Michael Mann, the American Lysenko

[The DC Superior Court reasons] Steyn’s evaluation of Mann’s scientific claims can be legally suppressed because Steyn dares to question the conclusions of established scientific institutions connected to the government. On this basis, the DC Superior Court arrives at the preposterous conclusion that it is a violation of Mann’s rights to “question his intellect and reasoning.” That’s an awfully nice prerogative to be granted by government: an exemption against any challenge to your reasoning.

All of this stems from Michael Mann’s defamation suit against Mark Steyn, the National Review, and the Competitive Enterprise Institute for publishing Rand Simberg’s characterization that Michael Mann “has molested and tortured data.” As we all know, for public figures, the burden of proof for libel is high in the US. You can read one perspective about the legal wrangling in this Newsweek column. I’d also recommend this post by Judith Curry, where she describes how Mann feels free to, well, I’ll just use her words:

I’ve written previously about Mann’s defaming me as a ‘serial climate misinformer‘ and ‘anti-science.’  In recent weeks he has gone after Anthony Watts,  Patrick Moore (founder of Greenpeace) and Bill Gates:

Michael E. Mann ‏@MichaelEMannJan 23  So Patrick Moore (aka “EcoSenseNow”) is no more than a garden variety troll w/ nothing serious to offer. Who knew! #JokersPosingAsThinkers
Michael E. Mann‏@MichaelEMannJan 22 @BillGates Gates made an indefensible blanket statement that obscures real challenges. To dismiss lacks class.

All of these insults are mud slinging without being accompanied by any substantive argument.  Mann’s defamation of me (a climate scientist) is of particular relevance in context of Mann’s case against Steyn, in light of the recent ruling:

Accusing a scientist of conducting his research fraudulently, manipulating his data to achieve a predetermined or political outcome, or purposefully distorting the scientific truth are factual allegations. They go to the heart of scientific integrity. They can be proven true or false. If false, they are defamatory. If made with actual malice, they are actionable.

Seems to me that ‘serial climate misinformer’ and ‘anti-science’ qualify as defamatory, and its difficult to imagine that the statements were not made with malice.

Robert Tracinski’s entire article–Mann versus Steyn, the Trial of the Century–is worth a read. As Tracinski says,

If it is a sin to doubt, then there is no science. If it is a crime to dissent, then there is no politics.


Bear in mind th…

Bear in mind that the representation of clouds in climate models (and of water vapour, which is intimately involved with cloud formation) is such as to amplify the forecast warming from increasing atmospheric carbon dioxide—on average over most of the models—by a factor of about three. In other words, two-thirds of the forecast rise in temperature derives from this particular model characteristic. Despite what the models are telling us—and perhaps because it is models that are telling us—no scientist close to the problem and in his right mind, when asked the specific question, would say that he is 95 per cent sure that the effect of clouds is to amplify rather than to reduce the warming effect of increasing carbon dioxide. If he is not sure that clouds amplify global warming, he cannot be sure that most of the global warming is a result of increasing carbon dioxide.



Compare the temperature increase between 1975-1998 main warming period in the latter part of the 20th century for both POGA H and POGA C:

  • POGA H: 0.68C natural plus anthropogenic
  • POGA C: 0.4C natural internal variability only

I’m not sure how good my eyeball estimates are, and you can pick other start/end dates. But no matter what, I am coming up with natural internal variability associated accounting for significantly MORE than half of the observed warming.

via Pause tied to equatorial Pacific surface cooling | Climate Etc..

As the climate models include more physical effects, the case for lukewarmism gets stronger. But note Xie’s response to Curry at the end. In any case, the observed climate behavior is falling outside the range of model runs without ‘prescribing’ temperature fits over roughly 8% of the globe.

NSIDC interactive graph of arctic sea ice coverage

Go to the National Snow and Ice Data Center for a nice interactive graphic on the extent of arctic sea ice. Click on 2013 and compare it to recent years. Discuss.

Der Spiegel interviews Hans von Storch on AGW

A nice (English language) interview with Dr. Hans von Storch at Der Spiegel is well worth a read. It is nice to see climate scientists valuing the observational record, even if it is inconsistent with the predictions of climate models. Speaking of which, he seems to agree that we are well outside a 95% confidence level that the various climate models are wrong. That doesn’t mean we don’t have warming, or that there isn’t an anthropogenic component, or even that the earlier predictions of significant warming are mistaken. But it does lower the confidence rational people should have in the accuracy of the current climate models.

I also completely agree with this:

Unfortunately, some scientists behave like preachers, delivering sermons to people. What this approach ignores is the fact that there are many threats in our world that must be weighed against one another.

Anthropogenic Global Warming is “the global threat of our time,” as President Obama recently said, only until we detect an Earth intersecting asteroid, or a supervolcano goes off, or we get a 1918-style global pandemic, or a Carrington Event occurs, or a thousand other scary scenarios that could happen. We shouldn’t close our eyes to the very real dangers that could come our way.

Historical Climate Catastrophe in the 17th Century

The evidence for major climate change in the 17th century is both copious and unambiguous. Consider the year 1675. In July, the Paris socialite Madame de Sévigné complained to her daughter, who lived close to the Mediterranean: “It is horribly cold: We have the fires lit, just like you, which is very remarkable.” She added: “We think the behavior of the sun and of the seasons has changed.”

Judith Curry points us to a study of the 17th century climate in in The Inevitable Climate Catastrophe. She has extensive quotes from Geoffrey Parker’s new book “Global Crisis: War, Climate Change and Catastrophe in the Seventeenth Century.” It is well worth a read, for this lesson if nothing else:

Nevertheless, it took human stupidity to turn crisis into catastrophe.

The historical record is also a great cautionary tale that cooling is much, much worse than warming. And, since a static climate is as unrealistic as a static universe…

Evidence, Skepticism, and the Scientific Method

Judith Luber-Narod, a high-school science teacher at the Abby Kelley Foster Charter Public School in Worcester, Mass., has incorporated climate change into her environmental studies classes, even though she teaches in a somewhat conservative area.

“I hesitated a little bit talking about something controversial,” she said. “But then I thought, how can you teach the environment without talking about it?”

Her students, on the other hand, love topics some deem controversial, she said. She devised an experiment in which she set up two terrariums with thermometers and then increased the level of carbon dioxide, the main greenhouse gas, in one of them.

The students watched as that terrarium got several degrees hotter than the other.

“I say to them, ‘I’m here to show you the evidence,’ ” she said. “ ‘If you want to believe the evidence when we’re done, that’s up to you.’ ”

I’m still working on that Dark Energy post, but it is proving to be ‘interesting’ to write. In the meantime, I wanted to talk a little about the role of experiment and skepticism in Science. The quote above comes from a New York Times science article New Guidelines Call for Broad Changes in Science Education. I don’t mean to be hard on the teacher. I do mean to be a little hard on the author and editors. But mostly, I’d like to use this as a cautionary tale showing why Good Science is not easy to do.

So, what’s wrong with the little experiment designed to show students how the greenhouse gas carbon dioxide raises Earth’s temperature? Almost everything. In particular, it is a great example of how a little knowledge is a dangerous thing, and how the role of experiment is often misunderstood.

First, the greenhouse effect is not really how a greenhouse warms. The glass of a greenhouse will indeed absorb infrared radiation, reradiating some heat–which would otherwise escape to the outside–back into the greenhouse. But this effect is quite minor, and real greenhouses warm because the glass enclosure blocks convection, preventing hot air from rising and being replaced by cooler air flowing in to take its place. It is (relatively) easy to demonstrate this by replacing the glass panes of a greenhouse with panes made of rock salt. The rock salt is transparent to infrared radiation, and so does not stop radiative cooling. The salt panes do block the formation of convective air currents just as well as glass. A greenhouse with rock salt panes will warm like a glass greenhouse, so the real warming mechanism is the elimination of convective flow and not the reduction in radiative cooling.

Similarly, in almost all terrarium experiments like the ones mentioned above, the real warming mechanism at work is not the carbon dioxide keeping the infrared radiation from carrying off heat energy, but the carbon dioxide inhibiting the formation of convective currents of air. The carbon dioxide, being heavier than air, stays within the open top terrarium. It doesn’t get hot enough to rise over the rim of the terrarium and allow cooler outside air to flow in. This is (relatively) easy to demonstrate by using argon gas instead of carbon dioxide. Argon is heavier than air, and argon is transparent to infrared radiation (like the rock salt). A terrarium filled with argon gas will heat just as well as one filled with carbon dioxide. Ergo, the warming effect has very little to do with the carbon dioxide reducing radiative cooling of the objects in the terrarium.

So, what about “I’m here to show you the evidence. If you want to believe the evidence when we’re done, that’s up to you” that the teacher claims? The problem is the experimental result (the terrarium warming) has more than one explanation, and the experiment isn’t designed to eliminate effects other than greenhouse gas style radiative warming. Good science is really hard, because even if you see a predicted effect, it is necessary to rule out alternative explanations for the observed evidence. If your hypothesis predicts A, but evidence shows B, the hypothesis is wrong. But if the hypothesis predicts A and the evidence shows A, this doesn’t necessarily show the hypothesis is correct. Experiments must be designed to test all other explanations for A and rule them out before the evidence shows the hypothesis is correct.

Science requires skepticism. Science requires more than even a theory agreeing with the evidence. Sometimes, what you see isn’t quite what you (or your teacher) think it is. Don’t be hasty to agree with authority. Be skeptical.

Matt Ridley: A Lukewarmer’s Ten Tests | The Global Warming Policy Foundation (GWPF)

For the benefit of supporters of climate change policy who feel frustrated by the reluctance of people like me to accept their assurances, here is what they would need to do to change my mind.

I agree with Matt Ridley.

How reliable is the global temperature record? Part two

Let’s introduce the characters in our story.

First, the satellite measurements.  Back in part 1, we found that satellites infer atmospheric temps by measuring microwave emissions from oxygen molecules.  There are two primary groups working with satellite data.  One is at the University of Alabama at Huntsville (UAH) and the other is Remote Sensing Systems (RSS); both work with the data from satellites to produce a temperature record.  Other groups are working with this data as well, but RSS and UAH are the major players. There is a lot of interesting physics and climate stuff here, but the data only go back to late 1978, and quite a substantial amount of processing is necessary to create the satellite temperature record.  The MSU post from Tamino’s Open Mind blog has a nice summary of the satellite info, albeit from 2007.  I plan to get back to this data later in our series.

The ground record of temperature comes from a variety of sources and are turned into monthly global-average readings by three independent research groups:

  1. The Met Office, in collaboration with the Climate Research Unit (CRU) at the University of East Anglia in the UK.
  2. The Goddard Institute for Space Sciences (GISS), part of the National Aeronautics and Space Administration in the US.
  3. The National Climate Data Center (NCDC), part of the National Oceanic and Atmospheric Administration in the US.

These three groups use different methods to collect and process the temperature readings in calculating the global-average numbers.  Their results are similar and they are in close agreement on the decade to decade trends.

The data sources for the Big Three come from different sources with each source having its own characteristics. It is generally agreed that reasonably reliable surface temperatures with wide geographic coverage begin around 1850.  Some records begin earlier, but have restricted geographic coverage.

The longest temperature record in use is the Central England Temperature record, dating from 1659 to the present.  It consists of monthly averages from 1659 to 1772, and daily averages from November 1772 onward.  The Met Office maintains the official CET record at the Hadley Centre.  In addition, the Hadley Centre maintains HADCRUT3, a global temperature dataset dating from 1850.

NASA maintains GIStemp, a record which provides monthly averages with wide geographic coverage from about 1880, although some records go back to the 1770s.  NOAO is responsible for the Global Historical Climatology Network (GHCN), which contains records as early as 1697. Widespread gridded monthly average temperatures are available from January 1880.  GHCN also has precipitation and pressure readings.  The US portion of the GHCN is the United States Historical Climate Network (USHCN) data, maintained by the NCDC and adjusted independently of the worldwide data.

Finally, the important antarctic records come from the Scientific Committee on Antarctic Research (SCAR) via the Reference Antarctic Data for Environmental Research (READER) program.  There are few fixed surface stations in Antarctica, and most stations have operated for short times, appearing and disappearing, leading to a very interesting data analysis program.

Next we’ll look at the problems facing the keepers of the datasets.

How reliable is the global temperature record? Part 1

What exactly is the global temperature?  How is it calculated?  And most importantly, from the climate change perspective, how can we know the global temperature is changing?  First, let’s look at how we measure heat.

Thermometers measure the heat energy of objects.  A thermometer uses a sensor, for example, the venerable glass tube filled with mercury, that responds to the thermal energy of its surrounding.  As the surroundings of the glass tube increase/decrease in heat, the mercury expands/contracts within the tube.  Place a scale alongside the tube, and the reading on the scale tells you how much heat is in the surroundings.  Calibrate the scale against standard temperatures, such as water boiling at 100 degrees Celsius, or with a known accurate thermometer, and the scale readings can be converted into temperature.  The accuracy of the reading tells how closely the measurement corresponds to the real temperature.  If your thermometer reads 51 degrees when a very accurate lab thermometer reads 50.0, the thermometer is accurate to at best one degree.  The precision of the reading tells how much information the scale gives; for example, if the marks on the scale are every two degrees, it is usually possible to read the scale to the nearest degree (on a mark or halfway between two marks).  Finally, the reproducibility of the thermometer tells if the same temperature always results in the same reading.  If the reproducibility is poor, comparisons between different readings become problematic.

If we are measuring air temperature, we must make sure the thermometer is in a neutral setting.  The thermometer can’t be in direct sun, or near buildings which are heated and cooled.  It can’t be shielded by a canopy of trees, and so on.  Every site has some environmental influences, such as that tree canopy, or the nearby city and airport, that have measurable effects on the temperature readings.  Ideally, the thermometer stays in the same place and nothing changes, but in reality, things change.  Trees grow, buildings go up and down, the population of the nearby area grows, the weather station is moved to make way for progress.

If a weather station has been measuring temperatures for a long time, without question a careful scientist would want to adjust the record a bit to account for these local environmental changes.  If one knows the station moved, one can look at the measurements in the time surrounding the move and see if, on average, the readings are just a bit higher or just a bit lower than before.  Similarly, when a new instrument is installed, one can compare before and after readings to see if the old instrument was reading a little lower or a little higher than the new instrument.  There are lots of reasons the longterm temperature record from a station might need some tweaking to give a consistent set of measurements.  The important point from a scientific perspective is that the adjustments are objectively calculated, and everyone knows why and by how much the raw readings were changed.

So now we have a reasonably consistent set of readings from a single station.  To compute a global temperature, ideally we’d place weather stations all over the global, take measurements, average the daily minimum and maximum temperature for each station, then take the daily averages of all stations and compute a global average.  In turn, each day’s global average could be compared against the same time period in prior years, and after collecting decades of readings, scientists would be able to predict the expected global average temperature for a time period.  The difference between that predicted ensemble average and the actual measured ensemble average is the anomaly. The difference between the measured temperature and a long-term average, or reference value, is the anomaly.  A warming climate gives a positive anomaly, and a cooling climate gives a negative anomaly.  Over time, the rate of change in the anomaly tells us if the worldwide climate is tending toward increasing or decreasing temperatures.  Note that the ensemble anomaly can be positive, but decreasing, and vice versa.

Satellites add an interesting variation to this.  Remote reading thermometers calculate the thermal energy in objects by measuring photon emission from the object in one or more wavelengths.  In the case of satellites, microwave emissions from atmospheric oxygen is measured.  Lots of work is necessary to accurately measure atmospheric temperature from a satellite, as Roy Spencer details.  Satellite measurements have lots of advantages over ground station measurements.  A single satellite can see large portions of the earth, the same instrument is used to measure temperatures in many places, and there are fewer tricky environmental changes to content with.  But satellite data only goes back to the 1970s.  However, it does provide a good check of the consistency and reproducibility of ground measurements.

Now we are ready to look at the various global temperature records in the next post.