Potential predictability of Northern America surface temperature in AGCMs and CGCMs

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• 作者：Youmin Tang ; Dake Chen ; Xiaoqin Yan
• 关键词：Seasonal climate prediction ; Potential predictability ; Ensemble predictions
• 刊名：Climate Dynamics
• 出版年：2015
• 出版时间：July 2015
• 年：2015
• 卷：45
• 期：1-2
• 页码：353-374
• 全文大小：3,494 KB
• 参考文献：Allen MR, Smith LA (1997) Optimal filtering in singular spectrumanalysis. Phys Lett 234:419-28View Article
  Barnett TP, Preisendorfer R (1987) Origins and levels of monthly and seasonal forecast skill for United States surface air temperatures determined by canonical correlation analysis. Mon Weather Rev 115:1825-850View Article
  Barnston AG, Smith TM (1996) Specification and prediction of global surface temperature and precipitation from global SST using CCA. J Clim 9:2660-697View Article
  Brunsell NA, Wilson CJ (2013) Multiscale interactions between water and carbon fluxes and environmental variables in a central U.S. Grassland. Entropy 15:1324-341. doi:10.-390/?e15041324 View Article
  DelSole T (2004) Predictability and information theory. Part I: measures of predictability. J Atmos Sci 61:2425-440View Article
  DelSole T, Tippett MK (2007) Predictability: recent insights from information theory. Rev Geophys 45:RG4002. doi:10.-029/-006RG000202 View Article
  Derome J, Brunet G, Plante A, Gagnon N, Boer GJ, Zwiers FW, Lambert S, Ritchie H (2001) Seasonal predictions based on two dynamical models. Atmos Ocean 39:485-01View Article
  Doblas-Reyes FJ et al (2009) Addressing model uncertainty in seasonal and annual dynamical ensemble forecasts. doi:10.-002/?qj.-64
  Duan W, Wei C (2012) The ‘spring predictability barrier-for ENSO predictions and its possible mechanism: results from a fully coupled model. Int J Climatol. doi:10.-002/?joc.-513
  Duan W, Liu X, Zhu K, Mu M (2009) Exploring the initial errors that cause a significant “spring predictability barrier-for El Ni?o events. J Geophys Res Ocean. doi:10.-029/-008JC004925
  Hoerling MP, Kumar A (2002) Atmospheric response patterns associated with tropical forcing. J Clim 15:2184-203View Article
  Jha B, Kumar A (2009) A comparison of the atmospheric response to ENSO in coupled and uncoupled model simulations. Mon Weather Rev 137:479-87View Article
  Jia X, Lin H, Derome J (2010) Improving seasonal forecast skill of North American surface air temperature in fall using a postprocessing method. Mon Weather Rev 138:1843-857View Article
  Kharin VV, Teng Q, Zwiers FW, Boer GJ, Derome J, Fontecilla JS (2009) Skill assessment of seasonal hindcasts from the Canadian Historical Forecast Project. Atmos Ocean 47:204-23View Article
  Kirtman BP (2003) The COLA anomaly coupled model: ensemble ENSO prediction. Mon Weather Rev 10:2324-341View Article
  Kirtman BP, Min D (2009) Multimodel ensemble ENSO prediction with CCSM and CFS. Mon Weather Rev 137:2908-930View Article
  Kleeman (2002) Measuring dynamical prediction utility using relative entropy. J Atmos Sci 59:2057-072View Article
  Krishnamurti TN, Kishtawal CM, LaRow TE, Bachiochi DR, Zhang Z, Willford CE, Gadgil S, Surendran S (1999) Improved weather and seasonal climate prediction forecasts from multimodel superensemble. Science 285:1548-550View Article
  Krishnamurti TN, Kishtawal CM, Zhang Z, LaRow T, Bachiochi D, Williford E, Gadgil S, Surendran S (2000) Multimodel ensemble forecasts for weather and seasonal climate. J Clim 13:4196-216View Article
  Kug J-S, Kang I-S, Choi D-H (2008) Seasonal climate predictability with tier-one and tier-two prediction systems. Clim Dyn 31:403-16View Article
  Kumar A, Hoerling MP (1998) Annual cycle of pacific-North American seasonal predictability associated with different phases of ENSO. J Clim 11:3295-308View Article
  Kumar A, Hoerling MP, Schubert SD, Suarez MS (2003) Variability and predictability of 200-mb seasonal mean height during summer and winter. J Geophys Res 108:4169. doi:10.-029/-002JD002728 View Article
  Latif M, Barnett TP (1994) Causes of decadal climate variability over the north pacific and North America. Science 266:634-37View Article
  Lin H, Brunet G, Derome J (2008) Seasonal forecasts of Canadian winter precipitation by postprocessing GCM integrations. Mon Weather Rev 136:769-83View Article
  Livezey RE, Masutani M, Ji M (1996) SST-forced seasonal simulation and prediction skill for versions of the NCEP/MRF model. Bull Am Meteorol Soc 77:507-17View Article
  Luo J, Masson S, Behera S, Shingu S, Yamagata T (2005) Seasonal climate predictability in a coupled OAGCM using a different approach for ensemble forecasts. J Clim 18:4474-496View Article
  Misra V, Li H, Wu Z, DiNapoli S (2013) Global seasonal climate predictability in a two tiered forecast system: part I: boreal summer and fall seasons. Clim Dyn. doi:10.-007/?s00382-013-1812-y
  Palmer T et al (2004) Development of a European multi-model ensemble system for seasonal to inter-annual prediction (DEMETER). Bull Am Meteorol Soc 85:853-72View Article
  Palmer TN, Doblas-Reyes FJ, Weisheimer A, Rodwell MJ (2009) Toward seamless prediction: calibration of climate change projections using seasonal forecasts reply. Bull Am Meteorol Soc 90:1551-554View Article
  Peng P, Kumar A, Wang W (2011) An analysis of
• 作者单位：Youmin Tang (1) (2)
  Dake Chen (2)
  Xiaoqin Yan (1) (3)
  
  1. Environmental Science and Engineering, University of Northern British Columbia, 3333 University Way, Prince George, BC, V2N 4Z9, Canada
  2. State Key Laboratory of Satellite Ocean Environment Dynamics, Hangzhou, China
  3. Department of Earth and Atmospheric Sciences, George Mason University, Fairfax, VA, USA
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Geophysics and Geodesy
  Meteorology and Climatology
  Oceanography
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1432-0894

文摘

In this study, the potential predictability of the Northern America (NA) surface air temperature (SAT) was explored using an information-based predictability framework and two multiple model ensemble products: a one-tier prediction by coupled models (T1), and a two-tier prediction by atmospheric models only (T2). Furthermore, the potential predictability was optimally decomposed into different modes for both T1 and T2, by extracting the most predictable structures. Emphasis was placed on the comparison of the predictability between T1 and T2. It was found that the potential predictability of the NA SAT is seasonal and spatially dependent in both T1 and T2. Higher predictability occurs in spring and winter and over the southeastern US and northwestern Canada. There is no significant difference of potential predictability between T1 and T2 for most areas of NA, although T1 has higher potential predictability than T2 in the southeastern US. Both T1 and T2 display similar most predictable components (PrCs) for the NA SAT, characterized by the inter-annual variability mode and the long-term trend mode. The first one is inherent to the tropical Pacific sea surface temperature forcing, such as the El Nino-Southern Oscillation, whereas the second one is closely associated with global warming. In general, the PrC modes can better characterize the predictability in T1 than in T2, in particular for the inter-annual variability mode in the fall. The prediction skill against observations is better measured by the PrC analysis than by principal component analysis for all seasons, indicating the stronger capability of PrCA in extracting?prediction targets.