From the UNIVERSITY OF EAST ANGLIA and the “We have 25 or so years invested in the work. Why should I make the data available to you, when your aim is to try and find something wrong with it.” department comes this laughable attempt to boost the image of climate science via making graphs “accessible to non-experts”. Yes, it’s the old canard “if only we could just make people understand it the way we do, they’d get behind it”. If they need a graph to make ‘accessible to non-experts’ they should start with “Mike’s Nature Trick“. They should make this required reading: Lies, Damned Lies, Statistics … and Graphs

New guidelines aim to improve understanding of scientific data
Drawing on cognitive and psychological sciences and using climate change data as an example, the team looked at how scientists and other communicators can increase the accessibility of graphics used to present information, while maintaining scientific accuracy and rigor.
Scientific information is one factor that can influence decision-making to achieve change, and visualisation of data through graphics – such as graphs, diagrams and thematic maps – plays an important role in the communication of climate change findings to both expert and non-specialist audiences.
However, graphics created for scientific assessments published by bodies such as the Intergovernmental Panel on Climate Change (IPCC) have been criticised for being inaccessible to non-experts.
The researchers from UEA and Temple University provide guidelines to support climate scientists in developing more accessible graphics. They show how they can be applied in practice and provide recommendations on how the IPCC might use these guidelines in the development of future reports.
The project was conducted in response to the IPCC itself asking how graphics and reports can be made more user-friendly as it looks ahead to the Sixth Assessment Report, due to be released in 2020-2021.
Writing in the journal Nature Climate Change, the researchers suggest that graphics should be tested during their development to understand viewers’ comprehension of them, for example by using eye tracking technology to measure visual attention.
Co-author Prof Kenny Coventry, an expert in the relationship between language and perception and head of UEA’s School of Psychology, said the cognitive and psychological sciences can provide valuable insights into how visualisations of data can be improved.
“Graphics of climate data are integral to scientific assessments of climate change, but only support communication and decision-making if they are understood,” said Prof Coventry.
“Testing graphics and applying insights from the science of human cognition to help overcome comprehension problems offers the potential to make climate science knowledge more accessible to decision-makers in society, while also retaining the integrity of the scientific data and evidence on which they are based.
“The ease of accessibility of graphics of climate science has implications for how society might make best use of scientific knowledge. Graphics of climate data that are accessible to all parties involved could support improved engagement, dialogue and decision-making between scientists, policy-makers, practitioners, communities and the public.
“While the science underpinning graphic comprehension is still developing, the guidelines we present provide a useful reference for climate scientists to apply psychological and cognitive insights when creating graphics of data.”
The researchers say that visual attention when viewing graphics can be limited and selective – visual information in a graphic may or may not be looked at and/or processed by viewers. An excess of visual information can also create visual clutter and impair comprehension, while the visual structure and layout of the data influences the conclusions drawn about it.
Animating a graphic may help or hinder comprehension, and the language used can influence thought about the graphic.
The team used the guidelines to re-design a figure from one of the IPCC’s Summaries for Policy Makers (SPMs), which are primarily aimed at experts working in government. This cognitively inspired version included larger font size to highlight key headings, emphasised important differences using contrast in colour, and reduced visual clutter. When tested with a sample of climate change researchers and non-experts, 80 per cent of them preferred the cognitively inspired version.
The guidelines include:
- Direct viewers’ visual attention to visual features of the graphic that support inferences about the data;
- Include only information for the intended purpose of the graphic; break down the graphic into visual ‘chunks’, each of which should contain enough information for the intended task or message;
- Identify the most important relationships in the data that are to be communicated; consider different ways of structuring the data that enable the viewer to quickly identify these relationships;
- Use text to help direct viewers’ understanding of the graphic, for example by providing key knowledge needed to interpret the graphic.
Jordan Harold, co-author and PhD researcher within UEA’s School of Psychology and the Tyndall Centre for Climate Change Research, said: “Visually representing climate data to inform decision-making can be challenging due to the multi-dimensionality of data, a diversity in users’ needs across different stakeholder groups, and challenges and limitations in the use of software and tools to create graphics.
“As the IPCC prepares for its Sixth Assessment Report, there is an opportunity for it to open up the review process and ask the psychology and cognitive science communities, and those working in associated disciplines, for feedback on drafts of graphics. Similar collaborations have led to improved communication in related scientific fields.”
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‘Cognitive and psychological science insights to improve climate change data visualisation’, authored by Jordan Harold, Irene Lorenzoni, Thomas Shipley and Kenny Coventry is published in Nature Climate Change.
My favorite graph that visually tells the story is the one of Napoleon’s march on and subsequent retreat from Russia. It even includes some weather data.
https://www.bing.com/images/search?q=graph+of+french+march+on+and+subsequent+retreat+from+russia&view=detailv2&qpvt=graph+of+french+march+on+and+subsequent+retreat+from+russia&id=C8B9EB3B12DD8EDDCF3794382801B8E48ABD7C1E&selectedIndex=6&ccid=RxcbzH4p&simid=608017192542012057&thid=OIP.M47171bcc7e291cd135896ede528af97ao0&ajaxhist=0
More evidence that cold weather is lethal.
Often it is not the graphs that are the problem, but the people failing to interpret them. One of the clearest examples is from the UNFCCC. Last year they globally aggregated all the INDC submissions – the country policy proposals – to see the impact. In total, if fully implemented, the policy proposal would not stop global emissions going up. In the climate alarmist terms to achieve the 1.5C or 2C target global emissions need to fall down. To make it really simple the UNFCCC made the policy impact a thick yellow band in a graph of global projected emissions against time. They then put thick blue arrows for 1.5C and 2C emissions pathways.
http://unfccc.int/files/focus/indc_portal/image/jpeg/fig2exec_syr_update_v27apr2016_905_withlegend.jpg
Despite this very clear statement, rather than declare mitigation policy was useless, they still signed an agreement still believing that the 2C emissions pathway was possible.
Good examples of this blindness to simple graphs is in the reactions to Donald Trump being elected President. Joe Romm claims that Trump will make reaching the 2C limit impossible, forgetting that the US produces less than one seventh of global emissions. Reading the graph will show a 100% reduction in US emissions from January 1st 2017 will not meet the 2C target for 2030. Even worse is the expert scientists at RealClimate. In their calculations they seem to believe that CO2 is the only greenhouse gas.
https://manicbeancounter.com/2016/11/29/the-climate-alarmist-reaction-to-a-trump-presidency/
Putting error bars on their graphs would be a start.
Just a thought.
Asmilwho: “Putting error bars on their graphs would be a start.”
The average climate “scientist” wouldn’t recognise an error bar if you beat them over the head with it.
Joseph Goebbels would be proud of these people…..
… and vice versa.
Sad but true…..
In other words only show graphics of data that backs up your argument for CAGW lest someone may realize the data doesn’t match your conclusion.
In god we trust. All others bring data.
Heller has been providing great graphics all along, n’est pas?
Yes, yes he has. Heller is making Gavin nervous. 🙂
Voodoo science and public relations, need there be more to invalidate the facts?
I pulled down the NOAA NH ice data used to make the 1990 FAR chart 7.20 we were discussing. The data were interestingly derived from the weekly charts produced by the Navy. For the ‘digization’, they put a grid over the map, pole to 50 degrees Lat. with 1 degree Lat. x 2.5 degrees Long. cels, and identified a cel as ‘ice’ if at least 1/2 of the cel had ice in at least 1/8th concentration. In the next pass, the cels were grouped in 10 degree long. Sections, pole to 50 degree latitude, and summed the areas of ‘ice’ for each 10 section, reporting each section in 1000s of sq km, to 2 decimal places. This approach gives 36 numbers per month, and spans from January 1973 through August, 1990.
One thing that makes the data a bit noisy is that they used only the chart from the last week of a month for the digitizing. The lowest month was sept ’79. At 6105.64 x 1000 km sq.
Small correction: …areas of ‘ice’ for each 10 degree latitude section…
One more time: 10 degree LONGITUDE section.
https://petition.parliament.uk/petitions/174557/sponsors/leEDsU5M84uVGdXkkvdk
This petition to parliament request that the university of East Anglia release the data.