Warmists are finally getting hot and bothered (pun intended) about the lack of warming in the last 15 years. Their improbable explanation is that other things are happening which "mask" an underlying warming trend. That is however an unfalsifiable explanation unless they can show what the pesky "other" influences are -- and they have made some attempts in that direction. The latest is excerpted below.
Warmists and skeptics alike know that eddying ocean currents in the Pacific have a big influence on temperatures and precipitation in Pacific-bordering countries and elsewhere. The two major eddies are customarily dubbed el nino and la nina. So Warmists want to point to them as having a slowly increasing cooling influence to offset an underlying slow warming over the last 15 years. And the article below tries to put bones on that unlikely theory.
The first problem is that ocean currents don't behave the way Warmists want. There is nothing steady about them. It is true that several La Nina (cooling) events have happened in recent times but they alternated with "neutral" and warming (el nino) events. Fear not, however! With statistical averages we can maybe smooth that out. And so to the article below.
And he makes a sort of a case if you ignore his starting point: How he detects la ninas, el ninos and other influences. He detects such events, quite conventionally, as periods of temperature that diverged from an average. So he removed those periods from his data and, Hey Presto! He gets the desired cooling effect.
So if you remove temperature periods that you don't like, you get a temperature pattern that you do like. That proves nothing. For him to have shown extraneous influences on temperature, he would have to have measures of those influences themselves, not just the temperature changes that are attributed to them. To use a rough analogy, he is standing in a bucket and trying to lift himself by the handle. He needs to get out of the bucket.
He himself admits "the need to find the cause of the actual global temperature changes" but does not do so. He just takes out one large component of "the actual global temperature changes" -- JR.
About the Lack of Warming.
It's common knowledge among those who follow such things that global temperatures have not gone up very much in the past several years. This has caused many to believe that the recent lack of warming contradicts what climate models say should happen in response to the increasing Tyndall gases. This, in turn, has provoked the counterargument that the Earth is still warming, just on a longer time scale, or that the recent period is too short to yield statistically significant results.
These counterarguments are not compelling. Fundamentally, any change in global temperature, even if it's just from one year to another, must have a cause. Saying that we need to look at longer time scales denies the need to find the cause of the actual global temperature changes (or lack thereof) at shorter time scales.
Such causes have been sought, and a few papers have proposed various combinations of cloud cover, volcanic aerosols, the El Ni¤o/Southern Oscillation (ENSO), deep ocean heat uptake, and so forth. A recent paper I like by Foster and Rahmsdorf (discussed here and here) takes a statistical approach to attempt to eliminate the effect of the other known forcing mechanisms, and what's left over is a fairly steady warming. Others have noted, more casually, that 2011 was the warmest La Ni¤a year on record.
I decided to take a simple approach at looking at the effect of ENSO. Using GISTemp Land/Ocean Index values and Ni¤o 3.4 values, I computed 12-month running averages of Ni¤o 3.4 and compared them to the average GISTemp values at lags of 0, 3, and 6 months. Foster and Rahmsdorf used a diferent ENSO index and found optimal lags between 2 and 5 months. So one would guess that a 3-month lag would fit the data best in my case, and indeed it did.
The normal threshold for El Ni¤o or La Ni¤a, as applied by the Climate Prediction Center, is for five consecutive months of at least 0.5 C above or below normal in a key region of the tropical Pacific. For working with annual data, I decided to call an annual average above 0.5 C an El Ni¤o and an annual average below -0.5 C a La Ni¤a. Then I plotted it up, color-coding each year for whether it was El Ni¤o, La Ni¤a, or neither (neutral).