More Global Warmist lying sacks of shit Pt. II

[Seth]

Australian Bureau of Meteorology accused of Criminally Adjusted Global Warming
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by James Delingpole 25 Aug 2014 post a comment
The Australian Bureau of Meteorology has been caught red-handed manipulating temperature data to show "global warming" where none actually exists.

At Amberley, Queensland, for example, the data at a weather station showing 1 degree Celsius cooling per century was "homogenized" (adjusted) by the Bureau so that it instead showed a 2.5 degrees warming per century.

At Rutherglen, Victoria, a cooling trend of -0.35 degrees C per century was magically transformed at the stroke of an Australian meteorologist's pen into a warming trend of 1.73 degrees C per century.

Last year, the Australian Bureau of Meteorology made headlines in the liberal media by claiming that 2013 was Australia's hottest year on record. This prompted Australia's alarmist-in-chief Tim Flannery - an English literature graduate who later went on to earn his scientific credentials with a PhD in palaeontology, digging up ancient kangaroo bones - to observe that global warming in Australia was "like climate change on steroids."

But we now know, thanks to research by Australian scientist Jennifer Marohasy, that the hysteria this story generated was based on fabrications and lies.

Though the Bureau of Meteorology has insisted its data adjustments are "robust", it has been unable to come up with a credible explanation as to why it translated real-world data showing a cooling trend into homogenized data showing a warming trend.

She wrote:

“Repetition is a propaganda technique. The deletion of information from records, and the use of exaggeration and half-truths, are �others. The Bureau of Meteorology uses all these techniques, while wilfully ignoring evidence that contradicts its own propaganda.’’

This is a global problem. Earlier this year, Breitbart reported that similarly dishonest adjustments had been made to temperature records by NASA and NOAA. Similarly implicated are the UK temperature records of the Met Office Hadley Centre and at Phil "Climategate" Jones's disgraced Climatic Research Unit at the University of East Anglia.

One of the many disingenuous arguments used by climate alarmists against sceptics is mockingly to accuse them of being conspiracy theorists. "How could global warming possibly not be a problem when all the world's temperature data sets from Australia to the US to the UK clearly show that it is? Are you seriously suggesting that so many different scientists and so many distinguished institutions from across the globe would collude in such a massive lie?" their argument runs.

Our answer: yes we bloody well are.

[Tero]

There was no climategate. It was fabricated.

Nasa had measured Australia data all along. Look it up.

[Hermit]

Delingpole's hysterical style of reporting distracts from the point he's trying to make. I think the article in The Australian that his diatribe is based on is rather more convincing because it does not resort to it. and also because it is more balanced. Its use of the graph illustrating the relationship between the raw and the homogenised data from the Amberley weather station also adds to its impact.



The author of the study, Jennifer Marohasy, a self-described libertarian, currently works as an adjunct Research Fellow at Central Queensland University. Her job is funded by the B. Macfie Family Foundation, about which I cannot find anything out at all. Considering that Doctor Marohasy has been a speaker at a climate conference funded by the Heartland Institute, has founded an organisation to fight anthropomorphic climate change, named the Australian Environment Foundation and funded by the likes of Monsanto, Bayer Crop Science, Auscott Limited and Murray Irrigation Ltd, one can see where she is approaching issues from.

Having got the Background out of the way, I hope that the discussion of her claims focuses on the data in dispute rather than Marohasy's right wing views. Macdoc?

[Tero]

Nasa summary. Australia effects less than many other parts of the globe

[macdoc]

not worth even commenting on. Anyone in denial of AGW these days is a lunatic.

Canadian winters are 3.3C warmer in the last 60 years and we occupy a sizeable portion of the planet.

agw denial is a failed meme...move on.

[macdoc]

lets see an unknown libby versus the entire science community....

Global warming is here, human-caused and probably already dangerous—and it's increasingly likely that the heating trend could be irreversible, a draft of a new international science report says.

The United Nations' Intergovernmental Panel on Climate Change on Monday sent governments a final draft of its synthesis report, which combines three earlier, gigantic documents by the Nobel Prize-winning group. There is little in the report that wasn't in the other more-detailed versions, but the language is more stark and the report attempts to connect the different scientific disciplines studying problems caused by the burning of fossil fuels, such as coal, oil and gas.

The 127-page draft, obtained by The Associated Press, paints a harsh warning of what's causing global warming and what it will do to humans and the environment. It also describes what can be done about it.

"Continued emission of greenhouse gases will cause further warming and long-lasting changes in all components of the climate system, increasing the likelihood of severe, pervasive and irreversible impacts for people and ecosystems," the report says. The final report will be issued after governments and scientists go over the draft line by line in an October conference in Copenhagen.
Depending on circumstances and values, "currently observed impacts might already be considered dangerous," the report says. It mentions extreme weather and rising sea levels, such as heat waves, flooding and droughts. It even raises, as an earlier report did, the idea that climate change will worsen violent conflicts and refugee problems and could hinder efforts to grow more food. And ocean acidification, which comes from the added carbon absorbed by oceans, will harm marine life, it says.
Without changes in greenhouse gas emissions, "climate change risks are likely to be high or very high by the end of the 21st century," the report says.

In 2009, countries across the globe set a goal of limiting global warming to about another 2 degrees Fahrenheit (-16.67 Celsius) above current levels. But the report says that it is looking more likely that the world will shoot past that point. Limiting warming to that much is possible but would require dramatic and immediate cuts in carbon dioxide pollution.
The report says if the world continues to spew greenhouse gases at its accelerating rate, it's likely that by mid-century temperatures will increase by about another 3.6 degrees Fahrenheit (2 degrees Celsius) compared to temperatures from 1986 to 2005. And by the end of the century, that scenario will bring temperatures that are about 6.7 degrees warmer (3.7 degrees Celsius).

http://phys.org/news/2014-08-panel-glob ... erous.html

[Hermit]

not worth even commenting on. Anyone in denial of AGW these days is a lunatic.

I expected a bit better than a cavalier wave of the hand. Dismissing AGW deniers as mere lunatics is not as convincing as explaining why the homogenised temperature graph representing measurements taken at Amberley is more realistic than the graph representing the raw data.



Have a go at it. I am genuinely interested.

[macdoc]

I'm not a statistician - you want an answer ask Gavin....
here ya go
gavin.a.schmidt@nasa.gov

One anomaly is meaningless and what the fuck is average annual minimum temperatures for one fucking obscure location.

Grasping at straws. Just another right wing paid for science hack.

[JimC]

Such a charming thread title, so evocative of calm, rational scientific debate...

[Hermit]

Such a charming thread title, so evocative of calm, rational scientific debate...

Yeah, that too. I was probably overly optimistic when I asked for a discussion focusing on facts rather than mud slinging. In respect to the latter Seth and Macdoc are remarkably alike, just on opposite sides of the fence.

[macdoc]

What "facts" were presented that relate to AGW??
None.

You have a single location, a single statistic....

average annual minimum temperatures

Care to expand?? Can you even define that?

Fuck off Hermit you sanctimonious prick....you want to discuss climate science?? - show me some - not some whacked bit of nonsense from Delingpole et al.

Australian scientist Jennifer Marohasy, is NOT a climate scietist and neither are you.

[macdoc]

learn something

Homogenization (climate)
From Wikipedia, the free encyclopedia
This article is about homogenization of climate data. For other meanings of homogenization, homogeneity, and related words, see Homogeneity (disambiguation).

Homogenization in climate research means the removal of non-climatic changes. Next to changes in the climate itself, raw climate records also contain non-climatic jumps and changes for example due to relocations or changes in instrumentation. The most used principle to remove these inhomogeneities is the relative homogenization approach in which a candidate stations is compared to a reference time series based on one or more neighboring stations. The candidate and reference station(s) experience about the same climate, non-climatic changes that happen only in one station can thus be identified and removed.

Climate observations[edit]
To study climate change and variability long instrumental climate records are essential, but are best not used directly. These datasets are essential since they are the basis for assessing century-scale trends or for studying the natural (long-term) variability of climate, amongst others. The value of these datasets, however, strongly depends on the homogeneity of the underlying time series. A homogeneous climate record is one where variations are caused only by variations in weather and climate. Long instrumental records are rarely, if ever homogeneous.

Results from the homogenization of instrumental western climate records indicate that detected inhomogeneities in mean temperature series occur at a frequency of roughly 15 to 20 years.[1][2][3][4][5] It should be kept in mind that most measurements have not been specifically made for climatic purposes, but rather to meet the needs of weather forecasting, agriculture and hydrology.[6] Moreover the typical size of the breaks is often of the same order as the climatic change signal during the 20th century.[1][2][3][4][5] Inhomogeneities are thus a significant source of uncertainty for the estimation of secular trends and decadal-scale variability.

If all inhomogeneities would be purely random perturbations of the climate records, collectively their effect on the mean global climate signal would be negligible. However, certain changes are typical for certain periods and occurred in many stations, these are the most important causes as they can collectively lead to artificial biases in climate trends across large regions. [3][7][8]

Causes of inhomogeneities[edit]


Tokyo, an example of an urban heat island. Normal temperatures of Tokyo go up more than those of the surrounding area.
The best known inhomogeneity is the urban heat island effect. The temperature in cities can be warmer than in the surrounding country side, especially at night. Thus as cities grow, one may expect that temperatures measured in cities become higher. On the other hand, with the advent of aviation, many meteorological offices and thus their stations have often been relocated from cities to nearby, typically cooler, airports.[9]



Exterior of a Stevenson screen
Other non-climatic changes can be caused by changes in measurement methods. Meteorological instruments are typically installed in a screen to protect them from direct sun and wetting.[10] In the 19th century it was common to use a metal screen in front of a window on a North facing wall. However, the building may warm the screen leading to higher temperature measurements. When this problem was realized the Stevenson screen was introduced, typically installed in gardens, away from buildings. This is still the most typical weather screen with its characteristic double-louvre door and walls for ventilation. The historical Montsouri and Wilds screens were used around 1900 and are open to the North and to the bottom. This improves ventilation, but it was found that infra-red radiation from the ground can influence the measurement on sunny calm days. Therefore, they are no longer used. Nowadays automatic weather stations, which reduce labor costs, are becoming more common; they protect the thermometer by a number of white plastic cones.[8] This necessitated changes from manually recorded liquid and glass thermometers to automated electrical resistance thermometers, which reduced the recorded temperature values in the USA.[2]

Also other climate elements suffer from inhomogeneities. The precipitation amounts observed in the early instrumental period, roughly before 1900, are biased and are 10% lower than nowadays because the precipitation measurements were often made on a roof. At the time, instruments were installed on rooftops to ensure that the instrument is never shielded from the rain, but it was found later that due to the turbulent flow of the wind on roofs, some rain droplets and especially snow flakes did not fall into the opening. Consequently measurements are nowadays performed closer to the ground.

Other typical causes of inhomogeneities are a change in measurement location; many observations, especially of precipitation are performed by volunteers in their garden or at their work place. Changes in the surrounding can often not be avoided, e.g., changes in the vegetation, the sealing of the land surface, and warm and sheltering buildings in the vicinity. There are also changes in measurement procedures such as the way the daily mean temperature is computed (by means of the minimum and maximum temperatures, or by averaging over 3 or 4 readings per day, or based on 10 minute data). Also changes in the observation times can lead to inhomogeneities. A recent review by Trewin focused on the causes of inhomogeneities.[9]

The inhomogeneities are not always errors. This is seen most clear for stations affected by warming due to the urban heat island effect. From the perspective of global warming, such local effects are undesirable, but to study the influence of climate on health such measurements are fine. Other inhomogeneities are due to compromises that have to be made been ventilation and protection against the sun and wetting in the design of a weather shelter. Trying to reduce one type of error (for a certain weather condition) in the design will often lead to the more errors from the other factors. Meteorological measurements are not made in the laboratory. Small errors are inevitable and may not be relevant for meteorological purposes, but if such an error changes, it may well be an inhomogeneity for climatology.

Homogenization[edit]
To reliably study the real development of the climate, non-climatic changes have to be removed. The date of the change is often documented (called meta data: data about data), but not always. Meta data is often only available in the local language. In the best case, there are parallel measurements with the original and the new set-up for several years.[11] This is a WMO (World Meteorological Organisation) guideline, but parallel measurements are unfortunately not very often performed, if only because the reason for stopping the original measurement is not known in advance, but probably more often to save money. By making parallel measurement with replicas of historical instruments, screens, etc. some of these inhomogeneities can still be studied today.



One way to study the influence of changes in measurement techniques is by making simultaneous measurements with historical and current instruments, procedures or screens. This picture shows three meteorological shelters next to each other in Murcia (Spain). The rightmost shelter is a replica of the Montsouri screen, in use in Spain and many European countries in the late 19th century and early 20th century. In the middle, Stevenson screen equipped with automatic sensors. Leftmost, Stevenson screen equipped with conventional meteorological instruments.
Because you are never sure that your meta data (station history) is complete, statistical homogenization should always be applied as well. The most commonly used statistical principle to detect and remove the effects of artificial changes is relative homogenization, which assumes that nearby stations are exposed to almost the same climate signal and that thus the differences between nearby stations can be utilized to detect inhomogeneities.[12] By looking at the difference time series, the year to year variability of the climate is removed, as well as regional climatic trends. In such a difference time series, a clear and persistent jump of, for example 1 °C, can easily be detected and can only be due to changes in the measurement conditions.

If there is a jump (break) in a difference time series, it is not yet clear which of the two stations it belongs to. Furthermore, time series typically have more than just one jump. These two features make statistical homogenization a challenging and beautiful statistical problem. Homogenization algorithms typically differ in how they try to solve these two fundamental problems.[13]

In the past, it was customary to compute a composite reference time series computed from multiple nearby stations, compare this reference to the candidate series and assume that any jumps found are due to the candidate series.[14] The latter assumption works because by using multiple stations as reference, the influence of inhomogeneities on the reference are much reduced. However, modern algorithms, no longer assume that the reference is homogeneous and can achieve better results this way. There are two main ways to do so. You can compute multiple composite reference time series from subsets of surrounding stations and test these references for homogeneity as well. [15] Alternatively, you can only use pairs of stations and by comparing all pairs with each other determine which station most likely is the one with the break.[4] If there is a break in 1950 in pair A&B and B&C, but not in A&C, the break is likely in station B; with more pairs such an inference can be made with more certainty.

If there are multiple breaks in a time series, the number of combinations easily becomes very large and it is becomes impossible to try them all. For example in case of five breaks (k=5) in 100 years of annual data (n=100), the number of combinations is about 1005=1010 or 10 billion. This problem is sometimes solved iteratively/hierarchically, by first searching for the largest jump and then repeating the search in both sub-sections until they are too small. This does not always produce good results. A direct way to solve the problem is by an efficient optimization method called dynamic programming.

Sometimes there are no other stations in the same climate region. In this case, sometimes absolute homogenization is applied and the inhomogeneities are detected in the time series of one station. If there is a clear and large break at a certain date, you may well be able to correct it, but smaller jumps and gradually occurring inhomogeneities (urban heat island or a growing vegetation) cannot be distinguished from real natural variability and climate change. Data homogenized this way does not have the quality you may expect and should be used with much care.

Inhomogeneities in climate data[edit]
By homogenizing climate datasets, it was found that sometimes inhomogeneities can cause biased trends in raw data; that homogenization is indispensable to obtain reliable regional or global trends. For example, for the Greater Alpine Region a bias in the temperature trend between the 1870s and 1980s of half a degree was found, which was due to decreasing urbanization of the network and systematic changes in the time of observation.[16] The precipitation records of the early instrumental period are biased by -10% due to the systematic higher installation of the gauges at the time.[17] Other possible bias sources are new types of weather shelters[3][18] the change from liquid and glass thermometers to electrical resistance thermometers,[2] as well as the tendency to replace observers by automatic weather stations,[8] the urban heat island effect and the transfer of many urban stations to airports.[9]

In the project HOME homogenization algorithms were recently tested on artificial climate data with known inhomogeneities and it was found that relative homogenization improves temperature records and that the modern methods that do not work with a homogeneous reference are most accurate.[13]

[mistermack]

The thing is that this was already known, that meteorologists are very happy to bend their data to show what they want to show.
It's very like religion. They think they are doing good by lying. They bend the truth with a clear conscience, because they have such a strong preconceived notion that we are ''destroying the planet''.

That's because all of the people who retained a proper scientific scepticism have been made unwelcome, or hounded out. And all you have left in the industry now are dyed-in-the-wool activists.

It would be better if the world put them on ignore, and stopped funding their rubbish, until they learn to be scientific.

Luckily, the planet hasn't listened, it stopped warming nearly 20 years ago, and clearly hasn't made it's mind up what to do next. Even after 20 years of drastically increasing CO2 emissions, it refuses to warm. Nice one, mother.

[Hermit]

What "facts" were presented that relate to AGW??
None.

You have a single location, a single statistic....

average annual minimum temperatures

Care to expand?? Can you even define that?

Fuck off Hermit you sanctimonious prick....you want to discuss climate science?? - show me some - not some whacked bit of nonsense from Delingpole et al.

Australian scientist Jennifer Marohasy, is NOT a climate scietist and neither are you.

Macdoc, I never claimed to be a climate scientist. What I did, was to ask for a discussion of the data as they are presented. What I got from you instead was exactly the sort of thing I very explicitly stated not to want: Aspersions as to an author's character instead of a refutation of the author's claim. So I asked again: Why is the homogenised temperature graph representing measurements taken at Amberley more realistic than the graph representing the raw data? Your second step was to basically admit that there's an anomaly. In other words, that the lunatic was actually correct with her factual assertion. The third step was to say that you don't know the answer because you are not a statistician. And now you are resorting to personal abuse. Why? Because I had the temerity to ask you if you can explain the discrepancy between the two apparently conflicting data series?

[mistermack]

I know of no reason why temperature records should be ''homogenised'' UPWARDS !!

The heat-island effect is well understood, and might well make it sensible to adjust the raw data from certain locations downwards, in a scientific manner, through known and published methods and reasons.

But how and why does any raw data need to be moved upwards? Are we creating ''cold-islands'' as well?
The difference between homogenisation and fiddling of the figures is the reasons given, the methods employed all being published, as opposed to someone just making them say what they want.

But anyway, why would figures need moving upwards? Any answers ?