Posts tagged ‘Climate’

IFTTT and Zapier

The other day you may have seen some test posts here on trying to cross-post between blogs.  It turns out there are surprisingly few wordpress apps for this, and those that exist are not being maintained.  I have a ManageWP account where I can simultaneously post to multiple accounts with the same post, but that was not exactly what I was looking for.  So I thought of my IFTTT account, which I had not played around with for a while.

I am not really an expert on this space, but I have used a site / program called "If This Then That" (IFTTT.com) for several years.  What it does is set up simple rules to fire off certain actions based on triggers.  For example, I cannot stand iphoto and the absolute mess of duplicates that icloud and iphoto make, so I now have an IFTTT rule that every time my iphone takes a picture, it automatically puts it in a folder on my Google Drive account.  I have IFTTT rules based on everything from my Nest thermostat at home to highlighting items in my feed reader.

IFTTT is really easy to use, but part of that is that there are limited options.  One limitation is that for each object - eg Twitter account or WordPress Account - you can only have one version.  In other words, if I have 3 WordPress accounts, IFTTT can only recognize one so, obviously, IFTTT is not going to be able to trigger based on a post at one blog and then do something on another blog.  Which is exactly what I wanted to do.  Whenever I make a climate post at Coyote Blog, I wanted to cross-post it at Climate Skeptic.

So I tried a similar site called Zapier.  Zapier allows me to do exactly what I wanted with WordPress accounts, and for each trigger and action it seems to give me, from my limited poking around, a lot more choices than IFTTT.  For example, a lot more different WordPress events can act as a trigger.  So I am now using it to cross-post, and we will see how it works.

Overall, IFTTT is a bit more mature, it has more choices of integrations, and probably most important has both iphone and android apps that give it a lot of integration options with your phone.  The limitation to one instance of each sort of trigger or action is a limitation they have been promising to fix for years, but still have not addressed.   Zapier is more complicated to use, but for the triggers and actions it has, gives a lot more options.  Unfortunately, it does not have much, if any, iphone or android integration which I think is a huge limitation for this type of functionality.

Both are worth checking out.  They are free (up to a point) and you can create a rule without programming in less than five minutes on either, so you can see if it is something you find useful.

Again, I am not an expert on this space and if there is a third, better choice, let me know in the comments.

 

Thank God For Scientists: "Unexpected Link Between Solar Activity and Climate Change"

Without scientists, we would never be apprised of the fact that the behavior of the sun affects how warm or cold it is on Earth (emphasis added)

For the first time, a research team has been able to reconstruct the solar activity at the end of the last ice age, around 20 000–10 000 years ago, by analysing trace elements in ice cores in Greenland and cave formations from China. During the last glacial maximum, Sweden was covered in a thick ice sheet that stretched all the way down to northern Germany and sea levels were more than 100 metres lower than they are today, because the water was frozen in the extensive ice caps. The new study shows that the sun’s variation influences the climate in a similar way regardless of whether the climate is extreme, as during the Ice Age, or as it is today.

“The study shows an unexpected link between solar activity and climate change. It shows both that changes in solar activity are nothing new and that solar activity influences the climate, especially on a regional level. Understanding these processes helps us to better forecast the climate in certain regions”, said Raimund Muscheler, Lecturer in Quaternary Geology at Lund University and co-author of the study.

My snarky tone is a bit unfair here.  While the sun seems an obvious candidate as a major climate driver, changes in its actual energy hitting the Earth have always appeared small compared to what would be needed to explain observed temperature changes.  This team hypothesizes that the changes in the sun's output have effects on atmospheric circulation that have a larger than expected impact on temperatures.  Henrik Svensmark explains it a different way, hypothesizing that cloud formation is heavily influenced by cosmic rays, and higher solar activity tends to shield the Earth from cosmic rays, thus reducing cloud formation and increasing temperatures.

Skeptics find this sudden realization that the sun affects climate to be kind of funny, since they have argued for years that higher temperatures in the late 20th century have coincided with a very active sun, probably more active than it has been in hundreds of years.   Climate alarmists have denied any influence to the sun.  Sun deniers!  This absolutist stance may seem odd, given that most skeptics (despite what is said of us) actually accept some amount of warming from CO2, but here are these folks who wrap themselves in the mantle of science that deny any effect from the sun?  The problem that warmists have is that higher climate sensitivities, on the order of 3 degrees C per doubling of CO2, greatly over-predict past warming (as I demonstrate in my videos, see around the 59 minute mark).  If anything else whatsoever other than CO2 caused one iota of the warming over the last 50 years, then this over-prediction just gets worse.  In fact, warmists have to assume crazy high levels of aerosol cooling -- that go beyond what most of the science supports -- to make their forecasts work looking backwards.

Scott Sumner Explains a Lot of Climate Alarmism, Without Discussing Climate

Scott Sumner is actually discussing discrimination, and how discrimination is often "proven" in social studies

The economy operates in very subtle ways, and often when I read academic studies of issues like discrimination, the techniques seem incredibly naive to me. They might put in all the attributes of male and female labor productivity they can think of, and then simply assume than any unexplained residual must be due to "discrimination." And they do this in cases where there is no obvious reason to assume discrimination. It would be like a scientist assuming that magicians created a white rabbit out of thin air, at the snap of their fingers, because they can't think of any other explanation of how it got into the black hat!

Most alarming climate forecasts are based on the period from 1978 to 1998.  During this 20 year period world temperatures rose about a half degree C.  People may say they are talking about temperature increases since 1950, but most if not all of those increases occurred from 1978-1998.  Temperatures were mostly flat or down before and since.

A key, if not the key, argument for CO2-driven catastrophic warming that is based on actual historic data (rather than on theory or models) is that temperatures rose in this 20 year period farther and faster than would be possible by any natural causes, and thus must have been driven by man-made CO2.  Essentially what scientists said was, "we have considered every possible natural cause of warming that we can think of, and these are not enough to cause this warming, so the warming must be unnatural."  I was struck just how similar this process was to what Mr. Sumner describes.  Most skeptics, by the way, agree that some of this warming may have been driven by manmade CO2 but at the same time argue that there were many potential natural effects (e.g. ocean cycles) that were not considered in this original analysis.

Reconciling Seemingly Contradictory Climate Claims

At Real Science, Steven Goddard claims this is the coolest summer on record in the US.

The NOAA reports that both May and June were the hottest on record.

It used to be the the media would reconcile such claims and one might learn something interesting from that reconciliation, but now all we have are mostly-crappy fact checks with Pinocchio counts.  Both these claims have truth on their side, though the NOAA report is more comprehensively correct.  Still, we can learn something by putting these analyses in context and by reconciling them.

The NOAA temperature data for the globe does indeed show May and June as the hottest on record.  However, one should note a couple of things

  • The two monthly records do not change the trend over the last 10-15 years, which has basically been flat.  We are hitting records because we are sitting on a plateau that is higher than the rest of the last century (at least in the NOAA data).  It only takes small positive excursions to reach all-time highs
  • There are a number of different temperature data bases that measure the temperature in different ways (e.g. satellite vs. ground stations) and then adjust those raw readings using different methodologies.  While the NOAA data base is showing all time highs, other data bases, such as satellite-based ones, are not.
  • The NOAA database has been criticized for manual adjustments to temperatures in the past which increase the warming trend.  Without these adjustments, temperatures during certain parts of the 1930's (think: Dust Bowl) would be higher than today.  This was discussed here in more depth.  As is usual when looking at such things, some of these adjustments are absolutely appropriate and some can be questioned.  However, blaming the whole of the warming signal on such adjustments is just wrong -- satellite data bases which have no similar adjustment issues have shown warming, at least between 1979 and 1999.

The Time article linked above illustrated the story of these record months with a video partially on wildfires.  This is a great example of how temperatures are indeed rising but media stories about knock-on effects, such as hurricanes and fires, can be full of it.  2014 has actually been a low fire year so far in the US.

So the world is undeniably on the warm side of average (I won't way warmer than normal because what is "normal"?)  So how does Goddard get this as the coolest summer on record for the US?

Well, the first answer, and it is an important one to remember, is that US temperatures do not have to follow global temperatures, at least not tightly.  While the world warmed 0.5-0.7 degrees C from 1979-1999, the US temperatures moved much less.  Other times, the US has warmed or cooled more than the world has.  The US is well under 5% of the world's surface area.  It is certainly possible to have isolated effects in such an area.  Remember the same holds true the other way -- heat waves in one part of the world don't necessarily mean the world is warming.

But we can also learn something that is seldom discussed in the media by looking at Goddard's chart:

click to enlarge

First, I will say that I am skeptical of any chart that uses "all USHCN" stations because the number of stations and their locations change so much.  At some level this is an apples to oranges comparison -- I would be much more comfortable to see a chart that looks at only USHCN stations with, say, at least 80 years of continuous data.  In other words, this chart may be an artifact of the mess that is the USHCN database.

However, it is possible that this is correct even with a better data set and against a backdrop of warming temperatures.  Why?  Because this is a metric of high temperatures.  It looks at the number of times a data station reads a high temperature over 90F.  At some level this is a clever chart, because it takes advantage of a misconception most people, including most people in the media have -- that global warming plays out in higher daytime high temperatures.

But in fact this does not appear to be the case.  Most of the warming we have seen over the last 50 years has manifested itself as higher nighttime lows and higher winter temperatures.  Both of these raise the average, but neither will change Goddard's metric of days above 90F.  So it is perfectly possible Goddard's chart is right even if the US is seeing a warming trend over the same period.  Which is why we have not seen any more local all-time daily high temperature records set recently than in past decades.  But we have seen a lot of new records for high low temperature, if that term makes sense.  Also, this explains why the ratio of daily high records to daily low records has risen -- not necessarily because there are a lot of new high records, but because we are setting fewer low records.  We can argue about daytime temperatures but nighttime temperatures are certainly warmer.

This chart shows an example with low and high temperatures over time at Amherst, MA  (chosen at random because I was speaking there).  Note that recently, most warming has been at night, rather than in daily highs.

Computer Modeling as "Evidence"

The BBC has decided not to every talk to climate skeptics again, in part based on the "evidence" of computer modelling

Climate change skeptics are being banned from BBC News, according to a new report, for fear of misinforming people and to create more of a "balance" when discussing man-made climate change.

The latest casualty is Nigel Lawson, former London chancellor and climate change skeptic, who has just recently been barred from appearing on BBC. Lord Lawson, who has written about climate change, said the corporation is silencing the debate on global warming since he discussed the topic on its Radio 4 Today program in February.

This skeptic accuses "Stalinist" BBC of succumbing to pressure from those with renewable energy interests, like the Green Party, in an editorial for the Daily Mail.

He appeared on February 13 debating with scientist Sir Brian Hoskins, chairman of the Grantham Institute for Climate Change at Imperial College, London, to discuss recent flooding that supposedly was linked to man-made climate change.

Despite the fact that the two intellectuals had a "thoroughly civilized discussion," BBC was "overwhelmed by a well-organized deluge of complaints" following the program. Naysayers harped on the fact that Lawson was not a scientist and said he had no business voicing his opinion on the subject.

...

Among the objections, including one from Green Party politician Chit Chong, were that Lawson's views were not supported by evidence from computer modeling.

I see this all the time.  A lot of things astound me in the climate debate, but perhaps the most astounding has been to be accused of being "anti-science" by people who have such a poor grasp of the scientific process.

Computer models and their output are not evidence of anything.  Computer models are extremely useful when we have hypotheses about complex, multi-variable systems.  It may not be immediately obvious how to test these hypotheses, so computer models can take these hypothesized formulas and generate predicted values of measurable variables that can then be used to compare to actual physical observations.

This is no different (except in speed and scale) from a person in the 18th century sitting down with Newton's gravitational equations and grinding out five years of predicted positions for Venus (in fact, the original meaning of the word "computer" was a human being who ground out numbers in just his way).  That person and his calculations are the exact equivalent of today's computer models.  We wouldn't say that those lists of predictions for Venus were "evidence" that Newton was correct.  We would use these predictions and compare them to actual measurements of Venus's position over the next five years.  If they matched, we would consider that match to be the real evidence that Newton may be correct.

So it is not the existence of the models or their output that are evidence that catastrophic man-made global warming theory is correct.  It would be evidence that the output of these predictive models actually match what plays out in reality.  Which is why skeptics think the fact that the divergence between climate model temperature forecasts and actual temperatures is important, but we will leave that topic for other days.

The other problem with models

The other problem with computer models, besides the fact that they are not and cannot constitute evidence in and of themselves, is that their results are often sensitive to small changes in tuning or setting of variables, and that these decisions about tuning are often totally opaque to outsiders.

I did computer modelling for years, though of markets and economics rather than climate.  But the techniques are substantially the same.  And the pitfalls.

Confession time.  In my very early days as a consultant, I did something I am not proud of.  I was responsible for a complex market model based on a lot of market research and customer service data.  Less than a day before the big presentation, and with all the charts and conclusions made, I found a mistake that skewed the results.  In later years I would have the moral courage and confidence to cry foul and halt the process, but at the time I ended up tweaking a few key variables to make the model continue to spit out results consistent with our conclusion.  It is embarrassing enough I have trouble writing this for public consumption 25 years later.

But it was so easy.  A few tweaks to assumptions and I could get the answer I wanted.  And no one would ever know.  Someone could stare at the model for an hour and not recognize the tuning.

Robert Caprara has similar thoughts in the WSJ (probably behind a paywall)  Hat tip to a reader

The computer model was huge—it analyzed every river, sewer treatment plant and drinking-water intake (the places in rivers where municipalities draw their water) in the country. I'll spare you the details, but the model showed huge gains from the program as water quality improved dramatically. By the late 1980s, however, any gains from upgrading sewer treatments would be offset by the additional pollution load coming from people who moved from on-site septic tanks to public sewers, which dump the waste into rivers. Basically the model said we had hit the point of diminishing returns.

When I presented the results to the EPA official in charge, he said that I should go back and "sharpen my pencil." I did. I reviewed assumptions, tweaked coefficients and recalibrated data. But when I reran everything the numbers didn't change much. At our next meeting he told me to run the numbers again.

After three iterations I finally blurted out, "What number are you looking for?" He didn't miss a beat: He told me that he needed to show $2 billion of benefits to get the program renewed. I finally turned enough knobs to get the answer he wanted, and everyone was happy...

I realized that my work for the EPA wasn't that of a scientist, at least in the popular imagination of what a scientist does. It was more like that of a lawyer. My job, as a modeler, was to build the best case for my client's position. The opposition will build its best case for the counter argument and ultimately the truth should prevail.

If opponents don't like what I did with the coefficients, then they should challenge them. And during my decade as an environmental consultant, I was often hired to do just that to someone else's model. But there is no denying that anyone who makes a living building computer models likely does so for the cause of advocacy, not the search for truth.

The Real Money in the Climate Debate

I have yet to meet a skeptic who reports getting any money from mysterious climate skeptics.  A few years ago Greenpeace had a press release that was picked up everywhere about how Exxon was spending big money on climate denialism, with numbers that turned out to be in the tens of thousands of dollars a year.

The big money has always been in climate alarmism.  Climate skeptics are outspent a thousand to one.  Here is just one example

It sounds like the makings of a political-action thriller. The National Geospatial Intelligence Agency (NGA) has awarded Arizona State University a five-year, $20 million agreement to research the effects of climate change and its propensity to cause civil and political unrest.

The agreement is known as the Foresight Initiative. The goal is to understand how climate-caused disruptions and the depletion of natural resources including water, land and energy will impact political instability.

The plan is to create visually appealing computer models and simulations using large quantities of real-time data to guide policymakers in their decisions.

To understand the impacts of climate change, ASU is using the latest advances in cloud computing and storage technologies, natural user interfaces and machine learning to create real-time computer models and simulations, said Nadya Bliss, principal investigator for the Foresight Initiative and assistant vice president with ASU's Office of Knowledge and Development.

I can tell you the answer to this study already.  How do I know?  If they say the security risks are minimal, there will be zero follow-up funding.  If they say the security risks are huge, it will almost demand more and larger follow-up studies.  What is your guess of the results, especially since the results will all be based on opaque computer models whose results will be extremely sensitive to small changes in certain inputs?

Postscript:  I can just imagine a practical joke where the researchers give university officials a preview of results.  They say that the dangers are minimal.  It would be hilarious to see the disappointment in the eyes of all the University administrators.  Never in history would such a positive result be received with so much depression.  And then the researchers would say "Just kidding, of course it will be a catastrophe, it will be much worse than predicted, the badness will be accelerating, etc."

Another Plea to Global Warming Alarmists on the Phrase "Climate Denier"

Stop calling me and other skeptics "climate deniers".  No one denies that there is a climate.  It is a stupid phrase.

I am willing, even at the risk of the obvious parallel that is being drawn to the Holocaust deniers, to accept the "denier" label, but it has to be attached to a proposition I actually deny, or that can even be denied.

As help in doing so, here are a few reminders (these would also apply to many mainstream skeptics -- I am not an outlier)

  • I don't deny that climate changes over time -- who could?  So I am not a climate change denier
  • I don't deny that the Earth has warmed over the last century (something like 0.7C).  So I am not a global warming denier
  • I don't deny that man's CO2 has some incremental effect on warming, and perhaps climate change (in fact, man effects climate with many more of his activities other than just CO2 -- land use, with cities on the one hand and irrigated agriculture on the other, has measurable effects on the climate).  So I am not a man-made climate change or man-made global warming denier.

What I deny is the catastrophe -- the proposition that man-made global warming** will cause catastrophic climate changes whose adverse affects will outweigh both the benefits of warming as well as the costs of mitigation.  I believe that warming forecasts have been substantially exaggerated (in part due to positive feedback assumptions) and that tales of current climate change trends are greatly exaggerated and based more on noting individual outlier events and not through real data on trends (see hurricanes, for example).

Though it loses some of this nuance, I would probably accept "man-made climate catastrophe denier" as a title.

** Postscript -- as a reminder, there is absolutely no science that CO2 can change the climate except through the intermediate step of warming.   If you believe it is possible for CO2 to change the climate without there being warming (in the air, in the oceans, somewhere), then you have no right to call anyone else anti-science and you should go review your subject before you continue to embarrass yourself and your allies.

Trend That Is Not A Trend: Changes in Data Definition or Measurement Technology

This chart illustrates a data analysis mistake that is absolutely endemic to many of the most famous climate charts.  Marc Morano screencapped this from a new EPA web site  (update:  Actually originally from Pat Michaels at Cato)

The figure below is a portion of a screen capture from the “Heat-Related Deaths” section of the EPA’s new “Climate Change Indicators” website. It is labeled “Deaths Classified as ‘Heat-Related’ in the United States, 1979–2010.”

click to enlarge

The key is in the footnote, which says

Between 1998 and 1999, the World Health Organization revised the international codes used to classify causes of death. As a result, data from earlier than 1999 cannot easily be compared with data from 1999 and later.

So, in other words, this chart is totally bogus.  There is an essentially flat trend up to the 1998 switch in data definition and an essentially flat trend after 1998.  There is a step-change upwards in 1998 due to the data redefinition.  This makes this chart useless unless your purpose is to fool generally ignorant people that there is an upwards trend, and then it is very useful.  It is not, however, good science.

Other examples of this step change in a metric occurring at a data redefinition or change in measurement technique can be found in

  • The hockey stick  (and here)
  • Ocean heat content  (sorry, can't find the link but the shift from using thermometers in pails dipped from ships to the ARGO floats caused a one time step change in ocean heat content measurements)
  • Tornadoes
  • Hurricanes

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.

Wherein I Almost Agree With Thomas Friedman on a Climate Issue

Thomas Friedman outlines what he would do first to attack climate change

Well, the first thing we would do is actually slash income taxes and corporate taxes and replace them with a carbon tax so we actually encourage people to stop doing what we don't want, which is emitting carbon, and start doing what we do want, which is hiring more workers and getting corporations to invest more in America.

Friedman is a bit disingenuous here, as he proposes this in a way that implies that deniers (and probably evil Republicans and libertarians) oppose this common sense approach.  Some may, but I would observe that no one on the alarmist side or the Left side of the aisle is actually proposing a carbon tax that 1:1 reduces other taxes.  The only person I know who has proposed this is Republican Jeff Flake, who proposed a carbon tax that would 1:1 reduce payroll taxes.

As I said back then, I am not a big fan of taxes and think that the alarm for global warming is overblown, but I could easily get behind such a plan.  Payroll taxes are consumption taxes on labor.  I can't think of anything much more detrimental to employment and economic health.  So Flake's proposed shift from a consumption tax on labor to a consumption tax on carbon-based energy sources is something I could get behind.  I probably would do the same for Friedman's idea of shifting taxes from income to carbon.  But again, no one is proposing that for real in Congress.  The only plan that came close to a vote was a cap and trade system where the incremental payments would go into essentially a crony slush fund, not reduce other taxes.

Of course, since this is Friedman, he can't get away without saying the government should invest more in infrastructure

 the federal government would borrow money at almost 0 percent and invest it in infrastructure to make our cities not only more resilient, but more efficient.

In TARP and the stimulus and various other clean energy bills, the government borrowed almost a trillion dollars at 0% interest.  How much good infrastructure got done?  About zero.  Most of it just went to feed government bureaucrats and planning studies or ended up as crony payments to well-protected entities (Solyndra, anyone?).  The issues with government infrastructure investments, which Friedman has never addressed despite zillions of articles on infrastructure, are not the borrowing rate but

  • The incentive and information problems the government has in making investments of any sort.
  • The vast environmental, licensing, and NIMBY factors that make it virtually impossible to do infrastructure projects any more, at least in any reasonable time frame.

Climate Alarmism In One Statement: "Limited Evidence, High Agreement"

From James Delingpole:

The draft version of the report's Summary For Policymakers made the startling admission that the economic damage caused by "climate change" would be between 0.2 and 2 percent of global GDP - significantly less than the doomsday predictions made in the 2006 Stern report (which estimated the damage at between 5 and 20 percent of global GDP).

But this reduced estimate did not suit the alarmist narrative of several of the government delegations at the recent IPCC talks in Yokahama, Japan. Among them was the British one, comprising several members of the deep green Department of Energy and Climate Change (DECC), which insisted on doctoring this section of the Summary For Policymakers in order to exaggerate the potential for more serious economic damage.

"Losses are more likely than not to be greater, rather than smaller, than this range (limited evidence, high agreement)"

There was no evidence whatsoever in the body of the report to justify this statement.

I find it fascinating that there can be "high agreement" to a statement for which there is limited or no evidence.  Fortunately these are all self-proclaimed defenders of science or I might think this was purely a political statement.

Note that the most recent IPCC reports and new published studies on climate sensitivity tend to say that 1) warming in the next century will be 1-2C, not the much higher numbers previously forecast; 2)  That warming will not be particularly expensive to manage and mitigate and 3) we are increasingly less sure that warming is causing all sorts of negative knock-on effects like more hurricanes.  In other words, opinion is shifting to where science-based skeptics have been all along (since 2007 in my case).  No surprise or shame here.  What is shameful though is that as evidence points more and more to the lukewarmer skeptic position, we are still called evil heretical deniers that should be locked in jail.  Like telling Galileo, "you were right about that whole heliocentric thing but we still think you are evil for suggesting it."

Ideological Turing Tests, Climate, and Minimum Wage

Yesterday I was interviewed for a student radio show, I believe from the USC Annenberg school.  I have no quarrel with the staff I worked with, they were all friendly and intelligent.

What depressed me though, as I went through my usual bullet points describing the "lukewarmer" position that is increasingly common among skeptics, was that most of what I said seemed to be new to the interviewer.   It was amazing to see that someone presumably well-exposed to the climate debate would actually not have any real idea what one of the two positions really entailed (see here and here for what I outlined).  This gets me back to the notion I wrote about a while ago about people relying on their allies to tell them everything they need to know about their opponent's position, without ever actually listening to the opponents.

This topic comes up in the blogosphere from time to time, often framed as being able to pass an ideological Touring test.  Can, say, a Republican write a defense of the minimum wage that a reader of the Daily Kos would accept, or will it just come out sounding like a straw man?  I feel like I could do it pretty well, despite being a libertarian opposed to the minimum wage.  For example:

There is a substantial power imbalance between minimum wage workers and employers, such that employers are able to pay such workers far less than their labor is worth, and far less than they would be willing to pay if they had to.  The minimum wage corrects this power imbalance and prevents employers from unfairly exploiting this power imbalance.  It forces employers to pay employees something closer to a living wage, though at $7.25 an hour the minimum wage is still too low to be humane and needs to be raised.  When companies pay below a living wage, they not only exploit workers but taxpayers as well, since they are accepting a form of corporate welfare when taxpayers (through food stamps and Medicare and the like) help sustain their underpaid workers.

Opponents of the minimum wage will sometimes argue that higher minimum wages reduce employment.  However, since in most cases employers of low-skilled workers are paying workers less than they are willing and able to pay, raising the minimum wage has little effect on employment.  Studies of the fast food industry by Card and Walker demonstrated that raising the minimum wage had little effect on employment levels.  And any loss of employment from higher minimum wages would be more than offset by the Keynesian stimulative effect to the economy as a whole of increasing wages among lower income workers, who tend to consume nearly 100% of incremental income.

Despite the fact that I disagree with this position, I feel I understand it pretty well -- far better, I would say, than most global warming alarmists or even media members bother to try to understand the skeptic position.  (I must say that looking back over my argument, it strikes me as more cogent and persuasive than most of the stuff on Daily Kos, so to pass a true Turing test I might have to make it a bit more incoherent).

Back in my consulting days at McKinsey & Company, we had this tradition (in hindsight I would call it almost an affectation) of giving interviewees business cases** to discuss and solve in our job interviews.  If I were running a news outlet, I would require interviewees to take an ideological Touring test - take an issue and give me the argument for each side in the way that each side would present it.

This, by the way, is probably why Paul Krugman is my least favorite person in journalism.  He knows very well that his opponents have a fairly thoughtful and (to them) well intention-ed argument but pretends to his readers that no such position exists.  Which is ironic because in some sense Krugman started the dialog on ideological Turing tests, arguing that liberals can do it easily for conservative positions but conservatives fail at it for liberal positions.

 

** Want an example?  Many of these cases were just strategic choices in some of our consulting work.  But some were more generic, meant to test how one might break down and attack a problem.  One I used from time to time was, "what is the size of the window glass market in Mexico?"  Most applicants were ready for this kind of BS, but I do treasure the look on a few faces of students who had not been warned about such questions.  The point of course was to think it through out loud, ie "well there are different sectors, like buildings and autos.  Each would have both a new and replacement market. Within buildings there is residential and commercial.  Taking one of these, the new residential market would be driven by new home construction times some factor representing windows per house.  One might need to understand if Mexican houses used pre-manufactured windows or constructed them from components on the building site."  etc. etc.

A Proposal For Better Management of the (Soon to Be) California Climate Slush Fund

California is about to implement a new climate tax via a cap and trade system, where revenues from the tax are supposed to be dedicated to carbon reduction projects.  Forget for a moment all my concerns with climate dangers being overhyped, or the practical problems (read cronyism) inherent in a cap-and-trade system vs. a straight carbon tax.  There is one improvement California can and should make to this system.

Anyone who can remember the history of the tobacco settlement will know that the theory of that settlement was that the funds were needed to pay for additional medical expenses driven by smoking.  Well, about zero of these funds actually went to health care or even to smoking reduction programs  (smoking reduction programs turn out to be fiscally irresponsible for states, since they lead to reduced tax revenues from tobacco taxes).  These funds just became a general slush fund for legislators.   Some states (New York among them, if I remember correctly), spent the entire 20 year windfall in one year to close budget gaps.

If California is serious that these new taxes on energy should go to carbon reduction programs, then these programs need to be scored by a neutral body as to their cost per ton of CO2 reduction.  I may think the program misguided, but given that it exists, it might as well be run in a scientific manner, right?  I would really prefer that there be a legislated hurdle rate, e.g. all programs must have a cost per ton reduction of $45 of less -- or whatever.  But even publishing scores in a transparent way would help.

This would, for example, likely highlight what a terrible investment this would be in reducing CO2.

 

The Thought Experiment That First Made Me A Climate Skeptic

Please check out my Forbes post today.  Here is how it begins:

Last night, the accumulated years of being called an evil-Koch-funded-anti-science-tobacco-lawyer-Holocaust-Denier finally caught up with me.  I wrote something like 3000 words of indignation about climate alarmists corrupting the very definition of science by declaring their work “settled”, answering difficult scientific questions with the equivalent of voting, and telling everyone the way to be pro-science is to listen to self-designated authorities and shut up.  I looked at the draft this morning and while I agreed with everything written, I decided not to publish a whiny ode of victimization.  There are plenty of those floating around already.

And then, out of the blue, I received an email from a stranger.  Last year I had helped to sponsor a proposal to legalize gay marriage in Arizona.  I was doing some outreach to folks in the libertarian community who had no problem with gay marriage (after all, they are libertarians) but were concerned that marriage licensing should not be a government activity at all and were therefore lukewarm about our proposition.  I suppose I could have called them bigots, or homophobic, or in the pay of Big Hetero — but instead I gathered and presented data on the number of different laws, such as inheritance, where rights and privileges were tied to marriage.  I argued that the government was already deeply involved with marriage, and fairness therefore demanded that more people have access to these rights and privileges.  Just yesterday I had a reader send me an email that said, simply, “you changed my mind on gay marriage.”  It made my day.  If only climate discussion could work this way.

So I decided the right way to drive change in the climate debate is not to rant about it but instead to continue to model what I consider good behavior — fact-based discussion and a recognition that reasonable people can disagree without that disagreement implying one or the other has evil intentions or is mean-spirited.

This analysis was originally published about 8 years ago, and there is no longer an online version.  So for fun, I thought I would reproduce my original thought experiment on climate models that led me to the climate dark side.

I have been flattered over time that folks like Matt Ridley have picked up on bits and pieces of this analysis.  See it all here.

Congratulations to Nature Magazine for Catching up to Bloggers

The journal Nature has finally caught up to the fact that ocean cycles may influence global surface temperature trends.  Climate alarmists refused to acknowledge this when temperatures were rising and the cycles were in their warm phase, but now are grasping at these cycles for an explanation of the 15+ year hiatus in warming as a way to avoid abandoning high climate sensitivity assumptions  (ie the sensitivity of global temperatures to CO2 concentrations, which IMO are exaggerated by implausible assumptions of positive feedback).

Here is the chart from Nature:

click to enlarge

 

I cannot find my first use of this chart, but here is a version I was using over 5 years ago.  I know I was using it long before that

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It will be interesting to see if they find a way to blame cycles for cooling in the last 10-15 years but not for the warming in the 80's and 90's.

Next step -- alarmists have the same epiphany about the sun, and blame non-warming on a low solar cycle without simultaneously giving previous high solar cycles any credit for warming.  For Nature's benefit, here is another chart they might use (from the same 2008 blog post).  The number 50 below is selected arbitrarily, but does a good job of highlighting solar activity in the second half of the 20th century vs. the first half.

click to enlarge

 

Ugh -- Krugman Bringing Climate-Style Argument by Marginalization to Economics

Climate alarmists have mastered the trick of portraying opposition to their theories as not just being wrong, but being anti-science.  For years many scientists who have not looked into climate science at all have reflexively signed petitions supporting the alarmists, in the belief they were supporting science against anti-science. (By the way, time and again when these physicists and Earth scientists have actually later looked at the quality of climate science work, they have been astounded at the really poor quality garbage they were implicitly supporting -- I know, I am in that camp myself).

It looks like Paul Krugman, the most politicized economist ever(TM), is trying to bring the same style argumentation to economics.  If you don't agree with him, you are not just wrong, you are anti-science.  He is Galileo, and you are the ill-informed mystic.

So let me summarize: we had a scientific revolution in economics, one that dramatically increased our comprehension of the world and also gave us crucial practical guidance about what to do in the face of depressions. The broad outlines of the theory devised during that revolution have held up extremely well in the face of experience, while those rejecting the theory because it doesn’t correspond to their notion of common sense have been wrong every step of the way.

Yet a large part of both the political establishment and the economics establishment rejects the whole thing out of hand, because they don’t like the conclusions.

Galileo wept.

There are two other similarities between economics and climate that support this kind of blind (but unwarranted) certainty:

  1. There are few if any opportunities for controlled experiments to truly test cause and effect
  2. There are near infinite numbers of moving parts and variables, such that one can almost always find an analysis that shows your favored variable correlated to something good or bad -- as long, of course, as you are willing to pretend that a zillion other variables weren't changing at the same time which could have equally likely been part of the causation.

Explaining the Flaw in Kevin Drum's (and Apparently Science Magazine's) Climate Chart

I won't repeat the analysis, you need to see it here.  Here is the chart in question:

la-sci-climate-warming

My argument is that the smoothing and relatively low sampling intervals in the early data very likely mask variations similar to what we are seeing in the last 100 years -- ie they greatly exaggerate the smoothness of history and create a false impression that recent temperature changes are unprecedented (also the grey range bands are self-evidently garbage, but that is another story).

Drum's response was that "it was published in Science."  Apparently, this sort of appeal to authority is what passes for data analysis in the climate world.

Well, maybe I did not explain the issue well.  So I found a political analysis that may help Kevin Drum see the problem.  This is from an actual blog post by Dave Manuel (this seems to be such a common data analysis fallacy that I found an example on the first page of my first Google search).  It is an analysis of average GDP growth by President.  I don't know this Dave Manuel guy and can't comment on the data quality, but let's assume the data is correct for a moment.  Quoting from his post:

Here are the individual performances of each president since 1948:

1948-1952 (Harry S. Truman, Democrat), +4.82%

1953-1960 (Dwight D. Eisenhower, Republican), +3%

1961-1964 (John F. Kennedy / Lyndon B. Johnson, Democrat), +4.65%

1965-1968 (Lyndon B. Johnson, Democrat), +5.05%

1969-1972 (Richard Nixon, Republican), +3%

1973-1976 (Richard Nixon / Gerald Ford, Republican), +2.6%

1977-1980 (Jimmy Carter, Democrat), +3.25%

1981-1988 (Ronald Reagan, Republican), 3.4%

1989-1992 (George H. W. Bush, Republican), 2.17%

1993-2000 (Bill Clinton, Democrat), 3.88%

2001-2008 (George W. Bush, Republican), +2.09%

2009 (Barack Obama, Democrat), -2.6%

Let's put this data in a chart:

click to enlarge

 

Look, a hockey stick , right?   Obama is the worst, right?

In fact there is a big problem with this analysis, even if the data is correct.  And I bet Kevin Drum can get it right away, even though it is the exact same problem as on his climate chart.

The problem is that a single year of Obama's is compared to four or eight years for other presidents.  These earlier presidents may well have had individual down economic years - in fact, Reagan's first year was almost certainly a down year for GDP.  But that kind of volatility is masked because the data points for the other presidents represent much more time, effectively smoothing variability.

Now, this chart has a difference in sampling frequency of 4-8x between the previous presidents and Obama.  This made a huge difference here, but it is a trivial difference compared to the 1 million times greater sampling frequency of modern temperature data vs. historical data obtained by looking at proxies (such as ice cores and tree rings).  And, unlike this chart, the method of sampling is very different across time with temperature - thermometers today are far more reliable and linear measurement devices than trees or ice.  In our GDP example, this problem roughly equates to trying to compare the GDP under Obama (with all the economic data we collate today) to, say, the economic growth rate under Henry the VIII.  Or perhaps under Ramses II.   If I showed that GDP growth in a single month under Obama was less than the average over 66 years under Ramses II, and tried to draw some conclusion from that, I think someone might challenge my analysis.  Unless of course it appears in Science, then it must be beyond question.

If You Don't Like People Saying That Climate Science is Absurd, Stop Publishing Absurd Un-Scientific Charts

Kevin Drum can't believe the folks at the National Review are still calling global warming science a "myth".  As is usual for global warming supporters, he wraps himself in the mantle of science while implying that those who don't toe the line on the declared consensus are somehow anti-science.

Readers will know that as a lukewarmer, I have as little patience with outright CO2 warming deniers as I do with those declaring a catastrophe  (for my views read this and this).  But if you are going to simply be thunderstruck that some people don't trust climate scientists, then don't post a chart that is a great example of why people think that a lot of global warming science is garbage.  Here is Drum's chart:

la-sci-climate-warming

 

The problem is that his chart is a splice of multiple data series with very different time resolutions.  The series up to about 1850 has data points taken at best every 50 years and likely at 100-200 year or more intervals.  It is smoothed so that temperature shifts less than 200 years or so in length won't show up and are smoothed out.

In contrast, the data series after 1850 has data sampled every day or even hour.  It has a sampling interval 6 orders of magnitude (over a million times) more frequent.  It by definition is smoothed on a time scale substantially shorter than the rest of the data.

In addition, these two data sets use entirely different measurement techniques.  The modern data comes from thermometers and satellites, measurement approaches that we understand fairly well.  The earlier data comes from some sort of proxy analysis (ice cores, tree rings, sediments, etc.)  While we know these proxies generally change with temperature, there are still a lot of questions as to their accuracy and, perhaps more importantly for us here, whether they vary linearly or have any sort of attenuation of the peaks.  For example, recent warming has not shown up as strongly in tree ring proxies, raising the question of whether they may also be missing rapid temperature changes or peaks in earlier data for which we don't have thermometers to back-check them (this is an oft-discussed problem called proxy divergence).

The problem is not the accuracy of the data for the last 100 years, though we could quibble this it is perhaps exaggerated by a few tenths of a degree.  The problem is with the historic data and using it as a valid comparison to recent data.  Even a 100 year increase of about a degree would, in the data series before 1850, be at most a single data point.  If the sampling is on 200 year intervals, there is a 50-50 chance a 100 year spike would be missed entirely in the historic data.  And even if it were in the data as a single data point, it would be smoothed out at this data scale.

Do you really think that there was never a 100-year period in those last 10,000 years where the temperatures varied by more than 0.1F, as implied by this chart?  This chart has a data set that is smoothed to signals no finer than about 200 years and compares it to recent data with no such filter.  It is like comparing the annualized GDP increase for the last quarter to the average annual GDP increase for the entire 19th century.   It is easy to demonstrate how silly this is.  If you cut the chart off at say 1950, before much anthropogenic effect will have occurred, it would still look like this, with an anomalous spike at the right (just a bit shorter).  If you believe this analysis, you have to believe that there is an unprecedented spike at the end even without anthropogenic effects.

There are several other issues with this chart that makes it laughably bad for someone to use in the context of arguing that he is the true defender of scientific integrity

  • The grey range band is if anything an even bigger scientific absurdity than the main data line.  Are they really trying to argue that there were no years, or decades, or even whole centuries that never deviated from a 0.7F baseline anomaly by more than 0.3F for the entire 4000 year period from 7500 years ago to 3500 years ago?  I will bet just about anything that the error bars on this analysis should be more than 0.3F, much less the range of variability around the mean.  Any natural scientist worth his or her salt would laugh this out of the room.  It is absurd.  But here it is presented as climate science in the exact same article that the author expresses dismay that anyone would distrust climate science.
  • A more minor point, but one that disguises the sampling frequency problem a bit, is that the last dark brown shaded area on the right that is labelled "the last 100 years" is actually at least 300 years wide.  Based on the scale, a hundred years should be about one dot on the x axis.  This means that 100 years is less than the width of the red line, and the last 60 years or the real anthropogenic period is less than half the width of the red line.  We are talking about a temperature change whose duration is half the width of the red line, which hopefully gives you some idea why I say the data sampling and smoothing processes would disguise any past periods similar to the most recent one.

Update:  Kevin Drum posted a defense of this chart on Twitter.  Here it is:  "It was published in Science."   Well folks, there is climate debate in a nutshell.   An 1000-word dissection of what appears to be wrong with a particular analysis retorted by a five-word appeal to authority.

Update #2:  I have explained the issue with a parallel flawed analysis from politics where Drum is more likely to see the flaws.

Climate Humor from the New York Times

Though this is hilarious, I am pretty sure Thomas Lovejoy is serious when he writes

But the complete candor and transparency of the [IPCC] panel’s findings should be recognized and applauded. This is science sticking with the facts. It does not mean that global warming is not a problem; indeed it is a really big problem.

This is a howler.  Two quick examples.  First, every past IPCC report summary has had estimates for climate sensitivity, ie the amount of temperature increase they expect for a doubling of CO2 levels.  Coming into this IPCC report, emerging evidence from recent studies has been that the climate sensitivity is much lower than previous estimates.  So what did the "transparent" IPCC do?  They, for the first time, just left out the estimate rather than be forced to publish one that was lower than the last report.

The second example relates to the fact that temperatures have been flat over the last 15-17 years and as a result, every single climate model has overestimated temperatures.  By a lot. In a draft version, the IPCC created this chart (the red dots were added by Steve McIntyre after the chart was made as the new data came in).

figure-1-4-models-vs-observations-annotated (1)

 

This chart was consistent with a number of peer-reviewed studies that assessed the performance of climate models.  Well, this chart was a little too much "candor" for the transparent IPCC, so they replaced it with this chart in the final draft:

figure-1-4-final-models-vs-observations

 

What a mess!  They have made the area we want to look at between 1990 and the present really tiny, and then they have somehow shifted the forecast envelopes down on several of the past reports so that suddenly current measurements are within the bands.   They also hide the bottom of the fourth assessment band (orange FAR) so you can't see that observations are out of the envelope of the last report.  No one so far can figure out how they got the numbers in this chart, and it does not match any peer-reviewed work.  Steve McIntyre is trying to figure it out.

OK, so now that we are on the subject of climate models, here is the second hilarious thing Lovejoy said:

Does the leveling-off of temperatures mean that the climate models used to track them are seriously flawed? Not really. It is important to remember that models are used so that we can understand where the Earth system is headed.

Does this make any sense at all?  Try it in a different context:  The Fed said the fact that their economic models failed to predict what actually happened over the last 15 years is irrelevant because the models are only used to see where the economy is headed.

The consistent theme of this report is declining certainty and declining chances of catastrophe, two facts that the IPCC works as hard as possible to obfuscate but which still come out pretty clearly as one reads the report.

The Key Disconnect in the Climate Debate

Much of the climate debate turns on a single logical fallacy.  This fallacy is clearly on display in some comments by UK Prime Minister David Cameron:

It’s worth looking at what this report this week says – that [there is a] 95 per cent certainty that human activity is altering the climate. I think I said this almost 10 years ago: if someone came to you and said there is a 95 per cent chance that your house might burn down, even if you are in the 5 per cent that doesn’t agree with it, you still take out the insurance, just in case.”

"Human activity altering climate" is not the same thing as an environmental catastrophe (or one's house burning down).  The statement that he is 95% certain that human activity is altering climate is one that most skeptics (including myself) are 100% sure is true.  There is evidence that human activity has been altering the climate since the dawn of agriculture.  Man's changing land uses have been demonstrated to alter climate, and certainly man's incremental CO2 is raising temperatures somewhat.

The key question is -- by how much?  This is a totally different question, and, as I have written before, is largely dependent on climate theories unrelated to greenhouse gas theory, specifically that the Earth's climate system is dominated by large positive feedbacks.  (Roy Spenser has a good summary of the issue here.)

The catastrophe is so uncertain that for the first time, the IPCC left estimates of climate sensitivity to CO2 out of its recently released summary for policy makers, mainly because it was not ready to (or did not want to) deal with a number of recent studies yielding sensitivity numbers well below catastrophic levels.  Further, the IPCC nearly entirely punted on the key question of how it can reconcile its past high sensitivity/ high feedback based temperature forecasts with past relative modest measured warming rates, including a 15+ year pause in warming which none of its models predicted.

The overall tone of the new IPCC report is one of declining certainty -- they are less confident of their sensitivity numbers and less confident of their models which have all been a total failure over the last 15 years. They have also backed off of other statements, for example saying they are far less confident that warming is leading to severe weather.

Most skeptics are sure mankind is affecting climate somewhat, but believe that this effect will not be catastrophic.  On both fronts, the IPCC is slowly catching up to us.

Hearing What You Want to Hear from the Climate Report

After over 15 years of no warming, which the IPCC still cannot explain, and with climate sensitivity numbers dropping so much in recent studies that the IPCC left climate sensitivity estimates out of their summary report rather than address the drop, the Weather Channel is running this headline on their site:

weatherch

 

The IPCC does claim more confidence that warming over the past 60 years is partly or mostly due to man (I have not yet seen the exact wording they landed on), from 90% to 95%.  But this is odd given that the warming all came from 1978 to 1998 (see for yourself in temperature data about halfway through this post).  Temperatures are flat or cooling for the other 40 years of the period.  The IPCC cannot explain these 40 years of no warming in the context of high temperature sensitivities to CO2.  And, they can't explain why they can be 95% confident of what drove temperatures in the 20 year period of 1978-1998 but simultaneously have no clue what drove temperatures in the other years.

At some point I will read the thing and comment further.

 

Update On My Climate Model (Spoiler: It's Doing a Lot Better than the Pros)

In this post, I want to discuss my just-for-fun model of global temperatures I developed 6 years ago.  But more importantly, I am going to come back to some lessons about natural climate drivers and historic temperature trends that should have great relevance to the upcoming IPCC report.

In 2007, for my first climate video, I created an admittedly simplistic model of global temperatures.  I did not try to model any details within the climate system.  Instead, I attempted to tease out a very few (it ended up being three) trends from the historic temperature data and simply projected them forward.  Each of these trends has a logic grounded in physical processes, but the values I used were pure regression rather than any bottom up calculation from physics.  Here they are:

  • A long term trend of 0.4C warming per century.  This can be thought of as a sort of base natural rate for the post-little ice age era.
  • An additional linear trend beginning in 1945 of an additional 0.35C per century.  This represents combined effects of CO2 (whose effects should largely appear after mid-century) and higher solar activity in the second half of the 20th century  (Note that this is way, way below the mainstream estimates in the IPCC of the historic contribution of CO2, as it implies the maximum historic contribution is less than 0.2C)
  • A cyclic trend that looks like a sine wave centered on zero (such that over time it adds nothing to the long term trend) with a period of about 63 years.  Think of this as representing the net effect of cyclical climate processes such as the PDO and AMO.

Put in graphical form, here are these three drivers (the left axis in both is degrees C, re-centered to match the centering of Hadley CRUT4 temperature anomalies).  The two linear trends (click on any image in this post to enlarge it)

click to enlarge

 

And the cyclic trend:

click to enlarge

These two charts are simply added and then can be compared to actual temperatures.  This is the way the comparison looked in 2007 when I first created this "model"

click to enlarge

The historic match is no great feat.  The model was admittedly tuned to match history (yes, unlike the pros who all tune their models, I admit it).  The linear trends as well as the sine wave period and amplitude were adjusted to make the fit work.

However, it is instructive to note that a simple model of a linear trend plus sine wave matches history so well, particularly since it assumes such a small contribution from CO2 (yet matches history well) and since in prior IPCC reports, the IPCC and most modelers simply refused to include cyclic functions like AMO and PDO in their models.  You will note that the Coyote Climate Model was projecting a flattening, even a decrease in temperatures when everyone else in the climate community was projecting that blue temperature line heading up and to the right.

So, how are we doing?  I never really meant the model to have predictive power.  I built it just to make some points about the potential role of cyclic functions in the historic temperature trend.  But based on updated Hadley CRUT4 data through July, 2013, this is how we are doing:

click to enlarge

 

Not too shabby.  Anyway, I do not insist on the model, but I do want to come back to a few points about temperature modeling and cyclic climate processes in light of the new IPCC report coming soon.

The decisions of climate modelers do not always make sense or seem consistent.  The best framework I can find for explaining their choices is to hypothesize that every choice is driven by trying to make the forecast future temperature increase as large as possible.  In past IPCC reports, modelers refused to acknowledge any natural or cyclic effects on global temperatures, and actually made statements that a) variations in the sun's output were too small to change temperatures in any measurable way and b) it was not necessary to include cyclic processes like the PDO and AMO in their climate models.

I do not know why these decisions were made, but they had the effect of maximizing the amount of past warming that could be attributed to CO2, thus maximizing potential climate sensitivity numbers and future warming forecasts.  The reason for this was that the IPCC based nearly the totality of their conclusions about past warming rates and CO2 from the period 1978-1998.  They may talk about "since 1950", but you can see from the chart above that all of the warming since 1950 actually happened in that narrow 20 year window.  During that 20-year window, though, solar activity, the PDO and the AMO were also all peaking or in their warm phases.  So if the IPCC were to acknowledge that any of those natural effects had any influence on temperatures, they would have to reduce the amount of warming scored to CO2 between 1978 and 1998 and thus their large future warming forecasts would have become even harder to justify.

Now, fast forward to today.  Global temperatures have been flat since about 1998, or for about 15 years or so.  This is difficult to explain for the IPCC, since about none of the 60+ models in their ensembles predicted this kind of pause in warming.  In fact, temperature trends over the last 15 years have fallen below the 95% confidence level of nearly every climate model used by the IPCC.  So scientists must either change their models (eek!) or else they must explain why they still are correct but missed the last 15 years of flat temperatures.

The IPCC is likely to take the latter course.  Rumor has it that they will attribute the warming pause to... ocean cycles and the sun (those things the IPCC said last time were irrelevant).  As you can see from my model above, this is entirely plausible.  My model has an underlying 0.75C per century trend after 1945, but even with this trend actual temperatures hit a 30-year flat spot after the year 2000.   So it is entirely possible for an underlying trend to be temporarily masked by cyclical factors.

BUT.  And this is a big but.  You can also see from my model that you can't assume that these factors caused the current "pause" in warming without also acknowledging that they contributed to the warming from 1978-1998, something the IPCC seems loath to do.  I do not know how the ICC is going to deal with this.  I hate to think the worst of people, but I do not think it is beyond them to say that these factors offset greenhouse warming for the last 15 years but did not increase warming the 20 years before that.

We shall see.  To be continued....

Update:  Seriously, on a relative basis, I am kicking ass

click to enlarge

About That "Thousand Year" Storm in Colorado....

Last week I expressed my doubts that the storm in Colorado was really, as described breathlessly at the Weather Underground, a once in a thousand year storm (the logic of the article, and many others, being that one in a thousand is the same as "zero" and thus the storm could not have occurred naturally and therefore Global Warming).

Turns out it is not even close.  From the Colorado Climate Center at Colorado State University:

How much rain fell on Colorado this week? And where? Colorado residents can help the weather experts at Colorado State University answer these questions.

In response to the incredible recent rains and flooding in parts of the state, the Colorado Climate Center will be mapping rainfall totals and graphing hourly intensities for the entire state for the period beginning Sunday, Sept. 8 (as storms first developed over southern Colorado) through the end of the storm later this weekend

"As is typical of Colorado storms, some parts of the state were hard hit and others were untouched. Still, this storm is ranking in the top ten extreme flooding events since Colorado statehood," said Nolan Doesken, State Climatologist at CSU. "It isn't yet as extreme or widespread as the June 1965 floods or as dramatic as the 1935 floods but it ranks right up there among some of the worst.”

Among the worst, according to Climate Center data, occurred in May 1904, October 1911, June 1921, May 1935, September 1938, May 1955, June 1965, May 1969, October 1970, July 1976, July 1981, and, of course, the Spring Creek Flood of July 1997 that ravaged Fort Collins and the CSU campus.

."Every flood event in Colorado has its own unique characteristics," said Doesken. "But the topography of the Colorado Front Range makes this area particularly vulnerable when the necessary meteorological conditions come together as they did this week."

So it is perhaps a one in fifteen year flood.  Note that (by the math in my previous article linked above) a one in fifteen year flood covering an area half the size of Colorado should occur on overage over 60+ times a year around the world.  Our intuition about tail of the distribution event frequency is not very good, which is just another reason they make a poor proxy for drawing conclusions about trends in the mean of some phenomenon.

 

The Magic Theory

Catastrophic Anthropogenic Climate Change is the magic theory -- every bit of evidence proves it.   More rain, less rain, harder rain, drought, floods, more tornadoes, fewer tornadoes, hotter weather, colder weather, more hurricanes, fewer hurricane -- they all prove the theory.  It is the theory that it is impossible not to confirm.  Example

It will take climate scientists many months to complete studies into whether manmade global warming made the Boulder flood more likely to occur, but the amount by which this event has exceeded past events suggests that manmade warming may have played some role by making the event worse than it otherwise would have been...

An increase in the frequency and intensity of extreme precipitation events is expected to take place even though annual precipitation amounts are projected to decrease in the Southwest. Colorado sits right along the dividing line between the areas where average annual precipitation is expected to increase, and the region that is expected to become drier as a result of climate change.

That may translate into more frequent, sharp swings between drought and flood, as has recently been the case. Last year, after all, was Colorado's second-driest on record, with the warmest spring and warmest summer on record, leading to an intense drought that is only just easing.

Generally one wants to point to a data trend to prove a theory, but look at that last paragraph.  Global warming is truly unique because it can be verified by there being no trend.

I hate to make this point for the five millionth time, but here goes:  It is virtually impossible (and takes far more data, by orders of magnitude, than we posses) to prove a shift in the mean of any phenomenon simply by highlighting occasional tail-of-the-distribution events.  The best way to prove a mean shift is to actually, you know, track the mean.  The problem is that the trend data lines for all these phenomenon -- droughts, wet weather, tornadoes, hurricanes -- show no trend, so the only tool supporters of the theory have at their disposal is to scream "global warming" as loud as they can every time there is a tail-of-the-distribution event.

Let's do some math:  They claim this flood was a one in one thousand year event.  That strikes me as false precision, because we have only been observing this phenomenon with any reliability for 100 years, but I will accept their figure for now.  Let's say this was indeed a one in 1000 year flood that it occurred over, say, half the area of Colorado (again a generous assumption, it was actually less that that).

Colorado is about 270,000 KM^2 so half would be 135,000 KM^2.  The land area of the world (we really should include oceans for this but we will give these folks every break) is about 150,000,000 km^2.  That means that half of Colorado is a bit less than 1/1000 of the world land area.

Our intuition tells us that a 1 in 1000 year storm is so rare that to have one means something weird or unusual or even unnatural must be going on.  But by the math above, since this storm covered 1/1000 of the land surface of the Earth, we should see one such storm on average every year somewhere in the world.  This is not some "biblical" unprecedented event - it is freaking expected, somewhere, every year.  Over the same area we should also see a 1 in 1000 year drought, a 1 in 1000 year temperature high, and a one in one thousand year temperature low -- every single damn year.  Good news if you are a newspaper and feed off of this stuff, but bad news for anyone trying to draw conclusions about the shifts in means and averages from such events.

Climate Theory vs. Climate Data

This is a pretty amazing statement Justin Gillis in the New York Times.

This month, the world will get a new report from a United Nations panel about the science of climate change. Scientists will soon meet in Stockholm to put the finishing touches on the document, and behind the scenes, two big fights are brewing....

In the second case, we have mainstream science that says if the amount of carbon dioxide in the atmosphere doubles, which is well on its way to happening, the long-term rise in the temperature of the earth will be at least 3.6 degrees Fahrenheit, but more likely above 5 degrees. We have outlier science that says the rise could come in well below 3 degrees.

In this case, the drafters of the report lowered the bottom end in a range of temperatures for how much the earth could warm, treating the outlier science as credible.

The interesting part is that "mainstream science" is based mainly on theory and climate models that over the last 20 years have not made accurate predictions (overestimating warming significantly).  "Outlier science" is in a lot of cases based on actual observations of temperatures along with other variables like infrared radiation returning to space.  The author, through his nomenclature, is essentially disparaging observational data that is petulantly refusing to match up to model predictions.  But of course skeptics are anti-science.