Here is the second major claim contained in van Ommen and Morgan from the abstract:
Here we report a signiï¬cant inverse correlation between the records of precipitation at Law Dome, East Antarctica and southwest Western Australia over the instrumental period, including the most recent decades.
The actual figures quoted for correlation are as follows.
The results show significant negative correlation between seasonal June–August average values of the SWWA regional series and LawDome.
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An issue in question here is whether the recent snowfall at Law Dome is unusually high relative to the 750 year long record (and therefore, so the argument goes, probably due to AGW).
Below is the snowfall at Law Dome from the ice core. Above is the actual snowfall, and below is the accumulation of the series minus the mean (using the R function cumsum) indicating where snowfall is above or below average.
This simple approach is not used in the paper. While the accumulation of snow at present
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After yesterdays post on the gibberish proof of global warming due to increased Antarctic Circulation, Andrew drew attention to Jones, J. M. and M. Widmann, 2004, Early peak in Antarctic oscillation index claiming 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.
Tas Van Ommen claims to have found that snowfall has increased in East Antarctica. Looking into his previous publications, one of the first I pulled
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A 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
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The 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
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Until 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.
It 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!.
Andrew Bolt recently reported on base
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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.
I found Monckton (and Plimer) a little disappointing in quality of presentation and slides. A fair bit of time was put into boosting the audience, but his essential points on low climate sensitivity were rushed over.
Plimer gave a hand-waving review of geological history, making the point that CO2 has never been responsible for the
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Monckton'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
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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.
In Climate Change 2007: Working Group II: Impacts, Adaption and Vulnerability it is stated,
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The 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.
one
Historic. 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
NEWCASTLE
Thursday 28 January
12:30 Public lecture, Newcastle City Hall – Banquet Room Download PDF
contact: Anthony Cox, 0412 474916, akcsjAToptusnet.com.au
BRISBANE
Friday 29 January
12:00 – 2.00 Brisbane
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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:
One 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
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The 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.
Our chart shows the satellite data from UAH with three primary medium-term indicators (oscillators). The first is the Bollinger Bands around the actual global temperatures. As
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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,
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As 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
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Is 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.
The minimum temperature (red and orange lines are the minimums) for the Torok and
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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.
I must admit I don't understand
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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.
Above are the monthly minimum temperatures for the
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Digging 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
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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.
This way we are dealing only in annual increments, up until the final summation. The result differs from the previous, as the pop-up in 1914 is lowered, and the temperatures post 2000 are raised. However, it still seems to depart
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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
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Steve's new site is here. Search the emails from CRU here. Browse the leaked FOIA files here.
A department is going to hire a new climate scientist and summons a series of candidates. The selection panel asks each applicant, "What is two plus two?" The first two candidates answer, "Four." They don't get the job. The third responds, "What do you want it to be?" He gets hired.
HT: http://www.powerlineblog.com/archives/2009/11/024995.php
Is it too soon to say "We wus right!"?
A heartfelt thanks
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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.
You can see each of the modes, their strength and phase, and the uncertainty. The initial modes are very uncertain, not worth including in the model, so only a few IMF are used in the
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Thomas Fuller
The 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.
Softly,
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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.
Sea 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
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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
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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
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An 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).
Also given the known issues with this data set, it's bizarre to see top bureaucrats and scientists like Wong/Steffen
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Here, out-of-sample tests are used to test the robustness of the linear regression models of natural variation in global temperature. Previous models were developed on the whole data set. Here we develop them on partial data sets and examine how well they predict temperatures on the other part. These are also called independent tests.
The models that do well on the unseen data are in some sense more robust, reliable, and it gives you a feel for the constraints the data are placing on the models.
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To continue our excursion into natural variation models of global temperature: What do they predict?
Here are a couple of different models fit with data up to the year 1990. This was in order to compare their projections with out-of-sample reality after 1990. The year 1990 is also the start of the major IPCC projections from the TAR WG1 available here.
The upper panel shows the entire HadCRUT global temperature in black up to 1990, the linear models are in red, while the IPCC projections
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