A Closer Look At the HadCrut 60-Month Trends
Posted by The Diatribe Guy on August 1, 2008
I first presented the above chart in my July 2008 Update on Global Temperature – Additional HadCrut Analysis post. I’d like to take a little closer look at it and ponder the implications of looking at it from a purely technical chart analysis point of view.
It’s important to see the entire chart above, but let’s take a closer look at what has happened to the far right of the chart, during the current trend period. To get a better look at that, I started the chart at 1945 and added a couple lines for a visual:
Let me digress for a moment and discuss technical chart analysis. It is a concept used by many traders in the stock and commodities markets. I have utilized the concept myself in options markets. I won’t go into great detail, because for our purposes here a general overview will suffice.
There is a theory of perfectly efficient markets where traders believe that ALL available information is already considered in the evaluation of a stock’s price. Thousands of people every day are scouring the papers, watching the economy, looking at trends, watching company management, and so on and so forth. This creates a situation where all new information is almost immediately processed and a determination is made as to the impact of earnings, dividends, etc. A price is established, and other than the inherent discount given for risk/reward, nobody investing in a stock/commodity has an informational advantage. People who adhere to this idea believe the markets strictly follow a random walk on a general path upward according to the return given due to the risk/reward nature of the stock. The risk is usually considered based on stock volatility measures.
Then there are a group of traders who basically say “that’s all well and good, and it makes sense, but there are other factors that simply don’t figure into price.” Those factors are intangible ideas of collective market psyche, profit-taking, and other human factors that are not strictly valuation based. These traders take a look at historical charts and attempt to identify patterns in the charts that indicate a strong move in one direction or another. If the chart above were a stock, for example, the trader would consider the red line under the successive troughs a support level. In other words, when prices swing down, they tend to swing back up before crossing that red line. The technical trader would watch a falling price, and at the sight of a reversal just before it hit the line, he would assume that the pattern is holding and it’s a good time to buy on the upswing. Alternatively, if the trader sees a break through a support level, the inclination is to sell or go short, because it may indicate a strong move in the opposite direction now that the support has given way. There are many other patterns in the charts that traders look for, but that works for now. I’m not here to argue the merits of that approach, just to present it for understanding.
So, why am I discussing this? Because I think there’s an interesting parallel in the slope patterns. While the temperature doesn’t break out of patterns due to human psyche, it does seem to have certain breaks from the norm due to all factors combined, seen and unseen. So, while a certain pattern seems to hold for a while (increasing support points according to some line), there are times where that trend breaks down and something seems to change.
If we observe the initial, total chart, we see a very similar trend of increasing troughs in the early part of the 20th century. When there was a break through the support level of that time, the slope value kept falling, and falling, and falling. It hit the steepest negative slope since 1905, and has not fallen to that level since. At that point the trend seemed to start anew. The troughs came, but each successive major trough bottomed out at a slope slightly higher than the previous one. Similar to the period of the 1930s, the 1990s reached a point where negative slopes were relatively uncommon, short-lived, and not at all steep. The pattern of the last few years of slope measures compared to the late 1930s and early 1940s is pretty consistent.
Support seemed to be broken in about 1946, and the negative slope hit its trough value in 1948. The slope would not be positive again until 1952.
Now, I’m not saying the same thing will happen, but it is clear to see from the chart that our “support line” has been transgressed. This occurred in 2007 at some point (the actual placement of support is somewhat subjective). Kind of like market theory, where people think they know a lot, but other unknown factors enter the fray, I suggest that it is entirely possible that – despite what the models say – some congruence of factors, both known and unknown, have changed things. If the current period does follow the form of 60-70 years ago, we can expect a continued cooling trend – and a very significant one at that – until 2013. The peak of the rapidness in the cooling (measured my 60-month slopes) will be in 2009.
To compare against my predictive model based on monthly weights of slope changes going back 11 years, I extended out the timeline to see what it generated for future temperature anomalies and corresponding slopes. The model actually predicts a more severe downturn than the simple chart comparison suggests. The negative slope continues to get more and more negative until November of 2011. I did not extend the analysis to see when we would see actual warming, but it is safe to say that it would likely extend past 2013. The trough slope value would be -1.082, which makes it both steeper than the 1905 trough value, and it would appear this time around could be more drawn out than the 1940s cold spell. Consistent negative anomalies are predicted starting around mid-2010, and many of these negative anomalies reach double-digit levels, including some in the -20 range. Even though the trough is in 2011, there would be continued negative slopes after that period for a while, so some of the future anomalies could get even cooler. For the record, I hope my model is wrong…
Anyway, I thought it was an interesting exercise to go through. Who knows if there’s anything to the technical analysis argument, and who knows if my predictive model has any merit for the long term. It seems to do fairly well (with sparse data points so far) in the short term, but long-term predictions are a different story.
Closing the Post with an anecdote alert!
Another story in the “anecdotal evidence” category caught my eye today. It’s from the UN, in fact. It seems that there has been a major and near-catastrophic cold season in Peru. The normal cold season starts in June, but this year it came 3 months early and has put crops and livestock in peril. I can only believe that if this were a heat wave, we would be hearing all about it as evidence of “climate change.”
The El friaje phenomenon involves a combination of unseasonable low temperatures, frosts, snow and hail that damages crops and the high-altitude pastures on which alpacas graze, according to Marc Vandersmissen, FAO’s Emergency Coordinator in Peru.
This year, the cold arrived well ahead of the usual season – in March and April, instead of June – and many small-scale farmers have not been able to harvest their crops.
The early arrival of the cold weather has greatly affected alpaqueros – smallholders in high-altitude areas whose livelihoods depend completely on raising alpacas. Pastures have been covered in snow which has frozen over, making grazing impossible. Unable to find adequate food, the alpacas have become weak and susceptible to disease, Mr. Vandersmissen said.
The gravity of the situation has led the Peruvian Government to declare a state of emergency in 11 of the country’s 25 provinces.
I found another story on it, and it’s not just crops and animals in peril.
The authorities in Peru say severe cold weather has killed at least 59 people, most of them children, in the south-east of the country. The freezing cold has left more than 60,000 people without food and shelter.
Vice President Raul Diez Canseco said some remote communities, already living in extreme misery, needed urgent aid.
The cold snap has also killed one-fifth of the country’s herds of llamas and alpacas – the mainstay of the rural economy.
Please keep these poor people in your prayers. And if colder weather is truly ahead, people will realize how good we had it over the last few decades.