Skip to main content
Log in

The flexible global ocean-atmosphere-land system model, Grid-point Version 2: FGOALS-g2

  • Published:
Advances in Atmospheric Sciences Aims and scope Submit manuscript

Abstract

This study mainly introduces the development of the Flexible Global Ocean-Atmosphere-Land System Model: Grid-point Version 2 (FGOALS-g2) and the preliminary evaluations of its performances based on results from the pre-industrial control run and four members of historical runs according to the fifth phase of the Coupled Model Intercomparison Project (CMIP5) experiment design. The results suggest that many obvious improvements have been achieved by the FGOALS-g2 compared with the previous version,FGOALS-g1, including its climatological mean states, climate variability, and 20th century surface temperature evolution. For example,FGOALS-g2 better simulates the frequency of tropical land precipitation, East Asian Monsoon precipitation and its seasonal cycle, MJO and ENSO, which are closely related to the updated cumulus parameterization scheme, as well as the alleviation of uncertainties in some key parameters in shallow and deep convection schemes, cloud fraction, cloud macro/microphysical processes and the boundary layer scheme in its atmospheric model. The annual cycle of sea surface temperature along the equator in the Pacific is significantly improved in the new version. The sea ice salinity simulation is one of the unique characteristics of FGOALS-g2, although it is somehow inconsistent with empirical observations in the Antarctic.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Bodas-Salcedo, A., and Coauthors, 2011: COSP: Satellite simulation software for model assessment. Bull. Amer. Meteor. Soc., 92(8), 1023–1043.

    Article  Google Scholar 

  • Brohan, P., J. J. Kennedy, I. Harris, S. F. B. Tett, and P. D. Jones, 2006: Uncertainty estimates in regional and global observed temperature changes: A new data set from 1850. J. Geophys. Res., 111, D12106, doi: 10.1029/2005JD006548.

    Article  Google Scholar 

  • Canuto, V. M., A. Howard, Y. Cheng, and M. S. Dubovikov, 2001: Ocean turbulence. Part I: Onepoint closure model-Momentum and heat vertical diffusivities. J. Phys. Oceanogr., 31, 1413–1426.

    Article  Google Scholar 

  • Canuto, V. M., A. Howard, Y. Cheng, and M. S. Dubovikov, 2002: Ocean turbulence. Part II: Vertical diffusivities of momentum, heat, salt, mass, and passive scalars. J. Phys. Oceanogr., 32, 240–264.

    Article  Google Scholar 

  • Capotondi, A., A. Wittenberg, and S. Masina, 2006: Spatial and temporal structure of tropical Pacific interannual variability in 20th century climate simulations. Ocean Modelling, 15, 274–298.

    Article  Google Scholar 

  • Cionni, I., and Coauthors, 2011: Ozone database in support of CMIP5 simulations: Results and corresponding radiative forcing. Atmos. Chem. Phys., 11, 11267–11292, doi: 10.5194/acp-11-11267-2011.

    Article  Google Scholar 

  • Collins, W. D., and Coauthors, 2003: Description of the NCAR community atmospheric model (CAM2). NCAR, Boulder, 190pp.

    Google Scholar 

  • Craig, A. P., R. L. Jacob, B. Kauffman, T. Bettge, J. Larson, E. Ong, C. Ding, and Y. He, 2005: Cpl6: The new extensible, high-performance parallel coupler for the community climate system model. In ternational Journal of High Performance Computing Applications, 19, 309–327.

    Article  Google Scholar 

  • Cunningham, S. A., and Coauthors, 2007: Temporal variability of the Atlantic meridional overturning circulation at 26.5°N. Science, 317, 935–937.

    Article  Google Scholar 

  • Deser, C., and Coauthors, 2012: ENSO and Pacific decadal variability in community climate system model version 4. J. Climate, 25, 2622–2651.

    Article  Google Scholar 

  • Dong, L., L. J. Li, and W. Y. Huang, Y. Wang, and B. Wang, 2012: Preliminary evaluation of the cloud fraction simulations by GAMIL2 using COSP. Atmos. Oceanic Sci. Lett., 5, 258–263.

    Google Scholar 

  • Gent, P. R., and Coauthors, 2011: The community climate system model version 4. J. Climate, 24, 4973–4991.

    Article  Google Scholar 

  • Hurrell, J. W., J. J. Hack, D. Shea, J. M. Caron, and J. Rosinski, 2008: A new sea surface temperature and sea ice boundary dataset for the community atmosphere model. J. Climate, 21, 5145–5153, doi: http://dx.doi.org/10.1175/2008JCLI2292.1.

    Article  Google Scholar 

  • Latif, M., and Coauthors, 2001: ENSIP: The El Niño simulation intercomparison project. Climate Dyn., 18, 255–276.

    Article  Google Scholar 

  • Lean, J., cited 2009: Calculations of solar irradiance: monthly means from 1882 to 2008, annual means from 1610 to 2008. [Available online at http://sparcsolaris.gfzpotsdam.de/Inputdata/CalculationsofSolarIrradiance.pdf.]

    Google Scholar 

  • Li, L. J., and B. Wang, 2010: Influences of two convective schemes on the radiative energy budget in GAMIL1.0. Acta Meteorologica Sinica, 24(3), 318–327.

    Google Scholar 

  • Li, L. J., B. Wang, and T. J. Zhou, 2007a: Contributions of natural and anthropogenic forcings to the summer cooling over eastern China: An AGCM study. Geophys. Res. Lett., 34, L18807, doi: 10.1029/2007GL030541.

    Article  Google Scholar 

  • Li, L. J., B. Wang, Y. Q. Wang, and H. Wan, 2007b: Improvements in climate simulation with modifi-cations to the Tiedtke convective parameterization in the grid-point atmospheric model of IAP LASG (GAMIL). Adv. Atmos. Sci., 24, 323–335, doi: 10.1007/s00376-007-0323-3.

    Article  Google Scholar 

  • Li, L. J., X. Xie, B. Wang, and L. Dong, 2012: Evaluating the performances of GAMIL1.0 and GAMIL2.0 during TWP-ICE with CAPT. Atmos. Oceanic Sci. Lett., 5, 38–42.

    Google Scholar 

  • Li, L. J., and Coauthors, 2013: Evaluation of gridpoint atmospheric model of IAP LASG, version 2.0 (GAMIL 2.0). Adv. Atmos. Sci., doi: 10.1007/s00376-013-2157-5.

    Google Scholar 

  • Lin, J., 2007: The double-ITCZ problem in IPCC AR4 coupled GCMs: Ocean-atmosphere feedback analysis. J. Climate, 20, 4497–4525.

    Article  Google Scholar 

  • Lin, P. F., H. L. Liu, and X. H. Zhang, 2007: Sensitivity of the upper ocean temperature and circulation in the equatorial Pacific to solar radiation penetration due to phytoplankton. Adv. Atmos. Sci., 24, 765–780, doi: 10.1007/s00376-007-0765-7.

    Article  Google Scholar 

  • Lin, P. F., H. L. Liu, Y. Q. Yu, and X. H. Zhang, 2011: Response of sea surface temperature to chlorophyll-a concentration in the tropical Pacific: Annual mean, seasonal cycle and interannual variability. Adv. Atmos. Sci., 28(3), 492–510, doi: 10.1007/s00376-010-0015-2.

    Article  Google Scholar 

  • Lin, P. F., Y. Q. Yu, and H. L. Liu, 2013a: Long-term stability and oceanic mean state simulated by the coupled model FGOALS-s2. Adv. Atmos. Sci., doi: 10.1007/s00376-012-2042-7.

    Google Scholar 

  • Lin, P. F., Y. Q. Yu, and H. L. Liu, 2013b: Oceanic climatology in the coupled model FGOALS-g2: Improvements and biases, Adv. Atmos. Sci., doi: 10.1007/s00376-012-2137-1.

    Google Scholar 

  • Lin, P. F., H. L. Liu, Y. Q. Yu, and T. Z. Zhou, 2013c: Long-term behaviors of two versions of FGOALS. Adv. Atmos. Sci., doi: 10.10071/s00376-013-2186-0.

    Google Scholar 

  • Liu, H. L., X. H. Zhang, W. Li, Y. Q. Yu, and R. C. Yu, 2004a: A eddy-permitting oceanic general circulation model and its preliminary evaluations. Adv. Atmos. Sci., 21, 675–690.

    Article  Google Scholar 

  • Liu, H. L., Y. Q. Yu, W. Li, and X. H. Zhang, 2004b: Manual for LASG/IAP Climate System Ocean Model (LICOM1.0). Science Press, Beijing, 1–128. (in Chinese)

    Google Scholar 

  • Liu, H. L., P. F. Lin, Y. Q. Yu, and X. H. Zhang, 2012: The baseline evaluation of LASG/IAP climate system ocean model (LICOM) version 2.0. Acta Meteorologica Sinica, 26, 318–329.

    Article  Google Scholar 

  • Liu, J., 2010: Sensitivity of sea ice and ocean simulations to sea ice salinity in a coupled global climate model. Science in China (D), 53(6), 911–916.

    Article  Google Scholar 

  • Lumpkin, R., and K. Speer, 2007: Global ocean meridional overturning. J. Phys. Oceanogr., 37, 2550–2562.

    Article  Google Scholar 

  • IPCC, 2007a: Global climate projections. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. S. Solomon et al., Eds., Cambridge University Press, Cambridge, United Kingdom and New York, New York, USA, 772–774.

    Google Scholar 

  • IPCC, 2007b: Observations: Surface and atmospheric climate change. Climate Change 2007: The Physical Science Basis, S. Solomon et al., Eds., Cambridge University Press, Cambridge, United Kingdom and New York, New York, USA, 235–336.

    Google Scholar 

  • Maloney, E. D., and D. L. Hartmann, 2001: The sensitivity of intraseasonal variability in the NCAR CCM3 to changes in convective parameterization. J. Climate, 14, 2015–2034.

    Article  Google Scholar 

  • Mechoso, C. R., and Coauthors, 1995: The seasonal cycle over the tropical Pacific in coupled ocean-atmosphere general circulation models. Mon. Wea. Rev., 123, 2825–2838.

    Article  Google Scholar 

  • Morrison, H., and A. Gettelman, 2008: A new two-moment bulk stratiform cloud microphysics scheme in the community atmosphere model, version 3 (CAM3). Part I: Description and numerical tests. J. Climate, 21(15), 3642–3659.

    Article  Google Scholar 

  • Oleson, K. W., and Coauthors, 2010: Technical description of version 4.0 of the community land model (CLM), NCAR Tech. Note NCAR/TN-478+STR, 1–257.

    Google Scholar 

  • Rasch, P. J., and J. E. Kristjánsson, 1998: A comparison of the CCM3 model climate using diagnosed and predicted condensate parameterizations. J. Climate, 11(7), 1587–1614.

    Article  Google Scholar 

  • Rasmusson, E., and T. H. Carpenter, 1982: Variations in tropical sea surface temperature and surface wind fields associated with the Southern Oscillation/El Niño. Mon. Wea. Rev., 110, 354–384.

    Article  Google Scholar 

  • Schneider, B., M. Latif, and A. Schmittner, 2007: Evaluation of different methods to assess model projections of the future evolution of the Atlantic meridional overturning circulation. J. Climate, 20, 2121–2132.

    Article  Google Scholar 

  • Shi, X. J., B. Wang, and X. H. Liu, M. H. Wang, L. J. Li, and L. Dong, 2010: Aerosol indirect effects on warm clouds in the grid-point atmospheric model of IAP LASG (GAMIL). Atmos. Oceanic Sci. Lett., 3, 237–241.

    Google Scholar 

  • Slingo, J. M., 1987: The development and verification of a cloud prediction scheme for the ECMWF model. Quart. J. Roy. Meteor. Soc., 113, 899–927.

    Article  Google Scholar 

  • Syed, T. H., J. S. Famiglietti, M. Rodell, J. Chen, and C. R. Wilson, 2008: Analysis of terrestrial water storage changes from GRACE and GLDAS. Water Resour. Res., 44, W02433, doi: 10.1029/2006WR005779.

    Article  Google Scholar 

  • Taylor, K. E., R. J. Stouffer and G. A. Meehl, 2009: A summary of the CMIP5 experiment design. [available online at http://cmip-pcmdi.llnl.gov/cmip5/docs/TaylorCMIP5design.pdf]

    Google Scholar 

  • Thompson, D. W. J., J. J. Kennedy, J. M. Wallace, and P. D. Jones, 2008: A large discontinuity in the mid-twentieth century in observed global-mean surface temperature. Nature, 453, 646–649, doi: 10.1038.

    Article  Google Scholar 

  • Waliser, D. and Coauthors, 2009: MJO simulation diagnostics. J. Climate, 22, 3006–3030.

    Article  Google Scholar 

  • Wang, B., H. Wan, Z. Z. Ji, X. Zhang, R. C. Yu, Y. Q. Yu, and H. L. Liu, 2004: Design of a new dynamical core for global atmospheric models based on some ef-ficient numerical methods. Science in China (A), 47, 4–21.

    Article  Google Scholar 

  • Wang, B., T. J. Zhou, Y. Q. Yu and B. Wang, 2009a: A review on earth system model development. Acta Meteorologica Sinica, 23(1), 1–17.

    Google Scholar 

  • Wang, X. C., J. P. Liu, Y. Q. Yu, H. L. Liu, and L. J. Li, 2009b: Numerical simulation of polar climate with FGOALS-g1.1. Acta Meteorologica Sinica, 67, 961–972. (in Chinese)

    Google Scholar 

  • Wheeler, M. C., and H. H. Hendon, 2004: An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Mon. Wea. Rev., 132, 1917–1932.

    Article  Google Scholar 

  • Wilcox, E. M., and L. J. Donner, 2007: The frequency of extreme rain events in satellite observations and an atmospheric circulation model. J. Climate, 20, 53–69.

    Article  Google Scholar 

  • Willmott, C. J., and K. Matsuura, 2001. Terrestrial air temperature and precipitation: Monthly and annual time series (1950-1999) Version 1.02. [Available online at http://climate.geog.udel.edu/~climate/htmlpages/download.html.]

    Google Scholar 

  • Wu, F., H. Liu, W. Li, and X. Zhang, 2005: Effect of adjusting vertical resolution on the eastern equatorial Pacific cold tongue. Acta. Meteorologica Sinica, 24, 1–12.

    Google Scholar 

  • Xia, K., B. Wang, L. J. Li, S. Shen, W. Y. Huang, S. M. Xu, L. Dong, and L. Liu, 2013: Evaluation of snow covers by two versions of the flexible global ocean-atmosphere-land system model. Adv. Atmos. Sci., submitted.

    Google Scholar 

  • Xiao, C., 2006: Adoption of a two-step shape-preserving advection scheme in an OGCM and its coupled experiment. M.S. thesis, Institute of Atmospheric Physics, Chinese Academy of Sciences, 89pp. (in Chinese)

    Google Scholar 

  • Xie, X., B. Wang, L. J. Li, and L. Dong, 2012: MJO simulations by GAMIL1.0 and GAMIL2.0. Atmos. Oceanic Sci. Lett., 5, 48–54.

    Google Scholar 

  • Xin, X. G., T. J. Zhou, and R. C. Yu, 2008: The Arctic oscillation in coupled climate models. Chinese Journal of Geophysics, 51(2), 337–351. (in Chinese with English abstract)

    Google Scholar 

  • Xu, K. M., and S. K. Krueger, 1991: Evaluation of cloudiness parameterizations using a cumulus ensemble model. Mon. Wea. Rev., 119, 342–367.

    Article  Google Scholar 

  • Yu, J.-Y., C. R. Mechoso, J. C. McWilliams, and A. Arakawa, 2002: Impacts of the Indian Ocean on the ENSO cycle. Geophys. Res. Lett., 29(8), 1204, doi: 10.1029/2001GL014098.

    Article  Google Scholar 

  • Yu, R. C., 1994: A two-step shape-preserving advection scheme. Adv. Atmos. Sci., 11, 79–90.

    Article  Google Scholar 

  • Yu, R. C., and T. J. Zhou, 2004, Impacts of winter-NAO on March cooling trends over subtropical Eurasia continent in the recent half century. Geophys. Res. Lett., 31, L12204, doi: 10.1029/2004GL019814.

    Article  Google Scholar 

  • Yu, Y., R. Yu, X. Zhang, and H. Liu, 2002: A flexible global coupled climate model. Adv. Atmos. Sci., 19, 169–190.

    Article  Google Scholar 

  • Yu, Y., and Coauthors, 2008: Coupled model simulations of climate changes in the 20th century and beyond. Adv. Atmos. Sci., 25(4), 641–654, doi: 10.1007/s00376-008-0641-0.

    Article  Google Scholar 

  • Yu, Y., W. Zheng, B. Wang, H. Liu, and J. Liu, 2011: Versions g1.0 and g1.1 of the LASG/IAP flexible global ocean-atmosphere-land system model. Adv. Atmos. Sci., 28(1), 99–117, doi: 10.1007/s00376-010-9112-5.

    Article  Google Scholar 

  • Zeng, G., W. C. Wang, and C. M. Shen, 2012: Association of the rainy season precipitation with low-level meridional wind in the Yangtze River valley and North China. J. Climate, 25(2), 792–799.

    Article  Google Scholar 

  • Zhang, G. J., and M. Mu, 2005a: Effects of modifications to the Zhang-McFarlane convection parameterization on the simulation of the tropical precipitation in the national center for atmospheric research community climate model. version 3. J. Geophys. Res., 110, D09109, doi: 10.1029/2004JD005617.

    Article  Google Scholar 

  • Zhang, G. J., and M. Mu, 2005b: Simulation of the Madden-Julian oscillation in the NCAR CCM3 using a revised Zhang-McFarlane convection parameterization scheme. J. Climate, 18, 4049–4067.

    Google Scholar 

  • Zhang, G. J., and N. A. McFarlane, 1995: Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian Climate Centre general circulation model. Atmos.-Ocean, 33, 407–446.

    Article  Google Scholar 

  • Zhang, X., and X. Liang, 1989: A numerical world ocean general circulation model. Adv. Atmos. Sci., 6, 43–61.

    Google Scholar 

  • Zhang, X., G. Shi, H. Liu, and Y. Q. Yu, 2000: IAP Global Ocean-Atmosphere-Land System Model. Science Press, Beijing, 252pp.

    Google Scholar 

  • Zhou, T. J., X. H. Zhang, R. C. Yu, Y. Q. Yu, and S. W. Wang, 2000: The North Atlantic Oscillation simulated by version 2 and 4 of IAP/LASG GOALS model. Adv. Atmos. Sci., 17(4), 601–616.

    Article  Google Scholar 

  • Zhou, T. J., and Coauthors, 2005: The climate system model FGOALS s using LASG/IAP spectral AGCM SAMIL as its atmospheric component. Acta. Meteorologica Sinica, 63(5), 702–715. (in Chinese)

    Google Scholar 

  • Zhou, T. J., Y. Yu, H. Liu, W. LI, X. You, and G. Zhou, 2007: Progress in the development and application of climate ocean models and ocean-atmosphere coupled models in China. Adv. Atmos. Sci., 24(6), 1109–1120, doi: 10.1007/s00376-007-1109-3.

    Article  Google Scholar 

  • Zhou, T. J., B. Wu, X. Y. Wen, L. J. Li, and B. WANG, 2008: A fast version of LASG/IAP climate system model and its 1000-year control integration. Adv. Atmos. Sci., 25(4), 655–672, doi: 10.1007/s00376-008-0655-7.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bin Wang  (王 斌).

Rights and permissions

Reprints and permissions

About this article

Cite this article

Li, L., Lin, P., Yu, Y. et al. The flexible global ocean-atmosphere-land system model, Grid-point Version 2: FGOALS-g2. Adv. Atmos. Sci. 30, 543–560 (2013). https://doi.org/10.1007/s00376-012-2140-6

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00376-012-2140-6

Key words

Navigation