This article was first posted at Watts Up With That on July 12, 2014
People in different places are wondering: What are temperatures doing in my area? Are they trending up, down or sideways? Of course, from official quarters, the answer is: The globe is warming, so it is safe to assume that your area is warming also.
But what if you don’t want to assume and don’t want to take someone else’s word for it. You can answer the question yourself if you take on board one simplifying concept:
“If you want to understand temperature change,
you should analyze the changes, not the temperatures.”
Analyzing temperature change is in fact much simpler and avoids data manipulations like anomalies, averaging, gridding, adjusting and homogenizing. Temperature Trend Analysis starts with recognizing that each micro-climate is distinct with its unique climate patterns. So you work on the raw, unadjusted station data produced, validated and submitted by local meteorologists. This is accessed in the HADCRUT3 dataset made public in July 2011. Of course, there are missing datapoints which cause much work for climatologists. Those are not a big deal for trend analysis.
The dataset includes 5000+ stations around the world, and only someone adept with statistical software running on a robust computer could deal with all of it. But the Met Office provides it in folders that cluster stations according to their WMO codes.
I am not the first one to think of this. Richard Wakefield did similar analyses in Ontario years ago, and Lubos Motl did trend analysis on the entire HADCRUT3 in July 2011. With this simplifying concept and a template, it is possible for anyone with modest spreadsheet skills and a notebook computer to answer how area temperatures are trending. I don’t claim this analysis is better than those done with multimillion dollar computers, but it does serve as a “sanity check” against exaggerated claims and hype.
The method involves creating for each station a spreadsheet that calculates a trend for each month for all of the years recorded. Then the monthly trends are averaged together for a lifetime trend for that station. To be comparable to others, the station trend is presented as degrees per 100 years. A summary sheet collects all the trends from all the sheets to provide trend analysis for the geographical area of interest.
I have built an Excel workbook to do this analysis, and as a proof of concept, I have loaded in temperature data for Kansas . Kansas is an interesting choice for several reasons:
1) It’s exactly in the middle of the US with little change in elevation;
2) Kansas has a manageable number of HCN stations:
3) It has been the subject lately of discussion about temperature processing effects;
4) Kansas legislators are concerned and looking for the facts; and
5) As a lad, my first awareness of extreme weather was the tornado in OZ, after which Dorothy famously said: “We’re not in Kansas anymore, Toto.”
For the Kansas example, we see that BEST shows on its climate page that the State has warmed 1.98 +/-0.14°C since 1960. That looks like temperatures will be another 2°C higher in the next 50 years, and we should be alarmed.
Well, the results from temperature trend analysis tell a different story.
From the summary page of the workbook:
|Area||State of Kansas, USA|
|History||1843 to 2011|
So in the last century the average Kansas station has warmed 0.70+/-0.45°C , with at least one site cooling over that time. The +/- 0.45 deviation shows that climate is different from site to site even when all are located on the same prairie.
And the variability over the seasons is also considerable:
Note that February and March are warming strongly, while September is sideways . That’s good news for farming, I think.
Temperature change depends on your location and time of the year. The rate of warming here is not extreme and if the next 100 years is something like the last 100, in Kansas there will likely be less than a degree C added.
When you look behind the summary page at BEST, it reports that the Kansas warming trend since 1910 is 0.75°C +/-0.08, close to what my analysis showed. So the alarming number at the top was not the accumulated rise in temperatures, it was the Rate for a century projected from 1960. The actual observed century rate is far less disturbing. And the variability across the state is considerable and is much more evident in the trend analysis. I had wanted to use raw data from BEST in this study, because some stations showed longer records there, but for comparable years, the numbers didn’t match with HADCRUT3.
Not only does this approach maintain the integrity of the historical record, it also facilitates what policy makers desperately need: climate outlooks based on observations for specific jurisdictions. Since the analysis is bottom-up, micro-climate trends can be compiled together for any desired scope: municipal, district, region, province, nation, continent.
This example analyzed monthly average temperatures at a set of stations. This study used HADCRUT3, but others are done with CRUTEM4 and GHCN. The same technique can be applied to temperature minimums and maximums, or to adjusted and unadjusted records. And since climate is more than temperatures, one could also study precipitation histories, or indeed any weather measure captured in a time series.
The trend analysis workbook is provided below. It was the first iteration and the workbook was refined and enhanced in subsequent studies, also posted at this blog.