Rick T. here. Over on my Twitter feed someone opined/asked about the recent spell of wet weather in Fairbanks-land and that it was more than we've had in recent years. So this got me to thinking again about how we might quantify "dampness" using climate data. I'm thinking of "dampness" in an Alaskan content, so not in terms of humidity or dew points but rather in terms of frequent rainy weather.
I've looked at this a couple of times before, but especially in 2016, which by almost any reckoning was a very wet summer in Fairbanks. In that work I combined the monthly total precipitation with the number of days with measurable precipitation to come up with a simple cumulative index that looks like this:
This produces values that seem intuitively in the ballpark: 2016 had the third highest May-August value, while 2004 and 2013 have low index values. However, this kind of index, while fine for looking back at the past, is less useful in near real-time since it relies monthly data and is really designed to look at compare complete seasons. People don't tend to experience weather at a monthly scale with a "hard reset" at the first of each month. Perhaps "frequent wet weather" would be better assessed using daily data. Which brings me back to the Twitter comment: by August 22ⁿᵈ, for this person at least, the warm, dry weather of late July was clearly no longer on their "environmental radar". So below is an effort at a dampness index with a shorter time horizon.
Here I've used the same combination (total precipitation times days with measurable precipitation) but applied this over a running 15-day window, so that each day gets an index value. So, to illustrate, on June 30, the index is calculated as the total precipitation from June 16-30ᵗʰ times the number of days with measurable precipitation in the same 15 day period. For July 1ˢᵗ, the window is June 17 to July 01. Do that for the whole of the warm season. For the last few years, the daily plot of this index looks like this (through Aug 25, 2018):
I particularly like this presentation, as the timing of "frequent wet weather" through the summer stands out clearly and make year-to-year comparison comparatively easy.
Of course, we can derived multi-month summary statistics from the daily index. Here's a plot of the average daily May-August index value:
This graphic does show some differences with the monthly-derived plot (Figure 1, above). For instance, 1967 now ranks as the second "dampiest" summer, and 1930 drops down a bit. Both of these seem like improvements. Even before the flooding rains of mid-August, 1967 had been a rainy summer, and 1930 had a lot of rain but much of that was concentrated in short bursts, e.g. 1.80" on July 2ⁿᵈ was from one thunderstorm: most of that rain fell in under an hour: the other 30 days in July had a total of 0.82"of rain. On the other hand, 1949 was a crappy summer no matter how you slice it. And in case you're wondering, with less than a week to go in August, the average index value for May-August 2018 is a comparatively low 3.7, though that will creep up a little with rain likely the next few days.
Perhaps a future improvement of this kind of index would be to incorporate some temperature measure, which might improve resolving between days with convective showers and those day-long steady rains.
It would be interesting to try using the hourly precip data to distinguish between wet-convective and wet-stratiform summers, or just to refine the "dampness index".ReplyDelete