Leveraging Artificial Intelligence To Raise the Urban ‘Climate IQ’
Today, New York City. Tomorrow (well, make that, about three years from tomorrow), the world.
Building on its post-Hurricane Sandy partnership with New York City government, over the next three years The New School’s Urban Systems Lab (USL) intends to develop and test an open-source climate risk assessment tool available to cities worldwide.
Its enabling technology: Artificial Intelligence.
Called ClimateIQ, the ambitious project received a major boost in September, via a $5 million grant from Google.org, the philanthropic arm of the ubiquitous information tech company. Coupled with a pledge to find ways to support ClimateIQ with Google researchers, designers, and engineers, the grant will allow USL to hire data analysts, machine learning specialists, and other technical staff.
Their mission: Synthesizing the vast and ever-growing ocean of climate-related data – much of it generated by low-orbit satellites maintained by the National Oceanic and Atmospheric Administration (NOAA, the parent organization of the National Weather Service) and the Copernicus “eyes on the Earth” program of the European Union – as well as from other sources.
Partnerships with up to 11 cities around the globe will form another key element in the project. Ideally, says USL associate director Christopher Kennedy, the selected cities will occupy a broad array of the Earth’s regions and, consequently, confront a wide variety of climate change issues, from coastline sea level rise to landlocked desertification.
So far, New York City is on board. Kennedy says the USL team is also considering working with Phoenix, the “Exhibit A” city for the mega-drought and record-shattering summer heat that have gripped the American Southwest in recent years. (It has prompted Phoenix’s establishment of an Office of Heat Response and Mitigation). Feelers are out to European, Asian, African, and Latin American cities, too.
The partner cities, and participating private sector and academic researchers in Australia, Scandinavia, and the US, will help establish what Kennedy calls “a generative learning environment” intended to test and enhance ClimateIQ’s A.I. findings. They also will – by the end of the project’s third year – have been involved in trial-running and refining a free, interactive, and multi-platform “dashboard” app, to be created by a private sector partner, ClimaSens.
A.I.’s power to use machine learning to model climate scenarios will produce information cities can, it’s hoped, use in infrastructure planning and decision-making about climate resiliency and adaptation measures.
ClimateIQ will attempt to democratize climate information now sometimes made less accessible by copyrights, paywalls, or other factors. Among its intended beneficiaries, Kennedy says, will be less-resourced or smaller cities that lack the climate analysis and modeling capabilities of larger cities.
ClimateIQ is intended to give them, and all its users, multi-hazard climate risk information. That includes presenting the ways that extreme weather can have multiple and cascading consequences – that a heat wave can intensify air pollution or result in a power outage, or that sea level rise can interact with rainfall-indued flooding in inland cities, too.
It also entails putting a human face on the high social costs closely associated with climate change and extreme weather events. Many of the poorest New Yorkers, for example, suffered most from Hurricane Sandy – a harsh lesson about the consequences of locating so much high-rise public housing along the shorelines Sandy inundated. New York now faces years of “target hardening” such areas against storms and rising sea levels. By showing cities how climate change interacts with such demographic fault lines, it’s hoped that ClimateIQ can help them avoid similar human misery and budgetary burdens.
Since its founding in 2015, USL has cooperated with New York City governmental agencies (most recently, through the Mayor’s Office of Climate and Environmental Justice) to model future flood and heat risks (A USL map of potential future coastline flooding in Lower Manhattan is pictured, above). Along with scientists from other institutions, USL and colleagues at The New School’s Tishman Environment and Design Center are currently co-leading a City-coordinated study of a broad range of social and economic vulnerabilities related to those factors.
A recent upshot of USL’s work is its Ocellus XR app and web site. (Ocellus is the zoological term for the kind of simple eye found in most invertebrates, and XR stands for “extended reality.”) Download the app to a tablet or mobile phone and you can then project 3-D street maps of New York City onto a tabletop or other flat surface – maps layered with a rich combination of physical, environmental, and social data. Using the app, you also can, for example, locate a nearby subway station – and see how likely it might be to flood in the kind of overwhelming rainstorm New Yorkers experienced in late September.
Ocellus XR, like ClimateIQ, is designed to help grassroots climate activists – such as a longtime USL partner, Northern Manhattan’s widely respected WE ACT for Environmental Justice – be more effective. “If they’re going to the Speaker of the City Council and saying ‘We need more trees on this block,’ these apps can help them present the case more specifically and vividly,” Kennedy says. It’s also being pitched as a tool of “community science,” allowing users to upload photos or videos to the web site, augmenting or modifying the information there.
“We feel it closes the gap between expert audiences and communities in New York,” says David Sauter, also a USL associate director – making both Ocellus and ClimateIQ new tools in actualizing USL’s core goals of encouraging urban sustainability, livability, and justice.
Bruce Cory is editorial advisor at the Center for New York City Affairs at The New School.
Opening image: Courtesy of Urban Systems Lab