The relationship among probabilistic, deterministic and potential skills in predicting the ENSO for the past 161 years

Ting Liu, Youmin Tang, Dejian Yang, Yanjie Cheng, Xunshu Song, Zhaolu Hou, Zheqi Shen, Yanqiu Gao, Yanling Wu, Xiaojing Li, Banglin Zhang
<span title="2019-09-20">2019</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6gpmoa2quzf45hytgyhi3tjnzm" style="color: black;">Climate Dynamics</a> </i> &nbsp;
Here, we explored in depth the relationship among the deterministic prediction skill, the probabilistic prediction skill and the potential predictability. This was achieved by theoretical analyses and, in particular, by an analysis of long-term ensemble ENSO hindcast over 161 years from 1856 to 2016. First, a nonlinear monotonic relationship between the deterministic prediction skill and the probabilistic prediction skill, derived by theoretical analysis, was examined and validated using the
more &raquo; ... emble hindcast. Further, the co-variability between the potential predictability and the deterministic prediction skill was explored in both perfect model assumption and actual model scenario. On these bases, we investigated the relationship between the potential predictability and probabilistic prediction skill from both the practice of ENSO forecast and theoretical perspective. The results of the study indicate that there are nonlinear monotonic relationships among these three kinds of measures. The potential predictability is considered to be a good indicator for the actual prediction skill in terms of both the deterministic measures and the probabilistic framework. The relationships identified here exhibit considerable significant practical sense to conduct predictability researches, which provide an inexpensive and moderate approach for inquiring prediction uncertainties without the requirement of costly ensemble experiments.
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