Can see that there’s a lot of variation in the patterns. Looking at the cycle of events from November of 1997 to June 1998 suggests that effects were stronger in the austral summer. That is typically the case \cite{Cr_tat_2010}, and also the season when ENSO activity in the Pacific tends to be strongest. Looking at the summer months you can squint, and suggest that there are some common themes, but even they are not fully consistent within the small sample.

The scale of the anomalies also varies. This is expected as rainfall amounts themselves vary between regions and seasons. One of the reasons for selecting the GPCP product for this example is that this group provides error estimates for its monthly estimates. While they state that the procedure for deriving these values is simplistic \cite{Huffman_2009}, these estimates are still very useful for suggesting which anomalies are beyond the margin of error for the calculated value. What does the figure above [\ref{fig:elnino_samples}] look like when we only consider anomalies that are strongly positive or negative enough to be beyond the estimated measurement error? This does filter out some noise in favor of the major events, although the images themselves are more complicated [\ref{fig:elnino_samples_masked}].