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THE next really big breakthrough in environmental management could come from better forecasting of droughts and floods. In particular, using machine learning to mine historical climate data, build models based on clever algorithms, and use these to forecast rainfall.

If you would like to understand this technique that John Abbot and I have developed, consider downloading our most recent book chapter. It can be downloaded as a PDF from this link, from the ClimateLab.com.au.

As a consequence of my involvement in this work, and searching for the best long historical temperature series, I stumbled across deficiencies in how the Australian Bureau of Meteorology archives its temperature data – and how it remodels temperature series to make them more consistent with human-caused global warming theory.

Over the last year I’ve come to realize that the problem extends far beyond remodeling raw data. There are also issues with the calibration of the electronic probes that have been used to measure temperatures since November 1996, this casts doubt over the integrity of the actual raw data.

Of course, fundamental to machine learning is the integrity of the data. So, in corrupting the measurements the Bureau may not only be artificially exaggerating the extent of recent warming, it is compromising our ability to forecast rainfall using the latest big data techniques forever.

I didn’t explain this in my recent letter to Australia’s Chief Scientist Alan Finkel. I mostly detailed how the Bureau’s measuring system may not be fit for purpose – and suggested he look into it. I emailed and posted the letter to Alan Finkel on 4th May, 2018. You can download a pdf copy by clicking here.

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My latest scientific publications, including on rainfall forecasting, are listed at the Climate Modelling Laboratory website.

I wrote the following two statements down on a scrap of paper when I was an undergraduate at the University of Queensland in the early 1980s.  They seemed to resonate more with me as each year passes:

1. Belief in the truth of a theory is inversely proportional to the precision of the science.

2. The creativity of a scientist is directly proportional to how much [s]he knows, and inversely proportional to how much [s]he believes.


For many years this website operated as a weblog, rapidly building a regular readership of several thousand.   Since 2007 the entire website has been archived by the National Library of Australia, annually, each February.


I moved to Noosa, in southeastern Queensland, a few years ago. In 2015, I established the Climate Modelling Laboratory to progress my work with John Abbot developing a technique for monthly rainfall forecasting using artificial neural networks: a form of artificial intelligence/machine learning/big data analytics – finding patterns, building models, projecting foreward, measuring the model’s skill at forecasting.

As well as interrogating large datasets, I enjoy swimming in the ocean, yoga, meditation and the occasional walk in the rain. My heros include William of Ockham, Thomas Huxley, Clement Wragge and Emile du Chatelet.

Jen cropped 70


For a list of my papers on rainfall forecasting and temperature reconstructions click here; a more comprehensive list of scientific publications is click here.  Over recent years I have been published in: Atmospheric Research, Advances in Atmospheric Research, Wetlands Ecology and Management, Human and Ecological Risk Assessment, Public Law Review and  Environmental Law and Management.

I was published every fortnight for about 10 years by The Land newspaper, Fairfax Media Ltd (April 2004 – November 2014).  I resigned as columnist, and also stopped regularly blogging, to concentrate more on my scientific research.

The skill of our forecasts can be measured in terms of root mean square errors (RMSE) and mean absolute error (MAE) relative to observed rainfall.  This means that our forecasts could be easily compared in a rigorous and quantitative way against the forecasts from general circulation models including the Bureau’s POAMA.  However, so far, the Bureau has resisted any comparisons being made, as I detailed in a letter to Simon Birmingham in August 2014, which can be downloaded here.  The skill of our rainfall forecasts is affected by the quality of the temperature series inputted as part of multidimensional arrays, which is why I have become somewhat vocal about the often ad hoc process of homogenization undertaken to temperature series by the Bureau.

I am also a senior fellow at the Institute of Public Affairs, with this work funded by the philanthropic B. Macfie Family Foundation.

For nearly two decades I have advocated the restoration of the Murray River’s estuary through removal of the 6.7 kilometres of barrage. From July 2011 through until August 2017 I maintained the ‘Myth and the Murray’ website.


On Line Opinion, Australia’s e-journal of social and political debate, published me from 2003 to 2017, with links to these articles here. I recently started writing for The Spectator, with my author page here.

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