A new approach, the conditional nonlinear optimal perturbation (CNOP) is introduced to study the predictability of El Ni駉-Southern Oscillation (ENSO) using a theoretical coupled ocean-atmosphere model. The difference...A new approach, the conditional nonlinear optimal perturbation (CNOP) is introduced to study the predictability of El Ni駉-Southern Oscillation (ENSO) using a theoretical coupled ocean-atmosphere model. The differences between CNOP and linear singular vector (LSV) are demonstrated. The results suggest that the nonlinear model and CNOP are superior in determining error growth for studying predictability of the ENSO. In particular, the CNOP approach is used to explore the nature of the 憇pring predictability barrier?in ENSO prediction.展开更多
基金supported by the National Key Basic Research Proiect(Grant No.G1998040910)the National Natural Science Foundation of China(Grant Nos.40023001 and 40075015)of the Chinese Academy of Sciences (Grant No.KZCX2-208).
文摘A new approach, the conditional nonlinear optimal perturbation (CNOP) is introduced to study the predictability of El Ni駉-Southern Oscillation (ENSO) using a theoretical coupled ocean-atmosphere model. The differences between CNOP and linear singular vector (LSV) are demonstrated. The results suggest that the nonlinear model and CNOP are superior in determining error growth for studying predictability of the ENSO. In particular, the CNOP approach is used to explore the nature of the 憇pring predictability barrier?in ENSO prediction.
