I have divided each year into five-day blocks (we often call one of these blocks a bin), and then taken the average number of recorded fatal landslides within that bin over the seven year period. So, bin number one is 1st to 5th January, the second is 6th to 10th, etc. I have then looked at the cycle through time by plotting a graph in which I have smoothed the data using a 25 day filter - this is a noisy dataset, so this is needed given the comparatively short window:

The minimum period coincides I think with the onset of winter in the northern hemisphere (which is a dry period for many of the most landslide prone areas) but is before the rainy season really gets going in SE Asia. By early January the rains in for example Indonesia are really under way, and the occurrence of landslides increases.
The standard deviation is a measure of variability between years. So, if for a specific bin the number of fatal landslides was always three then the standard deviation would be low. If however one year there were none, the next six, the next ten and the next two then the standard deviation would be much higher. It is interesting that as the average number of fatal landslides increases in the N. Hemisphere summer so does the standard deviation - this is to be expected. However, in the post-peak period the standard deviation remains high for a while before declining. I think that this probably reflects the influence of tropical cyclones in this period, which tend to landfall rather sporadically but then to cause many landslides over a small area. Over the seven year period many of the bins in this period have been affected by a tropical cyclone.
I hope to see you at the session!
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