After yesterdays post on the gibberish proof of global warming due to increased in the Antarctic Circulation, Andrew drew attention to Jones, J. M. and M. Widmann, 2004. Early peak in Antarctic oscillation index. who found that the Antarctic Oscillation has changed in the last thirty to forty years, but is only where it was in the late fifties to early sixties.
CommentsA transcript of an interview with Tas van Ommen on the link between Antarctic excess and West Australian deficits of precipitation displays questionable proof of anthropogenic global warming.
A natural circulation pattern surrounding Antarctica has three lobes because of the three continents and three ocean basins in the Southern Hemisphere. Tas claims in the past 30 to 40 years the strength of that three-lobe pattern has increased, bringing moisture and warmth into Antarctica and dry air back up to Western Australia.
He claims that a natural explanation has a 1:1000 probability.
Well, it is a real smoking gun I guess. It could be that we have just happened to find something that is really one in actual fact, thousands flukey event to get such a large snowfall. The more natural interpretation is that there is something been going on in the last 30 to 40 years and we know what that something is. It is the human impact on the atmosphere.
This was reported as ‘proof of climate change‘. But he admits it is an assumption.
CommentsThe latest submission to arXiv:physics.ao-ph is entitled Interglacials, Milankovitch Cycles, and Carbon Dioxide by Gerald E. Marsh. Here is a review of the evidence regarding the timing of Termination II, the penultimate interglacial transition 140k years ago, and factors that may have caused it: CO2, Milankovitch induced insolation changes, or changes in solar magnetic flux, altering the Earth’s albedo through cosmic ray flux.
To appreciate the importance of this period, and a clear logical analysis of it, consider the recent lecture tour of Australia by Lord Monckton and Prof. Plimer. Lord Monckton argues strongly that climate sensitivity to CO2 is very low, too low to be of concern, and an increasing number of peer-reviewed papers using independent observational methods — Douglass, Lindzen, Spencer, Schwartz, Pinker, Shaviv — back him up. Prof. Plimer argues that the history of climate has been enormously variable, and not related to CO2 levels in the atmosphere.
This contrast of low sensitivity but high natural variation has prompted criticism on the irony of a tour by sceptics with contradictory viewpoints. As I understand their view, they maintain “the sensitivity of the climate to CO2 cannot be as low as suggested by these results because low sensitivity cannot explain the large glacial-interglacial transitions”. A solar cause for the penultimate transition has been scoffed at because the timing is wrong. It must have been a volcano or something that kicked off the chain of CO2 feedback that resulted in the warm interglacial.
CommentsUntil recently, even hardened climate skeptics when asked about the science would say: “Well we think it is warming, but how much is caused by humans is uncertain”. Now a rash of revelations are coming out to challenge even this bedrock claim, e.g.
CommentsIt seems that when we leave out the great number of weather stations that were introduced in the last 50 years or so, that the tendency is absolutely not a rise in temperature, see Global Warming Vs Clojure!.
A few impressions from Monckton’s talk at the Brisbane Irish Club, providing some novel points not seen elsewhere. Some interesting impressions did come out of it.
CommentsMonckton’s main argument seems to be represented by the statement that climate sensitivity to CO2 has been overestimated by the IPCC by around 6-7 times, giving exaggerated projections of warming for a business as usual scenario of CO2 emissions. The IPCC range is around 2-6C degrees warming by 2100, and Monckton’s is 0.5C. While he provides some calculations, this view is also supported by a measure of respectable scientific literature.
The view that CO2 sensitivity is being grossly exaggerated is the one that is shared by myself and the likes of Spencer, Shaviv, Lindzen, Douglass and others. The most concise illustration of this is the one produced by Spencer, showing where the various authors lie, relative to the IPCC model projections.
WUWT reports in The IPCC: More Sins of Omission – Telling the Truth but Not the Whole Truth the greatest failing of the IPCC, if not environmental sciences. The article describes how the effects of climate change on climate, hunger and water storage are misrepresented to exaggerate negative effects. Here I show that the same deception is in play with the statements on species extinctions in AR4.
CommentsThe Brisbane Institute luncheon Panel Debate (Monckton, Plimer, Readfearn, Brook) in the Grand Ballroom, from 12:00 – 2.00pm is sold out. Seats are still available at the Irish Club, across the street from 3pm to 5pm.
CommentsHistoric. Not to be missed. I will be at the Brisbane events. Come and say hi.
SYDNEY
Wednesday 27 January,
12:15, Luncheon, The Union Club, SOLD OUT
17:30 Public lecture, Sheraton on the Park download PDF
contact: John Smeed, phone or SMS 0417 269 216 johnsmeedATadna.com.au
An opinion on the The Social Cost of Transparency — a defense of secrecy — was given by an Australian economist on Mish’s blog.
Steve Keen says:
CommentsOne quick perusal of that article and I could consign it to neoclassical gibberish. The key giveaway is in the first sentence of the abstract:
“I study a class of models commonly used to motivate monetary exchange, extended to include a physical asset whose expected short-run return is subject to exogenous news events, but whose expected long-run return is independent of this information”
The part of bold is the give: this is a model where the future is subject to randomness, but not change: whatever happens in the short term has no impact on the future.
JoNova noticed a Canberra Times article that the Tasmanian drought may not be due to global warming after all.
CommentsThe UAH Index is approaching new highs, but there is overhead resistance immediately ahead, and primary medium-term indicators are becoming modestly overheated.
Does this spell trouble ahead for the AGW bulls? Eventually. Overheated conditions generally indicate an imminent drop, usually between -0.6-0.8 degrees C.
Concluding that:
Approaching the problem under the premise that fuller transparency is always desirable may not be the right place to start.
an article On the Social Cost of Transparency in Monetary Economies from the St Louis Fed explains why secrecy and non-disclosure of data may be advantageous.
For an asset economy then, the prescription of “full transparency” is not generally warranted.
After many pages of mathematics, their argument is summarized:
In competitive economies, the disclosure of high-frequency information unrelated to an asset’s “long-run fundamentals” may be detrimental to economic welfare when claims to such assets serve as high-velocity payment instruments. The equilibrium price of a liquid asset is excessively volatile when asset prices capitalize all information.
If we translate this into a more familiar example, such as climate data and code, it would seem to argue that disclosure of all data and code may be detrimental to the value of the research to the author of an article, the university, the journal, coauthors etc.
CommentsAs any financial analyst knows, fools and their tools can find confirmation for any pet theory. The only route to certitude is falsification.
Realclimate shows numerous examples of confirmation bias in their recent article. In particular, gavin dicusses an update to Hansen’s famous graph of projections made back in 1984.
They ‘confirm’ that scenario B — increasing CO2 — matches current trends.
The trends are probably most useful to think about, and for the period 1984 to 2009 (the 1984 date chosen because that is when these projections started), scenario B has a trend of 0.26+/-0.05 ºC/dec (95% uncertainties, no correction for auto-correlation).
Scenario C — no increase in CO2 — is more consistent with the temperature increase. A statistical test of the alternate hypothesis Ha, rejecting the view that observed temperature differs from the no increase in CO2 scenario, provides support for the view that CO2 is irrelevant.
Quasi-scientists have one thing in common with scam artists, emphasis on confirmation and ignoring contradictory evidence. Note the RealClimate article fails to mention scenario C at all in their post. See ClimateAudit for details of the scenarios and updates.
CommentsEnvironment minister Peter Garratt claimed recent figures on Australian temperature prove Opposition leader Tony Abbott was wrong to claim that the world had stopped warming.
Substitute Australia for the World, and the last 100 years for 10 years, and you might get close to the actual claim, similar to that made by respected climate physicist Roy Spencer that “there has been no net warming in the last 11 years or so”.
It’s easy — but confused — to find a limited region with a different climate, over a different time period, then use it for rebuttal.
David Jones of the BoM claims, referring to their Annual Report that the upward trend of temperature since 1920(?) should silence the critics once and for all.
CommentsIs there a “New Zealand Effect” in Australian data? Quite possibly. The Torok and Nicholls network of stations which can be downloaded from the BoM ftp site, not yet adjusted to produce the ‘official’ BoM version, shows little warming.
The blue line is the ‘official’ BoM mean temperature, the black line is the mean for all stations combined using my patented normalization method, described in a previous post.
Read the rest of this entry…
Willis Eschenbach has written a comprehensive article on adjustments to temperature in Darwin, some increasing the rate of warming by as much as 5C/century. Thanks to readers I have the daily temperatures from the Torok and Nicholls network, and plotted their minimum, maximum and mean temperatures for Darwin. The rates of warming are 1.3C/century and 1.4C/century for the min and max respectively. Moreover, the T&N adjustments are too small to distinguish.
Continuing my preliminary look into the Torok and Nicholls Adjusted Network of Australian temperatures, I now focus on the mean monthly minimum temperatures. As shown in the previous post, maximum temperatures are flat from 1850 to the 1990s, only the minimums show global warming. The annual means usually shown are based on the average of the minimum and the maximum, so there is no point in examining anything other than minimum temperatures.
CommentsDigging deeper into the Australian Temperature Adjustments, below are data from 224 stations in the Torok and Nicholls network. It looks like most of the increase in Australian temperature in the last 150 years is due to a step-like increase in the mean annual minimum temperature since 1975!
CA examined the sometimes considerable adjustments of individual stations here and here. Steve also plotted up the raw station data. I don’t know how he did the plots for ‘before adjustment’ as all the data seems to be ‘post adjustment’ by Torok.
Here I use a differenced normalization method described previously to account for the differences in mean temperature at each station, without averaging over areas. Its not exactly the same, but it produces a similar trend result, as shown in the last figure below.
The Torok network contains the mean annual maximum and minimum temperatures of 224 stations, and these are plotted below with the ‘official’ BoM mean temperature (blue) of high quality network of 103 stations. While the minimum and mean temperatures are clearly increasing, the maximum temperature has not increased at all.
Paz pointed out that the normalization used previously might not remove geographic biases introduced by fugitive weather stations, so here is another approach. I have differenced each of the records, averaged the differences and then cumulative summed the result.
If you have seen the articles on the NZ temperature adjustments and Nordic temperature adjustments you might be interested in the Australian data.
The issue with NZ and Nordic data that the raw temperature data for weather stations do not show the temperature increases indicated by the IPCC, raising the question of how the data have been adjusted.
As Prof. Karlen states in the ClimateGate email #1221683947, temperature at many stations has not exceeded early 20th century temperatures:
.. data sets show an increase after the 1970s to the same level as in the late 1930s or lower. None demonstrates the distinct increase IPCC indicates.
Here is the plot of means of Australian raw data for 103 temperature stations, based on the file Aus.tab downloaded from the Australian BoM web site and collated by Steve McIntyre.
Below are the results of applying the EMD algorithm (Empirical Mode Decomposition) to Australian Rainfall, and predicting the future rainfall with a VAR model (Vector Autoregression).
First, EMD splits the rainfall into IMF’s (Intrinsic Mode Functions) that are cyclical but variable in amplitude and frequency.
CommentsThe one message I’d like to convey is we do not need to rush on this. This will be around to examine and feed our discussions for a long time to come. If we start right, it will go better for us. There seems to be some indications of possible unethical behaviour, if these are true representations of email communications. It isn’t right to tell people to delete emails that may be the subject of FOI requests, at the very least. But we don’t need to pile onto this right now.
Have you noticed a distinct change in the rhetoric around global warming? Seems like revisionism going on in the mainstream media in the form of shift in focus to the most likely values, or expectations of global warming, rather than emphasizing the low probability, worse possible scenario.
For example, this one on sea level from nature.com.
CommentsSea level rise – not so fast.
In the latest salvo of the scientific debate over future sea level rise, a new report counters claims that rapidly swelling seas will soak estimates published by the UN climate planel in 2007.
A major “it’s worse than we thought” story out of March’s Copenhagen Climate Congress, for example, was that sea level could climb more than a metre by 2100 – seemingly far worse than the rise of up to 59 centimetres indicated in the 2007 report from the Intergivernmental Panel on Climate Change (IPCC). This was in fact something of a straw-man comparison, since the IPCC total explicitly excluded the impacts of accelerated glacier melt, and the new studies were attempting to add these impacts in.
How to predict with EMD? Because the EMD algorithm decomposes time series into a number of periodics of different frequency (IMFs), and a residue trend, prediction in EMD is by extrapolating each of the IMFs separately (a VAR model is recommended) and fitting a cubic polynomial to the residue (example code at end of here). The predictions are then added together.
Below are a couple of examples of EMD predictions on familiar data sets, the HadCRU global surface temperature, and the TLT series from the satellite MSU RSS data. In both I have also applied the recommended prediction techniques to extend the result into the future.
The first is the satellite TLT, and I have used up to IMF 5 so that variation up to annual quasi-periodicity is represented. The residue in this case, the red arch, has peaked and is projected to decline, along with the overall temperature, in the next few years. The amplitude of variability is also declining.
Our approach so far has been to model natural climate variation of global temperature with sinusoidal curves, and potential AGW as increasing trends. A new algorithm called EMD (Empirical Mode Decomposition) promises to more robustly identify cyclical natural variation (NV), showing the contribution of NV and AGW to global temperature, and testing the IPCC claim that most of the recent warming is due to AGW.
Underestimation of natural variation (NV) is a crucial flaw in the IPCC’s logic, according to Dr Roy Spencer:
They ignore the effect of natural cloud variations when trying to diagnose feedback, which then leads to overestimates of climate sensitivity. … By ignoring natural variability, they can end up claiming that natural variability does not exist. Admittedly, their position is internally consistent. But then, so is all circular reasoning.
The relative contribution of AGW to temperature increase in the late 20th century underpins the IPCC global warming claims, according to the Wiki page on Scientific Opinion on Climate Change:
National and international science academies and scientific societies have assessed the current scientific opinion, in particular on recent global warming. These assessments have largely followed or endorsed the Intergovernmental Panel on Climate Change (IPCC) position of January 2001 that states:
An increasing body of observations gives a collective picture of a warming world and other changes in the climate system… There is new and stronger evidence that most of the warming observed over the last 50 years is attributable to human activities.[1]
Since 2007, no scientific body of national or international standing has maintained a dissenting opinion.
So estimating the relative proportion of natural variation vs. trend is very important. While widely used in other fields, EMD is relatively little used in climate science.
As an example, Lin and Wang (2004) used EMD for analysis of solar insolation. They claim that the solar eccentricity signal is much larger than previously estimated, more than 1% of solar irradiance, and adequate for controlling the formation and maintenance of quaternary ice sheets. This is a potential resolution of the 100,000 year problem, that has also been used to justify the necessity of CO2 feedback in producing ice ages.
Conventional spectral methods are strictly periodic — the period is constant in both frequency and amplitude. EMD relaxes these assumptions, allowing quasi-periodicity, which might explain why more variation is potentially explained. The EMD algorithm proceeds by first extracting out the highest frequency, called an intrinsic mode function (IMF) and leaving a residual. It does this to the next highest frequency, and so on, until only a trend is left.
While it is possible the residual is also part of a cycle — it is always possible to model a trend with a sinusoidal of long enough period — we treat this as AGW trend in order to estimate the maximum possible contribution of AGW to global warming.
Here are the results of applying EMD to the CRU global temperature series. Figure 1 below shows each of the 5 IMF’s and the residual, the remainder after subtracting out the periodics.
Each of the IMF’s is shown, with mean periods of 4.0, 6.6, 11.9, 23.4, and 55.1 years respectively. Most readers would be well aware of the similarity of these periods to major solar and oceanic cycles.
CommentsAn objective analysis of the evidence for global warming suggests little if any anthropogenic effect, consistent with a direct radiative effect from increased CO2. It is also obvious that global temperature and ocean heat content should be related, so it’s somewhat surprising to see OHC rising so fast around 2002-3 when ocean temperature is relatively stable (upper line below).
