Abstract
Atmospheric General Circulation models (AGCMs) forced by prescribed sea surface temperature (SST) climatological seasonal cycle simulate interannual variabilities that have cyclic characteristics. Such cyclic characteristics generate relationships between one year and the next in the model output. We document these relationships by computing lag-1-year autocorrelation in hundreds of years of CAM3 and ECHAM5 simulations. The autocorrelation is found to be generally less than 0.2, but contain robust structures. In case of zonal averaged zonal wind and air temperature the winter hemisphere is characterized by negative autocorrelation and the summer hemisphere characterized by positive autocorrelation. The presence of autocorrelation means that an average over a 10∼25 year AGCM simulation in an effort to reduce the influence of interannual variability on externally-driven climate change might not be very effective. In view of this, we investigate if ensemble runs instead of a continuous simulation is more effective in reducing such influences. The reduction gain by using N 1-year long ensemble runs over N years of continuous run is generally less than 30% and mainly limited to the areas where the autocorrelation is positive. We thus conclude that each year in a continuous simulation can generally be treated as largely independent of the next year in an AGCM run with fixed SST forcing.
Similar content being viewed by others
References
Bryan, K., 1984: Accelerating the convergence to equilibrium of oceanclimate models. J. Phys. Oceanogr., 14, 666–673, doi:10.1175/1520-0485(1984)014〈0666:ATCTEO〉2.0.CO;2.
Carré, M., J. P. Sachs, J. M. Wallace, and C. Favier, 2012: Exploring errors in paleoclimate proxy reconstructions using Monte Carlo simulations: paleotemperature from mollusk and coral geochemistry. Climate Past, 8, 433–450, doi:10.5194/cp-8-433-2012.
Chung, C. E., and V. Ramanathan, 2006: Weakening of North Indian SST gradients and the monsoon rainfall in India and the Sahel. J. Climate, 19, 2036–2045, doi:10.1175/JCLI3820.1.
_____, ______, and Kiehl, J. T., 2002: Effects of the South Asian absorbing haze on the Northeast Monsoon and Surface-Air heat exchange. J. Climate, 15, 2462–2476, doi:10.1175/1520-0442(2002)015〈2462:EOTSAA〉2.0.CO;2.
Collins, W. D., and Coauthors, 2006: The formulation and atmospheric simulation of the Community Atmosphere Model Version 3 (CAM3). J. Climate, 19, 2144–2161, doi:10.1175/jcli3760.1.
Cubasch, U., and Coauthors, 2001: Projections of future climate change. Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change [Houghton, J.T., Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. Maskell, and C.A. Johnson (eds.)], Cambridge University Press, 881 pp.
Danabasoglu, G., and P. R. Gent, 2009: Equilibrium climate sensitivity: Is it accurate to use a Slab Ocean Model? J. Climate, 22, 2494–2499, doi:10.1175/2008JCLI2596.1.
Deser, C., A. Phillips, V. Bourdette, and H. Teng, 2012: Uncertainty in climate change projections: the role of internal variability. Climate Dyn., 38, 527–546, doi:10.1007/s00382-010-0977-x.
Ham, S., and S. Hong, 2013: Sensitivity of simulated intraseasonal oscillation to four convective parameterization schemes in a coupled climate model. Asia-Pac. J. Atmos. Sci., 49, 483–496, doi: 10.1007/s13143-013-0043-9.
Haughton, N., 2012: Climate model ensemble generation and model dependence. Dissertation, Climate Change Research Centre, University of New South Wales, 65 pp.
Jin, C.-S., C.-H. Ho, J.-H. Kim, D.-K. Lee, D.-H. Cha, and S.-W. Yeh, 2013: Critical role of northern off-equatorial sea surface temperature forcing associated with central pacific El Niño in more frequent tropical cyclone movements toward East Asia. J. Climate, 26, 2534–2545, doi:10.1175/JCLI-D-12-00287.1.
Kalnay, E., and S. C. Yang, 2010: Accelerating the spin-up of ensemble kalman filtering. Quart. J. Roy. Meteor. Soc., 136, 1644–1651, doi: 10.1002/qj.652.
Kiehl, J. T., C. A. Shields, J. J. Hack, and W. D. Collins, 2006: The climate sensitivity of the Community Climate System Model version 3 (CCSM3). J. Climate, 19, 2584–2596, doi:10.1175/JCLI3747.1.
Kug, J.-S., Y.-G. Ham, M. Kimoto, F.-F. Jin, and I.-S. Kang, 2010: New approach for optimal perturbation method in ensemble climate prediction with empirical singular vector. Climate Dyn., 35, 331–340, doi:10.1007/s00382-009-0664-y.
Kumar, O. S. R. U. B., S. R. Rao, S. Ranganathan, and S. S. Raju, 2010: Role of intra-seasonal oscillations on monsoon floods and droughts over India. Asia-Pac. J. Atmos. Sci., 46, 21–28, doi:10.1007/s13143-010-0003-6.
Leith, C. E., 1973: The standard error of time-average estimates of climatic means. J. Appl. Meteorol., 12, 1066–1069, doi:10.1175/1520-0450(1973)012〈1066:TSEOTA〉2.0.CO;2.
Merkel, U., and M. Latif, 2002: A high resolution AGCM study of the El Nino impact on the North Atlantic/European sector. Geophys. Res. Lett., 29, 5-1–5-4, doi:10.1029/2001GL013726.
Ott, L., and Coauthors, 2010: Influence of the 2006 Indonesian biomass burning aerosols on tropical dynamics studied with the GEOS-5 AGCM. J. Geophys. Res.-Atmos., 115, doi:10.1029/2009JD013181.
Räisänen, P., and H. Järvinen, 2010: Impact of cloud and radiation scheme modifications on climate simulated by the ECHAM5 atmospheric GCM. Quart. J. Roy. Meteor. Soc., 136, 1733–1752, doi:10.1002/qj.674.
_____, S. Järvenoja, and H. Järvinen, 2008: Noise due to the Monte Carlo independent-column approximation: short-term and long-term impacts in ECHAM5. Quart. J. Roy. Meteor. Soc., 134, 481–495, doi:10.1002/qj.231.
Randall, D. A., and Coauthors, 2007: Climate models and their evaluation. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)], J.-W. Kim, and J. Stone, Eds., Cambridge University Press, 991 pp.
Roeckner, E., and Coauthors, 2003: The atmospheric general circulation model ECHAM 5. PART I: Model description. Max Planck Institute for Meteorology Rep. 349, 127 pp.
Taschetto, A. S., and M. H. England, 2008: Estimating ensemble size requirements of AGCM simulations. Meteor. Atmos. Phys., 100, 23–36, doi:10.1007/s00703-008-0293-8.
Toth, Z., and E. Kalnay, 1997: Ensemble forecasting at NCEP and the breeding method. Mon. Wea. Rev., 125, 3297–3319, doi:10.1175/1520-0493(1997)125〈3297:EFANAT〉2.0.CO;2.
Wilks, D. S., 1997: Resampling hypothesis tests for autocorrelated fields. J. Climate, 10, 65–82, doi:10.1175/1520-0442(1997)010〈0065:rhtfaf〉2.0.co;2.
_____, 2011: Statistical methods in the atmospheric sciences. Third edition 2011 ed. Vol. 100, Academic Press, 704 pp.
Yoo, S.-H., C.-H. Ho, S. Yang, H. J. Choi, and J. G. Jhun, 2004: Influences of tropical western and extratropical pacific SST on East and Southeast Asian climate in the summers of 1993–94. J. Climate, 17, 2673–2687, doi:10.1175/1520-0442(2004)017〈2673:IOTWAE〉2.0.CO;2.
Yoshimori, M., T. F. Stocker, C. C. Raible, and M. Renold, 2005: Externally forced and internal variability in ensemble climate simulations of the maunder minimum. J. Climate, 18, 4253–4270, doi:10.1175/JCLI3537.1.
Zwiers, F. W., and H. Von Storch, 1995: Taking serial correlation into account in tests of the mean. J. Climate, 8, 336–351, doi:10.1175/1520-0442(1995)008〈0336:tsciai〉2.0.co;2.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Decremer, D., Chung, C.E. Comparison of model noise in AGCM independent ensemble runs and continuous simulation. Asia-Pacific J Atmos Sci 50, 263–270 (2014). https://doi.org/10.1007/s13143-014-0014-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13143-014-0014-9