 I have had the extraordinary opportunity to actually be a satellite. These amazing views just dazzle you completely. Everything you've probably heard other astronauts say is true. You see shapes you recognize from maps and things like that. You don't see the typical country borders. You get a very different sense on a lot of scales of the planet. Exclusive economic zones, territorial boundaries, things that animate our news and our awareness every day are not present and a whole other dimension comes through. But at the same time as this picture shows, you also clearly see the hand of man. And this is what we are the first generation of humans to ever do. Not only to be able to see the Earth from this perspective, but as I'll show you in a moment to develop technical means that let us take very sophisticated snapshots, essentially of the whole globe, essentially simultaneously, and develop the computational and scientific techniques that let us turn that into very powerful situational awareness about what's happening in what the state of the planet is at any given moment. And even more importantly, to transform these data into foresight, into practical predictions about what conditions are likely to be some time down the road. And that's where we see really novel things happening in our era of society as that gets incorporated into decisions from the mundane. One of, did you bring an extra hat or scarf today and did you realize it was going to snow? You know, to decisions of much greater import. So without further ado, this is, by the way, space shuttle altitude, Italy and the Adriatic, the kind of thing you see once around the Earth every 90 minutes, a sunrise and a sunset twice, 16 each in a 24-hour period. It is quite a stunning experience. It's a very novel technology, as I'm sure you all know, and so let's take a look a bit at the history of this. These are some of the earliest satellite-based images that were taken. They're from a system called Corona that the United States launched in the early 60s. When we sent these images to the forum staff to mount them up for this presentation, several times each they came back and said, oh, these are really very bad resolution, don't you have a better version? In their time, they were three times better in resolution than anything that had been taken by aerial photography before. The motivation, as you appreciate, was initially the classic high ground motivation of humankind to have a sense of the lay of the land and of the actions of other parties that might be competitors or might be adversaries, military intelligence, troop movements, missile emplacements, those sorts of things, pivotal role in the Bay of Pigs. It was an astonishing and revolutionary capability at its time, and just as an aside, to me maybe even the more astonishing bit was how you got these images back. You actually popped them out of the rocket at very high altitude, huge spools of film. You think your old film camera was complex in the back the way it was on the film out. You ain't seen nothing yet. Run it through, take the picture, spool it again in the nose cone, pop it off, and then fly an airplane by at the right place in the right time to snag the parachute out of the air and bring it back to the lab. They got pretty good at that, but obviously some fair amounts of data were lost. And it was not timely, it was not low latency. It took quite some time to get that to the earth and then to the lab and then through the lab and then to you who perhaps wanted to use it. And obviously data rates were low and obviously data reliability was low. And I point that out, obvious though it is just to remind us that in this, as in other things, it is transformations through every link of the chain from the taking of a measurement to the use of it. Transformations all along that chain are what transform our use of them and the way they can engage society and shape our lives. Looking where people are and what people are doing was one dimension, weather has always been a factor in human affairs, both economically and public safety and militarily. So very shortly after implementation was to try to see what can we learn and can we begin to develop better forecasts of the weather if we have an overhead view. These are two of the earliest weather satellites and the kind of imagery they took. Truly very simple, black and white, quite like your film camera. Just simple cloud images. But if you live in California and you're dependent on weather systems that are coming in from over the Pacific Ocean, if you live in Europe where you've got 3,000 miles of ocean upstream of you, the ability to see what cloud formations are over that ocean, because they're going to sort of stay intact and come your way three or four or five days later, that alone was pretty revolutionary weather reconnaissance in its day. Just figuratively this graphic shows some of the United States overhead observing systems. These are all civilian scientific systems, NASA, NOAA, the US Geological Survey. They do things ranging from measure cloud properties to measurements that help us understand the water cycle, soil moisture, Landsat for land cover, solar irradiance, all sorts of different measurements that we developed over these decades, specific sensors that can provide the raw data that we can convert into those attributes. Satellites don't measure those attributes directly. They measure radiance. They measure light that's scattered or emitted from the Earth. And it is a body of scientific knowledge accumulated through a lot of research that lets us translate those radiances into these particular properties that are of interest to business planning or to agriculture. So quite an array now. Europe has a number of satellites that do similar functions, Japan and others are joining this club and adding to the stock of satellites and sensors that help us understand this Earth. And as I've alluded to, there are different kinds of eyes, if you will, on each of those satellites. And I show here just a few global representations of the kinds of measurements we now can make. You have in the upper left sea surface temperature. Again, how revolutionary was it to be able to see the whole globe almost simultaneously for sea surface temperature? It's that data. It's the global view of those data in the early 1970s that transformed our understanding of El Nino from a local fisheries crisis that hit Peru occasionally to understanding it's a global oscillation in the Pacific Ocean. It's one of the fundamental heartbeats of the planet. It affects the ocean and the atmosphere and it drives about half of the weather variability of Europe or the Central United States. Transformational understanding of what was going on there. In the upper right you see the gravity field of the Earth, again measured from space, measured by satellite. The lower left is chlorophyll, land cover vegetation on the land surface, and chlorophyll or the biological productivity of the ocean in the ocean areas. And finally on the lower right, the sulfate aerosol content of the atmosphere, one month's worth of aerosols in the atmosphere. To be able to see these properties on a global basis, near simultaneously is scientifically quite transformative. But again you're measuring radiances that also are quantitative and rigorous and so it lets you not only make a map but proceed into other analyses that are even more useful to society. We've been able to monitor change over time which is important on a number of levels for different planning. On the left here you see the human development, the civilization, habitation, settlement patterns around the Las Vegas area, you see Lake Mead sort of fluctuate through these seasonal cycles. And on the right you see the flow of sediment and nutrients, fertilizer, chemicals into the Gulf of Mexico, through the Mississippi Delta. 41% of the United States land area drains down that river shed into that one point in the Gulf of Mexico. We sometimes have dead zones there that are without oxygen that are the size of several of our states. We can watch sulfur in the atmosphere, that's what the image on the left is. A year's worth of sulfur emissions and aerosols, you see small volcanoes, you see large urban industrial areas as in eastern China, you see little tiny filaments in the southern Indian Ocean where there are tiny little volcanoes that are continuously emitting sulfur. On the right again with a gravity measurement monitoring the state of the entire ice mass on the continent of Greenland. And in each of these cases there are not only pretty loops and fascinating movies, but expert scientists in these phenomena when we can see that whole picture come to recognize features and aspects of the dynamic system that were not apparent before that we then can hone in on and refine our understanding of. And of course we can zoom in and look at more narrow phenomena like the dynamics over time of a single glacier, in this case in the areas of Alaska. You commonly hear people say, well satellites give us this, satellites tell us that, satellites don't. There is a global measurement, a global raw data of sunlight that can be translated, that can be transformed because of the decades of research and understanding how sunlight interacts with the earth and of going and collecting signature libraries so we know we can recognize the fingerprint of a conifer forest versus a different kind of forest. We can recognize the fingerprint of a healthy wheat crop versus a distressed wheat crop. We can recognize the fingerprint of chlorophyll that is abundant plankton in the ocean. So when you see these pretty loops and images, again to appreciate, it takes all of that and it also takes measurements on the ground to anchor and calibrate those sensors. Understanding the El Nino in a way that we can turn to practical forecast takes the satellite temperatures but also an array of buoys in the ocean that give us the third dimension of the ocean itself. At NOAA, the agency I lead, this is our business, to take knowledge of the earth with all the timely, useful information we call an environmental intelligence to deliver it to our citizens to inject it into the business for their decision making. That's what we do for a living. And here are a couple of the kinds of products that we put out from long range climate predictions decades to half centuries out into the future to the drought monitor. This is a recent image about a year ago actually of the drought conditions in the United States. It's now much more intense in California than a combination of on the ground measurements and overhead measurements that give us this synoptic view. The conventional ones we all know of course are hurricane measurements and daily weather forecasts. 80% of the way your weather forecast is made, 80% of the data that are involved in making your daily weather forecast come from these overhead satellites that measure vertical profiles of the atmosphere. You crunch that through a numerical model and you produce a prediction of what the state of the atmosphere will be 2448 so many hours out. That is how it is done. This is India. India in monsoon conditions. Flooded ground, heavy downpours. The monsoon usually starts around the June timeframe in India and its rainfall is absolutely critical to the food crop, to the wheat crop and its yield. In 2009 no as a bilateral exchange exchange climate and weather model capability with the Indian Meteorological Service and training and capacity building. If the monsoon doesn't develop as expected if the rains fail the wheat crop fails and you find yourself a few months later in a pretty significant food security crisis. Well, the whole world by this point is seeing the failure of crops in the drought affected areas and prices have begun to spike. So by the time you know you don't have a monsoon you also cannot afford to go to the market and buy enough wheat on the open market to feed your people. Climate predictions based on these satellite information now allow the Indian government to have an affirmative signal months ahead of that whether they will have a monsoon or not and to know whether they need to go preemptively to the commodities market and hedge the food risk by buying wheat in advance. Satellites taking a major national country out of the spot market for wheat because of the foresight that practical prediction lets us develop. These applications are beginning to develop in many, many, many different arenas. So we're trying to understand how to use these principles as human beings when it comes to really understanding how to infuse this kind of environmental intelligence into social and commercial and economic decision making and having the tools that connect the data to the information to the insight in ways that are useful to those practitioners. It doesn't do to write the fancy science paper and put it in a journal and leave it on its shelf. That strands the insight. How do we get it into these decisions? Water stress in particular but also crop health and forecast as in India? Renewable energy siding boundary layer winds, where are the favorable areas? Consistently favorable areas? The retail environment on the bottom right we know half a dozen major consumer retailers just in the United States alone that look always at the Tuesday weather forecast that we put out to make their Thursday shipping decisions for their weekend shopping. So optimizing your supply chain and optimizing production across a simple thing as consumer retail. Obviously transportation weather, both the operational weather but also the hot and cold that can affect installed systems like rail tracks these forms of information are increasingly getting into stock trading and commodities trading desks. In the United States the model is that NOAA produces the foundational data the basic underpinning and the basic underpinning products and we stop there and these sorts of analytics and tailored services are done by private sector companies. They are more nimble at meeting the evolving need of both society and the consumer but the underlying data are treated as global public goods. They are an open innovation platform for anyone to use and that also helps ensure that the basic governmental proposition of ensuring the safety of our public is never something that becomes a fee service it is always that basic public good that we can deliver. What might be a next in just this arena like the earth and turning it into useful information? Science and technology will continue advance sensors will be able to see finer spots of ground and they will be able to see with finer spectral resolution so to distinguish more signatures of key features and phenomena. I think a companion trend that will revolutionize this enterprise in very fundamental ways is densifying sensor networks on the ground so that you can take this kind of insight and bring it down to more localized and specific impact levels, urban environments for example, this is a big data arena NOAA produces 20 terabytes of data per day, twice our Library of Congress but architecturally we can only get 10% of that out into this enterprise that I've been talking to. How can we turn that around so that this tailored analytics enterprise is working on all 20 terabytes and what new applications might that enable? The kind of forecasting and work that we're talking about here today is not something that will ever be just a data mining proposition. It's so dynamic on so many levels you will always have to be taking the pulse of the planet. There are companies now at least in the photography arena that find it financially viable to finance the satellite themselves and sell the data to different customers who want it. Should that migrate into this domain or are there benefits and virtues to global data as a global public good that we should work to preserve? So with that let me leave you with a couple of other fun glimpses a little blue marble that we live on and turn the podium back to Aachen.