A few years ago, my daughter, who is a social worker, introduced me to a new term (at least new to me). We were watching my grandchildren (her children and their two cousins) sitting on a floor ankle deep in toys. There was occasional noise. I said something about how they were all doing together, and she laughed and said, “Oh, Dad, that’s only parallel play. Just give them a couple more years.” What she meant was, they were occupying the same space, but they were really engaged in toddler’s solitaire, focused on a few toys and oblivious to the others around them, except when possession of a toy would come into dispute.
Her forecast verified. Today, the oldest is only eight, but already when those same kids are together, the engagement is on an entirely different plane. There’s talk, there’s laughter. There’s common purpose and shared energy. They’re cooking up projects. It’s amazing. I can hardly wait until we hit the next level.
Something like that is happening in meteorology. Back in the postwar world of the late 1940’s (see the August 8 post, Billionaires follow lead of former private-sector meteorologist), Lewis Cullman and his fellow private-sector meteorologists were sharing the same space with the Weather Bureau, and frustrated by what they saw as unfair competition in the service delivery. It was only this one aspect that concerned them. Everyone conceded that the government would be responsible for the observations, for the communication and compiling of all that information. Numerical modeling still lay a few years in the future. The issue was who would deliver the paltry weather information of the time that last mile to the public, and to specialized users.
Fast forward sixty years. Today public and private sector are partnering up across every link in the chain from weather observations to use of that information to save lives, grow the economy, protect the environment, and foster national security. The government still owns many of the observing instruments and platforms. But the radars, the satellite sensors, the satellite platforms themselves, the data links, and the big computing facilities are all built by the private sector. And when it comes to surface sensor networks, federal government agencies today own only a small fraction of the sensors. The rest are in multiple hands. Go into any government computing centers, where the big numerical weather predictions models are being run, and it won’t be uncommon to find contractors working side by side with government employees, in operations and maintenance, doing model development, etc. Virtually all of the service delivery is in private hands – and a wide range of those to boot. What once was the purview of the daily newspapers, radio stations, is now everywhere – on the internet, on laptops, handhelds, in cars – you name it. And at every step, it’s hard, and in some sense, rather pointless, for users to separate out the respective roles of public- and private-sector players in bringing this information to them.
And this collaboration is facing complex new challenges. Let’s look at just one – wind energy. Every evening, when you and I are watching television, we see advertisements touting green energy, and more likely than not, showing a farm of wind turbines, majestically towering above the terrain, and turning slowly in the background. But there’s a complicated reality behind all this. The towers are now 100 meters high (think of a football field turned upwards on its end). Wind speeds are variable from top to bottom of the turbine blades. In fact the blades are now so big that wind direction can be substantially different between top and bottom of the blades. The resulting stresses increase the need for maintenance, and reduce the turbine lifetimes. Don’t believe me? Go to Google Images, and type in “wind turbine damage.” You’ll see pictures of turbines missing blades, of blades so warped they look like something from a Salvador Dali painting, of turbines on fire, of burnt-out turbine hulks. At the same time, the complexities of temporally-variable low-level winds over the irregular terrain where we find many of these wind farms mean power output is less than what may have been hoped.
One of the keys to reducing the need for turbine maintenance, and increasing the power output from wind farms is better numerical weather prediction, not on global scales, but on the scale of the wind farms themselves, and for just a few hours. Turns out that such forecast capabilities have other uses as well – for solar power, or for agriculture, or to support ground transportation. So what should we do? And who should do it? And how will we pay for it? To tackle these issues requires that government, corporations, and academic researchers all pull together. The conversations here at State College are partly about sorting all that out, on strategic as well as tactical levels.
Today, here in State College, as the private sector, the public sector, and academic researchers convene, we’re only eight years old in weather,-water,-and-climate-services-and-sciences years. Our field is still young. But there’s talk, there’s laughter. There’s common purpose and shared energy. We’re cooking up projects. It’s amazing. I can hardly wait until we hit the next level.