“We’re right on the very tipping edge of this field now,” says Meadows. “So far, all of our work has been theoretical. We have never actually observed an atmosphere or ocean on a terrestrial exoplanet. Technology has not been capable of doing this. But that will come in the next five years with JWST and big telescopes on the ground. VPL has been providing the theoretical scientific foundations for the observations we are going to see.”

Meadows anticipates that JWST will “collapse a whole bunch of possibilities” that VPL’s computer models have predicted. Through direct observation, some predictions will be proven wrong and others may be confirmed, which will lead to more targeted virtual planetary work.

As JWST prepares to launch, an even more powerful telescope is in the early planning stages that may eventually replace JWST. Meadows has a hand in that telescope planning, serving on the committee studying instrument and telescope options. In fact, VPL is so instrumental in identifying the needs of future space technology that NASA recently awarded it a grant totaling $11 million over the next five years.

“At VPL we use simulators with different capabilities to figure out what instrument would work best to make the sort of observations we want to make,” says Meadows. “We share this information with NASA, because NASA wants to know how it can use its assets to best search for life in the Universe.”

It is likely to be decades before JWST’s successor telescope is launched. But for astronomers whose time scales tend toward billions of years, that’s nothing. “Biologists think we’re insane,” Meadows laughs. “How can we possibly plan instruments and experiments that take 27 years to build? But we do. Space telescopes are very challenging technologically and massively expensive, and we have to plan.”

VPL researchers must also continue their modeling, which will serve as the foundation for future observation work. With every question JWST may answer, there will undoubtedly be more questions raised.

“We have opened up some possibilities that people would not have considered if we hadn’t done the modeling,” says Meadows. “Once we get the data, we may find that the models are incorrect. If that happens, we’ll be able to say, ‘Oh, that’s not what’s going on. Why is that?’ And answering that question pushes our science forward.”