Mistaking Cyclical Variations for the Trend

I titled my very first climate video “What is Normal,” alluding to the fact that climate doomsayers argue that we have shifted aspects of the climate (temperature, hurricanes, etc.) from “normal” without us even having enough historical perspective to say what “normal” is.

A more sophisticated way to restate this same point would be to say that natural phenomenon tend to show various periodicities, and without observing nature through the whole of these cycles, it is easy to mistake short term cyclical variations for long-term trends.

A paper in the journal Water Resources Research makes just this point using over 200 years of precipitation data:

We analyze long-term fluctuations of rainfall extremes in 268 years of daily observations (Padova, Italy, 1725-2006), to our knowledge the longest existing instrumental time series of its kind. We identify multidecadal oscillations in extremes estimated by fitting the GEV distribution, with approximate periodicities of about 17-21 years, 30-38 years, 49-68 years, 85-94 years, and 145-172 years. The amplitudes of these oscillations far exceed the changes associated with the observed trend in intensity. This finding implies that, even if climatic trends are absent or negligible, rainfall and its extremes exhibit an apparent non-stationarity if analyzed over time intervals shorter than the longest periodicity in the data (about 170 years for the case analyzed here). These results suggest that, because long-term periodicities may likely be present elsewhere, in the absence of observational time series with length comparable to such periodicities (possibly exceeding one century), past observations cannot be considered to be representative of future extremes. We also find that observed fluctuations in extreme events in Padova are linked to the North Atlantic Oscillation: increases in the NAO Index are on average associated with an intensification of daily extreme rainfall events. This link with the NAO global pattern is highly suggestive of implications of general relevance: long-term fluctuations in rainfall extremes connected with large-scale oscillating atmospheric patterns are likely to be widely present, and undermine the very basic idea of using a single stationary distribution to infer future extremes from past observations.

Trying to work with data series that are too short is simply a fact of life — everyone in climate would love a 1000-year detailed data set, but we don’t have it.  We use what we have, but it is important to understand the limitations.  There is less excuse for the media that likes to use single data points, e.g. one storm, to “prove” long term climate trends.

A good example of why this is relevant is the global temperature trend.  This chart is a year or so old and has not been updated in that time, but it shows the global temperature trend using the most popular surface temperature data set.  The global warming movement really got fired up around 1998, at the end of the twenty year temperature trend circled in red.

click to enlarge


They then took the trends from these 20 years and extrapolated them into the future:

click to enlarge

But what if that 20 years was merely the upward leg of a 40-60 year cyclic variation?  Ignoring the cyclic functions would cause one to overestimate the long term trend.  This is exactly what climate models do, ignoring important cyclic functions like the AMO and PDO.

In fact, you can get a very good fit with actual temperature by modeling them as three functions:  A 63-year sine wave, a 0.4C per century long-term linear trend  (e.g. recovery from the little ice age) and a new trend starting in 1945 of an additional 0.35C, possibly from manmade CO2.Slide52

In this case, a long-term trend still appears to exist but it is exaggerated by only trying to measure it in the upward part of the cycle (e.g. from 1978-1998).


Typhoons and Hurricanes

(Cross-posted from Coyoteblog)

The science that CO2 is a greenhouse gas and causes some warming is hard to dispute.  The science that Earth is dominated by net positive feedbacks that increase modest greenhouse gas warming to catastrophic levels is very debatable.  The science that man’s CO2 is already causing an increase in violent and severe weather is virtually non-existent.

Seriously, of all the different pieces of the climate debate, the one that is almost always based on pure crap are the frequent media statements linking manmade CO2 to some severe weather event.

For example, Coral Davenport in the New York Times wrote the other day:

As the torrential rains of Typhoon Hagupit flood thePhilippines, driving millions of people from their homes, the Philippine government arrived at a United Nationsclimate change summit meeting on Monday to push hard for a new international deal requiring all nations, including developing countries, to cut their use of fossil fuels.

It is a conscious pivot for the Philippines, one of Asia’s fastest-growing economies. But scientists say the nation is also among the most vulnerable to the impacts of climate change, and the Philippine government says it is suffering too many human and economic losses from the burning of fossil fuels….

A series of scientific reports have linked the burning of fossil fuels with rising sea levels and more powerful typhoons, like those that have battered the island nation.

It is telling that Ms. Davenport did not bother to link or name any of these scientific reports.  Even the IPCC, which many skeptics believe to be exaggerating manmade climate change dangers, refused in its last report to link any current severe weather events with manmade CO2.

Roger Pielke responded today with charts from two different recent studies on typhoon activity in the Phillipines.  Spot the supposed upward manmade trend.  Or not:




I am not a huge fan of landfalling cyclonic storm counts because whether they make landfall or not can be totally random and potentially disguise trends.  A better metric is the total energy of cyclonic storms, land-falling or not, where again there is no trend.

Via the Weather Underground, here is Accumulated Cyclonic Energy for the Western Pacific (lower numbers represent fewer cyclonic storms with less total strength):



And here, by the way, is the ACE for the whole globe:


Remember this when you see the next storm inevitably blamed on manmade global warming.  If anything, we are actually in a fairly unprecedented (in the last century and a half) hurricane drought.

Those Who Follow Climate Will Definitely Recognize This

This issue will be familiar to anyone who has spent time with temperature graphs.  We can ask ourselves if 1 degree of global warming is a lot, when it is small compared to seasonal variations, or even intra-day variation, you would find in most locations.  That is not a trick question.  It might be important, but certainly how important an audience  considers it may be related to how one chooses to graph it.  Take this example form an entirely unrelated field:

Last spring, Adnan sent me a letter about … something, I can’t even remember exactly what. But it included these two graphs that he’d drawn out in pencil. With no explanation. There was just a Post-it attached to the back of one of the papers that said: “Could you please hold these 2 pages until we next speak? Thank you.”

Here’s what he sent:

Price of tea at 7-11 

Price of tea at C-Mart 

This was curious. It crossed my mind that Adnan might be … off his rocker in some way. Or, more excitingly, that these graphs were code for some top-secret information too dangerous for him to send in a letter.

But no. These graphs were a riddle that I would fail to solve when we next spoke, a couple of days later.

Adnan: Now, so would you prefer, as a consumer, would you rather purchase at a store where prices are consistent or items from a store where the prices fluctuate?

Sarah: I would prefer consistency.

Adnan: That makes sense. Especially in today’s economy. So if you had to choose, which store would you say has more consistent prices?

Sarah: 7-11 is definitely more consistent.

Adnan: As compared to…?

Sarah: As compared to C-Mart, which is going way up and down.

Look again, Adnan said. Right. Their prices are exactly the same. It’s just that the graph of C-Mart prices is zoomed way in — the y-axis is in much smaller cost increments — so it looks like dramatic fluctuations are happening. And he made the pencil lines much darker and more striking in the C-Mart graph, so it looks more…sinister or something.

Layman’s Primer on the Climate Skeptic Position

I am a “lukewarmer”, which means a skeptic that agrees that man-made CO2 is incrementally warming the Earth but believes that the amount of that warming is being greatly exaggerated.  In addition, I believe that the science behind evidence of current “climate change” is really poor, with folks in the media using observations of tail-of-the-distribution weather effects to “prove” climate change rather than relying on actual trend data (which tend to show no such thing).

I have written two articles at Forbes.com summarizing this position and the debate.

Understanding the Global Warming Debate

Denying the Catastrophe: The Science of the Climate Skeptic’s Position

When Climate Alarmism Limits Environmental Progress

One of my favorite sayings is that “years from now, environmentalists will look back on the current obsession with global warming and say that it did incredible harm to real environmental progress.”  The reason is that there are many environmental problems worse than the likely impact of man-made global warming that would cost substantially less money to solve. The focus on climate change has sucked all the oxygen out of every other environmental improvement effort.

The recent Obama climate discussions with China are a great example.  China has horrendous environmental problems that need to be solved long before they worry about CO2 production.

Take coal plants.  Coal plants produce a lot of CO2, but without the aid of modern scrubbers and such, they also produce SOx, NOx, particulates matter and all the other crap you see in the Beijing air.  The problem is that the CO2 production from a coal plant takes as much as 10-100x more money to eliminate than it takes to eliminate all the other bad stuff.

While economically rational technology exists to get rid of all the other bad stuff from coal (technology that is currently in use at most US coal plants), there is no reasonable technology to eliminate CO2 from coal.  The only option is to substitute things like wind and solar which are much more expensive, in addition to a number of other drawbacks.

What this means is that the same amount of money needed to replace a couple percent of the Chinese coal industry with carbon-less technologies could probably add scrubbers to all the coal plants.  Thus the same money needed to make an only incremental change in CO2 output would make an enormous change in the breath-ability of air in Chinese cities.

So if we care about the Chinese people, why are we pushing them to worry about CO2?

PS-  by the way, there have been a number of studies that have attributed a lot of the Arctic and Greenland ice melting to the albedo effect of coal combustion particulate matter from China deposited on the ice.  The same technology that would make Beijing air breathable might also reduce Arctic ice melts.

Why We Are Exaggerating “Extreme Weather”

I have written in article at Forbes.com called Summer of the Shark, Global Warming Edition.  It describes why the media, and many average citizens, are exaggerating the degree and effects of extreme weather.  Here is a preview of that article, but I encourage you to read it all

In the summer of 2001, a little boy in Mississippi lost an arm in a shark attack.  The media went absolutely crazy.  For weeks and months they highlighted every shark attack on the evening news.  They ran aerial footage of sharks in the water near beaches.  They coined the term “Summer of the Shark.”  According to Wikipedia, shark attacks were the number three story, in terms of network news time dedicated, of the summer.

Bombarded by such coverage, most Americans responded to polls by saying they were concerned about the uptick in shark attacks.  In fact, there were actually about 10% fewer shark attacks in 2001 than in 2000.  Our perceptions were severely biased by the coverage.

Similarly, every bit of severe weather now makes the news, so the American public can be forgiven for thinking that maybe such weather is increasing.  But when one actually looks at data, it’s hard to see good evidence of a shift in severe weather.  Neitherextreme wet weather, extreme dry weather, tornadoes, or hurricanes show any real upward trend.  Sure we had some 100-year high temperatures in the US in March.  But in the same month the rest of the world was at or below its average temperature for the last couple of decades.


HydroInfra: Scam! Investment Honeypot for Climate Alarmists

Cross-posted from Coyoteblog.

I got an email today from some random Gmail account asking me to write about HyrdoInfra.  OK.  The email begins: “HydroInfra Technologies (HIT) is a Stockholm based clean tech company that has developed an innovative approach to neutralizing carbon fuel emissions from power plants and other polluting industries that burn fossil fuels.”

Does it eliminate CO2?  NOx?  Particulates?  SOx?  I actually was at the bottom of my inbox for once so I went to the site.  I went to this applications page.  Apparently, it eliminates the “toxic cocktail” of pollutants that include all the ones I mentioned plus mercury and heavy metals.  Wow!  That is some stuff.

Their key product is a process for making something they call “HyrdroAtomic Nano Gas” or HNG.  It sounds like their PR guys got Michael Crichton and JJ Abrams drunk in a brainstorming session for pseudo-scientific names.

But hold on, this is the best part.  Check out the description of HNG and how it is made:

Splitting water (H20) is a known science. But the energy costs to perform splitting outweigh the energy created from hydrogen when the Hydrogen is split from the water molecule H2O.

This is where mainstream science usually closes the book on the subject.

We took a different approach by postulating that we could split water in an energy efficient way to extract a high yield of Hydrogen at very low cost.

A specific low energy pulse is put into water. The water molecules line up in a certain structure and are split from the Hydrogen molecules.

The result is HNG.

HNG is packed with ‘Exotic Hydrogen’

Exotic Hydrogen is a recent scientific discovery.

HNG carries an abundance of Exotic Hydrogen and Oxygen.

On a Molecular level, HNG is a specific ratio mix of Hydrogen and Oxygen.

The unique qualities of HNG show that the placement of its’ charged electrons turns HNG into an abundant source of exotic Hydrogen.

HNG displays some very different properties from normal hydrogen.

Some basic facts:

  • HNG instantly neutralizes carbon fuel pollution emissions
  • HNG can be pressurized up to 2 bars.
  • HNG combusts at a rate of 9000 meters per second while normal Hydrogen combusts at a rate 600 meters per second.
  • Oxygen values actually increase when HNG is inserted into a diesel flame.
  • HNG acts like a vortex on fossil fuel emissions causing the flame to be pulled into the center thus concentrating the heat and combustion properties.
  • HNG is stored in canisters, arrayed around the emission outlet channels. HNG is injected into the outlets to safely & effectively clean up the burning of fossil fuels.
  • The pollution emissions are neutralized instantly & safely with no residual toxic cocktail or chemicals to manage after the HNG burning process is initiated.

Exotic Hyrdrogen!  I love it.  This is probably a component of the “red matter” in the Abrams Star Trek reboot.  Honestly, someone please tell me this a joke, a honeypot for mindless environmental activist drones.    What are the chemical reactions going on here?  If CO2 is captured, what form does it take?  How does a mixture of Hydrogen and Oxygen molecules in whatever state they are in do anything with heavy metals?  None of this is on the website.   On their “validation” page, they have big labels like “Horiba” that look like organizations thave somehow put their impremature on the study.  In fact, they are just names of analytical equipment makers.  It’s like putting “IBM” in big print on your climate study because you ran your model on an IBM computer.

SCAM!  Honestly, when you see an article written to attract investment that sounds sort of impressive to laymen but makes absolutely no sense to anyone who knows the smallest about of Chemistry or Physics, it is an investment scam.

But they seem to get a lot of positive press.  In my search of Google, everything in the first ten pages or so are just uncritical republication of their press releases in environmental and business blogs.   You actually have to go into the comments sections of these articles to find anyone willing to observe this is all total BS.   If you want to totally understand why the global warming debate gets nowhere, watch commenter Michael at this link desperately try to hold onto his faith in HydroInfra while people who actually know things try to explain why this makes no sens

Switching Back to Disqus

For a variety of reasons, I had to turn off Disqus a while back.  We are going back to it for comments.  Over the next few days you may see comments on old posts disappear and reappear.  If I don’t screw up, within 48 hours all existing comments should be back.

Reconciling Conflicting Climate Claims

Cross-posted from Coyoteblog

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 Models as “Evidence”

Cross-posted from Coyoteblog

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.

Another Plea to Global Warming Alarmists on the Phrase “Climate Denier”

Cross-posted from Coyoteblog

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.

My Thoughts on Steven Goddard and His Fabricated Temperature Data Claim

Cross-posted from Coyote Blog.

Steven Goddard of the Real Science blog has a study that claims that US real temperature data is being replaced by fabricated data.  Christopher Booker has a sympathetic overview of the claims.

I believe that there is both wheat and chaff in this claim, and I would like to try to separate the two as best I can.  I don’t have time to write a well-organized article, so here is just a list of thoughts

  1. At some level it is surprising that this is suddenly news.  Skeptics have criticized the adjustments in the surface temperature database for years
  2. There is certainly a signal to noise ratio issue here that mainstream climate scientists have always seemed insufficiently concerned about.  Specifically, the raw data for US temperatures is mostly flat, such that the manual adjustments to the temperature data set are about equal in magnitude to the total warming signal.  When the entire signal one is trying to measure is equal to the manual adjustments one is making to measurements, it probably makes sense to put a LOT of scrutiny on the adjustments.  (This is a post from 7 years ago discussing these adjustments.  Note that these adjustments are less than current ones in the data base as they have been increased, though I cannot find a similar chart any more from the NOAA discussing the adjustments)
  3. The NOAA HAS made adjustments to US temperature data over the last few years that has increased the apparent warming trend.  These changes in adjustments have not been well-explained.  In fact, they have not really be explained at all, and have only been detected by skeptics who happened to archive old NOAA charts and created comparisons like the one below.  Here is the before and after animation (pre-2000 NOAA US temperature history vs. post-2000).  History has been cooled and modern temperatures have been warmed from where they were being shown previously by the NOAA.  This does not mean the current version  is wrong, but since the entire US warming signal was effectively created by these changes, it is not unreasonable to act for a detailed reconciliation (particularly when those folks preparing the chart all believe that temperatures are going up, so would be predisposed to treating a flat temperature chart like the earlier version as wrong and in need of correction.
  4. However, manual adjustments are not, as some skeptics seem to argue, wrong or biased in all cases.  There are real reasons for manual adjustments to data — for example, if GPS signal data was not adjusted for relativistic effects, the position data would quickly get out of whack.  In the case of temperature data:
    • Data is adjusted for shifts in the start/end time for a day of measurement away from local midnight (ie if you average 24 hours starting and stopping at noon).  This is called Time of Observation or TOBS.  When I first encountered this, I was just sure it had to be BS.  For a month of data, you are only shifting the data set by 12 hours or about 1/60 of the month.  Fortunately for my self-respect, before I embarrassed myself I created a spreadsheet to monte carlo some temperature data and play around with this issue.  I convinced myself the Time of Observation adjustment is valid in theory, though I have no way to validate its magnitude  (one of the problems with all of these adjustments is that NOAA and other data authorities do not release the source code or raw data to show how they come up with these adjustments).   I do think it is valid in science to question a finding, even without proof that it is wrong, when the authors of the finding refuse to share replication data.  Steven Goddard, by the way, believes time of observation adjustments are exaggerated and do not follow NOAA’s own specification.
    • Stations move over time.  A simple example is if it is on the roof of a building and that building is demolished, it has to move somewhere else.  In an extreme example the station might move to a new altitude or a slightly different micro-climate.  There are adjustments in the data base for these sort of changes.  Skeptics have occasionally challenged these, but I have no reason to believe that the authors are not using best efforts to correct for these effects (though again the authors of these adjustments bring criticism on themselves for not sharing replication data).
    • The technology the station uses for measurement changes (e.g. thermometers to electronic devices, one type of electronic device to another, etc.)   These measurement technologies sometimes have known biases.  Correcting for such biases is perfectly reasonable  (though a frustrated skeptic could argue that the government is diligent in correcting for new cooling biases but seldom corrects for warming biases, such as in the switch from bucket to water intake measurement of sea surface temperatures).
    • Even if the temperature station does not move, the location can degrade.  The clearest example is a measurement point that once was in the country but has been engulfed by development  (here is one example — this at one time was the USHCN measurement point with the most warming since 1900, but it was located in an open field in 1900 and ended up in an asphalt parking lot in the middle of Tucson.)   Since urban heat islands can add as much as 10 degrees F to nighttime temperatures, this can create a warming signal over time that is related to a particular location, and not the climate as a whole.  The effect is undeniable — my son easily measured it in a science fair project.  The effect it has on temperature measurement is hotly debated between warmists and skeptics.  Al Gore originally argued that there was no bias because all measurement points were in parks, which led Anthony Watts to pursue the surface station project where every USHCN station was photographed and documented.  The net results was that most of the sites were pretty poor.  Whatever the case, there is almost no correction in the official measurement numbers for urban heat island effects, and in fact last time I looked at it the adjustment went the other way, implying urban heat islands have become less of an issue since 1930.  The folks who put together the indexes argue that they have smoothing algorithms that find and remove these biases.  Skeptics argue that they just smear the bias around over multiple stations.  The debate continues.
  5. Overall, many mainstream skeptics believe that actual surface warming in the US and the world has been about half what is shown in traditional indices, an amount that is then exaggerated by poorly crafted adjustments and uncorrected heat island effects.  But note that almost no skeptic I know believes that the Earth has not actually warmed over the last 100 years.  Further, warming since about 1980 is hard to deny because we have a second, independent way to measure global temperatures in satellites.  These devices may have their own issues, but they are not subject to urban heat biases or location biases and further actually measure most of the Earth’s surface, rather than just individual points that are sometimes scores or hundreds of miles apart.  This independent method of measurement has shown undoubted warming since 1979, though not since the late 1990’s.
  6. As is usual in such debates, I find words like “fabrication”, “lies”,  and “myth” to be less than helpful.  People can be totally wrong, and refuse to confront their biases, without being evil or nefarious.

Postscript:  Not exactly on topic, but one thing that is never, ever mentioned in the press but is generally true about temperature trends — almost all of the warming we have seen is in nighttime temperatures, rather than day time.  Here is an example from Amherst, MA (because I just presented up there).  This is one reason why, despite claims in the media, we are not hitting any more all time daytime highs than we would expect from a normal distribution.  If you look at temperature stations for which we have 80+ years of data, fewer than 10% of the 100-year highs were set in the last 10 years.  We are setting an unusual number of records for high low temperature, if that makes sense.

click to enlarge


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.