 The CZCS launched with Nimbus-7. It collected oceanographic data from 1978 to 1986 on the limited duty cycle, meaning it didn't capture the globe every day, but it got a lot of it. Most importantly, this was NASA's proof-of-constant 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 were 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 sun 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 backyard, 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 resuspended 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 and I can tell you what's in it. And 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 Jean 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 me to my personal story here. I'm not a spring chicken, but I was in grad school in the mid-90s. And at that time, CZCS has already been proved to be very successful and I was handed a textbook. And lo and behold, in my first oceanographic textbook there's 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 Nicely mentioned before. But it was very successful. I believe in the first 15 or 20 years there were 27 publications in science alone. I got to cover a couple of times. This is Jean'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, SEWIS mission, the EOS sensors, Terran Aqua. The European Space Agency got in the game too with Maris and now we have Swammy NPP and Veers, plus many, 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 is going to try to look at all of them. So just a couple of notable achievements in the first year of the SEWIS mission. It had the good or bad fortune to be launched at the time of a huge El Niño-La Niña transition. And the calibration team, of course, is like, oh, right, 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. And I don't think that's me. SEWIS is actually able to capture the transition from an El Niño condition in the Pacific Ocean back to La Niña. 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, looking at visible colors of the rainbow and able to study the land as well. And the study that came out in 2001 after three years of SEWIS data was the first paper to provide a consistent estimate of how land and ocean carbon flexes be hid. And what we're looking at down here is both x-axis are just three years, 1998, 1999, and 2000. The bottom is a vegetation index. The top is an index of its chlorophyll concentration, an index of phytoplankton biomass. These black dots are the annual cycles. And then these little hollow dots are the anomaly. 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. This is after three years. And the same series of authors put another paper out after six years. What I've hidden here is the remainder of the time series. So the first three years, this is chlorophyll again, this is productivity. This is the climb you saw 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. It's not just 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 are lightly because I've been here for 15 years, but this is a lot bigger than, a 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-reviewed publications that you see with data in 17 years. Modus Oceans 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 in the national community using ocean color 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 love phytoplankton, 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 a ton of other things that we can study using ocean color 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's light, but it's missing something else. You know, plants aren't growing, because they're into a lot of nutrients. And so if you look at these black areas of the ocean, they are 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 phytoplankters that are big, diatoms, huge chain-forming things that fish love to eat. Well, they're usually found up here in 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, some micron particles, that are evolutionarily adapted to be in the deserts, well, if their deserts 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 now, well, I should preface this by saying, Ocean Color now has an international governing office to make recommendations, the International Ocean Color Coordinating Group. It's not 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 a species or a function level. The need to do so is also written into the PACE Science Definition Team Report. There's a reminder PACE is an upcoming Ocean Color 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 the debates are lively on how to go forward with it. Because now we're saying 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'm going to focus on for my example are 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'm 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 1940 to 2000. And what you're looking at here are nutrient inputs in the Chesapeake Bay. And the punch line is they're going on over time. This is algal 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. If sunlight can't get all the way to the bottom, then seagrasses don't grow. Seagrasses don't grow. The chemistry of the bottom changes. The amount of oxygen in 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 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 boat. So what you think is pretty good coverage really isn't, whereas something like Modus aqua sees the whole bay in one day. I mean, in truth, you get really cloudy days, too. But in practice, you get 10 good views a year. 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 on the top line are the field measurements of algal biomass, I believe. And then the blue line is sea whiffs over the top of that. And so the ocean color instrument is doing a pretty good job of tracking the changes. But from the ocean color 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 swinch 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 other food for the phytoplankton. Well, then there's a lag because the water's 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 data set, 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 ocean color from Landsat. From that we're grateful to, 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 Sea Whiffs of 2007. It's got the vegetation index on land. It's got phytoplankton biomass as different colors again, cool, low biomass, reds, 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 five o'clock, so with that I will end. Thank you for your time.