It can be challenging to convey climate data, especially when the timescales are far greater than those people usually think about. This protocol allows users to create generative animations with visuals scaled to data. With this procedure, the data can be transformed into animations that convey information without relying on charts or graphs.
It is highly customizable in terms of data used and the visual aspects displayed. It would be interesting for a social experiment to be conducted on public perception of climate data based on different modes of data presentation. This work could be one visual technique alongside more traditional or artistic methods.
Coding in any new language or learning new software can be challenging. Online resources and internet searches for key terms or codes can help. After downloading the coding and visualization software, download the data and begin to code.
Drag the desired MPT file, MPT 1, MPT 2, MPT 3, or MPT 4 into the code editor to visualize it. In the explorer menu, click on the desired MPT folder, MPT 1, MPT 2, MPT 3, or MPT 4 to reveal a dropdown menu. Then click on the script, followed by clicking on index.html.
Left click the window portion with the code for index. html and select Open with live server from the menu. Repeat the steps, starting from selecting the MPT folder in the explorer menu for each subset of time.
To view the visualization based on future projections, open the future folder on the computer and drag either the accumulation or transition folder into the code editor. Next, select the folder name in the explorer window and click on index.html. Left click the portion of the window with code for index.
html and select Open with live server from the menu. To edit the visualizations, select the folder of interest in the explorer window of the code editor and open the main script file by clicking sketch.js. Perform any edits to visualization parameters within this code.
Look for code annotations with detailed descriptions of the code and its function, following double slashes and further identified by green texts. Define the variables that will be linked to data or used to customize visual parameters. Next, save the edits by simultaneously pressing the command and S keys.
View updated visuals by navigating to the index. HTML file. In the explorer window, left clicking and selecting Open with live server from the menu.
Visualizations corresponding to unique geological time periods were generated. Visual aspects such as color, size, and speed were quantitatively scaled to estimates of sea surface temperature, nitrogen, isotopic composition, and the rate of climate change. The data were either measured on deep sea sediments or modeled from the intergovernmental panel on climate change, or IPCCs representative carbon pathway, or RCP scenarios.
The animation generated from MPT 1 code corresponded to the earliest time segment about 1.2 to 1.118 million years ago. Well prior to glacial-interglacial lengthening and glacial cooling. The MPT 2 code corresponded to about 1.112 to 1.06 million years ago, immediately before glacial-interglacial lengthening and glacial cooling.
MPT 3 generated the visuals for the second latest segment of time with longer glacial-interglacial cycles, about 1.06 million to 900, 000 years ago. MPT 4 code generated the visuals for the most recent time segment, about 900, 000 to 600, 000 years ago when longer glacial-interglacial cycles were more established. The accumulation code generated model projection for future anthropogenic warming based on temperature estimates of RCP 8.5 model averages for New York.
The transition code created a simpler visual of the same, showing only the outline of orbs moving across the background. The product format allowed for the customization and presentation of data, creating immersive science communication exhibits. When editing the code, ensure it corresponds to the current data sections.
For future projections, only have the transition or the accumulation folders in the working space. Otherwise, the program will not work. This technique opens doors for including scientific data in graphic design.
Generative and immersive art are rapidly growing fields with many opportunities for art to interact with science and data.
