. Phys. Discuss., 11, 22893–22907, https://doi.org/10.5194/acpd-11-22893-2011, 2011.
Collins, W. D., Bitz, C. M., Blackmon, M. L., Bonan, G. B., Bretherton, C. S., Carton, J. A., Chang, P., Doney, S. C., Hack, J. J., Henderson, T. B., Kiehl, J. T., Large, W. G., McKenna, D. S., Santer, B. D., and Smith, R. D.: The Community Climate System Model Version 3 (CCSM3), J. Climate, 19, 2122–2143, https://doi.org/10.1175/JCLI3761.1, 2006.
Collins, W. J., Bellouin, N., Doutriaux-Boucher, M., Gedney, N., Halloran, P., Hinton, T., Hughes, J., Jones, C. D., Joshi, M., Liddicoat, S., Martin, G., O'Connor, F., Rae, J., Senior, C., Sitch, S., Totterdell, I., Wiltshire, A., and Woodward, S.: Development and evaluation of an Earth-System model – HadGEM2, Geosci. Model Dev., 4, 1051–1075, https://doi.org/10.5194/gmd-4-1051-2011, 2011.
Covey, C., Abe-Ouchi, A., Boer, G. J., Boville, B. A., Cubasch, U., Fairhead, L., Flato, G. M., Gordon, H., Guilyardi, E., Jiang, X., Johns, T. C., Le Treut, H., Madec, G., Meehl, G. A., Miller, R., Noda, A., Power, S. B., Roeckner, E., Russell, G., Schneider, E. K., Stouffer, R. J., Terray, L., and von Storch, J.-S.: The seasonal cycle in coupled ocean-atmosphere general circulation models, Clim. Dynam., 16, 775–787, https://doi.org/10.1007/s003820000081, 2000.
De Szoeke, S. P. and Xie, S.-P.: The tropical eastern Pacific seasonal cycle: Assessment of errors and mechanisms in IPCC AR4 coupled ocean-atmosphere general circulation models, J. Climate, 21, 2573–2590, https://doi.org/10.1175/2007JCLI1975.1, 2008.
Dewitt, D. G. and Edwin, K. S.: The processes determining the Annual Cycle of Equatorial Sea Surface Temperature: A coupled General Circulation Model Perspective, Mon. Weather Rev., 127, 381–395, https://doi.org/10.1175/1520-0493(1999)127<0381:TPDTAC>2.0.CO;2, 1999.
Dunne, J. P., John, J. G., Adcroft, A. J., Griffies, S. M., Hallberg, R. W., Shevliakova, E., Stouffer, R. J., Cooke, W., Dunne, K. A., Harrison, M. J., Krasting, J. P., Malyshev, S. L., Milly, P. C. D., Phillipps, P. J., Sentman, L. T., Samuels, B. L., Spelman, M. J., Winton, M., Wittenberg, A. T., and Zadeh, N.: GFDL's ESM2 Global Coupled Climate–Carbon Earth System Models. Part I: Physical Formulation and Baseline Simulation Characteristics, J. Climate, 25, 6646–6665, https://doi.org/10.1175/JCLI-D-11-00560.1, 2012.
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.: The Community Climate System Model version 4, J. Climate, 24, 4973–4991, https://doi.org/10.1175/2011JCLI4083.1, 2011.
Giese, B. S. and Carton, J. A.: The seasonal cycle in a coupled ocean-atmosphere model, J. Climate, 7, 1208–1217, https://doi.org/10.1175/1520-0442(1994)007<1208:TSCICO>2.0.CO;2, 1994.
Giorgetta, M. A., Jungclaus, J., Reick, C. H., Legutke, S., Bader, J., Böttinger, M., Brovkin, V., Crueger, T., Esch, M., Fieg, K., Glushak, K., Gayler, V., Haak, H., Hollweg, H.-D., Ilyina, T., Kinne, S., Kornblueh, L., Matei, D., Mauritsen, T., Mikolajewicz, U., Mueller, W., Notz, D., Pithan, F., Raddatz, T., Rast, S., Redler, R., Roeckner, E., Schmidt, H., Schnur, R., Segschneider, J., Six, K. D., Stockhause, M., Timmreck, C., Wegner, J., Widmann, H., Wieners, K.-H., Claussen, M., Marotzke, J., and Stevens, B.: Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the coupled model intercomparison project phase 5, J. Adv. Model. Earth Syst., 5, 572–597, https://doi.org/10.1002/jame.20038, 2013.
Griffies, S. M., Winton, M., Donner, L. J., Horowitz, L. W., Downes, S. M., Farneti, R., Gnanadesikan, A., Hurlin, W. J., Lee, H.-C., Liang, Z., Palter, J. B., Samuels, B. L., Wittenberg, A. T., Wyman, B. L., Yin, J., and Zadeh, N.: The GFDL CM3 Coupled Climate Model: Characteristics of the Ocean and Sea Ice Simulations, J. Climate, 24, 3520–3544, https://doi.org/10.1175/2011JCLI3964.1, 2011.
Hourdin, F., Foujols, M.-A., Codron, F., Guemas, V., Dufresne, J.-L., Bony, S., Denvil, S., Guez, L., Lott, F., Ghattas, J., Braconnot, P., Marti, O., Meurdesoif, Y., and Bopp, L.: Impact of the LMDZ atmospheric grid configuration on the climate and sensitivity of the IPSL-CM5A coupled model, Clim. Dynam., 40, 2167–2192, https://doi.org/10.1007/s00382-012-1411-3, 2013a.
Hourdin, F., Grandpeix, J.-Y., Rio, C., Bony, S., Jam, A., Cheruy, F., Rochetin, N., Fairhead, L., Idelkadi, A., Musat, I., Dufresne, J.-L., Lahellec, A., Lefebvre, M.-P., and Roehrig, R.: LMDZ5B: the atmospheric component of the IPSL climate model with revisited parameterizations for clouds and convection, Clim. Dynam., 40, 2193–2222, https://doi.org/10.1007/s00382-012-1343-y, 2013b.
Jones, C. D., Hughes, J. K., Bellouin, N., Hardiman, S. C., Jones, G. S., Knight, J., Liddicoat, S., O'Connor, F. M., Andres, R. J., Bell, C., Boo, K.-O., Bozzo, A., Butchart, N., Cadule, P., Corbin, K. D., Doutriaux-Boucher, M., Friedlingstein, P., Gornall, J., Gray, L., Halloran, P. R., Hurtt, G., Ingram, W. J., Lamarque, J.-F., Law, R. M., Meinshausen, M., Osprey, S., Palin, E. J., Parsons Chini, L., Raddatz, T., Sanderson, M. G., Sellar, A. A., Schurer, A., Valdes, P., Wood, N., Woodward, S., Yoshioka, M., and Zerroukat, M.: The HadGEM2-ES implementation of CMIP5 centennial simulations, Geosci. Model Dev., 4, 543–570, https://doi.org/10.5194/gmd-4-543-2011, 2011.
Latif, M., Sperber, K., Arblaster, J., Braconnot, P., Chen, D., Colman, A., Cubasch, U., Cooper, C., Delecluse, P., Dewitt, D., Fairhead, L., Flato, G., Hogan, T., Ji, M., Kimoto, M., Kitoh, A., Knutson, T., Le Treut, H., Li, T., Manabe, S., Marti, O., Mechoso, C., Meehl, G., Power, S., Roeckner, E., Sirven, J., Terray, L., Vintzileos, A., Voß, R., Wang, B., Washington, W., Yoshikawa, I., Yu, J., and Zebiak, S.: ENSIP: the El Nino simulation intercomparison project, Clim. Dynam., 18, 255–276, https://doi.org/10.1007/s003820100174, 2001.
Li, G. and Xie, S.-P.: Origins of tropical-wide SST biases in CMIP multi-model ensembles, Geophys. Res. Lett., 39, L22703, https://doi.org/10.1029/2012GL053777, 2012.
Li, G. and Xie, S.-P.: Tropical Biases in CMIP5 Multimodel Ensemble: The Excessive Equatorial Pacific cold tongue and Double ITCZ Problems, J. Climate, 27, 1765–1780, https://doi.org/10.1175/JCLI-D-13-00337.1, 2014.
Manabe, S. and Bryan, K.: Climate calculation with a combined ocean-atmosphere model, J. Atmos. Sci., 26, 768–789, https://doi.org/10.1175/1520-0469(1969)026<0786:CCWACO>2.0.CO:2, 1969.
Mechoso, C. R., Robertson, A. W., Barth, N., Davey, M. K., Delecluse, P., Gent, P. R., Ineson, S., Kirtman, B., Latif, M., Le Treut, H., Nagai, T., Neelin, J. D., Philander, S. G. H., Polcher, J., Schopf, P. S., Stockdale, T., Suarez, M. J., Terray, L., Thual, O., and Tribbia, J. J.: The seasonal cycle over the tropical Pacific in coupled ocean-atmosphere general circulation models, J. Climate, 123, 2825–2838, https://doi.org/10.1175/1520-0493(1995)123<2825:TSCOTT>2.0.CO:2, 1995.
Mitchell, T. P. and Wallace, J. M.: The annual cycle in equatorial convection and sea surface temperature, J. Climate, 5, 1140–1156, https://doi.org/10.1175/1520-0042(1992)005<1140:TACIEC>2.0.CO:2, 1992.
Nigam, S. and Chao, Y.: Evolution dynamics of tropical ocean-atmosphere annual cycle variability, J. Climate, 9, 3187–3205, https://doi.org/10.1175/1520-0442(1996)009<3187:EDOTOA>2.0.CO:2, 1996.
Qiao, F., Song, Z., Bao, Y., Shu, Q., Huang, C., and Zhao, W.: Description and evaluation of an earth system model climate with surface gravity wave, J. Geophys. Res.-Ocean., 118, 4514–4524, https://doi.org/10.1002/jgrc.20327, 2013.
Rotstayn, L., Collier, M., Dix, M., Feng, Y., Gordon, H., O'Farrell, S., Smith, I., and Syktus, J.: Improved simulation of Australian climate and ENSO-related climate variability in a GCM with an interactive aerosol treatment, Int. J. Climatology, 30, 1067–1088, https://doi.org/10.1002/joc.1952, 2010.
Shindell, D. T., Pechony, O., Voulgarakis, A., Faluvegi, G., Nazarenko, L., Lamarque, J.-F., Bowman, K., Milly, G., Kovari, B., Ruedy, R., and Schmidt, G. A.: Interactive ozone and methane chemistry in GISS-E2 historical and future climate simulations, Atmos. Chem. Phys., 13, 2653–2689, https://doi.org/10.5194/acp-13-2653-2013, 2013.
Smith, D. M., Eade, R., Dunstone, N. J., Fereday, D., Murphy, J. M., Pohlman, H., and Scaife, A. A.: Skilful multi-year predictions of Atlantic hurricane frequency, Nat. Geosci., 3, 846–849, https://doi.org/10.1038/ngeo1004, 2010.
Smith, T. M., Reynolds, R. W., Peterson, T. C., and Lawrimore, J.: Improvements to NOAA's historical merged land-ocean surface temperature analysis (1880–2006), J. Climate, 21, 2283–2296, https://doi.org/10.1175/2007JCLI2100.1, 2008.
Taylor, K. E., Stoufefer, R. J., and Meehl, G. A.: An overview of CMIP5 and the experimental design, Bull. Am. Meteorol. Soc., 93, 485–498, https://doi.org/10.1175/BAMS-D-11-00094.1, 2012.
Volodin, E. M., Diansky, N. A., and Gusev, A. V.: Simulating present-day climate with the INMCM4.0 coupled model of the atmospheric and oceanic general circulations, Izvestiya, Atmos. Ocean. Phys., 46, 414–431, https://doi.org/10.1134/S000143381004002X, 2010.
Wang, C., L. Zhang, S.-K. Lee., L. Wu, and C. R. Mechoso: A global perspective on CMIP5 climate model biases, Nat. Clim. Change, 4, 201–205, 2014.
Xie, S. P.: On the genesis of the equatorial annual cycle, J. Climate, 7, 2008–2013, https://doi.org/10.1175/1520-0442(1994)007<2008:OTGOTE>2.0.CO:2, 1994.
Xie, S. P.: The shape of continents, air-sea interaction, and the rising branch of the Hadley circulation, in: The Hadley Circulation: Past, Present and Future, Vol. 21, Advances in Global Change Research, edited by: Diaz, H. F. and Bradley, R. S., 121–152, Springer Netherlands, 2004.
Xie, S. P., Miyama, T., Wang, Y., Xu, H., de Szoeke, S. P., Small, R. J. O., Richards, K. J., Mochizuki, T., and Awaji, T.: A regional ocean-atmosphere model for eastern Pacific climate: toward reducing tropical biases, J. Climate, 20, 1504–1522, https://doi.org/10.1175/JCLI4080.1, 2007.
Yu, Y. Q., He, J., Zheng, W. P., and Luan, Y. H.: Annual cycle and interannual variability in the Tropical Pacific as Simulated by Three Versions of FGOALS, Adv. Atmos. Sci., 30, 621–637, https://doi.org/10.1007/s00376-013-2184-2, 2013.
Yukimoto, S., Adachi, Y., Hosaka, M., Sakami, T., Yoshimura, H., Hirabara, M., Tanaka, T. Y., Shindo, E., Tsujino, H., Deushi, M., Mizuta, R., Yabu, S., Obata, A., Nakano, H., Koshiro, T., Ose, T., and Kiton, A.: A new global climate model of the Meteorological Research Institute: MRI-CGCM3 – Model description and basic performance, J. Meteorol. Soc. Jpn. II, 90A, 23–64, https://doi.org/10.2151/jmsj.2012-A02, 2012.