The nature of blogging (“having a beer”) vs the nature of science

Robert Grumbine (a scientist-blogger well worth reading) explains how the scientific process works and how scientists communicate, and how it differs from blog debates (which he describes as “having a beer”). The following is lifted from his comment at Chris Colose’s blog a while ago. He sets up his argument in response to another commenter (self-identifying as “a genuine skeptic”):

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As a skeptic, I share your frustration equally, and as a genuine skeptic, and someone who does care about the environment, I am ready any day of the week to have my opinion sway back to believing in / trusting the consensus / IPCC position. Further, I know exactly what would sway me: dialogue, and constructive debate with the skeptics, in particular those skeptics of the ilk of Lindzen, Christy, and, although he refuses the label “skeptic”, Pielke Sr. (…)

(…) I’ve disagreed with Pielke Sr., for instance, but in the scientific norm. Tenderhearted readers, unaccustomed to the scientific norm, might have thought I was awfully hard on Roger. (One did say so.) But his own comment was that he appreciated my constructive discussion. This is a cultural issue that I think the general population does not understand. Normal exchanges, for science, about what’s going on, what’s good, or not, are fairly rough and tumble. It may not be the best thing that science is conducted this way, but it is what it is.

The scientific norm issue is a different matter. The scientific norm is the professional literature, not blog commentary. If you look in to Lindzen and the response in the scientific literature, you’ll find that he’s been met properly (by the standards of science, that is). Namely, he suggested his ‘adaptive iris’ idea. This was based on there being a certain relationship (it had to have a particular sign, and large magnitude) between surface temperatures in the tropics and cloudiness (and, for that matter, particular types of cloud). One paper in the scientific literature doesn’t buy you much. It is the start of the conversation to publish in the literature, not blessing as holy writ. He published, and then got the best possible response — other people used other (better) data sets and observing methods to see if they could get the same answer as he had gotten in his first cut. Unfortunately for his hypothesis, the better data sets erased his effect. Indeed, not only was the magnitude much smaller than he thought, the sign was the opposite of what he thought.

As far as scientific norms go, he got extremely good treatment. a) he did publish his idea (no ‘conspiracy to suppress’) and b) other people took a serious look at it. It is significant work to take a look at somebody else’s new idea. As a scientist, if you can get others to look at your idea, you have done extremely well. As happens in science, perfectly normally, the initial proposition got rejected by more detailed analysis. Since what was at hand was deriving a relationship between observational quantities, and Lindzen is a theoretician, it’s no great surprise or shame that he didn’t get all the niceties on his data sets right. As usual, devils lay in the details, and the responses were from groups familiar with all the devils laying in those details.

Where things went problematic was that contrary to proper scientific practice, Lindzen didn’t drop his disproven idea. A bit of ‘is so’ publishing (sorry, it was painful to read his response article and this is all I can say of it) in response to the objections was it. And then much complaining outside the scientific literature about conspiracy, scam, censorship, … To be honest, even his original Iris publication was an example of lenient reviewing. There were problems in his data management in the original paper that even I saw (correctly) would be a problem for his idea — and I’m not a tropical person (polar regions mostly), nor, then, sea surface temperature, nor then or now satellite sensing of clouds. The later publications — in the scientific literature — about his errors confirmed my suspicions, and, unsurprisingly, added a number of problems to what I suspected. But that’s not what you see out on the blog universe.

You can make some headway over at scholar.google.com. A fair amount of the non-scientific world shows up there, but a fair amount of the scientific world is present.

…
always see an ad hominem attack for what it is (I refer to the attacks by commenters at RealClimate, which were not removed by the editors). In most cases, straw men arguments can also be seen for what they are. And then an argument, “we don’t have to answer that ’cause it wasn’t peer-reviewed” always also increases the lay public’s skepticism. No one takes that response seriously, and again, skepticism can only increase.

I agree that outside the scientific community nobody takes seriously that something didn’t appear in the scientific literature.

That is a problem with outside the scientific community.

Doing science is difficult. Over the past 400 years, the modern scientific method has accumulated a lot of knowledge and understanding. Doing science means changing that body of knowledge and understanding. Sometimes that means saying that even though we used to think that something was the case, it really isn’t. Making that argument successfully is hard work. ‘Even’ the easier argument of making an addition is hard work. It’s hard work because other people have to be able to rely very strongly on everything you say in your paper. (…)

There are two parts to the scientific publication process important for your comment here. One is, to publish in the professional literature about your idea, you have to examine and explain your idea thoroughly. ‘thoroughly’ turns out to be a lot of work. Second is, you have to research all the relevant aspects of your problem and honestly discuss them. The up side of this is, once you’ve finished a proper scientific paper, it can stand for some time. You might turn out to be wrong about something — because there were different data than you used, or a better technique than you used, or … several things. Being shown wrong by later and much more labor-intensive examinations is fine. But being shown wrong because you failed to do your homework is disaster.

In contrast is blog posts and comments. The standard there is what I’ll call ‘chatting over a beer’. If you and I sit down and start talking, both of us with something we like to drink, having a relaxed conversation, that’s wildly different than scientific literature. Both of us will say what we think, but there’s no concern about tomorrow you trying to write a paper on which our professional reputations will hang based on what I say. We’re just chatting. I’ll give you my best answer at the time, but if I’ve forgotten something, or the answer is 25.0 instead of 2.50, eh. Just chatting over a beer. Just a blog comment. If someone started writing a scientific paper based on comments in blogs … all kinds of wild things could show up. The earth is flat, hollow, expanding, 6000 years old, and so on. Somebody, somewhere, in the blogosphere has said all such things.

To do science, we need something much more reliable than ‘anything anybody ever says anywhere’. We even need something better than “well, he’s normally pretty good so even tough he’s never worked on this kind of problem before and doesn’t know how the satellites detect what he’s working with, he _must_ be right anyhow.” That something more is the professional scientific literature.

Within the world of science (all 20 or so of us), it is an extremely telling, and negative, thing that much of what the general public thinks is the case about science is actually based on things which are said _only_ outside the scientific literature. If the speaker had confidence in his statement, he’d try to publish it in the literature. And, if they were right about the ‘conspiracy’, they should at least have a rejection letter and comments from the editor and reviewers to show. Instead, they talk about the conspiracy, but have no rejection letters (_I’ve_ got rejection letters — they’re normal to trying to do science.)

But the public perception is quite different. Still, I have to think if someone won’t go in front of his professional peers and stand for what he thinks is scientifically correct, he doesn’t really believe it himself. If his only or major audience is people who don’t know the science thoroughly, I have to figure he thinks that’s the only audience who’ll let him get away with whatever it is he’s saying now. Fine for you and me over a beer. No fine for doing science.

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Just to add a qualifier: Not everything that appeared in the scientific literature is necessarily “good science”. Likewise, not everything that appeared on a blog is necessarily unscientific or wrong. Just as in a bar, the greatest ideas and insights can be heard. But amidst a helluva lot of chatter about the weather. Which is actually pretty nice right now. Enjoy your beer!

Recent changes in the sun, CO2 and global average temperature

Several times in recent weeks people have commented that the sun is responsible for the current climate change rather than CO2. Ironically, this was sometimes argued by the same people who were cheering on the claim that there is no deterministic forcing at work in driving temperatures upwards (be it GHG or the sun or whatever else). So much for coherence.

Let’s look at how the global average temperature, CO2 and the sun changed over recent decades:

Temperatures jiggle up and down, but are increasing over the longer term (multiple decades). CO2 has a seasonal cycle due to the ‘breathing’ of the biosphere, but is steadily increasing over the years due to human emissions. The sun shows an 11-year cycle, but no secular increase or decrease over this time period.

Let’s go a bit farther back in time (HadCRU temperatures up to 2008; number of sunspots as a proxy of solar activity; original here):

And looking back at sunspot observations over the past 400 years (original):

So what does this tell us? Of course changes in the sun affect our climate (coherence check: This implies a certain degree of determinism). Low solar activity (e.g. during the Maunder and the Dalton minima) played a role in the so called ‘little ice age’. In the beginning of the 20th century solar activity increased, which contributed to the warming (together with greenhouse gases and a lack of volcanic activity). However, since the solar output (including cosmic rays) remained steady (or even decreased a bit) since the 1950’s, it doesn’t seem very likely that the sun contributed to the recent increase in temperatures since the 1970’s. The little ice age ended (~1850) long before the recent warming started (~1975), so no causal relation there either.

The main reasons that disqualify the sun as being a major culprit in recent global warming are:

• No increase in solar output (or decrease in cosmic rays) over the past 50 years

• Nighttime temperatures increased more than daytime (inconsistent with solar forcing; consistent with GHG forcing)

• Stratospheric cooling (inconsistent with solar forcing; consistent with GHG forcing)

See also Skeptical Science and Lockwood’s recent review paper (the first chapter, describing the context of the ‘controversy’ is well worth reading).

CRU inquiry: Published results still credible; focus on Phil Jones misplaced

The UK Parliamentary Committee released its report on the CRU email affair (I’m a bit late to the game, I know…)

Before going to the summary, let me highlight this important point made in the report:

Even if the data that CRU used were not publicly available—which they mostly are—or the methods not published—which they have been—its published results would still be credible: the results from CRU agree with those drawn from other international data sets; in other words, the analyses have been repeated and the conclusions have been verified.

Comparisons with other surface based datasets here; with satellite data sets here; with several bloggers’ reconstructions here.

CRU’s data handling has not inflated the warming trend, see e.g. here and here.

Here’s the summary:

The disclosure of climate data from the Climatic Research Unit (CRU) at the University of East Anglia (UEA) in November 2009 had the potential to damage the reputation of the climate science and the scientists involved.

We believe that the focus on CRU and Professor Phil Jones, Director of CRU, in particular, has largely been misplaced. Whilst we are concerned that the disclosed e-mails suggest a blunt refusal to share scientific data and methodologies with others, we can sympathise with Professor Jones, who must have found it frustrating to handle requests for data that he knew—or perceived—were motivated by a desire simply to undermine his work.

In the context of the sharing of data and methodologies, we consider that Professor Jones’s actions were in line with common practice in the climate science community. It is not standard practice in climate science to publish the raw data and the computer code in academic papers. However, climate science is a matter of great importance and the quality of the science should be irreproachable. We therefore consider that climate scientists should take steps to make available all the data that support their work (including raw data) and full methodological workings (including the computer codes). Had both been available, many of the problems at UEA could have been avoided. [I think that is a very naïve preposition. BV]

We are content that the phrases such as “trick” or “hiding the decline” were colloquial terms used in private e-mails and the balance of evidence is that they were not part of a systematic attempt to mislead. Likewise the evidence that we have seen does not suggest that Professor Jones was trying to subvert the peer review process. Academics should not be criticized for making informal comments on academic papers.

In the context of Freedom of Information (FOIA), much of the responsibility should lie with UEA. The disclosed e-mails appear to show a culture of non-disclosure at CRU and instances where information may have been deleted, to avoid disclosure. We found prima facie evidence to suggest that the UEA found ways to support the culture at CRU of resisting disclosure of information to climate change sceptics. The failure of UEA to grasp fully the potential damage to CRU and UEA by the non-disclosure of FOIA requests was regrettable. UEA needs to review its policy towards FOIA and re-assess how it can support academics whose expertise in this area is limited.

The Deputy Information Commissioner has given a clear indication that a breach of the Freedom of Information Act 2000 may have occurred but that a prosecution was time-barred; however no investigation has been carried out. In our view it is unsatisfactory to leave the matter unresolved. We conclude that the matter needs to be resolved conclusively—either by the Independent Climate Change Email Review or by the Information Commissioner.

We accept the independence of the Climate Change E-mail Review and recommend that the Review be open and transparent, taking oral evidence and conducting interviews in public wherever possible.

On 22 March UEA announced the Scientific Appraisal Panel to be chaired by Lord Oxburgh. This Panel should determine whether the work of CRU has been soundly built and it would be premature for us to pre-judge its work.

See also James Annan with a good dose of British sarcasm. Also Eli, Stoat. Image Nick Anderson.

Update: Another report investigating the CRU has been released, headed by Lord Oxburg of Liverpool. Its main conclusions are that they saw

no evidence of any deliberate scientific malpractice in any of the work of the Climatic Research Unit and had it been there we believe that it is likely that we would have detected it.

and they remark that

it is very surprising that research in an area that depends so heavily on statistical methods has not been carried out in close collaboration with professional statisticians.

The last conclusion seems very relevant in light of the recent discussions on this blog.

A ‘rooty’ solution to my weight gain problem

I just love brownies, chocolate fudge cake and the like. As a result of eating too many of those –so my dietician told me- I have gained weight over the past years. According to my dietician, somebody’s body weight depends on the ratio of their caloric input and output (i.e. someone’s personal ‘energy balance’). I also  believed that. Until recently.

Here’s a graph of my body weight over the past 32 years:

As you can see from this graph, I’ve been on quite a few diets. But often, as soon as I had lost a few pounds, they came back when I lost my appetite in carrots and hunted down the chocolate aisle again. In the nineties, I did quite a bit of sports, which prevented my weight from increasing too much. I’ve stopped since; it just makes me tired.

Over the past 8 years, despite the yo-yo effect of sometimes losing as much as 5 kg over the course of a few months, my weight has increased. My dietician told me that unless I change my eating and sporting habits in a sustainable way, my weight will probably keep yo-yo-ing up.

I was gonna go back to drinking carrot juice again, but then somebody pointed out that my weight increase had nothing to do with my eating too much chocolate or anything like that. Huh? 

He pointed out to me that the timeseries of my weight versus time (as shown in the graph above) contains a unit root! No, that’s not a consequence of eating too much carrots; it’s a characteristic of the time series. So what, you my ask? Well,

“a deterministic trend is inconsistent with a unit root”

Though admittedly,

“it can contain a drift parameter, which indeed predicts a ‘deterministic’ rise in a certain period”

According to this theory, my body weight just varies stochastically, e.g. between the blue lines in the graph below:

As you can see, the theory is valid: My weight has indeed remained between the blue lines. And for the next few years, my weight will be between 55 and 105 kg, irrespective of what I eat and how much I sport! After all, that would be deterministic, wouldn’t it? (i.e. my eating and other habits determining my weight)

Wow, if that’s the case, then I’ll stop my carrot juice diet right now and run to the corner store for a box of mars bars!! And I’ll cancel further consultations with my dietician. Energy balance… such nonsense. Never thought I’d be so happy with a root!

 

PS: This post is not meant to ridicule the arguments made in favor of a unit root. It is meant to draw attention to the fact that the physical (or biological in this case) context of the quantity we’re investigating is very important. If someone is riding a bike downhill, I could wonder if the bike could have gotten to where it is all by itself, and conclude that I cannot possibly predict when the bike will reach the valley. But that ignores the (deterministic) effect of the guy who is riding the bike. Share your favorite analogy in the comments!

[Some typos edited]

What do we know about climate change?

This excellent video gives a nice overview of what we know about climate change:

It’s part of Peter Sinclair’s (a.k.a. Greenman3610) “climate crocks” series.

(Script, graphs and links to some of the relevant papers here)

My short version:

– Globe is warming

– It’s due to us

– It’s bad news

– Uncertainty + Inertia = Danger

The relevance of rooting for a unit root

So what if the global average temperature series contained a unit root? It would mean that ordinary least squares regression may lead to spurious results in terms of inflated trend significance. It would *not* mean that phsyics-based climate models are suddenly invalid or that AGW is suddenly falsified (just as gravity is not falsified by observing a bird in the sky).

On a previous post, ‘VS’ commented that

“(…) global temperature contains a stochastic rather than deterministic trend, and is statistically speaking, a random walk.”

He later clarified (updated):

I agree with you that temperatures are not ‘in essence’ a random walk, just like many (if not all) economic variables observed as random walks are in fact not random walks.

And later still:

“I’m not ‘disproving’ AGWH here.
I’m not claiming that temperatures are a random walk.
I’m not ‘denying’ the laws of physics.”

However, many commenters started chiming in with a sense of “Yeah, somebody is taking on climate science and seems to have refuted it all!” Uhm, no.

Basically, a random walk towards warmer air temperatures would cause either a negative radiative imbalance at the top of the atmosphere, or the energy would have to come from other parts of the earth’s system. Neither is the case. It’s actually opposite: There is a positive radiation imbalance and other reservoirs (e.g. oceans, cryosphere) are also gaining more energy. Which makes sense, in the face of a radiative forcing.

Explaining the increase in global average temperatures by a mere ‘random walk’ would violate conservation of energy.

Ramanathan and Feng describe the earth’s radiation balance as follows:

So the process of the net incoming (downward solar energy minus the reflected) solar energy warming the system and the outgoing heat radiation from the warmer planet escaping to space goes on, until the two components of the energy are in balance. On an average sense, it is this radiation energy balance that provides a powerful constraint for the global average temperature of the planet.

I.e. The global average temperature only changes over climatic timescales (multiple decades or longer) if there is an imbalance in the radiation budget. As is now indeed the case. Climate is to a certain extent deterministic, irrespective of unit roots.

The presence/absence of a unit root (dependent on the nature of the assumed trend amongst other choices) does not disprove/prove that the extra greenhouse gases we put in the atmosphere are warming the planet.

Update: This discussion has focussed on global average air temperatures, but changes have been observed in many other parts of the earth system that point to a changing (warming) climate: Sea level rise, ocean heat content, ice sheets , sea ice, glaciers, ecosystems, radiation budget. A statement along the lines of ‘nothing anomalous is happening’ should take all these changes into account.

CO2 and temperature both increasing: D’Aleo’s attempt at falsification of AGW debunked

Below are two graphs of global average temperature and CO2 concentration. First I show the temperature anomaly from the three major datasets of surface temperature together with the CO2 concentration as measured at Mauna Loa since 1958:

The CO2 concentrations are plotted on a logarithmic axis because the temperature effect of CO2 is logarithmic. The 11 year running mean through the yearly temperature anomalies is given by the thick colored lines.

Before the 1970’s, the temperature trend was more or less flat for a few decades (see also the graphs in this earlier post). The strong increase in cooling aerosols (resulting from e.g. SO2 emissions) counteracted much of the greenhouse warming over that period. Since that time however, greenhouse forcing has been dominant, resulting in the temperature and CO2 trends following a similar pattern (at least over the multi-decadal timescale; short term variability is heavily influenced by e.g. El Nino/La Nina, major volcanic eruptions and other natural phenomena). A graph of the time evolution of relevant known climate forcings over the past 130 years can be found here.

A very popular graph that purportedly falsifies the whole “AGW dogma” is the following, showing unrelated trends of temperature and CO2 for a recent 11 year period. It’s been carefully crafted to create a certain impression:

However, this graph is entirely misleading:

– There are more factors than only CO2 that influence global average temperature.

– The expected trend in temperature does not necessarily rise above the expected level of yearly variability over the course of a decade.

– The graph purposefully starts at a record high temperature (1998) to maximize the visual impression of “falling temperatures”. It also strongly depends on the specific datasets used. This is a clear example of cherrypicking.

Using the same logic as this graph is based on, one could also falsify the theory of gravity by pointing to a bird in the sky (conveniently forgetting that there are more forces than gravity and that the bird has wings).

Is the increase in global average temperature just a ‘random walk’?

On the previous thread, a discussion ensued about whether the observed increase in global average temperature is just a ‘random walk’. A rundown (*):

– Anonymous commenter “VS” claims that according to some statistical method, the increase in global average temp is not statistically significant, and that global average temperature behaves like a ‘random walk’. Heiko confirms with a simple excel exercise that under the assumption of stacked cumulative errors a quantity can wander off in any direction in the absence of a forced trend.

– The practical relevance of VS’ claim escapes me in light of the graphs shown in the previous post. E.g. each single year of the past 30 years has been warmer than each single year between 1880 and 1930. Calling this merely coincidence makes me wonder, how lucky do you feel? (**) 

– The applicability of said statistic and of the assumption of stacked cumulative errors is questionable in light of the physical nature of the climate: Temperatures continuing to wander off towards warmer values without a change in radiative forcing as the driving factor would cause a negative energy imbalance, which would force the temperatures back to where they came from: Equilibration. There’s conservation of energy after all. In general, long term changes in global avg temp are the consequence of a non-zero radiative forcing, whereas temp juggle up and down without a clear trend if there is no net radiative forcing acting upon the system.

– The earth’s energy imbalance as measured from space and as deduced from adding up atmospheric and ocean heat content is actually positive: More energy is coming in than radiating back into space (***). This directly contradicts that the increase in global average temperature would be random (since in that case we would expect a negative energy imbalance)

– Radiative forcing of climate is reasonably well known (at least that of the greenhouse gases and of natural forcings such as changes in the output of the sun; much less so for aerosols). The net forcing is positive, so we know that the temperature is being pushed into the warmer direction. I.e. we know that it in this case the warming isn’t random. The question is then: Could such a warming theoretically be observed even in the absence of a forcing? I think not, for the physical reasons stated above (equilibration). But it’s a bit like asking if the bike could have moved downhill all by itself, even if you see that someone is riding the bike downhill. Interesting question for a late night drink at the bar, but not very relevant to the question of how the bike got to the bottom of the hill. Let me add though that understanding the nature of natural variability in global temperatures is definitely important, and the discussion in the previous thread was definitely thought provoking.

– Changes in atmospheric temperatures are not the only sign of a warming climate. There is the increase in ocean heat content, decrease in Arctic sea ice, thinning of Greenland and Antarctic ice sheets, retreat of glaciers, changes in ecology (e.g. growing season, blooming of flowers, etc), sea level rise, etc. Is this all coincidence? How lucky do you feel?

(*): I’ll admit that my knowledge of statistics is not such that I can argue the details of a statistical analysis. Instead, I’ll argue mostly from a physical perspective. I think that’s entirely appropriate –necessary even- in trying to understand a physical system. Conservation of energy is probably a sufficient reason to dismiss the idea of a random walk in temperatures.

(**): If you feel lucky, you may want to arrange a bet about future warming (or lack thereof) with e.g. James Annan or Brian Schmidt.

(***): Satellite measurements of outgoing longwave radiation find an enhanced greenhouse effect (Harries 2001, Griggs 2004, Chen 2007). This result is consistent with measurements from the Earth’s surface observing more infrared radiation returning back to the surface (Wang 2009, Philipona 2004, Evans 2006). Consequently, our planet is experiencing a build-up of heat (Murphy 2009). These findings provide ”direct experimental evidence for a significant increase in the Earth’s greenhouse effect that is consistent with concerns over radiative forcing of climate“

Update: Related discussions of the chaotic nature of climate here, here and here. Tamino chimes in as well.

Global average temperature increase GISS HadCRU and NCDC compared

I made some graphs of global temperature change according to the three major compilations based on measured surface temperatures: GISS, HadCRU and NCDC. They are expressed as the temperature difference (“anomaly”) with respect to the 1901-2000 average as the baseline.

Temperatures jiggle up and down, but the overall trend is up: The globe is warming.

To highlight the long term trend more clearly, below the same figure with in addition the 11 year running mean (which stops 5 years short of each endpoint for lack of data to calculate the mean):

Some people prefer you to only look at the last dozen of years:

Often, the last datapoint (representing 2009) is omitted, and only HadCRU temperatures (in blue) are shown, to create the most visually compelling picture for claiming that “global warming has stopped” or even reversed (“blogal cooling”, pun intended).

If however we look at the trend through the average of the three datasets over the period 1975-2009 (during which greenhouse gas forcing was the dominant driver of climate change), we see the following:

The trend over 1975 to 2009 is approximately the same (0.17 +/- 0.03 degrees per decade) for all three temperature series.

The error represents the 95% confidence interval for the trend, i.e. if you were to repeat the trend analysis a hundred times on the real underlying data, 95 times you would find that the trend is within the range 0.14 to 0.20 degrees per decade.

The thin black lines represent the 95% confidence “predictions bands” for the data: Based on the observed variability, 95% of the data are expected to fall within these lines.

The observed yearly variability in global temperatures (sometimes exceeding 0.2 degrees) is such that 10 years is too short to discern the underlying long term trend (0.17 degrees per decade). There is no sign that the warming trend of the past 35 years has recently stopped or reversed.

 More info:

A major difference between the datasets is that HadCRU omits the arctic (in effect assuming that is warms as the global average), while GISS estimates it by interpolation. I don’t know about NCDC. See also RealClimate and James Hansen.

Similar analysis of GISS, HadCRU and NCDC temperatures up to 2007 by Tamino. Other nifty analyses by Tamino relating to the same theme can be found here, here, here and here.

1998 was a record warm year in large part because of a very strong El Nino event. If the effect of the ENSO cycle is removed, the warming trend becomes even more apparent, see e.g. RealClimate. Other rebuttals of the spurious 1998-claim at SkepticalScience, Coby Beck, Zeke Hausfather, RealClimate, Scott Mandia, Greenfyre (including lots more links) and Peter Sinclair of the denial crock of the week youtube videoseries.

Four independent statisticians were given the data (up to 2008) and asked to look for trends, without being told what the numbers represented. Not surprisingly, they found no evidence of a downward trend. Story retold e.g. here and here.

Robert Grumbine explains the art of cherrypicking and why it is not science.

Update: If you want higher resolution versions of any of the figures here you can email me via the link on the right (under “pages”).

RealClimate on the IPCC errors and their significance

RealClimate has a good post on the recent string of (alleged) errors in the IPCC report. It explains the IPCC proces, the nature and significance of the errors, and highlights the spin put on them by several media outlets.

Excerpt about the reported amount of land in the Netherlands that is below sea level:

Sea level in the Netherlands: The WG2 report states that “The Netherlands is an example of a country highly susceptible to both sea-level rise and river flooding because 55% of its territory is below sea level”. This sentence was provided by a Dutch government agency – the Netherlands Environmental Assessment Agency, which has now published a correction stating that the sentence should have read “55 per cent of the Netherlands is at risk of flooding; 26 per cent of the country is below sea level, and 29 per cent is susceptible to river flooding”. It surely will go down as one of the more ironic episodes in its history when the Dutch parliament last Monday derided the IPCC, in a heated debate, for printing information provided by … the Dutch government. In addition, the IPCC notes that there are several definitions of the area below sea level. The Dutch Ministry of Transport uses the figure 60% (below high water level during storms), while others use 30% (below mean sea level). Needless to say, the actual number mentioned in the report has no bearing on any IPCC conclusions and has nothing to do with climate science, and it is questionable whether it should even be counted as an IPCC error.

 And wrapping up the context of this whole manufacured controversy:

Do the above issues suggest “politicized science”, deliberate deceptions or a tendency towards alarmism on the part of IPCC? We do not think there is any factual basis for such allegations. To the contrary, large groups of (inherently cautious) scientists attempting to reach a consensus in a societally important collaborative document is a prescription for reaching generally “conservative” conclusions. And indeed, before the recent media flash broke out, the real discussion amongst experts was about the AR4 having underestimated, not exaggerated, certain aspects of climate change. These include such important topics as sea level rise and sea ice decline (see the sea ice and sea level chapters of the Copenhagen Diagnosis), where the data show that things are changing faster than the IPCC expected.