Climate visualizations for the people: Probable Futures

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Nov 17, 2021

Climate visualizations for the people: Probable Futures

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Nov 17, 2021

Probable Futures just launched a strikingly detailed visualization platform to bring the reality of climate impacts to the general public. Mapbox has been working closely with their team as they processed complex data into web-ready maps and tilesets—all built for reuse by developers to produce tools like Azavea’s The 50 Hottest Places in US Politics. I wanted to learn more about their journey and set up to talk with Alison Smart, the executive director of Probable Futures, and Peter Croce and Zachary Harris from their software partner Postlight.

Probable Futures looks amazing. What drove you to build the site? What has been missing from the science and story of climate change?

Alison: We were missing a strong bridge between climate science and culture. For decades, scientists have built a trove of useful information about the future, but it was not well translated into publicly available and easily accessible tools. In partnership with a team of collaborators, we have built a global utility that vividly illustrates the consequences of climate warming through interactive maps and a sensory storytelling experience. 

Our intention for Probable Futures is to be intuitive, useful, and personal for every person, no matter where they live in the world, and help them to internalize the scope, the scale and the urgency of the crisis we are facing. This required a vigilant focus on simplicity. We were constantly editing ourselves and questioning when we had impulses to add features and knobs and buttons. Climate science is really quite intuitive, and we wanted our site to reflect that. Probable Futures allows users to explore the data at their own pace, with opportunities to reflect on and internalize what they’re seeing and reading—similar to the experience of reading a good book. Complexity in the design or functionality would have hindered that goal.

I understand that building web map platforms was new for your group. Once you decided on this direction, how did you assemble the team to make this happen?

Alison: We wanted to work with people who were curious and unconventional, and who didn’t come to the project with preconceived notions about “what works” when communicating climate change to the general public.

With Woodwell Climate Research Center as our science partner, we were confident in our ability to accurately and responsibly reflect climate science and geospatial climate data. But for Probable Futures to be accessible and inspiring, we knew that it would have to be beautifully designed and have an extraordinarily user-friendly interface. We recruited world-class agencies Postlight Digital Product Studio and Moth Design to help us. Not only are they highly-skilled in their crafts, they also have strong interests in climate change and science communication.

We’re also proud to partner with Mapbox for the mapping components of our project. We especially value its wealth of educational resources, support, and active communities of partners and builders. 

In short, we assembled a team that understands and appeals to the audiences we are trying to reach and shares the values and goals of our initiative. They have been and are the key to curating a successful map platform.

Climate model data is notoriously dense and difficult to work with. What did it take to prepare this data for use in your maps? What did you try, and what eventually worked?

Zach: The data was indeed dense, and our engineering team had to start by familiarizing ourselves with a three dimensional file format that is typically only used inside the climate science community: NetCDF. Because there was no obvious standard method for transforming these files into web-friendly formats like GeoJSON, we built a translator from scratch, and chose PostgreSQL/PostGIS for flexible experimentation with the process. 

Peter: The most important ingredient was a lot of communication and exchanging ideas between climate scientists, engineers, and designers. Working closely with Mapbox helped us appreciate just how novel the climate-data-translation work we were doing really was. The fact is that many of the systems and frameworks we use today are simply not conditioned to incorporate climate data. In fact, Mapbox accelerated previously-planned developments to their Mapbox Tiling Service architecture to increase and customize tile size when it became clear that it could be more compatible with climate data. 

In the cartography and design, we committed to accurately representing climate model data and keeping the design and usability simple and intuitive. For example, climate models produce grid cells, and those grid cells aggregate and average out the climate model simulations within that cell. Most map visualizations “smooth out” those grid cells into continuous color gradients. While this sends a visual signal of high-resolution precision, it actually dilutes the data. We decided to keep the grid cells intact, which enables users to explore the data behind those cells. This way, we can even educate the user about what kind of precision they should expect from other climate models.

What Mapbox tools did you employ and how? Have any feedback for us on what could be improved?

Zach: While a lot of climate data uses raster grids, vector tiles were better suited for Probable Futures because of their flexibility. With vector tiles, we were able to play around with different ways to organize and visualize the data in real time. For example, we spent some time as a team using our own internal, highly customizable version of the public map application to experiment with the visual classification of  “bins” for climate data until we found the ones that were most intuitive for the average user. 

After a fair amount of experimentation, we decided that we need to be a “power user” of the Mapbox Tiling Service. The interactive map had to be smooth and performant, especially when moving between maps. Comparing one warming scenario to another was a critical function and the transition between them needed to be seamless. After trying to build our own tiling system, it became clear that Mapbox tiles were the best way to achieve speed—both for rapid iteration of styles during the testing phase and for efficient load times in the browser for the finished product. 

Creating the recipes for the tilesets required a lot of trial and error because of a combination of factors. Mapbox engineers helped greatly by significantly increasing tile size limits during our development process. The Probable Futures datasets are enormous and vary in how spatially homogeneous their data are between scenarios. We understand MTS has standard size limits to optimize the map experience. However for climate model data as detailed as ours, the previous limits posed a challenge to processing our data effectively. We tried using a tileset recipe to slice the gridded data up into multiple “sources” to fit within the tileset limits, but the “slicing” parameters differed between tilesets because of different units of measurement (temperature, or time.) When we shared these challenges with Mapbox engineers, they helped us improve our recipes and the introduction of increased limits enabled us to move through the development process more efficiently and with much less trial and error.

The site isn’t the only way to work with the data. You’ve also made processed tilesets available for others to build with. What has been built so far and what do you hope to see?

Alison: Yes, we’ve seen really creative integrations already. Azavea built The 50 Hottest Places in U.S. Politics. They combined Probable Futures’ tilesets with Cicero, their database of elected officials, to highlight intensifying heat and future trends. Their project drives political action by informing their visitors and encouraging them to contact their elected officials. Kontur analyzed where increased temperatures corresponds with greatest density of people and integrated that combined metric into their disaster-preparedness product Disaster Ninja

These were two natural applications of the Probable Futures maps. But we know that climate change will directly and indirectly impact every aspect of life, so the potential applications are endless. That’s why we’re committed to making this information accessible to all. The Mapbox Data Exchange allows us to share our tilesets with others who want to build upon the maps and customize them for their own organizations, industries and communities. We are eager to see what others in the Mapbox community can imagine and build to more thoroughly explore the futures that the climate offers to us. 

Thanks to Probable Futures for insights into building this incredible climate data resource! If you want to try building climate data into your mapping application, find details about their shared climate tilesets in our data exchange.

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Maps feature data from Mapbox © Mapbox, OpenStreetMap © OpenStreetMap and their data partners, including Maxar (if applicable, © Maxar).

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