Posts tagged ‘Roger Pielke’

Wherein I Come Clean to Representative Grijalva

Here is the letter I wrote today (pdf) to Representative Grijalva confessing my climate funding biases.  The image is below.  I feel so much better.

grijalva-letter2

I wrote this in support particularly of Roger Pielke, who has educated a lot of people about climate and is not even really a climate skeptic and who has been pretty upset by this scrutiny.  Call it the "I am Spartacus" strategy.

My earlier post on funding and bias is here.

Climate Alarmists Coming Around to At Least One Skeptic Position

As early as 2009 (and many other more prominent skeptics were discussing it much earlier) I reported on why measuring ocean heat content was a potentially much better measure of greenhouse gas changes to the Earth rather than measuring surface air temperatures.  Roger Pielke, in particular, has been arguing this for as long as I can remember.

The simplest explanation for why this is true is that greenhouse gasses increase the energy added to the surface of the Earth, so that is what we would really like to measure, that extra energy.  But in fact the vast, vast majority of the heat retention capacity of the Earth's surface is in the oceans, not in the air.  Air temperatures may be more immediately sensitive to changes in heat flux, but they are also sensitive to a lot of other noise that tends to mask long-term signals.    The best analog I can think of is to imagine that you have two assets, a checking account and your investment portfolio.  Looking at surface air temperatures to measure long-term changes in surface heat content is a bit like trying to infer long-term changes in your net worth by looking only at your checking account, whose balance is very volatile, vs. looking at the changing size of your investment portfolio.

Apparently, the alarmists are coming around to this point

Has global warming come to a halt? For the last decade or so the average global surface temperature has been stabilising at around 0.5°C above the long-term average. Can we all relax and assume global warming isn't going to be so bad after all?

Unfortunately not. Instead we appear to be measuring the wrong thing. Doug McNeall and Matthew Palmer, both from the Met Office Hadley Centre in Exeter, have analysed climate simulations and shown that both ocean heat content and net radiation (at the top of the atmosphere) continue to rise, while surface temperature goes in fits and starts. "In my view net radiation is the most fundamental measure of global warming since it directly represents the accumulation of excess solar energy in the Earth system," says Palmer, whose findings are published in the journal Environmental Research Letters.

First, of course, we welcome past ocean heat content deniers to the club.  But second, those betting on ocean heat content to save their bacon and keep alarmism alive should consider why skeptics latched onto the metric with such passion.   In fact, ocean heat content may be rising more than surface air temperatures, but it has been rising MUCH less than would be predicted from high-sensitivity climate models.

The Missing Heat

It is possible for the theory that the climate has a high sensitivity to CO2 (ie that a doubling of CO2 concentrations will lead to global temperature increases of 2.5C or higher) to be correct while still having ten years of flat to declining surface temperatures.  That is because Earth's great surface heat reservoir is the oceans, not the atmosphere, and so the extra heat from the greenhouse effect could be going into the oceans rather than into near-surface air.

However, it is NOT possible, as least as we (and by "we" I mean everyone, skeptics and alarmists alike) understand the climate, for CO2 to be holding a lot of extra heat and it not show up either in surface temperatures or ocean heat content.  The greenhouse effect does not turn off -- its effects may be masked in the chaotic weather systems, perhaps for years, but if the climate sensitivity to CO2 is really as high as the IPCC says, there has to be new heat going somewhere.

That is why a number of folks, including Roger Pielke, have argued for years that the best way to monitor whether we are truly seeing an additional forcing or heat input to the climate is to look at ocean heat content.  Understand, changes in ocean heat content would not tell us where the heat is coming from (e.g. anthropogenic CO2 vs. solar activity).  But it is pretty much impossible for us to imagine a new heat input to the Earth's surface, like greenhouse gas forcing from anthropogenic CO2, without observing its effect in ocean heat content.

I will turn over the story to Jo Nova, who has a good post on the new tools we have to measure ocean heat content since 2003.  In short, though, we have seen no rise in measured ocean heat content since we started measuring with technology dedicated to the task.  This means, if those who believe the climate has a high sensitivity to CO2 are right, something like 50,000 quintillion joules of energy have gone missing since 2003.  This is the "missing heat", and though climate scientists sometimes discuss it in private, they almost never do so in public.  Ocean heat is the dinosaur bone fossil that the creationists simply don't want to acknowledge.

Read the whole thing.  It is very simple and well-written and written.

PS- note in the chart above, the y-axis is mis-labelled a bit, it is not absolute heat content but changes in heat content from some base period.  Scientists call this the "anomaly."  This is typical of many climate charts.

Using Computer Models To Launder Certainty

For a while, I have criticized the practice both in climate and economics of using computer models to increase our apparent certainty about natural phenomenon.   We take shaky assumptions and guesstimates of certain constants and natural variables and plug them into computer models that produce projections with triple-decimal precision.   We then treat the output with a reverence that does not match the quality of the inputs.

I have had trouble explaining this sort of knowledge laundering and finding precisely the right words to explain it.  But this week I have been presented with an excellent example from climate science, courtesy of Roger Pielke, Sr.  This is an excerpt from a recent study trying to figure out if a high climate sensitivity to CO2 can be reconciled with the lack of ocean warming over the last 10 years (bold added).

“Observations of the sea water temperature show that the upper ocean has not warmed since 2003. This is remarkable as it is expected the ocean would store that the lion’s share of the extra heat retained by the Earth due to the increased concentrations of greenhouse gases. The observation that the upper 700 meter of the world ocean have not warmed for the last eight years gives rise to two fundamental questions:

  1. What is the probability that the upper ocean does not warm for eight years as greenhouse gas concentrations continue to rise?
  2. As the heat has not been not stored in the upper ocean over the last eight years, where did it go instead?

These question cannot be answered using observations alone, as the available time series are too short and the data not accurate enough. We therefore used climate model output generated in the ESSENCE project, a collaboration of KNMI and Utrecht University that generated 17 simulations of the climate with the ECHAM5/MPI-OM model to sample the natural variability of the climate system. When compared to the available observations, the model describes the ocean temperature rise and variability well.”

Pielke goes on to deconstruct the study, but just compare the two bolded statements.  First, that there is not sufficiently extensive and accurate observational data to test a hypothesis.  BUT, then we will create a model, and this model is validated against this same observational data.  Then the model is used to draw all kinds of conclusions about the problem being studied.

This is the clearest, simplest example of certainty laundering I have ever seen.  If there is not sufficient data to draw conclusions about how a system operates, then how can there be enough data to validate a computer model which, in code, just embodies a series of hypotheses about how a system operates?

A model is no different than a hypothesis embodied in code.   If I have a hypothesis that the average width of neckties in this year's Armani collection drives stock market prices, creating a computer program that predicts stock market prices falling as ties get thinner does nothing to increase my certainty of this hypothesis  (though it may be enough to get me media attention).  The model is merely a software implementation of my original hypothesis.  In fact, the model likely has to embody even more unproven assumptions than my hypothesis, because in addition to assuming a causal relationship, it also has to be programmed with specific values for this correlation.

This is not just a climate problem.  The White House studies on the effects of the stimulus were absolutely identical.  They had a hypothesis that government deficit spending would increase total economic activity.  After they spent the money, how did they claim success?  Did they measure changes to economic activity through observational data?  No, they had a model that was programmed with the hypothesis that government spending increased job creation, ran the model, and pulled a number out that said, surprise, the stimulus created millions of jobs (despite falling employment).  And the press reported it like it was a real number.

Sheriff Arpaio Meets Al Gore

Not since the Reese's Peanut Butter Cups have there been two great populist tastes that go so great together.  In an amazing bit of fact-free scare mongering gauged to panic everyone across the political spectrum, Michael Oppenheimer (embarrassingly a professor at my alma mater) manages to combine demagoguing against Mexican immigration with climate alarmism

Climbing temperatures are expected to raise sea levels and increase droughts, floods, heat waves and wildfires.

Now, scientists are predicting another consequence of climate change: mass migration to the United States.

Between 1.4 million and 6.7 million Mexicans could migrate to the U.S. by 2080 as climate change reduces crop yields and agricultural production in Mexico, according to a study published online this week in the Proceedings of the National Academy of Sciences. The number could amount to 10% of the current population of Mexicans ages 15 to 65.

The proceedings of the NAS has become a joke of late.  Roger Pielke Jr responded:

To be blunt, the paper is guesswork piled on top of "what ifs" built on a foundation of tenuous assumptions. The authors seem to want to have things both ways -- they readily acknowledge the many and important limitations of their study, but then go on to assert that "it is nevertheless instructive to predict future migrant flows for Mexico using the estimates at hand to assess the possible magnitude of climate change"“related emigration." It can't be both -- if the paper has many important limitations, then this means that that it is not particularly instructive. With respect to predicting immigration in 2080 (!), admitting limitations is no serious flaw.

To use this paper as a prediction of anything would be a mistake. It is a tentative sensitivity study of the effects of one variable on another, where the relationship between the two is itself questionable but more importantly, dependent upon many other far more important factors. The authors admit this when they write, "It is important to note that our projections should be interpreted in a ceteris paribus manner, as many other factors besides climate could potentially influence migration from Mexico to the United States." but then right after they assert, "Our projections are informative,nevertheless, in quantifying the potential magnitude of impacts of climate change on out-migration." It is almost as if the paper is written to be misinterpreted

I thought this response was instructive

Philip Martin, an expert in agricultural economics at UC Davis, said that he hadn't read the study but that making estimates based solely on climate change was virtually impossible.

"It is just awfully hard to separate climate change from the many, many other factors that affect people's decisions whether to stay in agriculture or move," he said.

The same exact statement, by the way, could be made as to the relationship of climate change to the single variable manmade CO2 without reference to the myriad of other factors that affect the complex climate system.