From deploying the Hubble Telescope in space to overseeing environmental monitoring missions as the administrator of the National Oceanic and Atmospheric Administration (NOAA), RFF Board Member Kathryn D. Sullivan has dedicated her career to using information from space to improve natural resource decisionmaking. Resources recently caught up with the distinguished scientist, astronaut, and executive about how her time in space influenced her career.
Resources: You joined the NASA astronaut corps in 1978 and flew on three Space Shuttle missions during your tenure there. Would you share what it was like to see Earth from space for the first time?
Sullivan: I will never forget the moment eight and a half minutes into my first flight—because that’s when all the engines finally stopped burning, and I knew I had made it to orbit. Things were going the way they were supposed to go, unlike in our always trouble-riddled training simulations. And so I finally lifted my gaze up off the instrument panels and looked out the forward windows of the shuttle. It was just a stunning sight, the blue arc of Earth dotted with white clouds. It literally took my breath away, and I spontaneously and foolishly blurted out, “Wow, look at that!” That got me my very first chastisement from my mission commander because we were still in the middle of a checklist. It’s not the time to say, “Hey, guys, look out the window!” but happily that didn’t come with too many demerits. It’s a pretty natural response.
It was just a stunning sight, the blue arc of Earth dotted with white clouds. It literally took my breath away.
Resources: You also served aboard the mission that deployed the Hubble Space Telescope, an experience at the heart of your upcoming book, Handprints on Hubble. What can you tell us about it?
Sullivan: The book will be published by MIT Press in November 2019. If you think about it, Hubble is the first spacecraft—and, arguably, with the exception of the International Space Station—remains today the only spacecraft that was consciously designed from the outset to be maintainable in space. The birth of the idea goes all the way back to 1946, before there even had been astronauts in space. So the first part of my book tells this fascinating story of the vision of those working on the Hubble very early in the Space Age.
Part two looks at the work of translating that design intention of maintainability into a practical reality—work that happened between 1985 and 1990—focusing on about a dozen people, everyday engineers, whom I think of as the hidden figures of the Hubble story.
And I close with the really remarkable ways that the five servicing crews built on our early work. If we set the foundation stone, they built the cathedral upon it.
Resources: How did you become an astronaut?
Sullivan: I was inspired to throw my hat in the ring for the astronaut selection in 1978 for many reasons, but the factor that made it impossible to not apply, frankly, was that if I somehow succeeded, I would get to see the Earth with my own eyes. From an early age, the geography of the Earth—the physical geography, people, societies, and economies—was a driving force of my curiosity.
Resources: Will you give our readers a sense of how this interest eventually led you to RFF?
Sullivan: Sure! I can boil down many factors that led me to be interested in joining the RFF Board to two people and two questions. The two people were [former RFF President] Bob Fri and [former Vice President of Research] Molly Macauley.
I was on the board of a utility company for a number of years in Columbus with Bob Fri back when he was president of RFF. He would cite impressive work by RFF—for example, research that shed incisive light on the dynamics or the evolving trends in the energy sector. It struck me that these were never everyday, mundane comments but sharply focused, deep insights.
And then when I returned to NOAA in 2011, I bumped into Molly Macauley, and persuaded her to join our Science Advisory Board, where we mind-melded over two questions that we did a lot of work on while I was at NOAA: what is the value of space-based Earth observations per se, and what is the value of those observations in helping to make natural resource decisions? The question of the value of the observations per se was coming to the fore in the NOAA arena because some people were advocating for a significant shift away from a policy model that treats remote-sensing data from satellites as a global public good to one that treats it as a private, monetized good.
The ethos since the dawn of the Space Age has been that taking the pulse of the entire planet is beyond the scope of any individual country. Thus, all the basic measurements—like temperature in the atmosphere, distribution of moisture in the atmosphere, surface temperature of the ocean—should be shared globally and used in an open innovation platform by anyone, from another country’s weather service to a private corporation to a graduate student who has an idea for a new app.
The ethos since the dawn of the Space Age has been that taking the pulse of the entire planet is beyond the scope of any individual country.
But as the age of big data emerges, environmental information is woven more and more into the fabric of economies and business plans and so becomes more valuable. At the same time, as space technology changes, it is becoming feasible for a private company to raise enough money to build and launch and operate a satellite. Such a company would be well entitled to consider the measurements coming from that satellite as goods for sale.
At NOAA, we had many questions about the underlying economics. Would the government find it alluring that someone else would pay the big price tag of a satellite, and all it had to do is buy the data? Further, were we collecting the right sorts of data and delivering them in ways they could be used in economic decisionmaking? Oftentimes, environmental factors are not front and center in public and private decisionmaking. We started wondering: is that because they are not germane, or is it because the data are not available in a way that meshes with the decision framework that business leaders and public leaders are working with?
Knowing that one of RFF’s fortes is diving deep to understand the economics and the dynamics that underpin various economic policy models, I enlisted Molly to help me start thinking about these questions.
Resources: What do you see as the advantages and disadvantages of the two approaches?
Sullivan: I believe there have been tremendous prosperity benefits from the open innovation model, and it is very unclear whether a private goods model really equals or exceeds those.
We have seen huge success globally from the open innovation model. On innovation, look at the number and size of companies that are doing tailored weather services in the for-profit private-sector weather industry in the United States. Most are small. They are made up of a couple of folks and a good computer, and with all those data available, they can really begin to tailor the information to farmers or to certain business sectors, college students, or researchers.
Further, the global exchange of data is a tremendous instrument of soft diplomatic power for the United States. To provide the weather forecast in Columbus, Ohio, you need to model the whole globe. So the very same model you are running for the line of thunderstorms rolling over my house in Columbus can be shared—in a simple but powerful gesture—to help ensure that countries with very little technical means can have reliable weather forecast capability. It gives their citizens a tremendous boost in public safety. I think that’s a compelling bit of soft diplomacy for a country like the United States. Why throw it away, and turn it into a subscription service?
On the other hand, I personally don’t see a credible business case for what I call “selling ones and zeros,” especially fairly obscure measurements, like the vertical distribution of moisture in the atmosphere. How many entities have great need for a billion measurements a day of the vertical distribution of moisture in the atmosphere? Weather forecasters do. That’s the fuel of every weather model ever known to man. But it takes those measurements—plus supercomputers and a body of research that is embodied in the computer code and many other factors—to turn the data into a weather forecast. You are not going to make big money selling the raw data—the ones and zeroes—to countries that do not have their own weather forecast capacity.
That speaks to another of my policy worries around privatizing satellites: the risk of becoming enamored with shiny new toys, which are fun to build, while undervaluing the intellectual capital and knowledge base and scientific skills that have made even today’s capability possible. It’s important to understand no satellite actually measures the thing we say it measures. Satellites measure radiance. They measure the amount of energy in some portion of the electromagnetic spectrum. A huge body of research accumulated over decades lets us very reliably translate that radiance into certain physical properties.
So my own conviction is that the social value and the economic value at the 99.9 percent level is in the derived products—the value-added information services that are built on fundamental measurements.
The global exchange of data is a tremendous instrument of soft diplomatic power for the United States.
Resources: As you know, RFF is leading the VALUABLES Consortium, which brings together social scientists, NASA scientists and remote-sensing experts, and members of the wider Earth science community to measure the value of satellite information in making natural resource decisions. Can you tell us what role interdisciplinary collaboration between Earth scientists and social scientists plays in establishing a body of research that ensures we are getting value added from those ones and zeros, as you say? And what do you see as some of the biggest challenges for that kind of community building?
Sullivan: I think that bringing together physical scientists and social scientists in a way that generates thinking about the nature of research questions is hugely important. Economics has come into play at NOAA, for example, in understanding the value of information in providing severe weather watches and warnings—and more recently in wrapping our heads around weighing the costs of running Earth-orbiting satellites and taking measurements on the scale that is needed generate weather forecasts with the value of the services we’re providing.
But an important point that could be missed if the focus is only on bringing physical and social scientists together is the risk that they will focus on intriguing academic questions that are not of as high a societal value as some of the questions out there. How do both groups become more richly familiar with what questions are really pertinent to users of these data?
One anecdote stands out as my favorite illustration of this. I went to NOAA’s physical and social scientists and asked, “What’s the next thing we really need to figure out in hurricanes?” And they said, “We have a decent track forecast. We have X percent confidence at Day 5. We’d like to see it get closer to 95 percent and push that out to Day 7. And we haven’t figured out yet how to forecast intensity reliably.”
But when I asked the same question of the FEMA administrator at the time, Craig Fugate, a different picture emerged. He said he could not care less what the scientists can do at Days 5, 6, and 7. The critical point for him is Day 4. People are not going to pay attention prior to that, he explained. On Day 4, he needs an 85 to 90 percent accurate track forecast, because he needs to know what governors and what mayors he should start talking to about evacuations. And he needs to know which of FEMA’s volunteer cadres to preposition and where. So his answer was to ignore Days 5, 6 and 7, bump up the percentage of confidence on Day 4, and by all means please do figure out what’s going on with intensity.
If you didn’t bring Craig Fugate into the room, the social and physical scientists would be having a fascinating conversation about Days 6 and 7, but that is not the leverage point for key policy decisions.
So I would hope that the VALUABLES community will target some of its research questions around leverage points that they have identified by talking with some real-world decisionmakers.