Initial error-induced optimal perturbations in ENSO predictions, as derived from an intermediate coupled model

An improved simulation of the 2015 El Niño event by optimally correcting the initial conditions and model parameters in an intermediate coupled model

“…Furthermore, the CNOP-based technique is adopted to quantify errors in ICs and MPs that can make dominant contributions to prediction biases. In an idealized model setting, Tao et al (2017) has applied the CNOP approach to characterizing errors in ICs that can have the largest error growth in ENSO prediction (Mu et al 2003). On the basis of those developments, the CNOP-based technique was further applied to a realistic case for the 2015 El Niño event using the ICM.…”

“…Based on the ENSO model developed by Zebiak and Cane (1987), for example, this approach has been widely used to study ENSO predictability and targeted observing system designs (Xu 2006;Mu et al 2007Mu et al , 2014Duan et al 2009. In an idealized model setting for the IOCAS ICM, Tao et al (2017) more recently adopted the CNOP approach (Mu et al 2003) and theoretically demonstrated that the characterized errors in ICs can have largest error growth in ENSO predictions. A brief description of the CNOP approach is presented below.…”

“…Detailed implementations of the CNOP approach into the ICM are presented in Tao et al (2017). Two types of simulation experiments were performed.…”

“…In addition, the adjoint component involved with the 4-D Var data assimilation technique allows the calculation of the gradient of a defined object function with respect to ICs and/ or MPs. More recently, applying the CNOP approach to the ICM, Tao et al (2017) identified the spatial characteristics of errors in initial states that can lead to the largest growth in ENSO predictions. It was found that the CNOP-induced error evolution in the ICM exhibits a strong spring predictability barrier (SPB) phenomenon in ENSO predictions.…”

“…That is, when the CNOP-related errors in ICs are removed or reduced, ENSO prediction can be improved optimally and effectively. Note that these previous studies using the ICM are based on idealized experiments for ENSO predictability studies and predictions (Gao et al 2016;Tao et al 2017).…”