Abstract
Paleoclimate simulations usually require model runs over a very long time. The fast integration version of a state-of-the-art general circulation model (GCM), which shares the same physical and dynamical processes but with reduced horizontal resolution and increased time step, is usually developed. In this study, we configure a fast version of an atmospheric GCM (AGCM), the Grid Atmospheric Model of IAP/LASG (Institute of Atmospheric Physics/State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics), at low resolution (GAMIL-L, hereafter), and compare the simulation results with the NCEP/NCAR reanalysis and other data to examine its performance. GAMIL-L, which is derived from the original GAMIL, is a finite difference AGCM with 72×40 grids in longitude and latitude and 26 vertical levels. To validate the simulated climatology and variability, two runs were achieved. One was a 60-year control run with fixed climatological monthly sea surface temperature (SST) forcing, and the other was a 50-yr (1950–2000) integration with observational time-varying monthly SST forcing. Comparisons between these two cases and the reanalysis, including intra-seasonal and inter-annual variability are also presented. In addition, the differences between GAMIL-L and the original version of GAMIL are also investigated.
The results show that GAMIL-L can capture most of the large-scale dynamical features of the atmosphere, especially in the tropics and mid latitudes, although a few deficiencies exist, such as the underestimated Hadley cell and thereby the weak strength of the Asia summer monsoon. However, the simulated mean states over high latitudes, especially over the polar regions, are not acceptable. Apart from dynamics, the thermodynamic features mainly depend upon the physical parameterization schemes. Since the physical package of GAMIL-L is exactly the same as the original high-resolution version of GAMIL, in which the NCAR Community Atmosphere Model (CAM2) physical package was used, there are only small differences between them in the precipitation and temperature fields. Because our goal is to develop a fast-running AGCM and employ it in the coupled climate system model of IAP/LASG for paleoclimate studies such as ENSO and Australia-Asia monsoon, particular attention has been paid to the model performances in the tropics. More model validations, such as those ran for the Southern Oscillation and South Asia monsoon, indicate that GAMIL-L is reasonably competent and valuable in this regard.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Bao, Q., Y. Liu, T. Zhou, Z. Wang, G. Wu, and P. Wang, 2005: The Sensitivity of the New Atmospheric General Circulation Model SAMIL-R42L26 of LASG/IAP to the land-atmosphere flux. Chinese J. Atmos. Sci., 30(6), 1077–1090.
Blackmon, M., and Coauthors, 2001: The community climate system model. Bull. Amer. Meteor. Soc., 82, 2357–2376.
Boville, B. A., and P. R. Gent, 1998: The NCAR Climate System Model, version one. J. Climate, 11, 1307–1326.
Climate and Global Dyamics Division, 2004: Annual Scientific Report 2004: Community Climate System Model Narrative. [available online at http://www.cgd.ucar.edu/asr/asr04/ccsm/narrative_ccsm.html].
Collins, W. D., and Coauthors, 2003: Description of the NCAR Community Atmosphere Model (CAM2). National Center for Atmospheric Research, Boulder, Colorado, 171pp.
Dixon, K. W., T. L. Delworth, T. R. Knutson, M. J. Spelman, and R. J. Stouffer, 2003: A comparison of climate change simulations produced by two GFDL coupled climate models. Global and Planetary Change, 37, 81–102.
Hack, J. J., J. T. Kiehl, and J. W. Hurrell, 1998: The hydrologic and thermodynamic characteristics of the NCAR CCM3. J. Climate, 11, 1179–1206.
Hurrell, J.W., J. J. Hack, B. A. Boville, D. L. Williamson, and J. T. Kiehl, 1998: The dynamical simulation of the NCAR Community Climate Model version 3 (CCM3). J. Climate, 11, 1207–1236.
Jacob, R., C. Schafer, I. Foster, M. Tobis, and J. Anderson, 2001: Computational design and performance of the Fast Ocean Atmosphere Model. Proc. 2001 International Conference on Computational Science, Alexandrov et al. Eds., Springer-Verlag, 175–184.
Jones, C., J. Gregory, R. Thorpe, P. Cox, J. Murphy, D. Sexton, and P. Valdes, 2005: Systematic optimization and climate simulation of FAMOUS, a fast version of HadCM3. Climate Dyn., 25, 189–204.
Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc., 77, 437–471.
Kang, I.-S., and Coauthors, 2002: Intercomparison of the climatological variations of Asian summer monsoon precipitation simulated by 10 GCMs. Climate Dyn., 19, 383–395.
Kiehl, J. T., J. J. Hack, G. B. Bonan, B. A. Boville, D. L. Williamson, and P. J. Rasch, 1998a: The National Center for Atmospheric Research Community Climate Model: CCM3. J. Climate, 11, 1131–1149.
Kiehl, J. T., J. J. Hack, and J. W. Hurrell, 1998b: The energy budget of the NCAR Community Climate Model: CCM3. J. Climate, 11, 1151–1178.
Liu, Z., W. Lewis, and A. Ganopolski, 2004: An acceleration scheme for the simulation of long-term climate evolution. Climate Dyn., 22, 771–781.
Raphael, M. N., 1998: Quasi-stationary waves in the Southern Hemisphere: An examination of their simulation by the NCAR Climate System Model, with and without an interactive ocean. J. Climate, 11, 1405–1418.
Rayner, N. A., D. E. Parker, E. B. Horton, C. K. Folland, L. V. Alexander, D. P. Rowell, E. C. Kent, and A. Kaplan, 2003: Global analyses of SST, sea ice and night marine air temperature since the late nineteenth century. J. Geophys. Res., 108(D14), 4407, doi:10.1029/2002JD002670.
Russell, G. L., J. R. Miller, and D. Rind, 1995: A coupled atmosphere-ocean model for transient climate change studies. Atmos.-Ocean, 33, 683–730.
Tobis, M., C. Schafer, I. Foster, R. Jacob, and J. Anderson, 1997: FOAM: Expanding the horizons of climate modeling. Proc., Super Computing 1997, San Diego, California, ACM/IEEE, pp27.
Wang, B., H. Wan, Z. Ji, X. Zhang, R. Yu, Y. Yu, and H. Liu, 2004: Design of a new dynamical core for global atmospheric models based on some efficient numerical methods. Science in China, Ser. A, 47, 4–21.
Webster, P. J., and S. Yang, 1992: Monsoon and ENSO: selectively interactive systems. Quart. J. Roy. Meteor. Soc., 118, 877–926.
Wu, G., H. Liu, Y. Zhao, and W. Li, 1996: A nine-layer atmospheric general circulation model and its performance. Adv. Atmos. Sci., 13, 1–18.
Wu, T., P. Liu, Z. Wang, Y. Liu, R. Yu, and G. Wu, 2003: The performance of atmospheric component model R42L9 of GOALS/LASG. Adv. Atmos. Sci., 20, 726–742.
Xie, P. P., and P. A. Arkin, 1996: Analyses of global monthly precipitation using gauge observations, satellite estimates, and numerical model predictions. J. Climate, 9, 840–858.
Yu, R., W. Li, X. Zhang, Y. Yu, H. Liu, and T. Zhou, 2000: Climatic features related to eastern China summer rainfalls in the NCAR CCM3. Adv. Atmos. Sci., 17, 503–518.
Zeng, Q. C., C. G. Yuan, X. H. Zhang, X. Z. Liang, and N. Bao, 1987: A global grid point general circulation model. Collection of papers presented at the WMO/IUGG NWP Symposium, Tokyo, 4–8 Aug. 1986. J. Meteor. Soc. Japan, Special Volume, 121–124.
Zhang, X., N. Bao, R. Yu, and W. Wang, 1992: Coupling scheme experiments based on an atmospheric and oceanic GCM. Chinese J. Atmos. Sci., 16(2), 129–144.
Zhou, T. J., and Z. X. Li, 2002: Simulation of the East Asian summer monsoon by using a variable resolution atmospheric GCM. Climate Dyn., 19, 167–180.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Wen, X., Zhou, T., Wang, S. et al. Performance of a reconfigured atmospheric general circulation model at low resolution. Adv. Atmos. Sci. 24, 712–728 (2007). https://doi.org/10.1007/s00376-007-0712-7
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/s00376-007-0712-7