Open Climate Knowledge launches a Force11 Working Group—Join Up!

Open Climate Knowledge is an open research project supported by GenR. The project aims at making research related to climate change 100% open ASAP. To do this two strands of work are planned: firstly, data mining of open research paper repositories to build an open research knowledge base, and secondly, to make a plan for how to transition to 100% open. There is an open invitation to join the Force11 working group with an introductory video conference taking place on February 11th.

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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.

Cite as:

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
Cite as:

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 & Climate Change Resources: A Collaborative Index — Contribute!

🌍 The climate index is part of the GenR theme ‘Open Science and Climate Change‘ for which there are two areas of inquiry:

  • firstly, a low-carbon energy future — technologies and innovations, and;
  • secondly, climate sciences — monitoring and understanding the environment and the effects of climate change.

Contribute: Add a project, paper, software, data set, call-outs, etc!

Add an item, chat, or leave a comment

Join us over at the open pad on the CryptPad platform and add items or leave a comment.

In early autumn 2019 highlights of the Open Science & Climate Change Resources Index will be published on GenR and at a later date an open collaborative paper will follow summarizing the findings of the indexing process.