Abstract
This paper investigates the optimal observational array for improving the initialization of El Niño-Southern Oscillation predictions by exploring the sensitive areas for target observations of two types of El Niño predictions. The sensitive areas are identified by calculating the optimally growing errors (OGEs) of the Zebiak–Cane model, as corrected by the optimal forcing vector that is determined by assimilating the observed sea surface temperature anomalies (SSTAs). It is found that although the OGEs have similar structures for different start months of predictions, the regions covered by much large errors for the SSTA component tend to locate at different zonal positions and depends on the start months. Furthermore, these regions are also in difference between two types of El Niño events. The regions covered by large errors of OGEs represent the sensitive areas for target observations. Considering the dependence of the sensitive areas on related El Niño types and the start months of predictions, the present study propose a quantitative frequency method to determine the sensitive areas for target observations associated with two types of El Niño predictions, which is expected to be applicable for both types of El Niño predictions with different start months. As a result, the sensitive areas that describe the array of target observations are presented with a reversal triangle-like shape locating in the eastern Pacific, specifically the area of 120°W–85°W, 0°S–11°S, and an extension to the west along the equator and then gathering at the 180° longitude and the western boundary. “Hindcast” experiments demonstrated that such observational array is very useful in distinguishing two types of El Niño and superior to the TAO/TRITON array. It is therefore suggested that the observational array provided in the present study is towards the optimal one and the original TAO/TRITON array should be further optimized when applied to predictions of the diversities of El Niño events.
Highlights
El Niño-Southern Oscillation (ENSO) is the most dominant climate mode in the tropical Pacific
We correct the model errors of the Zebiak–Cane model by applying the optimal forcing vector (OFV) approach, and successfully reproduce three EP- and five CP-El Niño events. Based on these eight reproduced El Niño events, we investigate the optimally growing initial errors (OGEs) of EP- and CP-El Niño events by using the conditional nonlinear optimal perturbation (CNOP) approach and explore the sensitive areas for target observations for two types of El Niño events
The regions of large errors for OGEs are shown to be the sensitive area for target observations, i.e., the area that the additional observations should be preferentially deployed (Duan and Hu 2016; Hu and Duan 2016; Tian and Duan 2016; Mu et al 2014; Yu et al 2012)
Summary
El Niño-Southern Oscillation (ENSO) is the most dominant climate mode in the tropical Pacific. Considering that the Zebiak–Cane model is an intermediate ENSO model and does not have enough description of the subsurface layers, Duan and Hu (2016) and Hu and Duan (2016) further adopted a complex GCM and showed that the subsurface layer of western equatorial Pacific represent another sensitive area for El Niño forecasting Most of these above studies only focus on EP-El Niño events because most models do not have the ability to simulate two types of El Niño events well (Ham and Kug 2012; Kim and Yu 2012; Kug et al 2012).
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