Contribution of the location and spatial pattern of initial error to uncertainties in El Niño predictions

Abstract

With the Zebiak‐Cane model, the contribution of the location and spatial pattern of initial error in sea surface temperature anomalies (SSTA) to uncertainty in El Niño predictions is investigated using an approach based on conditional nonlinear optimal perturbation (CNOP), which seeks to find the initial error (i.e., the CNOP error) that satisfies a given constraint and that causes the largest prediction error at the prediction time. The computed CNOP error of SSTA has a dipole pattern in the equatorial central and eastern Pacific. The initial error from the equatorial central and eastern Pacific tends to grow more significantly than those from other locations. Because of the contribution of annual mean states the location of the initial error plays an important role in the error evolution; e.g., the shallow annual mean thermocline in the eastern Pacific favors feedback between the thermocline and sea surface temperature. Meanwhile, the specific dipole structure of the initial error is also crucial for optimal error growth. Even with the same magnitude as the CNOP error, random initial error in the equatorial central and eastern Pacific does not evolve significantly over time. Initial errors of SSTA with a similar spatial pattern to the CNOP error (i.e., the dipole pattern of SSTA error) give rise to larger prediction errors than those without similar spatial pattern do. Consequently, the magnitude of the prediction error at the prediction time depends on the combined effects of the location and spatial pattern of the initial error. If additional observation instruments are deployed to observe sea surface temperature with limited coverage, they should preferentially be deployed in the equatorial central and eastern Pacific.

Towards optimal observational array for dealing with challenges of El Niño-Southern Oscillation predictions due to diversities of El Niño

“…Specifically, with the start months changing from January through April and July to October, the regions of large errors tend to move westward. 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 Hu and Duan 2016;Tian and Duan 2016;Mu et al 2014;Yu et al 2012). Therefore, the result indicates that the sensitive areas for targeting observations associated with two types of El Niño events are dependent of the start months.…”

“…Correspondingly, if the target observations in the sensitive areas presented by Tian and Duan (2016) are used to decrease the initial errors, the forecast skill of the two types of El Niño would decrease with the start months changing from January (0) to October (0). Next, we show the correctness of this inference by using the regional division suggested by Yu et al (2012) (Fig. 4).…”

“…That is to say, the sensitive areas should be applicable for most of El Niño events predictions. Although Yu et al (2012) identified the sensitive area according to the composite of CNOPs calculated based on all the El Niño events involved in the study, they, as mentioned in the introduction, did not consider the effect of start months of predictions on target observations and only gave the approximate range of the sensitive area for targeting. In this paper, in order to identify the optimal layout of observation locations for targeting, we proposed a quantitative method which considers the differences among the CNOP-type initial errors calculated at different start months of predictions (see Sect.…”

“…Previous studies showed that the region with large values of the OGEs represent the sensitive area for target observation associated with El Niño predictions Hu and Duan 2016;Tian and Duan 2016;Mu et al 2014;Yu et al 2012); and the initial errors in these sensitive areas make greatest contribution to the prediction error and the prediction Fig. 1 The mean of the SSTAs during the mature phase for three EP-El Niño events (1982/1983, 1986/1987 and 1997/1998) and five CP-El Niño events (1991/1992, 1994/1995, 2002/2003, 2004/2005 (Fig.…”

“…In fact, Morss and Battisti (2004a, b), based on observation system simulation experiment (OSSE), suggested that for ENSO forecasting longer than a few months, the most important area for observations is the eastern equatorial Pacific, south of the equator; a secondary region of importance is the western equatorial Pacific. Yu et al (2012) used the Zebiak-Cane model (Zebiak and Cane 1987) and explored the target observations for El Niño events. They argued that the eastern equatorial Pacific is the sensitive areas for targeting observations associated with EP-El Niño forecasting.…”