## Thursday, February 5, 2015

### Upper Level Pattern Length

Last year I began looking at how to quantify the length of temperature patterns at the surface. It seems like when the temperature goes above normal, it stays that way for a while. Conversely, cold patterns tend to hang around a while too. Unfortunately, what happens at the surface does not alway reflect what is going on synoptically. Just this week, Anchorage has stayed quite cold even though an above normal airmass moved overhead. At the surface, the airmass change went nearly unnoticed. Therefore, I decided to use 850 mb temperature changes as a proxy measure of airmass changes. There are certainly other metrics as well. We could looks at 500 mb or 300 mb winds or height changes. For now, those will be left for another day.

There has been discussion in the scientific literature over the last few years about changes in jet stream "blockiness." A blocky pattern should be reflected in longer duration of upper air patterns. Once again, because the data is handy for me, I will look at the Anchorage International Airport balloon soundings (1948-2014). As we noted last week, the temperature at 850 mb in Anchorage has been steadily rising. Therefore, we need to compute daily normal temperatures and standard deviations based on 30-year climate periods. Figure 1 shows the normal 850 mb temperature for Anchorage.

Figure 1. Normal temperature at 850 mb for Anchorage International Airport. Four 30-year periods are shown.

How do we decide if an above normal or below normal pattern is present? For this study, I arbitrarily decided that if 6 out of 7 days are in the upper tercile of temperatures (>= 0.43 standard deviations above the mean), all 7 of those days are part of a "warm spell." Conversely, if 6 out of 7 days are in the bottom tercile of temperatures (<= -0.43 standard deviations below the mean), all 7 of those days are part of a "cold spell." This is a "gut feeling" definition but will suffice for now. Figure 2 shows a sample of my Excel calculation output. Note the columns titled "Above" and "Below." They denote warm spells and cold spells in December 2013. In that month, there was a 9-day warm spell and an 8-day cold spell based on the aforementioned criteria.

Figure 2. Excel screenshot showing calculation of warm and cold spells.

Now for the fun part. Has there been a change in the length of these patterns since 1948? The answer is yes and no. Let's look at a chart first. Figure 3 shows the length of all warm and cold spells since 1948. Since the minimum length of a warm or cold spell is 7 days, that is the minimum value on the y-axis. It is difficult to discern patterns from all the dots; therefore, I added trend lines to the data.

Figure 3. Length of time for all warm ad cold spells at 850 mb in Anchorage. Each dot represents the end point of a period.

At the beginning of the balloon record, warm spells and cold spells each lasted 12 days on average. Over the next 67 years, the length of cold spells dropped slightly to 11.5 days and the length of warm spells increased by 25% to an average length of 15 days. This is a quite dramatic increase in my opinion. If we look at it on a decade basis, we see that the patterns are quite consistent on that time scale. Figure 4 shows the average length of warm and cold spells by decade.

Figure 4. Length of time for all warm ad cold spells at 850 mb in Anchorage grouped by decade.

Not only are temperatures rising at the 850 mb level in Anchorage, but the average length of a warm period is increasing. What is most interesting is that the increase in the length of warm spells is not coming at the expense of the cold spells.

1. Nice work, Brian. By using the contemporary climate normals, it seems you've eliminated the possibility that the change simply reflects the mean warming. So I wonder if we can say that overall climate anomalies are more persistent now.

Did you look at the seasonal breakdown of changes? Would be interesting to know if summer or winter is more affected.

1. I have not looked at seasonal differences but will soon. One difficulty in a seasonal assessment is where to put the data point. If there is a 30-day warm period that spans from August 16 to September 15, does the point go in August or September – or both?

2. Your using Excel for the calculations. Now that is impressive!

A graph similar to Figure 1 has been produced before. And I've commented before that the difference line looks like the seasonal temperatures have all been drifting back a few weeks causing a small phase change. It's almost like all of the seasons have been starting a little earlier.

It seems in Figure 3 that times of positive PDO have shorter warm spells. Or maybe I'm reading it wrong. Maybe less stability means more systems to push spells away.

I think the seasonal analysis that Richard wondered about would help answer all of these questions.

1. Yes, Excel is always my first option for analysis. If there are too many records or I need to do some exotic stuff, I write a Java program.

The graph in Figure 1 is the same one I used for the Upper Air Warmth post on January 11, 2015. No point in re-inventing the wheel. For both posts, I wanted to make sure readers knew that upper air departures from normal were computed against their appropriate 30-year climate normal period.

As for PDO, I'll run some sort of correlation scatter plot and add a new image as an addendum. Probably tomorrow sometime.