  The 2014-2015 "Monster"/"Super" El Ni\~no failed to be predicted one year
earlier due to the growing importance of a new type of El Ni\~no, El Ni\~no
Modoki, which reportedly has much lower forecast skill with the classical
models. In this study, we show that, so far as of today, this new El Ni\~no
actually can be mostly predicted at a lead time of more than 10 years. This is
achieved through tracing the predictability source with an information
flow-based causality analysis, which is rigorously established from first
principles in the past decade. We show that the information flowing from the
solar activity 45 years ago to the sea surface temperature results in a causal
structure resembling the El Ni\~no Modoki mode. Based on this, a
multidimensional system is constructed out of the sunspot number series with
time delays of 22-50 years. The first 25 principal components are then taken as
the predictors to fulfill the prediction, which through information flow-based
causal deep learning reproduces rather accurately the events 12 years in
advance.
