Applications Of Nonlinear Optimization Methods To The Study Of ENSO Predictability

Conditional nonlinear optimal perturbation (CNOP) has been used to study the optimal precursors and"spring predictability barrier"of ENSO within the frames of simple coupled ocean-atmosphere models for ENSO in this thesis. Based on the theory of three predictability problems in numerical weather and climate prediction, in this thesis the predictability of ENSO is also studied quantificationally.The innovation of this thesis consists in (1) the utilization of nonlinear optimization methods in the study of ENSO predictability, (2) the revelation of the effects of nonlinearity on the predictability of ENSO.Major results of this thesis are:1. The differences between CNOP and linear singular vector (LSV) are revealed numerically.The nonlinear characteristics of the model are disclosed not only from the initial patterns but also from the nonlinear evolution by using conditional nonlinear optimal perturbation.2. The optimal precursors of ENSO are investigated.a) CNOP is introduced to study the precursors of ENSO. The results suggest that for the proper constraint condition, the CNOP of climatological mean state evolve into ENSO events more probably than the LSV. Consequently it is reasonable to regard CNOP as the optimal precursors of ENSO events;b) Observed anomalous monthly mean SST and depth of 20 0 C isotherm...