My husband, John Abbot, has kept going with research into AI and climate forecasting. One of his most important recent papers can be downloaded from Earth Sciences.
Some of the latest Nobel prizes in science, including in chemistry, have been for developments in artificial intelligence (AI). Of course, John Abbot and I began working on the application of this technology for forecasting rainfall soon after Brisbane flooded back in 2011. Back then, we had just started dating. It would be some years before we got married.
We had a first AI model developed just a couple of months later, this included some hindcasting showing that the flooding of Brisbane could have been forecast given the temperature and pressure setup across the Pacific Ocean through 2010, and natural climate cycles.
John Abbot and I published a series of papers together through until 2017, after that I lost interest in developing the temperature series that were part of the arrays that John inputted into the neural networks.
I gave-up in 2017, in part because of the hatred that was directed at me, and John, including on Twitter with what was the publication of perhaps our most important paper, newly published in the journal GeoResJ on the application of artificial intelligence, for evaluating anthropogenic versus natural climate change (GeoResJ, Vol. 14, Pgs 36-46 published in July 2017). This research was pilloried on Twitter, and we were defamed by Graham Readfearn in The Guardian. Meanwhile, the editor of the journal was under intense pressure for the paper to be retracted. And some time was expended in writing what seemed like endless letters in its defence. The paper was never retracted, but the journal was closed.
I also gave-up, because I lost confident in the integrity of the actual temperature measurements being recorded by the Australian Bureau of Meteorology. Previously I put a lot of work into ensuring that we inputted unhomogenised data. Then, when I realised the extent to which the new platinum resistance probes could be calibrated to basically measure up or down relative to a mercury thermometer and in fact, they were being recalibrated to measure hotter – well I gave up, in tears. My focus then become getting the parallel data to better understand the relationship between the two different types of temperature measuring.
I put a lot of effort into this until last April 2023, that was after the Administrative Appeals Tribunal Hearing, a front-page story in The Australian, and an understanding that not even the Conservative side of politics had any interest in holding the Bureau to account on this fraudulent remodelling. I understood that we were on our own.
Timing is everything they say, if one is to be successful at forcing change, and so it will need to be a team effort, we will need to be supported, we will need to wait.
Meanwhile, John Abbot, who tends to be less affected by the politics, and the injustices, has continued to run the AI. Instead of relying on me for long continuous temperature series, he began using much longer, and already published temperature series. And from both those who believe in the existence of Medieval Warm Period and those who dispute its existence.
He had an important paper published in 2021, further showing the application of AI for distinguishing natural from anthropogenic climate change. This research concludes:
The presence of oscillatory characteristics within proxy- temperature reconstructions across a range of time-scales, including millennial, centennial and decadal, has been reported in many investigations. The present study examines oscillations from spectral analysis applied to eight published multi-proxy temperature records, including examples representing both hockey stick [catastrophic recent warming] and MWP_LIA* cycles [it was warmer in the past during the medieval warm period].
The analysis shows that each record can be represented by a set of 4-11 sine curves from spectral analysis that include a dominant millennial oscillation and several centennial and decadal oscillations. The apparent divergence into either a hockey stick or MWP_LIA* cycles can be derived from the phase alignment of the centennial and decadal oscillations with respect to the millennial oscillation. The maximum temperature of the dominant oscillation at around 1000 AD is increased by superimposing the centennial/decadal oscillations for MWP-LIA* cycles, whereas it is reduced and the profile flattened for the hockey stick. This may explain why current temperatures may exceed any in past 1,000 years with hockey stick profile.
Forecasting through projection of pre-industrial temperature oscillatory patterns beyond 1880 AD by applying spectral analysis to generate input to train ANNs show that current atmospheric temperatures can be largely explained on basis of continuation of natural oscillations. This is the case irrespective of whether the hockey stick or MWP_LIA* cycles are operative. This process could give rise to temperatures higher that past 1000 years without major contribution from anthropogenic influences.
*Medieval Warm Period – Little Ice Age.
It is surprising that these important findings are not of more interest to those who claim to care about science and especially climate science.
Back in 2011, in fact right up until 2017, John and I were laughed at, including by our colleagues for suggesting the relevance of AI for elucidating natural climate cycles and using these same cycles to forecast monthly rainfall.
But perhaps the time is coming when it will be realised that we were just a bit ahead of the times.
Of course all our work was, and continues, to be funded by the B.Macfie Family Foundation through the Institute of Public Affairs for which we are grateful.
Relevant and related blog posts
- Fake justifications for rubbish temperature series:
https://jennifermarohasy.com/2023/05/averaging-last-seconds-versus-bureau-peer-review/
2. Holding Bureau to account:
https://jennifermarohasy.com/2016/02/rainfall-forecasts-should-be-benchmarked/
3. Confused and misguided colleagues:
https://ipa.org.au/ipa-today/cyclone-jasper-bom-forecasting-getting-to-the-truth/
Jennifer Marohasy BSc PhD is a critical thinker with expertise in the scientific method.
Appreciate your efforts. Frustration is part of the game – more so when you’re battling against the orthodox y. Truth is priceless nonetheless.
Thank you for the link to the unpaywalled Abbot 2021 paper. Free distribution of real scientific knowledge is unfortunately somewhat rare.
I also suspect that apart from the actual content, the fact that John Q Public can access papers such as this without significant financial output is part of activist dislike of such publications. It avoids their gatekeeping.
Good article. As you say, pity critical article only attract vilification rather than analysis and consideration. There are a lot of careers and egos involved in the status quo. Keep going; you will be vindicated.
The resistance by politicians to accept the John Abbot paper is another example of brainwashed ignorant politicians who actually think they know better than everybody else. The voters must kick them out asap.
How would you describe your treatment of BoM scientists? Pilloried or vilified?
Thanks Karen. There are some hardworking BoM technical people. But the current leadership, beginning with Andrew Johnson, are a national disgrace.
Any charlatan who deliberately corrupts data and tries to censor debate and denigrate and vilify those who hold different and more cogently argued opinions – whether scientific or anything else – just to promote a political and dictatorial mantra deserves to be called out and pilloried. Such smug and self-satisfied climate zealots – self-appointed petty dictators – are only too happy to ruin peoples lives so mere pillorying, even vilification is very tame in comparison.
The evidence for the widespread corruption of temperature data (and indeed much else) or, if one is being polite or more understanding of the genuine but misled technical people, misguided and erroneous ‘correction’ (aka ‘homogenization’) is so well explained by many inquisitive scientists that it is no longer a novel fact. Of course the climate zealots close their eyes and block their ears as religious extremists are wont to do.
I am sceptical of long-range forecasting, certainly the nonsense put out by the IPCC firstly because of the inability to have sufficient data to history match accurately – inventing data is not history matching – and even then no one knows what the future may bring. Essentially it is guesswork and should be treated as such.
But I applaud the efforts of John and Jennifer to better understand natural cycles and use that to provide some ideas for agriculture. I say ideas because I think that even short-term forecasts, which should be relatively easier to assess than long-term can still suffer great surprises. But providing several options for farmers to consider is a lot better than nothing. So their work can be extremely valuable.
And even if they were to discover that there were severe limitations to even short-term forecasts would that invalidate their work? No, far from it, because that is what science is all about; investigation, analysis, conclusion, hypothesis, challenge and modification when errors or new evidence appear.
Did anyone predict the Tongan volcanic eruption in 2021-22 and its impact on weather? No, and the same for countless other events. Could we experience an episode such as the immense volcanic activity that produced the Deccan Traps? Yes very easily. Can it be predicted? No, nor the meteor that hit Mexico a few millennia earlier.
Does any of this uncertainty deter religious zealots? Unfortunately not and they are just as busy trying to burn non-believers at the stake as they were a few centuries ago, just by other means.
The leadership of the BoM to which Jennifer refers, as of so many other national institutions – the UK Committee for Climate Change led by a board that is demonstrably guilty of financial fraud is just one – disdain ethical science and are indeed a disgrace and deserving of far pithier designations. Unless the scurrilous individuals who lead such organizations and their supporting bureaucrats are exposed for what they are we will continue to be fleeced to provide additional riches for the WEF elite. But the public will eventually say “enough” thanks to those who are prepared to put their neck on the line and withstand the brickbats and inane comments thrown at them.
Very ‘convoluted’ to try and project/predict a ‘Base 12’ Cycle, using ‘Base 10’ Maths.
I wonder if John Abbot has considered recalibrating the computer.
Peter, I totally support your comment on this situation. Jennifer and John, your work in exposing the deceit in climate science will surely bring you the recognition this deserves
Sensational work Jennifer, it’s beyond the comprehension of Luddites like me
Magnificent work.
“Any charlatan who deliberately corrupts data and tries to censor debate and denigrate and vilify those who hold different and more cogently argued opinions – whether scientific or anything else – just to promote a political and dictatorial mantra deserves to be called out and pilloried.”
Hmm, it seems like you are defending “political scientists” funded by the fossil fuel industry. Who’s paying you?
Jennifer,
Glad to see you and John are still in the fight.
You may want to follow this thread on Research Gate hosted by Peter Eirich
https://www.researchgate.net/post/The_physical_processes_of_global_warming_and_climate_change–How_can_alternative_viewpoints_be_resolved
Karen’s unselfawareness is as telling as her uninformed efforts at snark.
hunterson7, it seems you are ok with people disparaging BoM and NASA experts. Could it be that you are uninformed?
Does Karen Klemp work for BoM? She seems very defensive. Why? Surely the BoM can cope with rigorous scientific review and challenge? Jennifer Marohasy is doing exactly this. Thank you Jennifer.
Barbara Sheppard seems very defensive. Why? Does she work for the fossil fuel industry?
Karen = troll. And not an informed one at that. On ignore list.
I do not work for the fossil fuel industry, but I recognise the global importance of fossil fuels. Karen’s contempt confirms her ignorance.
“Homogenisation is the method of analysing and adjusting temperatures to remove the artificial influence of things such as site relocations and upgrades to equipment. The process of homogenisation seeks to answer a very simple question: what would Australia’s long-term temperature trend look like if all observations were recorded at the current sites with the current available technology? Homogenisation means we can compare apples with apples when it comes to temperature trends.
The Bureau’s methods have been extensively peer-reviewed and found to be among the best in the world. This is crucial, as it means the community can have confidence the Bureau is providing an accurate estimate of Australia’s true temperature trend.
You can read all about the methods in the ACORN-SAT peer reviewed technical report,”
Some are very sensitive regard the homogenization rorting and continue to attempt to justify the deliberate adulteration of the actual data to achieve a preconceived target. A bit like the flat earth society of the day.
Sounds more like a conspiracy theory promoted by climate change deniers. BoM backs their results up with actual rigorous data, not allegations. It’s all out there if you care to look.
https://media.bom.gov.au/releases/18/bureau-of-meteorology-media-statement-no-2-climate-records/
Philip Mulholland MSc has emailed, requesting I add this comment to the thread.
There are many natural processes that respond to and record environmental influences, such as seasonal temperature cycles. These processes include (but are not limited to):
1. Formation of glacial ice layers and ice caps whose thickness is recorded by coring
2. Lacustrine Sedimentary layers (Varves) also recorded by coring.
3. Growth patterns of Marine Corals
4. Growth patterns of tree rings (Dendrochronology).
5. Cave formation stalactites and stalagmites (Speleothems) formed by calcite minerals deposited during dissolution from water.
All these processes leave a natural record that can be collected and studied by data analysis. Seasonal and annual variations in layer thickness form a basic qualitative data series. However, a more robust analysis involves determining the stable element isotopic ratio of carbon and oxygen atoms in the material being measured. It is by this means that the relationship between the soft qualitative environmental data of layer thickness and the hard numerical data of temperature can be established. For this link to occur there must be a plausible geophysical process that determines variations in isotopic ratio.
Consider the case of cave speleothems. One of the most noticeable features of a cave environment in the vadose zone (the air-filled voids above the water table) is the constant long-term air temperature. So how is the step from a constant temperature cave environment to obtain a climate signal made? The answer lies in the analysis not of crystal layer thickness but in the stable isotopic ratio of the crystal structure. The link back to climate variability comes from the measured and established fractionation of light 16O water versus heavy 18O water https://en.wikipedia.org/wiki/Oxygen_isotope_ratio_cycle
The fractionation of precipitation water (rainfall and snowfall) in favour of the light 16O isotope that was reported by the Danish paleoclimatologist Willi Dansgaard, (1964) is a real geophysical process that produces a temperature signal which can be measured, quantified, and mapped to identify a valid climatic temporal response, even in the stable environment of a cave.
The use of isotope fractionation is also used in ice core analysis, but is not currently used in dendrochronology. This is why the 1974 work of Leona Marshall Libby is so important. (Libby, L.M. and Pandolfi, L.J., 1974). It takes us away from the measurement of ring thickness on an individual tree by tree basis that is highly variable, to the common overarching control on tree growth of atmospheric physics (temperature and isotopic composition).
It is imperative to get away from the kludge of mashing thickness data (tree rings and ice lake varves) into a data stream based on isotopic ratios (ice core and tropical cave speleothems) that forms the basis of the iconic hockey stick of Michael Mann. However, the key problem with the hockey stick is not just this mismatch of mixed data types (a correlation issue) it is in fact the calibration issue of applying a varve data set that has literally been inverted to damp the historic temperature response.
The use of the Korttajärvi lake varve data from Finland Tiljander et al (2003) is discussed in detail by Steve McIntyre in 2008 here in Mann et al 2008: Korttajärvi https://climateaudit.org/2008/09/03/mann-et-al-2008-korttajarvi/
In this 2008 post Larry Huldén of the Finnish Museum of Natural History writes:
The Finnish Lake sediments cannot be used for temperature interpretations in the 18th to 20th century unless you know exactly the history of the regional lake environment conditions. We have 180,000 lakes in Finland. It is very easy to cherry pick among them and say that it is a random sample. Of all lakes, 1,500 lakes are affected by lowering of water levels. These must be omitted. Many other are affected by agriculture including forestry. This affects the relative components of the sediments. This is well known although somebody can by chance use them for climate trends. Finnish prof. Matti Saarnisto has showed me graphs of lake sediments from Finland which can be used for temperature trends but still show strong deviations in the recent 200 years because of agriculture. These lakes are not always very close to agricultural sites.
In addition, we must remember that the fauna or flora in the sediments do not represent the temperature of the air because long term trends in water temperatures do not correlate with long term trends in air temperatures.
Fast forward from 2008 to 2021 where we have John’s work Using Oscillatory Processes in Northern Hemisphere Proxy Temperature Records to Forecast Industrial-era Temperatures. Earth Sciences, 10(3), 95-117 in which he states:
One perspective of temperatures over the past 1,000 years embodies a major oscillation with a peak corresponding with the Medieval Warm Period (MWP), a trough representing the Little Ice Age (LIA) and subsequent increasing temperatures to the present. An alternate temperature perspective, known as the “hockey stick” exhibits a slow long-term cooling trend downward from about 1000 AD to about 1900 AD, followed by relatively rapid warming in the 20th century and is a prominent feature in describing the apparent climate crisis. The present study, using spectral analysis, shows that both types of profile have a dominant millennial oscillation and a set of lower power centennial and decadal oscillations. The key difference in determination of development of the proxy temperature profile into either a hockey stick or MWP_LIA cycle is the phase alignments of centennial and decadal oscillations with respect to the millennial oscillation.
What I find interesting about John’s assessment is that he is implying that the iconic Hockey Stick reconstruction of Professor Mann and the foundational climatic reconstruction of Professor HH Lamb, are both representations of the same data resource that can be used to support conflicting climate narratives.
References:
Dansgaard, W., 1964. Stable isotopes in precipitation. Tellus, 16(4), pp.436-468. https://www.tandfonline.com/doi/pdf/10.3402/tellusa.v16i4.8993
Libby, L.M. and Pandolfi, L.J., 1974. Temperature dependence of isotope ratios in tree rings. Proceedings of the National Academy of Sciences, 71(6), pp.2482-2486. https://www.pnas.org/doi/pdf/10.1073/pnas.71.6.2482
Tiljander, M.I.A., Saarnisto, M., Ojala, A.E. and Saarinen, T., 2003. A 3000‐year palaeoenvironmental record from annually laminated sediment of Lake Korttajarvi, central Finland. Boreas, 32(4), pp.566-577. http://www.climateaudit.info/pdf/paleolimnology/Tiljanderetal.pdf