Abstract
A joint statistical-dynamical method addressing both the internal decadal variability and effect of anthropogenic forcing was developed to predict the decadal components of East Asian surface air temperature (EATs) for three decades (2010–2040). As previous studies have revealed that the internal variability of EATs (EATs_int) is influenced mainly by the ocean, we first analyzed the lead-lag connections between EATs_int and three sea surface temperature (SST) multidecadal modes using instrumental records from 1901 to 1999. Based on the lead-lag connections, a multiple linear regression was constructed with the three SST modes as predictors. The hindcast for the years from 2000 to 2005 indicated the regression model had high skill in simulating the observational EATs_int. Therefore, the prediction for EATs_int (Re_EATs_int) was obtained by the regression model based on quasi-periods of the decadal oceanic modes. External forcing from greenhouse gases is likely associated with global warming. Using monthly global land surface air temperature from historical and projection simulations under the Representative Concentration Pathway (RCP) 4.5 scenario of 19 Coupled General Circulation Models participating in the fifth phase of the Coupled Model Intercomparison Project (CMIP5), we predicted the curve of EATs (EATs_trend) relative to 1970–1999 by a second-order fit. EATs_int and EATs_trend were combined to form the reconstructed EATs (Re_EATs). It was expected that a fluctuating evolution of Re_EATs would decrease slightly from 2015 to 2030 and increase gradually thereafter. Compared with the decadal prediction in CMIP5 models, Re_EATs was qualitatively in agreement with the predictions of most of the models and the multi-model ensemble mean, indicating that the joint statistical-dynamical approach for EAT is rational.
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References
Allan R J, Lindesay J A, Reason C J C. 1995. Multidecadal variability in the climate system over the Indian Ocean region during the austral summer. J Clim, 8: 1853–1873
Chen W L, Jiang Z H. 2012. Evaluation of the decadal prediction skill over China based on four global atmosphere-ocean coupled climate models (in Chinese). Clim Environ Res, 17: 81–91
Chylek P, Folland C K, Dijkstra H A, et al. 2010. Ice-core data evidence for a prominent near 20 year time-scale of the Atlantic Multidecadal Oscillation. Geophys Res Lett, 38: L13704
Delworth T L, Mann M E. 2000. Observed and simulated multidecadal variability in the Northern Hemisphere. Clim Dyn, 16: 661–671
d’Orgeville M, Peltier W R. 2007. On the Pacific decadal oscillation and the Atlantic multidecadal oscillation: Might they be related? Geophys Res Lett, 34: L23705
Enfield D B, Mestas-Nuñez A M, Trimble P J. 2001. The Atlantic multidecadal oscillation and its relationship to rainfall and river flows in the continental US. Geophys Res Lett, 28: 2077–2080
Folland C K, Parker D E, Colman A W, et al. 1999. Large-scale Modes of Ocean Surface Temperature Since the Late Nineteenth Century. Berlin Heidelberg: Springer. 73–102
Fu C B, Qian C, Wu Z H. 2011. Projection of global mean surface air temperature changes in next 40 years: Uncertainties of climate models and an alternative approach. Sci China Earth Sci, 54: 1400–1406
Gao F, Xin X G, Wu T W. 2012. A study of the prediction of regional and global temperature on decadal time scale with BCC_CSM1.1 Model (in Chinese). Chin J Atmos Sci, 36:1165–1179
Hawkins E, Robson J, Sutton R, et al. 2011. Evaluating the potential for statistical decadal predictions of sea surface temperatures with a perfect model approach. Clim Dyn, 37: 2495–2509
Hoerling M, Hurrell J, Kumar A, et al. 2011. On North American decadal climate for 2011–2020. J Clim, 24: 4519–4528
Hurrell J W, Delworth T L, Danabasoglu G, et al. 2010. Decadal climate prediction: Opportunities and challenges. In: Harrison H J, Stammer D, eds. Proceeding of OceanObs: Sustained Ocean Observations and Information for Society. Venice: ESA Publication
Kaplan A, Cane M A, Kushnir Y, et al. 1998. Analyses of global sea surface temperature 1856–1991. J Geophys Res, 103: 567–589
Keenlyside N S, Latif M, Jungclaus J, et al. 2008. Advancing decadal-scale climate prediction in the North Atlantic sector. Nature, 453: 84–88
Knight J R, Allan R J, Folland C K, et al. 2005. A signature of persistent natural thermohaline circulation cycles in observed climate. Geophys Res Lett, 32: L20708
Li Q, Ren R C, Cai M, et al. 2012. Attribution of the summer warming since 1970s in Indian Ocean Basin to the inter-decadal change in the seasonal timing of El Niño decay phase. Geophys Res Lett, 39: L12702
Li S L, Bates G T. 2007. Influence of the Atlantic Multidecadal Oscillation (AMO) on the winter climate of East China. Adv Atmos Sci, 24: 126–135
Li S L, Luo F F. 2013. Lead-lag connection of the Atlantic Multidecadal Oscillation (AMO) with East Asian surface air temperatures in instrumental records. Atmos Ocn Sci Lett, 6: 138–143
Luo F F, Li S L, Gao Y Q, et al. 2012. A new method for predicting the decadal component of global SST. Atmos Ocn Sci Lett, 5: 521–526
Medhaug I, Furevik T. 2011. North Atlantic 20th century multidecadal variability in coupled climate models: Sea surface temperature and ocean overturning circulation. Ocean Sci Disc, 8: 353–396
Meehl G A, Goddard L, Murphy J, et al. 2009. Decadal prediction: Can it be skillful?. Bull Amer Meteorol Soc, 90: 1467–1485
Mitchell T D, Jones P D. 2005. An improved method of constructing a database of monthly climate observations and associated high resolution grid. Int J Climatol, 25: 693–712
Mochizuki T, Ishii M, Kimoto M, et al. 2010. Pacific decadal oscillation hindcasts relevant to near-term climate prediction. Proc Natl Acad Sci USA, 107: 1833–1837
Murphy J, Kattsov V, Keenlyside N, et al. 2010. Towards prediction of decadal climate variability and change. Proc Environ Sci, 1: 287–304
Otterå O H, Bentsen M, Drange H, et al. 2010. External forcing as a metronome for Atlantic multidecadal variability. Nat Geol, 3: 688–694
Pohlmann H, Johann J H, Köhl A, et al. 2009. Initializing decadal climate predictions with the GECCO oceanic synthesis: Effects on the North Atlantic. J Clim, 22: 3926–3938
Power S, Casey T, Folland C, et al. 1999. Inter-decadal modulation of the impact of ENSO on Australia. Clim Dyn, 15: 319–324
Qian W H, Lu B. 2010. Periodic oscillations in millennial global-mean temperature and their causes. Chin Sci Bull, 55, 4052–4057
Qian W H, Lu B, Zhu C W. 2010. How would global-mean temperature change in the 21st century? Chin Sci Bull, 55: 1963–1967
Rayner N A, Parker D E, Horton E B, et al. 2003. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res, 108: 4407
Smith D M, Cusack S, Colman A W, et al. 2007. Improved surface temperature prediction for the coming decadal from a global climate model. Science, 317: 796–799
Sutton R T, Hodson D L R. 2005. Atlantic Ocean forcing of North American and European summer climate. Science, 309: 115–118
Sutton R T, Hodson D L R. 2007. Climate response to basin-scale warming and cooling of the North Atlantic Ocean. J Clim, 20: 891–907
Tang G L, Ren G Y. 2005. Reanalysis of surface air temperature change of the last 100 years over China (in Chinese). Clim Environ Res, 10: 791–798
Taylor K E, Stouffer R J, Meehl G A. 2012. An overview of CMIP5 and the experiment design. Bull Amer Meteorol Soc, 93: 485–498
Tollefson J. 2013. Climate change: The forecast for 2018 is cloudy with record heat. Nature, 499:139–141
Wang B, Liu M, Yu Y, et al. 2012. Preliminary evaluations of FGOALS_g2 for decadal predictions. Adv Atmos Sci, 30: 674–683
Wang Y M, Li S L, Luo D H. 2009. Seasonal response of Asian monsoonal climate to the Atlantic Multidecadal Oscillation. J Geophys Res, 114: D02112
Wang T, Otterå O H, Gao Y Q, et al. 2012. The response of the North Pacific decadal variability to strong tropical volcanic eruptions. Clim Dyn, 39: 2917–2936
Wu B, Zhou T J. 2012. Prediction of decadal variability of Sea Surface temperature by a coupled global climate model FGOALS_gl developed in LASG/IAP. Chin Sci Bull, 57: 2453–2459
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Luo, F., Li, S. Joint statistical-dynamical approach to decadal prediction of East Asian surface air temperature. Sci. China Earth Sci. 57, 3062–3072 (2014). https://doi.org/10.1007/s11430-014-4984-3
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DOI: https://doi.org/10.1007/s11430-014-4984-3