Michaelyya/contrarian-claims huggingface dataset:
Treering proxy temperature measurements from Yamal have a pronounced upturn that helps to create a hockey stick shape with the blade rising in the 20th Century. These were used in Kaufman 2009 to show the Arctic apparently warming fast after 2000 years of steady cooling. This warming starts after thermometer records started. The pattern should therefore show in the thermometer records, especially around Yamal. But it does not.
First, here is Figure 1, entitledHockey stick graph of rising global temperatures. Sharp-eyed readers will notice that the Figure goes to 1998 or so,and that it grafts the instrumental record after 1902 onto the proxy record before 1901, with the grafting not mentioned in the caption.
Unfortunately Die Zeit forgot to mention that the hockey stick had been debunked thoroughly by Steven McIntyre and Hans von Storch, who labelled the hockey stick chart nonsense, and that Andrew Montford wrote an entire book about the fraud: The Hockey Stick Illusion . They also failed to mention that the National Academy of Sciences had also called Manns methodology flawed.
Global warming science nemesis Steve McIntyre of the solid Climate Audit site calls the new paper by Rahmstorf and Mann making claims about Atlantic Ocean currents based on proxies rather than onmeasurements much worse than we thought .
Thanks for the reply. Ive seen the Jacoby-dArrigo references and, in fact, thats what occasioned my interest. It was included in their northern treeline index which seemed a little odd to me, since the site is far from the treeline. I also notice that the earliest portion of the chronology (not used by Jacoby and dArrigo) is based only on one tree. If you were doing the chronology today, would you include the portion based on only one tree in your site chronology? Also do you know (from past notes or otherwise) any details about potential logging or other forestry operations in the area?
Jaworowski illustrates this by comparing ice core data to other CO2 proxy data, such as stomata indices, which gives higher atmospheric CO2, with more variation than the ice core data over the last 8,000 years.
i.e. therefore tree rings are useless as a proxy to show that 20th Century temperature rises are unprecedented, and that there was no Medieval Warm Period, since they apparently dont respond to increases in temperature.
Even though his work was as dodgy as anyones I feel sorry for Briffa at times. He appears to develop a kind of Stockholm Syndrome towards the hectoring Mann. In his heart he is well aware of the flaws in Manns research and in the early years he is capable of mutiny. 1024334440 , 2002. I am sick to death of Mann stating his reconstruction represents the tropical area just because it contains a few (poorly temperature representative ) tropical series. He is just as capable of regressing these data again any other target series , such as the increasing trend of self-opinionated verbage he has produced over the last few years , and (better say no more). Cook sympathises: Of course, I agree with you. We both know the probable flaws in Mikes recon, particularly as it relates to the tropical stuff. It is puzzling to me that a guy as bright as Mike would be so unwilling to evaluate his own work a bit more objectively.
Leaving that aside, did Mann get it right? . There is no doubt that reconstructing past temperatures from proxy data is fraught with danger. Take tree ring records. They sometimes reflect rain or drought rather than temperature. They also get smaller as a tree gets older so annual or even decadal detail is lost.
In Mr. Wigleys view at the time, ice cores were unreliable and correlate very poorly with temperature. He said the link between ice core and temperature variation was close to zero and tree rings were less than 50% reliable. The main external candidate is solar, and more work is required to improve the paleo solar forcing record. Another U.S. scientist, Gary Funkhauser of the Laboratory of Tree-Ring Research at the University of Arizona, was also cool to the idea of tree rings as indicators of past temperatures. He wrote in September, 1996, that he tried every trick out of my sleeve to get meaningful climate records out of certain tree ring records collected by Russian scientist Stephan Shiyatov.
*Paleoclimate reconstructions capture quite well moderate long term variability of 50 years and more but fail to pick up the much more variable decadal variability
The process quickly gets complicated when proxies from many areas are brought together to map out ancient climate trends for a region. Because different proxies yield varying pictures of changes through time, some paleoclimate maps can look vague and generalized. It's also a matter of having enough computer power to handle not only the data, but to incorporate it with the oceanic, atmospheric, and other models, says Hughes.
Aside from solving the various crossword puzzles, the more fundamental issue is: is this a valid way of adjusting the Mannian PC1? Does it make any sense to try to adjust the PC1 (as opposed to the individual chronologies)? What if the growth pulse in the bristlecones was not related to CO2 fertilization ??? an effect denied by other writers in the field?
The blink comparator below shows the huge changes which have been made to the US temperature record since 1999. The past has been massively cooled, and the present has been massively warmed. A cooling trend has been turned into a warming trend, by adjusting the data.
Indeed, the preponderance of evidence from the officially manipulated temperature datasets indicates fabricated cooling adjustments being applied to periods pre-1980 and a fabricated warming since 1980.
Putting these two graphs side by side, you can see huge differences. What is going on? Why does NIWAs graph show strong warming, but graphing their own raw data looks completely different? Their graph shows warming, but the actual temperature readings show none whatsoever!
By these calculations (averaging the trend at each site) the raw trend is 0.35 degrees C per 100 years, and the state trend is 0.83C. Thats a warming bias of 133%!
Official Fake Temperatures By Climate Agencies: The Temperature Fabrication Issue Bigger Than Thought
Earths temperature system cannot be adequately measured or controlled. Mathematical criteria devised in the 1960s that ensure a system is measurable, observable and controllable are not satisfied.
A different way of looking at this is to normalize the two graphs to 1978, showing how they have massively cooled the past.
Remember this is 11 years after Hansen??s comments of certainty to the Senate and five years after the 1995 IPCC Report. It is worse now with fewer weather stations and less data than in 1990.
And this is why I have no doubt that most of what we see in the global temperature is just fractal noise. And here are some other important properties of fractal noise:
The blue line is how Hansen currently shows Phoenix a sharp warming trend. Apparently the UHI effect in Phoenix has disappeared since he wrote his 1999 paper. He cooled the past by about a degree and warmed the present by almost that much.
Several oddities have turned up, unexpected variations which seem to have a pattern relating to station and station geographical location. Some of this may be related to UHI and similar thermal mass / water effects.
If people reading iPhones can spot such problems and know the temperature data isn??t valid, and a citizen run CWOP program can use MADIS analysis of the data sight unseen and note it??s FUBAR, why can??t our meteorological experts at The Weather Channel figure it out?
Climate realists are generally willing to assume, for the sake of argument, that the Earth has warmed somewhat in recent decades. In fact, though, it is not obvious that even this modest claim is true. Satellite data show no net warming for as long as such data have been collected, i.e., back to 1979. Ocean measurements show no net warming over that period, either; the evidence for warming is based on land measurements. But the accuracy of land measurements depends on proper siting and maintenance of weather stations. One obvious factor is the urban heat island effect: many weather stations are located in cities, which grow warmer as more people and buildings accumulate. Thus, increasing temperatures at such stations may be measuring urban development rather than the climate. We all know that the urban heat island effect is realchance of frost in outlying areasyet the data that alarmists rely upon do not take it into account.
The adjustments do seem to be very aggressive in identifying any effects that might have artificially created a cooling trendbut lax in finding and correcting effects that mighthave artificially created a warming trend. First and foremost, the changing urban heat island effect in growing cities seems to be under-corrected (Again there is debate on this -- the proprietors of the model believe they have fixed this with a geographic normalizing, correcting biases from nearby thermometers. I and others believe all they are doing is mathematically smearing the error over a larger geography).
Weather stations can no longer be trusted. 90% of the 1,064 weather stations do not meet government standards because contamination is present.
But this comment, although it appeared, is now lost in the barrage. And Michael Getner, the PBS ombudsman, is backpedalling the role PBS played in allowing Watts to speak to their viewers. But as they say, when you are taking flak, it means youre over the target. Anthony Watts, through ordinary careful data collation and analysis, threatens the standing of NOAAs assertions about the integrity and accuracy of U.S. temperature records, and that has the alarmosphere in apoplexy.
In 1980, a paper by a senior New Zealand meteorologist (JWD Hessell), which was peer-reviewed and published in a reputable science journal, concluded that there was no evidence of New Zealand warming since 1930. The author found that the raw data overstated the extent of warming because thermometers had been affected by shelter, screenage and urbanisation. This directly contradicts the Salinger thesis.
The sooner these simple facts are acknowledged by responsible journalists the sooner reason will return to this important matter of public interest. Kiwis deserve to have a national temperature record they can trust but at the moment it is dubious.
Furthermore, Hansens models predicted the temperature rise if human carbon dioxide emissions were cut back drastically starting in 1988, such that by year 2000 the atmospheric carbon dioxide level was not rising at all. But in reality, the temperature did not even rise that much. Which proves that the climate models dont have a clue about the effect of carbon dioxide on world temperature.
Moreover (and you wont find this in the Academy paper), even if you believe, wrongly, that 2014 was the hottest year on record, 2014 was yet another year where the deviation widened between the models hot forecasts and the actual cooler temperatures.
The figure is scientifically meaningless. A statistical distribution can be calculated over the results from the some 73 global climate models, but the models have never been validated and only one valid model would have been sufficient. As discussed above, the models have significant, unknown, internal uncertainty. Further, CO2 emissions do not explain the significant warming of the first part of the 20 th century, the current pause in warming of at least a decade (in the atmosphere and at least 15 years on the surface) and the regional nature of the of the warming, which is occurring in the northern part of the Northern Hemisphere with little warming elsewhere.
Lee et al.s controlled experiment (climate model) showed increased flow through the Indonesian Throughflow during the 2007/08 and 2008/09 La Nias. This is basically the explanation for why the ocean heat content of the Indian Ocean did not cool proportionally during those La Nias. Note, however, in Figure 3 that the ocean heat content of the Indian Ocean did drop during the 2005/06 La Nia, which seems to contradict Lee et al.s model. The Lee et al. model also did not appear to respond to the 1998-01 La Nia, while the data indicate the warming of the Indian Ocean actually began then, after a drop a few years earlier.
Claim C: On its face, the climate model assumptions (including high positive feedbacks) of substantial warming from small changes in CO2 are inconsistent with relatively modest past warming. Scientists use what is essentially an arbitrary plug variable to handle this, assuming anthropogenic aerosols have historically masked what would be higher past warming levels. The arbitrariness of the plug is obvious given that most models include a cooling effect of aerosols in direct proportion to their warming effect from CO2, two phenomenon that should not be linked in nature, but are linked if modelers are trying to force their climate models to balance. Further, since aerosols are short lived and only cover about 10% of the globes surface in any volume, nearly heroic levels of cooling effects must be assumed, since it takes 10C of cooling from the 10% area of effect to get 1C cooling in the global averages.
Each of the complex climate models used by the IPCC grossly overstates the amount of warming the planet has experienced during the past 120 or so years. In addition, based on the idea that temperatures should rise right along with CO 2 emissions, these models have missed the entire 18+ year hiatus in rising temperatures.
In order to take precautions, you have to know what you are taking them against. Some computer models project that the global temperature in ten years time will be warmer than todays. Other computer modelsproject that global temperature will be cooler ten years hence. Read more here .
In summing up their discussion of the subject, therefore, Laxon et al. simply state that their results ???show that errors are present in current simulations of Arctic sea ice,?? and they thus conclude, in the closing sentence of their paper, that ???until models properly reproduce the observed high-frequency, and thermodynamically driven, variability in sea ice thickness, simulations of both recent, and future, changes in Arctic ice cover will be open to question.??
In September, 2008, Der Spiegel here wrote: More heat waves, no snow in the winter: After years of calculation work, the climate prognoses of the German government are complete. With unprecedented accuracy they predict how the climate will change by the year 2100 region by region. Unfortunately the unprecedented accuracy theyve seen up to nowis not what they had in mind.
The geophysicist slammed the UN Intergovernmental Panel on Climate Change (IPCC), saying their stand on global warming is incorrect because only are based on mathematical models and presented results at scenarios that do not include, for example, solar activity.
The evidence, therefore, indicates that the current generation of climate models (when run as a group, with the CMIP5 prescribed forcings) do not reproduce the observed global warming over the past 20 years, or the slowdown in global warming over the past fifteen years.
Notice that the potential positive bias in model feedbacks can, in some sense, be attributed to a lack of model complexity compared to the real climate system. By complexity here I mean cloud variability which is not simply the result of a cloud feedback on surface temperature. This lack of complexity in the model then requires the model to have positive feedback built into it (explicitly or implicitly) in order for the model to agree with what looks like positive feedback in the observations.
It is also the scenario which, when fed into the worlds climate models, produces the greatest warming by the end of the centuryabout 4.5C (although the world abounds with observations that suggests that this temperature rise is overblown, but that is the subject of a different analysis).
Climate Models: On the Global Warming Policy Foundation blog, David Whitehouse discusses the failure of the IPCC to discard models that clearly have no predictive value. The average of the models used greatly overestimate the increase in temperatures from additional CO2. The continued use of these models illustrates a failure in IPCC methodology procedures. Discarding models that greatly overestimate warming would result in a significant reduction in the upper bound of climate sensitivity estimates. Such action would render many climate issues, such as species extinction, moot. The huge amounts of money provided by climate alarm would shrink, endangering many climate researchers.
So, even with all of 140 cherries picked, we still see evidence there is something wrong with the IPCC models in general. And I believe the problem is they are too sensitive, and thus are predicting too much future global warming.
why cant climate models properly simulate sea ice losses in the Arctic Ocean or sea ice gains in the Southern Ocean surrounding Antarctica?
The overall picture is clear. Scenario A is the emissions scenario from 1990 that is closest to the observed emissions outturn, and yet there has only been a third of a degree of global warming since 1990 about half of what the IPCC had then predicted with what it called substantial confidence.
Storch: If things continue as they have been, in five years, at the latest, we will need to acknowledge that something is fundamentally wrong with our climate models. A 20-year pause in global warming does not occur in a single modeled scenario. But even today, we are finding it very difficult to reconcile actual temperature trends with our expectations.
While this might sound reasonable, it turns out that the radiative signature of forcing is much larger than that of feedback. As a result, one can get pretty good agreement between models and observations even when the model feedbacks are greatly in error. Another way of saying this is that you can get good agreement between the model behavior and observations whether the cloud feedbacks are positive OR negative. This is another fact I will be demonstrating on December 16.
The authors compared recently constructed temperature data sets from Antarctica, based on data from ice cores and ground weather stations, to 20th century simulations from computer models used by scientists to simulate global climate. While the observed Antarctic temperatures rose by about 0.4 degrees Fahrenheit (0.2 degrees Celsius) over the past century, the climate models simulated increases in Antarctic temperatures during the same period of 1.4 degrees F (0.75 degrees C).
???observed surface solar radiation, as well as land and sea surface temperature spatio-temporal variations over the Euro-Mediterranean region are only reproduced when simulations include the realistic aerosol variations?? which the authors state are ???however hardly reproduced by global and regional climate models??
The group, which includes seven Apollo astronauts and two former directors of NASAs Johnson Space Center in Houston, are dismayed over the failure of NASA, and specifically the Goddard Institute For Space Studies (GISS), to make an objective assessment of all available scientific data on climate change. They charge that NASA is relying too heavily on complex climate models that have proven scientifically inadequate in predicting climate only one or two decades in advance.
The models systematically underestimate dust emission, transport and optical depth, and year-to-year changes in these properties bear little resemblance to observations, the authors wrote. These findings cast doubt on the ability of these models to simulate the regional climate and the response of African dust to future climate change.
Read here and here . Climate models are dependent on atmospheric relative humidity staying constant if CO2 increases are going to cause global temperatures to increase. Again, real world evidence proves models are wrong.
Twenty-eight million weather balloons had shown by 1999 that the key assumption in the climate models was wrong. Without feedbacks, the models only produce 1.2C of warming with a doubling of CO2. With feedbacks the simulations ramp that up to a dangerous 3 ??? 4 degrees C, and water vapor was the most important feedback. It??s just no fun for the Global Worriers without it.
These studies arebasedon models, ofwhich only a portion of which represent basic physics (e.g. the pressure gradient force, advection and the universal gravitational constant), with the remainder of the physics parameterized withtunedengineeringcode (e.g see ).
The two main points here are (1) the observations are much cooler than the mid-range of the model spread and are at theminimum of the model simulations and (2) the satelliteadjustment for surface comparisons is exceptionally good. The implication of (1) is that the best estimates of the IPCC models are too warm, or that they are too sensitive to CO2 emissions.
The Zombie in the room here is the dead science being revived endlessly by Brown and the IPCC, despite the evidence that climate models are based on flawed assumptions, which we know from 28 million weather balloons , 3000 ARGO buoys , 800,000 years of ice cores , and 30 years of satellites .
I think what they mean is that this is a somewhat implausible post-hoc rationalisation of the failure of the models to conform to reality; perhaps the copyeditor missed it.
The extended calculation using coupled runs confirms the earlier inference from the AMIPruns that underestimating the negative feedback from cloud albedo and overestimating the positive feedback from the greenhouse effect of water vapor over the tropical Pacific during ENSO is a prevalent problem of climate models.
The references here independently show that core model assumptions are wrong. Models assume that relative humidity will stay the same over the tropics as the world warms, that clouds are a positive feedback and not a negative one, and that cloud changes are a feedback and not a forcing in their own right. These are three critical and demonstrable errors.
Modeled versus observed correlations with time from 1982 to 2011 are shown in the following two maps. The scale below each map is correlation coefficient, not temperature. A positive correlation coefficient of 1.0 (hot pink) would indicate an area warmed linearly from 1982 to 2011, while a negative correlation coefficient of -1.0 (purple) would indicate an area cooled linearly over that period. Basically, what the maps are showing are the modeled and observed warming and cooling trend patterns. There are no similarities. Keep those two images in mind the next time you see a peer-reviewed paper that projects regional climate on decadal or multidecadal bases. The modelers have no hope of doing so unless they can predict ENSO and its impacts on regional sea surface and land surface temperatures. They simulate both poorly.
However, there is absolutely no evidence that the upper end climate models are anywhere close to being right.
Perhaps the trade-winds are affecting the climate. But what drives the trade-winds? The models cant predict the trade-winds until they understand what drives them. If it turns out to be cloud cover changes, or lunar orbits, or solar magnetic effects, cosmic ray effects, or all of the above that means there is another whole factor or lots of them that the models did not include. Every warming factor added to the models reduces the power of CO2 as a driver. How much does this reduce your future projections by? (Or your future job prospects?)
The models perform poorly in the North Pacific (Figure 16) and in the South Pacific (Figure 17), more than doubling the observed warming rates.
The simulation of clouds in climate models remains challenging. There is very high confidence that uncertainties in cloud processes explain much of the spread in modelled climate sensitivity. However, the simulation of clouds in climate models has shown modest improvement relative to models available at the time of the AR4, and this has been aided by new evaluation techniques and new observations for clouds. Nevertheless, biases in cloud simulation lead to regional errors on cloud radiative effect of several tens of watts per square meter.