The CZCS launched with Nimbus-7. It collected oceanographic data from 1978-1986 on a limited duty cycle; meaning it didn't capture the globe everyday but it got a lot of it. Most importantly, this was NASA's Proof of Concept Mission that you could study a marine biosphere from space. And while that might sound... well, we'll get to this, but it might sound a little silly, it required some significant technological advances; you're all to be commended, I wouldn't be here without these advances. But for the first time you're looking at a very, very dark ocean, and what I mean by dark is the ocean is really dark compared to the land for space and it's really dark compared to the atmosphere, and you have the compounding problem it's under the atmosphere. So what the satellite is actually seeing is 90% atmosphere and 10% water, and so to get to that water leaving signal, not only do you need a really, really good radiometer, but you need it to be really, really well calibrated. From what I hear, from the stories I've heard Gene and others tell, it was not necessarily an easy sell to get this bad boy on the spacecraft; you would know better than I but there were some naysayers who said it's technologically difficult, but also it's kind of pretty picture science. And to a first order it is pretty pictures, what the Coastal Zone Color Scanner did was measure the intensity of light at different colors of the rainbow, it looked at the color of the ocean, but the color of the ocean is shaped by what's in the ocean; very... clear water is very, very blue, but as you get to more productive green waters, where there are a lot of things growing in them, the lake in the back here, they turn green. Sometimes you have some nasty phytoplankton in there, they turn red. These are the ones that if they get into your oysters, you don't want to eat them. And then of course you have the brown water, where it is just recess bended sediments or some river responding to storm. So first principle, yeah, you're looking at the color, the science is based, if I know what the color is, then I can tell you what's in it. And you know, for some people that might have been hard to believe, but the mother worked. And not only did it work, but images like this, which Gene produced, it created a defining moment in oceanography. I had professors tell me that they remember when they saw their first images that they couldn't believe how this changed how they thought about the ocean. And in fact, it gets to my personal story here. I am not a spring chicken, but I was in grad school in the mid-90s, and at that time CZCS had already been proved to be very successful and I was handed a textbook, and lo and behold, in my first oceanographic textbook there was a picture of CZCS imagery. And so I come from a place where not only was biological oceanography from space possible, I was entitled to it, and now my kids can do it on their phone, as mentioned before. But it was very successful; I believe in the first 15 or 20 years there were 27 publications on Science alone, got the cover a couple of times; This is Gene's cover, really, really successful mission, and really changed the way oceanographers like myself can study the ocean. So standing on the shoulders of this giant there have been a number of follow-on missions, most notably the NASA Orbital Science at the time, SeaWiFS mission, the EOS sensors, Terra and Aqua; the European Space Agency got in the game to with MERIS and now we have SWAMI and PPN VEERS plus many, many others. CZCS looked at four different colors of the ocean and the visible colors of the rainbow, but some of these other satellites expanded the wavelength suites. The first principle of this is the more colors you look at, the more different things you can discriminate between. And the mission where Goddard actually is really fighting for in the future; PACE, we'll try to look at all of them. So just a couple of notable achievements in the first year of the SeaWiFS' mission, it had the good or bad fortune to be launched at the time of a huge El Nio, La Nia transition. And the calibration team of course is like, great, the first thing we look at is something different than what we would expect, but then you get to the science that you can do with this. I don't think that's me. SeaWiFS is able... actually able to capture the transition from an El Nio condition in the Pacific Ocean back to La Nia. You can't do this from a boat, you can't do this from an aircraft, you can't do this from even autonomous platforms, but you can do it from space and you can do it from space, in the first year of its launch for the first time. And so three years later one of the most interesting time series was put together, and I should have said right away too that, you know, looking at visible colors of the rainbow enable studying the land as well. And the study that came out in 2001 after three years of SeaWiFS data was the first paper to provide a consistent estimate of how land and ocean carbon fluxes behaved. And what we're looking at down here is on both X axis are just three years; 1998, 1999 and 2000. The bottom is a vegetation index. The top is an index of... it's chlorophyl concentration, which is an index of phytoplankton biomass. These black dots are the annual cycles and then these little hollow dots are the anomaly, you know, the chain... the month to month variations compared to the average, and what you can see is that land had a flat anomaly, the ocean did not; they were decoupled. So you could study the land and ocean simultaneously and start thinking about how they responded differently to carbon cycles. So this is after three years. And the same series of authors put another paper out after six years, what I have hidden here is the remainder of the time series. So the first three years, this is chlorophyl again, this is productivity, this is the climb you saw in the... in the previous slide. The thing is, is that when you add in another bunch of years to it, it changed directions, which is all to say that it's very, very important to be in the long haul. And I know I am preaching to the choir, but again, continuous missions really give you a chance to start thinking about long-term changes in response to climate. What I think our group is probably the most proud of, and I say our lightly because I've been here for 15 years, but this is a lot bigger than... lot longer than me, is that NASA correctly took an open data policy to this, and what that enabled as of two weeks ago when I created this chart is that there are over 2,300 unique peer review publications that use SeaWiFS data, in 17 years. MODIS ocean has another 1,900. If you add CZCS and you get rid of the ones that overlap, you're talking about 4,000 publications in 17 years from an international community using OceanColor data. That's not possible without the Nimbus program. So looking towards the future of what's possible, things you might see in headline news or the newspaper when you're thinking about the ocean and now that you're convinced you left phytoplankton and you're thinking about phytoplankton, the deserts in the ocean are expanding, Chesapeake Bay is dying; that might be a popular one too. And then there are ton of other things that we can study using OceanColor, like ocean acidification, where does all the carbon go? I don't think those budgets are reconciled, but I'll do two quick case studies to wrap this up. Expansion of the ocean deserts; now, what I mean by a desert in this case is kind of the classic desert with the cactus. It means it's an area that's not particularly productive, that there is light, but it's missing something else, you know, plants aren't growing, algae aren't growing because there aren't a lot of nutrients. And so if you look at these black areas of the ocean, they're the lowest biomass areas anywhere in the world, and according to several papers this is not just the only one, the aerial size of these deserts is getting bigger every year. So the ocean is somehow responding to climate change. What that means biologically is that what happens to be successful growing there is also changing. So you have these phytoplanktons that are big diatoms, huge chain forming things that fish love to eat. Well, they're usually found up here, you know, the very productive areas. The cool colors are low productivity, the reds and the oranges are high productivity. When you get to these little guys, the submicron particles, the ones that are evolutionarily adapted to be in the deserts, well, if their desert is bigger, they're moving, there's more of them. And this has influences for food webs, this has influences for all different kinds of trophic levels, carbon exports and things like that. And this is important enough that we... well, I should preface this by saying OceanColor now has an international governing office to make recommendations, the International Ocean Colour Coordinating Group, we're that popular now. But they actually have a series of technical reports and they've assembled groups of people to write reports on, not only how to tell you how much phytoplankton biomass is in the ocean, but what kind it is. That's the next generation, what is it exactly, almost at a species or a function level. The need to do so is also written into the PACE Science Definition Team report; and as a reminder PACE is an upcoming OceanColor mission that we hope for. So the science is going not just towards total abundances, but what's actually out there. It's a difficult problem, it's a really fun one, and to me it's a lively one and I want to go forward with it, because now we're seeing not only can we see microscopic plankton, but we can tell you what kind it is. So the second example would be watershed management; how can this stuff be used for watershed management? Well, there's a lot of pressures on coastal ecosystems. The one I am going to focus on for my example are, you know, human populations and land use, the fact that, for better or for worse, nitrogen or phosphorus are finding their way into Chesapeake Bay, what is the response to this? So I am going to show you three panels of work by other esteemed colleagues. All of them on the X axis are going to be time from roughly, you know, 1940-2000. And what you're looking at here are nutrient inputs in the Chesapeake Bay. And the punch line is they're going up over time. This is Algae Biomass and you're seeing the trend, as you add more food for the algae to feed upon, well, you're seeing more algae. But consequences of that are things like the percent cover of submerged aquatic vegetation are going down. You add more to the water, you make it a lot harder for sunlight to penetrate, sunlight can't get all the way to the bottom, then seagrasses don't grow. The seagrasses don't grow, the chemistry of the bottom changes, the amount of oxygen and the water column changes, you get erosion, you lose oysters. Well, nevertheless, we know these problems are happening and there are wonderful programs that have been operating since the 80s to go out and measure, to measure this. So the Chesapeake Bay program, just as an example, goes out more than every month, they visit 49 stations. They take 19 hydrographic measurements. They're a busy, busy group, and they get to these things that can give you some indicator of the health of the Bay. But these dots are big relative to the bulk. So what you think is pretty good coverage really isn't, whereas something like MODIS Aqua sees the whole Bay in one day. I mean, I am sure you see really cloudy days too, but in practice you get ten good views here. So it's a complementary dataset. It doesn't replace going to sea, but it sure is a nice complement to this. And in fact, if you start looking at time series of different water quality parameters in the Bay, you can really piece together a nice story. So the black dots in the top line are the field measurements of Algae Biomass I believe, and then the blue line is SeaWiFS over the top of that. And so, you know, the OceanColor instrument is doing a pretty good job of tracking the changes, but from the OceanColor instrument you also fill a lot of the gaps and you can start getting quantities of dissolved material, phytoplankton and other kinds of particles. If you squint your eyes you can start to piece together really great stories about this. So the green lines just indicate the year boundary. So wintertime, usually wetter, usually higher stream flow. Water... stream flow is higher, things are entering the Bay, dissolved material from land, from plants and terrestrial degradation flowing in. And you can see those peaks there. It's also bringing in nutrients, it's also bringing in food for the phytoplankton. Well, then there's a lag because the water is still cold and the sun really isn't out yet, just like your lawn is still brown in February and March. But all of a sudden in the summer, after all of this influx of things to eat, the phytoplankton start to graze and they start to pop up and their biomass increases. And then as they start to die off, other kinds of particles come up, either degradation particles or things that are eating the phytoplankton, and so the satellite data provides a really nice complementary dataset, not only to fill the gaps, but also to create other products that are, you know, complementary and a nice story really tends to emerge. But the time series I showed you is still just a fraction of these longer term time series out there, so just to drive the point home. And this isn't the audience for it, you all know this, because of Nimbus we can do these things, but we need to be in this decades and decades and decades long haul. And it's been so successful, even our friends in the land community put a blue band on so we can start doing OceanColor from land now. For that we're grateful too, because the spatial resolution is spectacular, it's very, very nice. And so I'll leave you with probably my favorite thing that I've seen come out, my favorite animation that's ever come out, this is the Global Biosphere that was created on the 10th anniversary of SeaWiFS, so 2007. It's got the Vegetation Index on Land, it's got Phytoplankton Biomass as different colors, again, cool low biomass, reds and greens, higher biomass. But if you sit and stare at it, you'll see something different than I do, you'll see something different than your neighbor, but this is unbelievable, and for me, it's like watching the earth actually breathe. And it's four minutes long so I won't make you suffer through that, it's 5 o'clock. So with that, I will end. Thank you for your time! [Applause]