All right, thanks very much! It's a real privilege and pleasure to be able to be here. I don't have any charts; I just got some notes for myself that I am going to use. Just to start out I am thinking, you know, gee, 50 years, it has gotten to be a while. And even if you think about, you know 15 years or so between the first and the last launch and then 15 years that the last one worked that meant that these 30 years that there's actual real operations and data acquisition going on, which is an enormous time and sort of what it meant to have coactive discipline. It's important I think that we... that we recognize that we've got both the individual spacecraft and the series aspect, because this is one of the things where, you know, the fact that there were multiple ones succeeding themselves is... is really big and then really the series didn't stop with numbers; the series... or at least for most of the things; for a lot of the things the series continued in the future. So if I try to think about, all right, so what did it really do for us? So I was... I was trying to break this up into a couple of different categories. So the first is I'll say, well, everybody got the planned results. Now, there are things that people set out to do for specific reasons and they worked, we got them. We had a path to the future, both little bit for research and for... for operations. So it becomes almost like a biblical chronology that you can think back for a lot of instrument screens, you know; LIMS we got CLAES, which we got hurdles. SAMS, we got ISAMS, leading to hurdles; you know, ERB to ERBS to CIRRUS to RBI; TOMS to... well, TOMS and TOMS and NOMI and UNTS, and there's a whole bunch of these things. There's so many of the datasets that we've all come to... to know and... and love really got their start with the Nimbus series. And when people are looking at long-term system evolution, in many cases and creating, working with the multi-instrument, multiplatform datasets, that that's the way that we have to, address system evolution, because we rarely are in a position of having any one dataset long enough to say, well, we'll just look at evolution with one; we've got to put them together. Well, for a lot of those things Nimbus is where it all started, you know? You look at a lot of those... the kind of quintessential, trends diagrams that you'll see, the left side of that is Nimbus. And there are some that transition to operation so that was always... is good as well, because transitioning things from research into operations continues to be a challenge for the nation. What are some other things it did? Well, you know, I was calling it unplanned results; maybe it's not unplanned, but unanticipated results are things where the smart folks, many of them actually worked here, you know, looked inside the data and found things in the data that, you know, maybe not weren't supposed to be there, but weren't supposed to be products, but people were really clever and figured out how to do that. And I think TOMS, that you'll probably hear more about from Paul was a really good example. I'll try to say a little bit more about that. Then you get some combined products, where people would say, well, if I take this from the Nimbus sensor and this from something else, I can do something else. That's the real definition of synergy. But, you know, two other the things that... that Nimbus really did for us; one is that, you know, we talk about kind of a discipline of earth system science, but as a discipline it's really pretty new. Before Nimbus I think, you know, you have meteorology and oceanography and a bunch of other things, but people did their own thing, but I think it was really when Nimbus came along and you successively work your way up to Nimbus-7, which was probably the... the... the one that... that really came furthest along, in fact that's what led people to really look at different parts of the earth system at the same time and begin to do the interdisciplinary work and look at how the different components of the earth system relate to each other. And also to begin to sort of integrate cause and effect so that you have enough comprehensiveness of measurement that you could look at different parameters and how they would vary in time and space and test them against models and see whether the pictures that one had held together in the face of data that essentially were now comprehensive enough that you couldn't get the right answer for the wrong reason anymore, you know. You had to... you know, if you were getting it right it had to be pretty much because it was right. And those were the kinds of things that... that... that Nimbus let us do. The other thing is it let us do a lot of that in 3D. You know, I think it's... it's hard for many of us to... to think back before that time, where for a lot of things, especially like say for 3D atmospheric constituents, you know, we'd have some balloon profiles and some aircraft trajectories, but we really didn't have 3D climatologies, let alone over a period long enough that you could look at, you know, what happens from one season to the next, what happens from one year to the next. And those are some of the things that we got. So I don't want to say a lot about the details of many of the things, because the speakers who are here after me are way more knowledgeable about those particular applications. So you know, I'll just maybe say a little bit about those instruments that, perhaps won't be represented by some of the people who are... who are here. And, you know, I mentioned LIMS; seven months of data, but going from, I am thinking, what, 84 North to 64 South weather, ozone, NO2, nitric acid, with three-dimensional distributions. So there's a whole bunch of things that... it had temperature as well, so things that that led us do. And when you combine that with the SBUV profiles and, you know, really we had this three-dimensional distribution of ozone with good spatial resolution working its way down into the lower stratosphere, and then with the NO2 and nitric acid being able to look at partitioning and be able to look at chemistry. I'll say a little bit more about some of the things that that meant. You had SAMS with the methane and NO2 files so that one was able to get a sense of these radioactively and chemically active source gases and the vertical rates of decay, which would provide some information about photochemistry and the balance between chemistry and dynamics in ways that were very difficult to have addressed before without that kind of information. You had SAMS-II with the polar stratospheric cloud measurements, and say after the ozone hole was discovered and people were trying to figure out what was causing that, having the distributions of polar stratospheric cloud from SAMS-II became really important to providing information about the... the climatology of the particles with services for the heterogeneous chemistry. And a lot of those I guess, you know... I am not going to say much about TOMS and SBUV; I think Paul will cover that. Those were kind of the planned products, but then you also had the, you know, unanticipated ones, like the say TOMS Aerosol and TOMS UV Reflectivity. The... you know what I mean, maybe they were planned all along but, you know, they... they... people thought of that or it started out like, you know, sometimes one person's noise is another person's signal and, you know, you start out showing, we've got to get rid of this stuff, and then, no wait, there's actually geophysical information in there and people figured it out. When I asked about the headquarters to some of my folks as well as a few people in the field, what are some of the things that I should say; one of my guys, David Considine did a Web of Science run and said, okay, give me Nimbus-7 and the top 10 papers that relate to atmospheric science and meteorology, and I think the largest won by a factor of 2 was I think one of the first TOMS absorbing Aerosol climatology papers. You know, something that wasn't... you know, wasn't supposed to be there, but people figured it out and went and did it, and there's a whole bunch of stuff that... you know, good stuff that came out of that, because it was a unique product. You had the Surface UV and say, you know, taught you about earth system science and 3D. Well, that also began to get us into applications; there's probably other ways that one... one could do but, you know, once you started getting Surface UV, people could work out into Surface UV forecasts and actually begin to think about, you know, how people can use that information in ways that weren't anticipated. So that's... oh, and then combined products; the TOMS and SAGE Residuals that people used to infer tropospheric ozone, and... and that became... people found this bulge out over the tropical Atlantic and then began to investigate that. So there's a whole bunch of things that... that came out in different ways. I... you know, I am personally grateful to the Nimbus series, you know, for... for my career. I arrived at Goddard in December of 1983 to be the chemist in the 3D Stratospheric Modeling Group, whereas I would like to say I was the right hand side with all the dynamical terms on the left hand side, so I used to say, yeah, call me P minus L. But... and obviously, you know to initialize and evaluate the chemistry in a 3D model, so what would I do? We've got ozone, NO2, Nitric Acid, one of the favorite from LIMS, got the N2O and Methane from the SAMS, got the ozone from... ozone from SBUV. I don't know how I would have started network if it weren't for Nimbus-7 and for me the timing was great because I think six months after I came to Goddard was when this really fat issue of JGR was published, they had all the validation papers for Nimbus-7, and you know that was one of the most used journals. And again, many of the people here and the predecessors are the ones who really made that work. And then when I decamped to headquarters to manage the Atmospheric Chemistry Modeling and Analysis Program and I started getting proposals from people, well, I think about what are some of the earliest proposals that I remember getting, and this is 1990 so this is stuff lying, but it was one of the decade after launch. Well, one was we processed the LIMS data. LIMS was seven months of data, six and-a-half or so, but yet one of the decade after the data ended it was like, how can we reprocess this? Now there is a whole bunch of stuff, new spectroscopy things that people were in, also the fact that that the... and this is something that's even hard for me to grasp is, they had to do a lot of the stuff with really kind of ancient computing. So it was hard to process stuff. So one of the things that LIMS folks said were, you know, we only process, only use one-fifth of the data, we didn't have the computing cycles to use all the data so now we can actually use all the data so they went and did that, they reprocessed the LIMS data. I remember a proposal to go back and use to get Nimbus-4 BUV data, because I think, you know, the idea is, that was close to a decade before Nimbus-7 and if they can go back and clean up the Nimbus-4 data and make it as consistent as possible within Nimbus-7 data, then you could start comparing, you know, trying to compare things from the early 70s to the late 70s. I remember a proposal that came in to look at the SCR data. I think also from Nimbus-4, and the idea there was it was a... it was a infrared... I never heard of SCR at that time, but there is... it had that... so I remember, it had the shapre brand and somebody said, let's go look over Antarctica because if may be we can pull the Antarctica ozone on that from the mid-70s and get some information as to whether or not there was an ozone hole, you know, before the Nimbus-7 data started, that one didn't workout, but I think it showed the community really creatively looking to see what they could get out of the historical data, and I want to say it didn't workout, I should be careful. They didn't get the ozone data but they think they learned more about the Infrared Radiative Transfer over Antarctica than one ever knew before, and I think that became exceedingly useful as one looked ahead. So that one may not have worked quite the way... it wasn't anticipated but I feel like, you know, it was a good investment. And then there were the TOMS additional products like the aerosols and surface UV product. And you know that one I feel, you know, may be a slight degree of paternity because I was small enough to say yes to the proposal. Frankly, I am sure they would have done it anyway, even if I haven't, personally, it would have been bootleg stuff, but I am sure it made it much easier for the people to actually be able to say, yes, we got that funded. So as I feel like I am involved in the drug trade, because let's say, I was a Nimbus user and the Nimbus enabler, and... but... in fact, it's still there now, as I put the word out to some people and said, you know, what are some of the things that I could say, and one of the things that I got, because it's a wonderfully response from the community as well as creative, was a preprint... it may actually be just a manuscript copy of a paper that's either out or will soon be out in JGR where people went back and assimilated LIMS in SBUV into the GMAO, into the GS5 model, and they actually looked that they are able to improve the quality of the assimilation with the data. So now when 25 years after the data were taken for LIMS people are still working with it, and finding that it improves the quality of the science that they can do today. So that's I think a pretty phenomenal kind of thing in the testament to the work of everybody associated with it. So I guess I will stop. I would personally like to thank those who made it happen. These are wonderful legacy datasets as well as pointing the pathway to the future in so many ways. I'd like to thank those who continue to exploit it, and the people who worked with the subsequent datasets because, you know, answering these questions that we have of either it's just an evolution, we lie that we get the most out of all the datasets, so for those people who are doing that, thank you and especially for... you know, really for all those who helped in doing this so that the earth system science that we know is an integrated discipline can exist today. I don't know how that would have happened without Nimbus. So I will stop there. Thank you! [Applause]