Sometimes it seems the clouds over climate science just won't lift. Computer models of Earth's climate have multiplied in number, complexity, and computational power, yet they remain unable to answer more precisely some of the questions most on the public's mind: How high must we build sea walls to last until 2100? How bad will heat waves get in the next decade? What will Arctic shipping routes look like in 2030? Climate models all agree that global temperatures will continue to rise in response to humanity's greenhouse gas emissions, but uncertainties stubbornly persist over how quickly that will happen and how high temperatures will go.
Tapio Schneider, a German-born climate dynamicist at the California Institute of Technology (Caltech) in Pasadena, believes climate science can do better. And he's not alone. Later this summer, an academic consortium led by Schneider and backed by prominent technology philanthropists, including former Google CEO Eric Schmidt and Microsoft co-founder Paul Allen, will launch an ambitious project to create a new climate model. Taking advantage of breakthroughs in artificial intelligence (AI), satellite imaging, and high-resolution simulation, that as-yet-unnamed model—the Earth Machine is one candidate—aims to change how climate models render small-scale phenomena such as sea ice and cloud formation that have long bedeviled efforts to forecast climate. A focus will be on the major source of uncertainty in current models: the decks of stratocumulus clouds that form off coastlines and populate the trade winds. A shift in their extent by just a few percentage points could turn the global thermostat up or down by a couple of degrees or more within this century—and current models can't predict which way they will go.
Guess that's better than plotting a war model driven by AI, which is being done, BTW. To read more, click here.