Channel Hunt: 10 Ways to Present Climate Change Science on YouTube

Image: Arctic sea ice likely reached its 2019 minimum extent of 1.60 million square miles (4.15 million square kilometers) on September 18th. This video is public domain and along with other supporting visualizations can be downloaded from the Scientific Visualization Studio at: http://svs.gsfc.nasa.gov/13309. YouTube channel: ‘NASA Goddard’, NASA, 2006. https://www.youtube.com/user/NASAexplorer.

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DOI

10.25815/e2c0-3118

Citation format: The Chicago Manual of Style, 17th Edition

Generation Research. ‘Channel Hunt: 10 Ways to Present Climate Change Science on YouTube’, 2019. https://doi.org/10.25815/e2c0-3118.

GenR has selected ten YouTube Climate Change channels to demonstrate different styles of presentation of scientific research on Climate Change to YouTube audiences. In a recent interview featured on GenR with the researcher Joachim Allgaier YouTube — Fix Your AI for Climate Change! An Invitation to an Open Dialogue’ (Allgaier and Worthington 2019) the recommendation was made to scientists working in fields related to climate change to post videos about their research on YouTube to ensure the voice of science is heard on this significant communications platform. To help scientists get to grips with how to engage with YouTube audiences GenR is offering up this varied selection of example climate change science channels.

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Modeling Low Carbon Energy Futures for the United States

Estimated U.S. Energy Consumption in 2018
Source: Estimated U.S. Energy Consumption in 2018: 101.2 Quads. LLNL March 2019. Lawrence Livermore National Laboratory and the Department of Energy, URL: https://flowcharts.llnl.gov/ *more info
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DOI

10.25815/xbvj-xa70

Citation format: The Chicago Manual of Style, 17th Edition

DeCarolis, Joseph. ‘Modeling Low Carbon Energy Futures for the United States’, 2019. https://doi.org/10.25815/xbvj-xa70.

A new project will create an Open Energy Outlook for the United States to complement the US Annual Energy Outlook, which produces modeled projections of domestic energy markets. The Open Energy Outlook will utilize an open source energy system optimization model to examine US technology and policy pathways for deep decarbonization. Energy models provide a self-consistent framework to evaluate the effects of technology innovation, shifts in fuel prices, and new energy and climate policies. The focus on open source code and data is intended to foster community involvement in the effort, allow researchers to interrogate the model and reproduce published results, and engender trust within the broader community of modelers, analysts, and decision makers. The project has been funded by the Sloan Foundation.

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Open Science, Collaboration and Participation in Energy System Research

Image: “StEmp-Tool Anhalt-Bitterfeld-Wittenberg“ © Reiner Lemoine Institut | CC BY 4.0

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DOI

10.25815/63vz-v811

Citation format: The Chicago Manual of Style, 17th Edition

Hülk, Ludwig. ‘Open Science, Collaboration and Participation in Energy System Research’, 2019. https://doi.org/10.25815/63vz-v811.

Open Energy Modelling has been built up as a research community over the last ten years aiming to bring transparency to the field using an array of Open Science methods for the planning of energy systems. The role of collaboration in the research cycle used by scientists in this engineering community is now an established Open Science practice. Similar practices of collaboration and participation outside of academia involving the public are still in their infancy. Harnessing public participation in energy planning and policy development is likely change as the energy sector is undergoing rapid changes due to its large contribution to greenhouse gases and the consequent demands for transparency and innovation to tackle climate change.

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An Open Energy System Modeling Community

Image: GPLv2+ license notice for the now‑defunct deeco energy system model added on 24 February 2003. Courtesy Robbie Morrison

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DOI

10.25815/ff3b-d154

Citation format: The Chicago Manual of Style, 17th Edition

Morrison, Robbie . ‘An Open Energy System Modeling Community’, 2019. https://doi.org/10.25815/ff3b-d154.

The Open Energy Modelling Initiative (shortened to openmod) is an online and offline umbrella community devoted to promoting open energy system modeling and analysis. While there are no restrictions on application area, the bulk of funded research is directed toward questions involving public policy. As of late‑2019, the openmod has about 600 participants on its mailing list, with most of them being full‑time researchers or analysts. More information on Wikipedia. Key URLs are listed in the infobox below.

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YouTube — Fix Your AI for Climate Change! An Invitation to an Open Dialogue

Image: Ganges River Delta. Image provided by the USGS EROS Data Center Satellite Systems Branch. Caption adapted from text provided by NASA’s Earth Observatory. Source: NASA/USGS Landsat 7; NASA Earth Observatory. From NASA Climate YouTube channel https://www.youtube.com/user/NASAClimate

An interview with Joachim Allgaier on his recently published study on how social media platforms such as YouTube have become hostile to climate science. When you search around climate change on YouTube the results are 50/50 climate science versus anti-science Chemtrails conspiracy theories. YouTube and Google Scholar have been strategically hijacked by groups posting anti-science content, while at the same time academia has neglected to use YouTube and recognise it as the vitally important channel for their scientific voices to be heard. The interview is a call for scientists to actively engage with the platform and for YouTube to reflect the values put forward by its CEO and Google co-founder Susan Wojcicki of an appreciation of the scholarly environment within Silicon Valley. These values could be actioned in YouTube’s AI to favor scientific factual content and by adopting Open Science practices of enhanced transparency across its platforms as anti-science Chemtrails content is also immediately found in search results on Google Scholar. Open has worked for Google’s support of its technology stack with open source, why not apply the same workings to its search indexing, dare it be said by applying a little open library science.