IPCC Scientists Caught Producing False Data To Push Global Warming

[KILLER_CLOWN]

Al Gore-linked Goddard Institute claimed “hottest October on record” after using temperature figures from September



Paul Joseph Watson
Prison Planet.com
Monday, November 17, 2008

Climate scientists allied with the IPCC have been caught citing fake data to make the case that global warming is accelerating, a shocking example of mass public deception that could spell the beginning of the end for the acceptance of man-made climate change theories.

On Monday, NASA’s Goddard Institute for Space Studies (GISS), run by Al Gore’s chief scientific ally, Dr James Hansen, announced that last month was the hottest October on record.

“This was startling,” reports the London Telegraph. “Across the world there were reports of unseasonal snow and plummeting temperatures last month, from the American Great Plains to China, and from the Alps to New Zealand. China’s official news agency reported that Tibet had suffered its “worst snowstorm ever”. In the US, the National Oceanic and Atmospheric Administration registered 63 local snowfall records and 115 lowest-ever temperatures for the month, and ranked it as only the 70th-warmest October in 114 years.”

It soon came to light that the data produced by NASA to make the claim, and in particular temperature records covering large areas of Russia, was merely carried over from the previous month. NASA had used temperature records from the naturally hotter month of September and claimed they represented temperature figures in October.


When NASA was confronted with this glaring error, they then attempted to compensate for the lower temperatures in Russia by claiming they had discovered a new “hotspot” in the Arctic, despite satellite imagery clearly showing that Arctic sea ice had massively expanded its coverage by 30 per cent, an area the size of Germany, since summer 2007.

The figures published by Dr Hansen’s institute are one of the primary sets of data used by the IPCC to promote its case for man-made global warming and they are widely quoted because they consistently show higher temperatures than other figures.

“Yet last week’s latest episode is far from the first time Dr Hansen’s methodology has been called in question,” reports the Telegraph. “In 2007 he was forced by Mr Watts and Mr McIntyre to revise his published figures for US surface temperatures, to show that the hottest decade of the 20th century was not the 1990s, as he had claimed, but the 1930s.”

Dr Rajendra Pachauri, chairman of the IPCC and a close ally of Hansen, also raised eyebrows recently during a presentation in Australia, during which he claimed that global temperatures have recently been rising “very much faster” than ever as he cited a graph showing purported temperature increases over the last decade. In fact, as even the vast majority of man-made global warming advocates will concede, temperatures since 1998 have moved sideways and over the last 18 months they have clearly begun a downward trend.

Whether such “mistakes” are made in genuine error or are part of a politicized push for man-made global warming to be universally accepted, and the evidence clearly suggests that latter is the case, the fact is that we can no longer tolerate the cry that “the debate is over” on man-made global warming in light of such gargantuan falsehoods.

Likewise, the push for carbon emissions to be reduced by 80 per cent or more, a figure that would completely cripple western economies and lower living standards to a near third world level, can no longer be accepted as a reasonable course of action now that the primary authority on man-made global warming, the UN IPCC, has been proven to be using fraudulent data to make its case.

Foisted upon the public by means of giant multi-million dollar PR campaigns and brainwashing mandates that have worked themselves into every sector of society, including education, movies, television the arts and culture, all the attention and funding is being lavished upon a manufactured hoax, peddled with the aid of phony data, as governments prepare to suck what’s left out of the middle class and poor with carbon taxes that do nothing to help the environment, while all the real environmental problems are left in the shadows.

http://www.prisonplanet.com/ipcc-scientists-caught-producing-false-data-to-push-global-warming.html

[StcChief]

well Al Gore, that Carbon Credit company, and Global warming stuff..... maybe it's your greed to a new corporation. Now give back the Nobel Prize.

[tiptap]

Two days, that is how long before the information was discovered and taken down. And guess who was the culprit. Well it was mainly RUSSIA. Somehow the Russian data, and some other that was collated, ended up submitting the previous months data as October. What happens with the Arctic data is an extrapolation in part from that Russian Siberian data set. So this is pretty old news. It involves one month. Get over it.

[jAZ]

ROFL @ "producing false data"

[MagicHef]

The figures published by Dr Hansen’s institute are one of the primary sets of data used by the IPCC to promote its case for man-made global warming and they are widely quoted because they consistently show higher temperatures than other figures.


Really? This was never questioned? When you are trying to make a conclusion from data, you don't use the outliers.

[SHTSPRAYER]

Really? This was never questioned? When you are trying to make a conclusion from data, you don't use the outliers.

Moonbats do.

[Mr. Kotter]

No way!!!! :spock:

I'm shocked. Shocked, I say.

[PhillyChiefFan]

When NASA was confronted with this glaring error, they then attempted to compensate for the lower temperatures in Russia by claiming they had discovered a new “hotspot” in the Arctic, despite satellite imagery clearly showing that Arctic sea ice had massively expanded its coverage by 30 per cent, an area the size of Germany, since summer 2007.


“In 2007 he was forced by Mr Watts and Mr McIntyre to revise his published figures for US surface temperatures, to show that the hottest decade of the 20th century was not the 1990s, as he had claimed, but the 1930s.”


How is this just now coming out? I can't believe that Artic ice actually expanded, How could they make such a bold statements without substantial, definitive, and reviewable evidence?

I was under the impression that IPCC findings were almost universally backed by most scientists. Are the scientists that now causing the IPCC to refute this evidence working independantly or are they on the payroll of an oil company or something?

For the record, I was taking this information at face value, because I am relatively ignorant about the subject and assumed the 'scientific findings' were reality.

[orange]

How is this just now coming out? I can't believe that Artic ice actually expanded, How could they make such a bold statements without substantial, definitive, and reviewable evidence?



Because Paul Joseph Watson (prisonplanet.com) lied. That article is basically plagiarized from the Telegraph article - with certain omissions.

The original paragraph that applies here reads:

The error was so glaring that when it was reported on the two blogs - run by the US meteorologist Anthony Watts and Steve McIntyre, the Canadian computer analyst who won fame for his expert debunking of the notorious "hockey stick" graph - GISS began hastily revising its figures. This only made the confusion worse because, to compensate for the lowered temperatures in Russia, GISS claimed to have discovered a new "hotspot" in the Arctic - in a month when satellite images were showing Arctic sea-ice recovering so fast from its summer melt that three weeks ago it was 30 per cent more extensive than at the same time last year.

[emphasis added]

NOT an overall recovery from its decades-long shrinkage - which is the inference Watson wants you to make.

The original: http://www.telegraph.co.uk/opinion/main.jhtml?xml=/opinion/2008/11/16/do1610.xml

[PhillyChiefFan]

Because Paul Joseph Watson (prisonplanet.com) lied. That article is basically plagiarized from the Telegraph article - with certain omissions.

The original paragraph that applies here reads:

The error was so glaring that when it was reported on the two blogs - run by the US meteorologist Anthony Watts and Steve McIntyre, the Canadian computer analyst who won fame for his expert debunking of the notorious "hockey stick" graph - GISS began hastily revising its figures. This only made the confusion worse because, to compensate for the lowered temperatures in Russia, GISS claimed to have discovered a new "hotspot" in the Arctic - in a month when satellite images were showing Arctic sea-ice recovering so fast from its summer melt that three weeks ago it was 30 per cent more extensive than at the same time last year.

[emphasis added]

NOT an overall recovery from its decades-long shrinkage - which is the inference Watson wants you to make.

The original: http://www.telegraph.co.uk/opinion/main.jhtml?xml=/opinion/2008/11/16/do1610.xml

That makes A LOT more sense. I could not believe that such a big error could be intentionally made.

Thanks for the post and the link :)

[tiptap]

Al Gore-linked Goddard Institute claimed “hottest October on record” after using temperature figures from September



Paul Joseph Watson
Prison Planet.com
Monday, November 17, 2008


The figures published by Dr Hansen’s institute are one of the primary sets of data used by the IPCC to promote its case for man-made global warming and they are widely quoted because they consistently show higher temperatures than other figures.

“Yet last week’s latest episode is far from the first time Dr Hansen’s methodology has been called in question,” reports the Telegraph. “In 2007 he was forced by Mr Watts and Mr McIntyre to revise his published figures for US surface temperatures, to show that the hottest decade of the 20th century was not the 1990s, as he had claimed, but the 1930s.”

http://www.prisonplanet.com/ipcc-scientists-caught-producing-false-data-to-push-global-warming.html

Here is a bold face lie. The data about 1930's and 1990's is different than a discussion of finding the consecutive 10 years averaging the highest temperatures. It is true that FOR THE UNITED STATES, the 1930's is warmer decade than the 1990's. But that is not true FOR THE WORLD DATA.

Here are both graphs of the US and World data over this time scale.

And as far as polar ice measurements, there are area measurements and there are volume measurements. The area measurements are what is stated as evidence of recovery but the volume measurements, that would include Naval submarine data for the last 50 years plus gravimetric measurements, all indicate a loss in mass over this period of time.

Finally for all of you, me included, that put the sun as the primary driver of temperature, and your favorite Solar Sun Spot theory puts this period of time as an EBB in solar sun spots and therefore energy reaching the earth. We might expect a pause in temperatures rising at this point. That pause will cease as sunspot activity picks up again.

http://www.prisonplanet.com/ipcc-scientists-caught-producing-false-data-to-push-global-warming.html[/QUOTE]

[cookster50]

Because Paul Joseph Watson (prisonplanet.com) lied. That article is basically plagiarized from the Telegraph article - with certain omissions.

The original paragraph that applies here reads:

The error was so glaring that when it was reported on the two blogs - run by the US meteorologist Anthony Watts and Steve McIntyre, the Canadian computer analyst who won fame for his expert debunking of the notorious "hockey stick" graph - GISS began hastily revising its figures. This only made the confusion worse because, to compensate for the lowered temperatures in Russia, GISS claimed to have discovered a new "hotspot" in the Arctic - in a month when satellite images were showing Arctic sea-ice recovering so fast from its summer melt that three weeks ago it was 30 per cent more extensive than at the same time last year.

[emphasis added]

NOT an overall recovery from its decades-long shrinkage - which is the inference Watson wants you to make.

The original: http://www.telegraph.co.uk/opinion/main.jhtml?xml=/opinion/2008/11/16/do1610.xml


So, this statement here:
massively expanded its coverage by 30 per cent, an area the size of Germany, since summer 2007.
is misleading? It CLEARLY states the expansion was since the summer of 2007. How the Herm is that misleading?

[orange]

So, this statement here:

is misleading? It CLEARLY states the expansion was since the summer of 2007. How the Herm is that misleading?

Because it LEAVES OUT that it's recovering from its summer melt - like it always does. It's lying by omission. Read message #8 above to see the take Watson is clearly aiming for. He clearly wants you to believe there's been a continuous expansion since 2007.

[KILLER_CLOWN]

So, this statement here:

is misleading? It CLEARLY states the expansion was since the summer of 2007. How the Herm is that misleading?

Arctic Ice Grows 30 Per Cent In a Year



Predictions of “ice free” summer for first time in history completely debunked
Paul Joseph Watson
Prison Planet
Tuesday, August 19, 2008

Alarmist scientists who predicted that the North Pole could be “ice free” this summer as a result of global warming have been embarrassed after it was revealed that Arctic ice has actually grown by around 30 per cent in the year since August 2007.

Back in June, numerous prominent voices in the scientific community expressed fears of a mass melting of the polar ice caps, including David Barber, of the University of Manitoba, who told National Geographic Magazine, “We’re actually projecting this year that the North Pole may be free of ice for the first time [in history].”

“This summer’s forecast—and unusual early melting events all around the Arctic—serve as a dire warning of how quickly the polar regions are being affected by climate change,” adds the article.

In February, Dr. Olav Orheim, head of the Norwegian International Polar Year Secretariat, told Xinhua, “If Norway’s average temperature this year equals that in 2007, the ice cap in the Arctic will all melt away, which is highly possible judging from current conditions.”

As per usual, the reality has failed to match the hype of the climate doomsayers.

According to collated data from the NASA Marshall Space Flight Center and the University of Illinois, Arctic ice extent was 30 per cent greater on August 11, 2008 than it was on the August 12, 2007. This is a conservative estimate based on the map projection.

Blue pixels represent increased ice coverage over the North Pole in the year since August 2007.

The video below highlights the differences between those two dates,” reports The Register. “As you can see, ice has grown in nearly every direction since last summer - with a large increase in the area north of Siberia. Also note that the area around the Northwest Passage (west of Greenland) has seen a significant increase in ice. Some of the islands in the Canadian Archipelago are surrounded by more ice than they were during the summer of 1980.”

<object width="425" height="344"><param name="movie" value="http://www.youtube.com/v/cKLiHWRaJU4&hl=en&fs=1"></param><param name="allowFullScreen" value="true"></param><param name="allowscriptaccess" value="always"></param><embed src="http://www.youtube.com/v/cKLiHWRaJU4&hl=en&fs=1" type="application/x-shockwave-flash" allowscriptaccess="always" allowfullscreen="true" width="425" height="344"></embed></object>

But what of the Antarctic down south? Figures tell us that ice coverage in the year since August 2007 has grown by nearly one million square kilometers.

As The Register article notes, “The Arctic did not experience the meltdowns forecast by NSIDC and the Norwegian Polar Year Secretariat. It didn’t even come close. Additionally, some current graphs and press releases from NSIDC seem less than conservative. There appears to be a consistent pattern of overstatement related to Arctic ice loss.”

A general cooling trend across the planet is now clearly apparent as sunspot activity, the main driver of climate change, dwindles to almost nothing.

As we reported last week, A top observatory that has been measuring sun cycles for over 200 years predicts that global temperatures will drop by two degrees over the next two decades as solar activity grinds to a halt and the planet drastically cools down, potentially heralding the onset of a new ice age.

While the mass media, Al Gore and politicized bodies like the IPCC scaremonger about the perils of global warming and demand the poor and middle class pay CO2 taxes, both hard scientific data and circumstantial evidence points to a clear cooling trend.

How man-made global warming advocates will spin this one remains to be seen - maybe they will just continue to adopt their current tactic by claiming that any geological or weather event whatsoever, be it hurricanes, earthquakes, droughts or floods, temperature increase or decrease, and even a 30 per cent growth of the polar ice cap - is a result of that evil life-giving gas that we exhale - CO2.

http://www.prisonplanet.com/arctic-ice-grows-30-per-cent-in-a-year.html

[tiptap]

http://www.realclimate.org/index.php/archives/2008/11/mountains-and-molehills/

As many people will have read there was a glitch in the surface temperature record reporting for October. For many Russian stations (and some others), September temperatures were apparently copied over into October, giving an erroneous positive anomaly. The error appears to have been made somewhere between the reporting by the National Weather Services and NOAA's collation of the GHCN database. GISS, which produces one of the more visible analyses of this raw data, processed the input data as normal and ended up with an October anomaly that was too high. That analysis has now been pulled (in under 24 hours) while they await a correction of input data from NOAA (Update: now (partially) completed).

There were 90 stations for which October numbers equalled September numbers in the corrupted GHCN file for 2008 (out of 908). This compares with an average of about 16 stations each year in the last decade (some earlier years have bigger counts, but none as big as this month, and are much less as a percentage of stations). These other cases seem to be mostly legitimate tropical stations where there isn't much of a seasonal cycle. That makes it a little tricky to automatically scan for this problem, but putting in a check for the total number or percentage is probably sensible going forward.

It's clearly true that the more eyes there are looking, the faster errors get noticed and fixed. The cottage industry that has sprung up to examine the daily sea ice numbers or the monthly analyses of surface and satellite temperatures, has certainly increased the number of eyes and that is generally for the good. Whether it's a discovery of an odd shift in the annual cycle in the UAH MSU-LT data, or this flub in the GHCN data, or the USHCN/GHCN merge issue last year, the extra attention has led to improvements in many products. Nothing of any consequence has changed in terms of our understanding of climate change, but a few more i's have been dotted and t's crossed.

But unlike in other fields of citizen-science (astronomy or phenology spring to mind), the motivation for the temperature observers is heavily weighted towards wanting to find something wrong. As we discussed last year, there is a strong yearning among some to want to wake up tomorrow and find that the globe hasn't been warming, that the sea ice hasn't melted, that the glaciers have not receded and that indeed, CO2 is not a greenhouse gas. Thus when mistakes occur (and with science being a human endeavour, they always will) the exuberance of the response can be breathtaking - and quite telling.

A few examples from the comments at Watt's blog will suffice to give you a flavour of the conspiratorial thinking: "I believe they had two sets of data: One would be released if Republicans won, and another if Democrats won.", "could this be a sneaky way to set up the BO presidency with an urgent need to regulate CO2?", "There are a great many of us who will under no circumstance allow the oppression of government rule to pervade over our freedom—-PERIOD!!!!!!" (exclamation marks reduced enormously), "these people are blinded by their own bias", "this sort of scientific fraud", "Climate science on the warmer side has degenerated to competitive lying", etc… (To be fair, there were people who made sensible comments as well).

The amount of simply made up stuff is also impressive - the GISS press release declaring the October the 'warmest ever'? Imaginary (GISS only puts out press releases on the temperature analysis at the end of the year). The headlines trumpeting this result? Non-existent. One clearly sees the relief that finally the grand conspiracy has been rumbled, that the mainstream media will get it's comeuppance, and that surely now, the powers that be will listen to those voices that had been crying in the wilderness.

Alas! none of this will come to pass. In this case, someone's programming error will be fixed and nothing will change except for the reporting of a single month's anomaly. No heads will roll, no congressional investigations will be launched, no politicians (with one possible exception) will take note. This will undoubtedly be disappointing to many, but they should comfort themselves with the thought that the chances of this error happening again has now been diminished. Which is good, right?

In contrast to this molehill, there is an excellent story about how the scientific community really deals with serious mismatches between theory, models and data. That piece concerns the 'ocean cooling' story that was all the rage a year or two ago. An initial analysis of a new data source (the Argo float network) had revealed a dramatic short term cooling of the oceans over only 3 years. The problem was that this didn't match the sea level data, nor theoretical expectations. Nonetheless, the paper was published (somewhat undermining claims that the peer-review system is irretrievably biased) to great acclaim in sections of the blogosphere, and to more muted puzzlement elsewhere. With the community's attention focused on this issue, it wasn't however long before problems turned up in the Argo floats themselves, but also in some of the other measurement devices - particularly XBTs. It took a couple of years for these things to fully work themselves out, but the most recent analyses show far fewer of the artifacts that had plagued the ocean heat content analyses in the past. A classic example in fact, of science moving forward on the back of apparent mismatches. Unfortunately, the resolution ended up favoring the models over the initial data reports, and so the whole story is horribly disappointing to some.

Which brings me to my last point, the role of models. It is clear that many of the temperature watchers are doing so in order to show that the IPCC-class models are wrong in their projections. However, the direct approach of downloading those models, running them and looking for flaws is clearly either too onerous or too boring. Even downloading the output (from here or here) is eschewed in favour of firing off Freedom of Information Act requests for data already publicly available - very odd. For another example, despite a few comments about the lack of sufficient comments in the GISS ModelE code (a complaint I also often make), I am unaware of anyone actually independently finding any errors in the publicly available Feb 2004 version (and I know there are a few). Instead, the anti-model crowd focuses on the minor issues that crop up every now and again in real-time data processing hoping that, by proxy, they'll find a problem with the models.

I say good luck to them. They'll need it.

[tiptap]

http://www.realclimate.org/index.php/archives/2008/11/faq-on-climate-models/

We discuss climate models a lot, and from the comments here and in other forums it's clear that there remains a great deal of confusion about what climate models do and how their results should be interpreted. This post is designed to be a FAQ for climate model questions - of which a few are already given. If you have comments or other questions, ask them as concisely as possible in the comment section and if they are of enough interest, we'll add them to the post so that we can have a resource for future discussions. (We would ask that you please focus on real questions that have real answers and, as always, avoid rhetorical excesses).
Quick definitions:

* GCM - General Circulation Model (sometimes Global Climate Model) which includes the physics of the atmosphere and often the ocean, sea ice and land surface as well.
* Simulation - a single experiment with a GCM
* Initial Condition Ensemble - a set of simulations using a single GCM but with slight perturbations in the initial conditions. This is an attempt to average over chaotic behaviour in the weather.
* Multi-model Ensemble - a set of simulations from multiple models. Surprisingly, an average over these simulations gives a better match to climatological observations than any single model.
* Model weather - the path that any individual simulation will take has very different individual storms and wave patterns than any other simulation. The model weather is the part of the solution (usually high frequency and small scale) that is uncorrelated with another simulation in the same ensemble.
* Model climate - the part of the simulation that is robust and is the same in different ensemble members (usually these are long-term averages, statistics, and relationships between variables).
* Forcings - anything that is imposed from the outside that causes a model's climate to change.
* Feedbacks - changes in the model that occur in response to the initial forcing that end up adding to (for positive feedbacks) or damping (negative feedbacks) the initial response. Classic examples are the amplifying ice-albedo feedback, or the damping long-wave radiative feedback.

Questions:

* What is the difference between a physics-based model and a statistical model?

Models in statistics or in many colloquial uses of the term often imply a simple relationship that is fitted to some observations. A linear regression line through a change of temperature with time, or a sinusoidal fit to the seasonal cycle for instance. More complicated fits are also possible (neural nets for instance). These statistical models are very efficient at encapsulating existing information concisely and as long as things don't change much, they can provide reasonable predictions of future behaviour. However, they aren't much good for predictions if you know the underlying system is changing in ways that might possibly affect how your original variables will interact.

Physics-based models on the other hand, try to capture the real physical cause of any relationship, which hopefully are understood at a deeper level. Since those fundamentals are not likely to change in the future, the anticipation of a successful prediction is higher. A classic example is Newton's Law of motion, F=ma, which can be used in multiple contexts to give highly accurate results completely independently of the data Newton himself had on hand.

Climate models are fundamentally physics-based, but some of the small scale physics is only known empirically (for instance, the increase of evaporation as the wind increases). Thus statistical fits to the observed data are included in the climate model formulation, but these are only used for process-level parameterisations, not for trends in time.


* Are climate models just a fit to the trend in the global temperature data?

No. Much of the confusion concerning this point comes from a misunderstanding stemming from the point above. Model development actually does not use the trend data in tuning (see below). Instead, modellers work to improve the climatology of the model (the fit to the average conditions), and it's intrinsic variability (such as the frequency and amplitude of tropical variability). The resulting model is pretty much used 'as is' in hindcast experiments for the 20th Century.


* Why are there 'wiggles' in the output?

GCMs perform calculations with timesteps of about 20 to 30 minutes so that they can capture the daily cycle and the progression of weather systems. As with weather forecasting models, the weather in a climate model is chaotic. Starting from a very similar (but not identical) state, a different simulation will ensue - with different weather, different storms, different wind patterns - i.e different wiggles. In control simulations, there are wiggles at almost all timescales - daily, monthly, yearly, decadally and longer - and modellers need to test very carefully how much of any change that happens because of a change in forcing is really associated with that forcing and how much might simply be due to the internal wiggles.


* What is robust in a climate projection and how can I tell?

Since every wiggle is not necessarily significant, modellers need to assess how robust particular model results are. They do this by seeing whether the same result is seen in other simulations, with other models, whether it makes physical sense and whether there is some evidence of similar things in the observational or paleo record. If that result is seen in multiple models and multiple simulations, it is likely to be a robust consequence of the underlying assumptions, or in other words, it probably isn't due to any of the relatively arbitrary choices that mark the differences between different models. If the magnitude of the effect makes theoretical sense independent of these kinds of model, then that adds to it's credibility, and if in fact this effect matches what is seen in observations, then that adds more. Robust results are therefore those that quantitatively match in all three domains. Examples are the warming of planet as a function of increasing greenhouse gases, or the change in water vapour with temperature. All models show basically the same behaviour that is in line with basic theory and observations. Examples of non-robust results are the changes in El Niño as a result of climate forcings, or the impact on hurricanes. In both of these cases, models produce very disparate results, the theory is not yet fully developed and observations are ambiguous.


* How have models changed over the years?

Initially (ca. 1975), GCMs were based purely on atmospheric processes - the winds, radiation, and with simplified clouds. By the mid-1980s, there were simple treatments of the upper ocean and sea ice, and clouds parameterisations started to get slightly more sophisticated. In the 1990s, fully coupled ocean-atmosphere models started to become available. This is when the first Coupled Model Intercomparison Project (CMIP) was started. This has subsequently seen two further iterations, the latest (CMIP3) being the database used in support of much of the model work in the IPCC AR4. Over that time, model simulations have become demonstrably more realistic (Reichler and Kim, 2008) as resolution has increased and parameterisations have become more sophisticated. Nowadays, models also include dynamic sea ice, aerosols and atmospheric chemistry modules. Issues like excessive 'climate drift' (the tendency for a coupled model to move away from the a state resembling the actual climate) which were problematic in the early days are now much minimised.


* What is tuning?

We are still a long way from being able to simulate the climate with a true first principles calculation. While many basic aspects of physics can be included (conservation of mass, energy etc.), many need to be approximated for reasons of efficiency or resolutions (i.e. the equations of motion need estimates of sub-gridscale turbulent effects, radiative transfer codes approximate the line-by-line calculations using band averaging), and still others are only known empirically (the formula for how fast clouds turn to rain for instance). With these approximations and empirical formulae, there is often a tunable parameter or two that can be varied in order to improve the match to whatever observations exist. Adjusting these values is described as tuning and falls into two categories. First, there is the tuning in a single formula in order for that formula to best match the observed values of that specific relationship. This happens most frequently when new parameterisations are being developed.

Secondly, there are tuning parameters that control aspects of the emergent system. Gravity wave drag parameters are not very constrained by data, and so are often tuned to improve the climatology of stratospheric zonal winds. The threshold relative humidity for making clouds is tuned often to get the most realistic cloud cover and global albedo. Surprisingly, there are very few of these (maybe a half dozen) that are used in adjusting the models to match the data. It is important to note that these exercises are done with the mean climate (including the seasonal cycle and some internal variability) - and once set they are kept fixed for any perturbation experiment.

* How are models evaluated?

The amount of data that is available for model evaluation is vast, but falls into a few clear categories. First, there is the climatological average (maybe for each month or season) of key observed fields like temperature, rainfall, winds and clouds. This is the zeroth order comparison to see whether the model is getting the basics reasonably correct. Next comes the variability in these basic fields - does the model have a realistic North Atlantic Oscillation, or ENSO, or MJO. These are harder to match (and indeed many models do not yet have realistic El Niños). More subtle are comparisons of relationships in the model and in the real world. This is useful for short data records (such as those retrieves by satellite) where there is a lot of weather noise one wouldn't expect the model to capture. In those cases, looking at the relationship between temperatures and humidity, or cloudiness and aerosols can give insight into whether the model processes are realistic or not.

Then there are the tests of climate changes themselves: how does a model respond to the addition of aerosols in the stratosphere such as was seen in the Mt Pinatubo 'natural experiment'? How does it respond over the whole of the 20th Century, or at the Maunder Minimum, or the mid-Holocene or the Last Glacial Maximum? In each case, there is usually sufficient data available to evaluate how well the model is doing.

* Are the models complete? That is, do they contain all the processes we know about?

No. While models contain a lot of physics, they don't contain many small-scale processes that more specialised groups (of atmospheric chemists, or coastal oceanographers for instance) might worry about a lot. Mostly this is a question of scale (model grid boxes are too large for the details to be resolved), but sometimes it's a matter of being uncertain how to include it (for instance, the impact of ocean eddies on tracers).

Additionally, many important bio-physical-chemical cycles (for the carbon fluxes, aerosols, ozone) are only just starting to be incorporated. Ice sheet and vegetation components are very much still under development.

* Do models have global warming built in?

No. If left to run on their own, the models will oscillate around a long-term mean that is the same regardless of what the initial conditions were. Given different drivers, volcanoes or CO2 say, they will warm or cool as a function of the basic physics of aerosols or the greenhouse effect.

* How do I write a paper that proves that models are wrong?

Much more simply than you might think since, of course, all models are indeed wrong (though some are useful - George Box). Showing a mismatch between the real world and the observational data is made much easier if you recall the signal-to-noise issue we mentioned above. As you go to smaller spatial and shorter temporal scales the amount of internal variability increases markedly and so the number of diagnostics which will be different to the expected values from the models will increase (in both directions of course). So pick a variable, restrict your analysis to a small part of the planet, and calculate some statistic over a short period of time and you're done. If the models match through some fluke, make the space smaller, and use a shorter time period and eventually they won't. Even if models get much better than they are now, this will always work - call it the RealClimate theory of persistence. Now, appropriate statistics can be used to see whether these mismatches are significant and not just the result of chance or cherry-picking, but a surprising number of papers don't bother to check such things correctly. Getting people outside the, shall we say, more 'excitable' parts of the blogosphere to pay any attention is, unfortunately, a lot harder.

* Can GCMs predict the temperature and precipitation for my home?

No. There are often large variation in the temperature and precipitation statistics over short distances because the local climatic characteristics are affected by the local geography. The GCMs are designed to describe the most important lage-scale features of the climate, such as the energy flow, the circulation, and the temperature in a grid-box volume (through physical laws of themodynamics, the dynamics, and the ideal gas laws). A typical grid-box may have a horizontal area of ~100×100 km2, but the size has tended to reduce over the years as computers have increased in speed. The shape of the landscape (the details of mounatins, coastline etc.) used in the models reflect the spatial resolution, hence the model will not have sufficient detail to describe local climate variation associated with local geographical features (e.g. mountains, velleys, lakes, etc.). However, it is possible to use a GCM to derive some information about the local climate through downscaling, as it is affected by both the local geography (a more or less given constant) as well as the large-scale atmospheric conditions. The results derived through downscaling can then be compared with local climate variables, and can be used for further (and more severe) assessments of the combination model-downscaling technique. This is however still an experimental technique.

* Can I use a climate model myself?

Yes! There is a project called EdGCM which has a nice interface and works with Windows and lets you try out a large number of tests. ClimatePrediction.Net has a climate model that runs as a screensaver in a coordinated set of simulations. GISS ModelE is available as a download for Unix-based machines and can be run on a normal desktop. NCAR CCSM is the US community model and is well-documented and freely available.

[tiptap]

# Steve Horstmeyer Says:
3 November 2008 at 10:28 AM

As a television meteorologist I frequently encounter the comment that because climate models are using “bad” data they are biased and do not reflect reality, therefore cannot be trusted and global warming either does not exits or exists an there is no anthropogenic influence.

My approach is to explain that the models are not dependent on observed data. I also explain that given any set of initial weather conditions (wintin reason) a good model will eventually reproduce realistic climate patterns.

To simplify I restrict the initial conditions under consideration to global temperature only. My example usually sets global temperature to a uniform 10C (50F) with all other variables at realistic values. I tell the viewer that given this scenario, if run for a sufficient amount of time (both model time and computational time of course). the model will reproduce realistic global temperature distributions.

My experience with the curious but uneducated in climate science reinforces the “keep it simple” approach.

Ten celsius (50F) works well because that temperature seems to be too cool for equatorial regions and too warm for polar regions in the mind of the average viewer.

I then explain that a climate model, as the computations are made will warm equatorial regions and cool polar regions.

The point then is that the model is not dependent on the observed data and because it is a representation of the physical processes governing the climate system the model eventually gets earth’s climate to where it is.

Often this is as far as I can go without getting a blank stare. For those who remain with me, this point is a great jumping off point to discuss how the same thing can be done with greehhouse gas concentrations.

If initial conditions are a realistic representation of 1960 earth and the only change made is by increasing greenhouse gasses by the amount that can be attributed to human activity the planet warms.

I am still met with skepticism in some cases but I feel I have at least exposed members of the public to a very basic look at how this all works.

1. Anyone see a flaw in the reasoning above?
2. Anyone have suggestions for improving the approach?
3. Anyone have and idea for taking this approach farther?

Recall the average American is barely functionally literate in science so simple is important.

Thanks for your time,
Steve Horstmeyer

[Silock]

Models != reality

[jidar]

Models != reality

Well of course they don't.


But the entire thing that starts this whole global warming debate can be broken down into this simple simple line of reasoning.

1: Is CO2 a greenhouse gas?
That is to say, does it hold more heat than the other gases in the atmosphere? This is easy to test and the answer is that yes it does. This is not controversial.

2: Are CO2 levels in the atmosphere rising?
Again, yes this is an easy thing to test, and yes they are. This is not controversial.

Okay those two facts are indisputable and all sides agree on them.

Then we go and make a simple observation. We burn millions of lbs of fossil fuel every day on this planet and we know roughly how much CO2 burning it gives off, and the rising CO2 in the atmosphere matches the amount we're burning pretty closely.

So there, you've got man-made global warming. The only question is how much and what kind of effect does it have.

[tiptap]

All models are restricted views of existence. After all no object falls at 9.8 meters per second per second on earth as expected by Galilean Theory of Gravity. Air resistance provides a counter force to gravity. The Ideal Gas Law is central to our understanding of the relationship between Pressure, Volume and Temperature. But there are no ideal gases. In the physical model of the atmosphere one of the essential non Ideal Gas Behavior is the changes in state by water. But as a first order approximation the Ideal Gas Law works even for water vapor.

So if you don't think any equations from science have any validity then you are entitled to be dismissive in four words rather than refuting the science.

[KILLER_CLOWN]

All models are restricted views of existence. After all no object falls at 9.8 meters per second per second on earth as expected by Galilean Theory of Gravity. Air resistance provides a counter force to gravity. The Ideal Gas Law is central to our understanding of the relationship between Pressure, Volume and Temperature. But there are no ideal gases. In the physical model of the atmosphere one of the essential non Ideal Gas Behavior is the changes in state by water. But as a first order approximation the Ideal Gas Law works even for water vapor.

So if you don't think any equations from science have any validity then you are entitled to be dismissive in four words rather than refuting the science.

So you would argue if one fell from say 10 miles distance that the fall would kill you? I say it's the sudden stop at the end. ;) Sorry I couldn't resist.

[KILLER_CLOWN]

The world has never seen such freezing heat
By Christopher Booker
Last Updated: 12:01am GMT 16/11/2008



A surreal scientific blunder last week raised a huge question mark about the temperature records that underpin the worldwide alarm over global warming. On Monday, Nasa's Goddard Institute for Space Studies (GISS), which is run by Al Gore's chief scientific ally, Dr James Hansen, and is one of four bodies responsible for monitoring global temperatures, announced that last month was the hottest October on record.


A sudden cold snap brought snow to London in October
Read more from Christopher Booker
This was startling. Across the world there were reports of unseasonal snow and plummeting temperatures last month, from the American Great Plains to China, and from the Alps to New Zealand. China's official news agency reported that Tibet had suffered its "worst snowstorm ever". In the US, the National Oceanic and Atmospheric Administration registered 63 local snowfall records and 115 lowest-ever temperatures for the month, and ranked it as only the 70th-warmest October in 114 years.

So what explained the anomaly? GISS's computerised temperature maps seemed to show readings across a large part of Russia had been up to 10 degrees higher than normal. But when expert readers of the two leading warming-sceptic blogs, Watts Up With That and Climate Audit, began detailed analysis of the GISS data they made an astonishing discovery. The reason for the freak figures was that scores of temperature records from Russia and elsewhere were not based on October readings at all. Figures from the previous month had simply been carried over and repeated two months running.

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The error was so glaring that when it was reported on the two blogs - run by the US meteorologist Anthony Watts and Steve McIntyre, the Canadian computer analyst who won fame for his expert debunking of the notorious "hockey stick" graph - GISS began hastily revising its figures. This only made the confusion worse because, to compensate for the lowered temperatures in Russia, GISS claimed to have discovered a new "hotspot" in the Arctic - in a month when satellite images were showing Arctic sea-ice recovering so fast from its summer melt that three weeks ago it was 30 per cent more extensive than at the same time last year.

A GISS spokesman lamely explained that the reason for the error in the Russian figures was that they were obtained from another body, and that GISS did not have resources to exercise proper quality control over the data it was supplied with. This is an astonishing admission: the figures published by Dr Hansen's institute are not only one of the four data sets that the UN's Intergovernmental Panel on Climate Change (IPCC) relies on to promote its case for global warming, but they are the most widely quoted, since they consistently show higher temperatures than the others.

If there is one scientist more responsible than any other for the alarm over global warming it is Dr Hansen, who set the whole scare in train back in 1988 with his testimony to a US Senate committee chaired by Al Gore. Again and again, Dr Hansen has been to the fore in making extreme claims over the dangers of climate change. (He was recently in the news here for supporting the Greenpeace activists acquitted of criminally damaging a coal-fired power station in Kent, on the grounds that the harm done to the planet by a new power station would far outweigh any damage they had done themselves.)

Yet last week's latest episode is far from the first time Dr Hansen's methodology has been called in question. In 2007 he was forced by Mr Watts and Mr McIntyre to revise his published figures for US surface temperatures, to show that the hottest decade of the 20th century was not the 1990s, as he had claimed, but the 1930s.

Another of his close allies is Dr Rajendra Pachauri, chairman of the IPCC, who recently startled a university audience in Australia by claiming that global temperatures have recently been rising "very much faster" than ever, in front of a graph showing them rising sharply in the past decade. In fact, as many of his audience were aware, they have not been rising in recent years and since 2007 have dropped.

Dr Pachauri, a former railway engineer with no qualifications in climate science, may believe what Dr Hansen tells him. But whether, on the basis of such evidence, it is wise for the world's governments to embark on some of the most costly economic measures ever proposed, to remedy a problem which may actually not exist, is a question which should give us all pause for thought.


http://www.telegraph.co.uk/opinion/main.jhtml?xml=/opinion/2008/11/16/do1610.xml

[Silock]

So if you don't think any equations from science have any validity

Yeah, that's EXACTLY what I said. :shake:ROFL

All I'm saying is that in models, there are usually assumptions that are inaccurate that skew the results. And it usually takes someone saying "Holy crap - this assumption we made was wrong," to fix the models to make them more accurate.

[tiptap]

What is the difference between a model and an equation? The difference is the laboratory vs the environment. In a controlled settings you can isolate factors. And the result is that relationships can be found. But in a larger uncontrolled setting all the factors cannot be controlled. To say that the model is skewed than is false. It may not be correct because of a failing to represent all of the factors, but the model is not skewed. The term implies a statistical bias and weather models are not based upon statistical data. They are based upon Physical systems. If you start with the temperature at 50 degrees F (10 degrees C) all over the world a statistical projection would have temperatures around 50 all over the world. But a Physical System model does not. It moves to reflect warmer temperatures at the equator and cooler temperatures at the poles.

Your statement is meant to reflect a bias in the input of the model. One supposedly reflecting a false increase in temperatures because you think that these are statistical models.

If you wish to discuss the physics of the models then we can do that.