Monitoring Earth's Vital Signs with Fifty Years of Satellite Altimetry - Helen Amanda Fricker

[00:00:00]Thank you Arin and good morning everyone and hi to everyone online. I think it's connected to online right? Yeah. Thank you very much for joining us. My name is Shinuyama, the president of International Graological Society.

[00:00:19]And today I am deeply honored and delighted to be with you to celebrate Helen for the Seligan Crystal.

[00:00:32]I have some words before leaving the citation of this award.

[00:00:39]The international graciological society was founded in 1936.

[00:00:48]So it's just 90 years ago.

[00:00:51]And sometime later in 1962 the council of IGS decided to establish this ceremon crystal which is awarded in recognition of outstanding scientific contribution to grassology and since then so it's 64 years since this award was established only 45 graiologist awarded for this crystal. So it doesn't happen so frequently. We are very happy to be here to witness and the segment crystal shall be awarded to a single person or collab collaborative group or team that has made exceptional scientific contributions to grassology which is defined as any snow and ice studies.

[00:01:53]The nominees research contributions should have had a longlasting impact on the understanding the direction of focus of agraological discipline and have transformed the discipline in a unique way.

[00:02:12]This may include opening up a new area of the discipline or radically transforming thinking in an area and will typically include producing a substantial high impact body of consistently leading edge work.

[00:02:35]And now I have the citation for Helen's award.

[00:02:42]Professor Hen Amand Fria from scripts institution of oceanography is an international leader in polar remote sensing. Her work with satellitebased laser ultimately has led to groundbreaking advances in our understanding of the dynamics of the Antarctic ice sheet.

[00:03:09]One of Professor Fria's most significant contributions to glaciology is the use of ultimately to devolutionize the study of ice sheet ocean interactions.

[00:03:24]She has used satellite derived data to observe sub eyes shelf oceanographic processes crucial for understanding mass fluxes in the Antarctic ice sheet. Her research has shown that sinning ice shaves reduce their battering effect on glaciers and ice streams leading to accelerated ice loss.

[00:03:55]Equally significant is Professor Fria's use of laser ultimatry to discover large active subgrass lakes beneath the Antarctic ice sheet. Subgrass lakes had been presumed to be static futures of the ice sheet. But her work demonstrated for the first time that the lakes could fluctuate or rapid time scales of weeks or months.

[00:04:30]Other outstanding scientific discoveries include the first mapping of marine ice at base of the Amir ice shelf and more recently a 30-year record of ice sheet height change that has revealed peressive mus across Antarctica.

[00:04:54]Such record are critical for better constraining and tactical contribution to global sea level rise.

[00:05:05]Professor Fria is a generous and tireless contributor to the giological community.

[00:05:13]She has been instrumental to the success of NASA's ISAT and ISAT 2 satellite missions, pushing boundaries for new satellite missions.

[00:05:28]and has established one of the world's most productive glaciological research centers in scripts glassology group.

[00:05:40]She has transformed the careers of many junior scientist through her mentorship and support.

[00:05:51]Notably, the majority of her papers are first authored by her students and postdoal mentees speaking to her generosity as a scientist and mentor.

[00:06:07]Her activities have extended well beyond her science to advocate for increased understanding of Antarctica and its implications for the planet, including briefing senior politicians and advisers.

[00:06:28]Professor Fria's extensive body of work and her dedication to the scientific community have made her a leading figure in glaciology and polar remote sensing.

[00:06:45]Her innovation and insight in applying new data sources to longstanding graological problems have transformed.

[00:06:58]how we now think about the dynamic processes shaping Antarctica.

[00:07:04]On behalf of the awards committee of the international giological society, Sue Cook the chair of the committee. So congratulations Helen.

[00:07:40]I'm so delighted. [laughter] >> I don't want to drop it.

[00:07:46]>> Congratulations.

[00:07:47]>> Thank you so much. Thank you. Oh, you're welcome.

[00:07:57]Shall I put it? I'll show the >> uh maybe here.

[00:07:59]>> Maybe we should show the audience [laughter] >> before I drop it.

[00:08:07]>> Thank you for your generous words.

[00:08:09]>> This is my small [laughter] >> for your next.

[00:08:14]>> Thank you so much.

[00:08:17]This is so so nice. I will open this later.

[00:08:24]So it's over to [clears throat] listen to you. So that's why it's yours.

[00:08:28]>> Ah, thank you.

[00:08:30]>> Thank you so much, Shin. It's really um to sit and listen to those words. It's Yeah, it's hard to hear things about yourself, but I your words were so generous and kind and thank you and thank you for coming all this way to this meeting and again to all of you for coming here to this meeting. Um we actually had this meeting booked as I said at the beginning on Monday for five years. Um so I didn't know I was getting this award until 2024 when I got selected. So uh it just happened to be uh you know serendipitous that that IGS came to me to award the Celigman crystal which is great because it means that my family and friends can be here as well. So uh and thanks to everyone joining online um as well. It's really really nice uh to be able to do this. Um but with that uh with that said, I also know many of you because of uh my uh English roots are quite keen for this to be done in 32 minutes. So I'm going to do my best. Um and hopefully there'll be no score if I go over time. Um and yeah, I'll just do what I can. We did not know about this class either. Um so thank you so much and thanks for giving me the opportunity to give this talk and tell my story a little bit. Um it's kind of two stories um in one sort of intertwined um some of the um the things that you referred to Shin in your in my citation I'm going to talk about actually um I hadn't seen the citation so um so it's sort of a little bit like an abstract almost um but I wanted to talk about what we've learned from all of these radar and laser altimeter systems that we've had flying over Earth um since the uh since the sort of early '7s or so um and give a little bit of a story there. But also alongside that, I want to intertwine my own personal story and how it all fits together um in terms of where I was in the different stages of these altimeter developments and um sort of the people I met along the way to lead me to where I am today. And just to sort of get to the punchline before we get to the end, um right now I'm actually PI of a recently selected laser altimeter mission for NASA. So, how did I get to that point?

[00:10:50]Um, you'll learn that in this talk. So, uh, so thank you for giving me the opportunity to to do this. Um, and I will go ahead and try and work all of this technology. Um, because there's a lot going on here. Um, okay. Yep. So, I can't Oh, on here. No. Everybody's had trouble with this. Why?

[00:11:18]Okay. Yeah, now I can see the slides.

[00:11:20]Okay, that's great. Okay, so just for context, like why am I talking about vital signs of the Earth system at a glaciology meeting? We've already heard this a little bit at this meeting. And I think, you know, as humans living on this planet, we need to understand our role as, you know, glaciologists don't exist in a little glaciology bubble. Um, we're actually a part of a a large interconnected system which is our planet that's also our home. Um, and as we know, um, all too well, um, how do I get the movie to go? Okay. Um, the Earth is warming. Um, everywhere around the world is having heat waves right now. Maybe even Australia uh, in the winter, but it does in its summer, too. There's hot hot days all the time.

[00:12:05]uh the global average temperature is increasing every year with time and because it's an interconnected system there are many things in the system that are actually interacting with each other and so it's not just anymore about just the ice sheets just the sea ice just the glacias it's about other things as well and on the right here we have a map of what we call tipping elements they're climate tipping elements and so these are all of the um the the sort of entities in the Earth's system that have been identified to be vulnerable to irreversible retreat should a certain temperature be uh be breached. Um and so 1.5 degrees centigrade above pre-industrial is stay close. Okay, I'm being told I'm moving too much. You knew I would though. Um is where we're sort of currently very close to. Um and some of these tipping points will be breached um fairly soon as we go into the sort of 2030s uh that next decade. And this is something to be very concerned about. We need to keep an eye on these tipping points and make tipping elements and make sure that the tipping points if they do get breached we know where they're at. We need uh we need basically tools to help us navigate through this period of uncertainty as humanity has to learn how to live on this planet that we're warming. So the tools are super important and they have all sorts of societal relevance. Um and I'll talk about some of these things. Sea level rise, flooding, fires, um even orangutans. We'll talk about orangutans.

[00:13:39]Uh how many That's probably the first time at a glaciology meeting that we've talked about orangutans. Um which is great. Um and so yeah, you know, as the climate's changing, we know that the frequency and intensity of extreme weather events is increasing. I think we all know that wherever we've been in the last month or so, we've probably felt this somewhere. Um and so this leads to very extreme things, heavy rainfall, drought, all sorts of things that we really uh have to try and uh adapt to.

[00:14:06]And it's kind of a um basically uh learning to live with this and become more resilient to these changes. The last IPCC report told us this. Uh we've known this for a long time. So one of the things that um people u need to know about alimmetry if they don't know this is it's not a complicated uh measurement at all. is just literally the Earth's height. Everybody knows what height is.

[00:14:30]Every single person, trust me. But I'll show you right now what the two halves of the hemisphere look like with ISAT 2.

[00:14:37]This is sort of a punch line, but I'll show you the movie at the end if I have time. Um, this shows you the uh the mean forest height, the mean terrain height, the ocean topography, the sea ice, and the land ice all on one map, all from one instrument. And it's basically by looking at the Earth's height. Um, I'm just going to move the I need to move the Okay, there's I can see people moving on the screen, so it's Oh, okay.

[00:15:01]It's kind of How do we How do we close that? Because it's it's distracting >> me. Um, okay. Um, and so we will >> Your mom's there.

[00:15:11]>> Your mom is there. [laughter] >> But I could just see the Okay. Well, there you go. That's fine. That's totally fine.

[00:15:20]>> It's all good. Um, so literally everybody does this when their kids grow up. Oh my gosh.

[00:15:31]Okay. Right. You measure your height of your kids against the uh some sort of I don't know makeshift thing on your kitchen wall um to measure how high your kids are. This is height with time. So we're literally making this experiment as our kids are growing up or as we grew up. You probably remember this. Um, and this is literally all alimemetry is doing. It's making a map of height versus time for everything on the planet, like whether it's a tree or a forest or a glacia or a ocean. Just how high is that thing above a certain reference point. Super important information. Uh, this is actually from Oregon State. Um, so I told you guys I love Oregon State and one of this is why one of the reasons we go up there quite a bit. And um so this was a really cool sand uh experiment using height, but it's time to show how uh 3D topography shapes uh the earth and how different processes um sort of conform to it and really important for learning and uh and that kind of thing. So alimemetry measures surface height super simple um above a a reference point. You don't need to worry too much about these but you sometimes hear us going on about these things. Geoid, ellipoid, whatever.

[00:16:42]You guys don't need to worry about any of this. You just need to know that alimemetry gives you height versus time of a thing at a time. And then if you do it at another time, you get the change in height. And that can tell you something about the thing that you're looking at, which is really all it is.

[00:16:57]Um, and so how do we get all these amazing instruments flying around orbiting our Earth? Well, we owe it to um the insight of um some really smart people in the late 60s. It was actually 1968, which is before I was born. So my story doesn't quite uh overlap with this. Um and so this is a report that I really urge you if you're in ali any kind of alimemetry field or you're a student or a early career person read this because this is super cool. It's like the first blueprint that we had for ocean altimery. It also put forward the uh gravity instruments that we now see as grace. It also put forward SAR. These are like the three main techniques that we use for earth observing, for solid earth, for cryo, for ocean. And it's all in this document like the sort of pattern and what we're going to do.

[00:17:46]Really, really great. And so NASA sort of uh ended up launching in the mid70s um an instrument called Goss. Um many most of these are launched from Vandenberg just up the street. In fact, you can see them from scripts when they launch. Um they probably saw this. Um so Gio was the first one and then Seesat which many of you would have heard of designed primarily to operate over the ocean. Why over the ocean? Well the ocean turns out is a really um simple surface to map with radar alimmetry. The waveforms the return everything is really well behaved and you can really understand what you're getting back from it. So that was one of the reasons why and they put this forward as a technique to map sea level height.

[00:18:28]I don't know why is it not working.

[00:18:30]Okay. Um, and so Gio, some of you will have heard of this. Um, very very early days, but you know, it was a a big project and got some data and the quality was actually way uh way better than they thought it was going to be.

[00:18:42]Um, and in the end they used the data um in a way that was not anticipated before. And so there's a theme sort of that does run through this talk a little bit which is a lot of these instruments would were launched for certain applications and then the data ended up being used for something completely different which was really great and it led to a whole sort of explosion of different techniques and like a sideline of uh or a sidebar of different um different technologies. Um, and so GEOS in particular, they discovered that actually it clipped the edges of the ice sheets even though it was in an orbit that didn't go over the ice sheets uh very much. It just got a little bit round the edges. Um, and remember that word edge, very key. Um, and it would actually turns out it maintains track.

[00:19:29]So people did things with these data which is really really cool. Um, I cannot get the hang of this computer.

[00:19:35]I'm really sorry. Um, okay. So a sort of an explosion in what could be done and basically huge uh potential future for activity and just this sort of excitement that we actually could have this kind of quantum jump in knowledge uh not just in oceanography but geoysics um and ice sheets as well all sort of like round about the mid70s. So people started doing this. We know some of these people. We even talked about some of these people at this meeting. Um they did this uh analysis in the early 70s.

[00:20:04]Got it published in nature like some of the first surface topographic um maps. This is actually the first topographic map ever of an ice sheet.

[00:20:13]Looks pretty looks pretty bad, doesn't it? Um but you know it was kind of the bee's knees at the time. Like this is actually a 3D plot of an ice sheet. Some profiles. We didn't know any of this before. We didn't know the topography of the eye sheet because we didn't have that height. Um, and so people started doing a lot of things with these data.

[00:20:31]Sorry, this is a really horrible interface for me. Sorry. I'm really sorry. Um, okay. Um and okay so uh for example uh Seesat when it was launched in the bit later in the 80s very short mission actually only lasted for 3 months but it was able to it went about to about this point here 72 degrees south. So it clipped the uh top of the Antarctic Peninsula, a little bit of this part of Antarctica here, which is a bit further north than the rest. Um, and provided some really useful data which could be used to then try and come up with algorithms to do this thing better if we if we could actually cover in the regions we want to. And that's in the end what the data set became that people use to figure out how to put other instruments up and do this properly for ice. So this is Okay, I'll just use this one. Okay, so here we are. We've got to seesat in the 70s and then we um sort of started to explore. Geocat was launched in the 80s and with Geosat we ended up having actually a full DM of Antarctica. Okay, so not full because there's this hole because that's the orbit limit. Um but pretty good like there's actually some topography there that you can see and this is really nice. We're suddenly starting to see even some like drainage basins and even some outlet glacia um sort of 3D uh formations there. Really foundational stuff at the time in the mid 80s. This was really cool stuff like way way more than we had before. And then the colors come in. Look at this.

[00:22:06]This is Jay in the late 80s. We had some slides like this yesterday. These kinds of colors. Um so Jay was always in we always got at Jay for his color schemes but this was probably the one of the best. this candy cane cover of uh sort of map stripe map of Greenland but this is all the individual tracks and this is basically as I said height that's it it's just height so the height of the ice sheet higher in the middle lower at the edges we didn't kind of know all this we knew that but we didn't know the actual number until we had the altimeter to tell us that so this was a sort of foundational point where we suddenly had even topographic maps that could actually then be used for modeling and and things like that um many of you know Uta Herzfield, she did a lot of work as well with um with Seesat and and Geosat and published this this atlas. This is actually the first uh DEM of a marine life shelf um which you know this is actually all floating here and you can see and what you notice here is there's actually a kind of a lot of noise here um so we're going to talk about that um because that is one of the downfalls of radar ultimatry um struggling in the places where there's topography. Um, so Jay and and other people came up with this technique. It's just basically comparing where the orbits cross over.

[00:23:21]It's just a crossover difference to look for changes in height with time. And they published something which actually ended up being wrong, but it didn't matter because, you know, that's kind of how things go in science. Um, but this was basically the first like intermission uh height map change uh for the whole of Greenland. Um, so you know, Jay was kind of in this territory that we're all in now, but um with with a very limited data set. Um, and so with these data, what we realized had to be done was examine these data and figure out how to make the algorithms better so that you can get more information from these noisy data. As I said, alimemetry was designed to operate over the ocean.

[00:24:05]This is what you call a waveform. It's what you get back. This is kind of the main thing that you get back from alimter. It's like the power versus time. And it's kind of a nice shape over the ocean. It's very smooth. Over ice, not so much. Kind of wiggly, kind of a mess, really noisy. So you have to figure out how um to interpret this and how to um create algorithms that actually give you the actual height that corresponds to the mean surface that you're observing with the altimeter which turns out it's over quite a large footprint because radar at that wavelength has a a sort of couple of kilometers or so footprint. So we have to figure this stuff out and um so Chris Rley why is he up there? Well, this is where my sort of storyline intertwines here. Um, I was an undergraduate at UCL in the uh late 80s, early 90s. Um, and I met Chris Bradley. He actually honestly changed my whole career. U because I was doing maths and physics and I met him and he did this class called physics of the earth and it was like, wow, okay, now I get it. Um, and I did a project with him and he at the time, this is serendipitous. I mean I'm very lucky that I landed at the place where he worked at the time they were working on these algorithms. Uh IS1 had not yet been launched but they were all talking about it. I remember the birth it was launched in June 1991. I just graduated after that. Um so I sort of disappeared but um but the the data were amazing because ERS1 had an ice mode. So Chris was very involved in understanding these waveforms and really uh very uh instrumental in figuring out a lot of this stuff in collaboration with Godard with Jay and others. But they really you know they publish a lot of these and if you're if you're a PhD student looking at radar optimmetry these reports are really really useful. Uh there's a lot they're really thick too. Um but these reports were so foundational. And then right afterwards this report came out.

[00:26:02]uh this is the first IPCC report and so this is all happening around that time we're sort of building up the techniques to the point that we can understand the ice sheet and then we're also getting the first IPCC report which is telling us that you know the earth is warming and maybe the ice is changing we don't really know yet but you know this time in the 90s we didn't really know whether the ice was changing but we're just getting the techniques ready to primed to tell us whether it's changing or not so this is all happening at uh sort of at all at the same time simultaneously ly. So, I'm back with this interface.

[00:26:35]Okay.

[00:26:36]Um, okay. Um, we don't need to worry about the details, but if you're a student, [laughter] you will worry about this. So, you can look at this another time, but it's basically how you get the height measurement, which is the best place on that waveform that corresponds to the mean uh surface. And, you know, there's some clever things you can do, and you can take a whole class on this, and I'm definitely not going to go into it now. Um, but the basically the the punch line is return waveforms for a radar altimeter are different over different surfaces, right? They're really nice over the ocean. That's actually nice. Uh, this is nice waveforms. Uh, they're narrow peaked over sea ice and they're kind of um a little bit funky shaped over ice shelves because you've got different features there. You've got topography, you've got creasses, you got all this stuff. So, when a altimeter goes off the ocean and onto land, it starts to get noisy. And that's what we had to figure out and got through to come up with all the algorithms that we use now to get the best heights we can out of um out of uh the the altimeters. And this is another example over a lake where they're really messy and then they go smooth again and they go messy again. Um so yeah, really important information but hard to extract. And I looked at way too many waveforms during my PhD. Like I almost never want to see another one again. Um so so this is a time like right when ERS1 was launched in 1991 um was kind of the time where I I talk of it talk about it as like a sort of like a splitting or a bifocation of the branches of alimemetry. So seesat or gios before it over here and then seesat and then geocsat they were all on the same branch and then they split off and we had two different lines of alimmetry that that got developed. One of them is Ocean Ultimatry and you all know about Topex and Poseidon and SWAT and Jason and sorry Topex Poseidon Jason SWAT Sentinel 6 all of those they're all ocean altimeters designed to measure sea level rise are in a certain orbit they only have an ocean mode and all of that and then there's a second mode which you've all heard of as well but they're completely independent um they're actually ISSA European Space Agency they're not NASA they're a different um different group or different uh sort management and everything. Um, and IS1 was the first satellite that was launched that carried a radar altimeter.

[00:28:55]Um, it had everything else on board as well, like a SAR and a scatterometer and many things. Um, but the radar altimeter was what I'm talking about now. And this was the DEM that came out of that um of that first uh mission here. It's a bit bigger. Um, so you also see a little hole again, right? Because it's kind of smooth in the middle and there's a hole.

[00:29:16]That's because ERS1 only went to 82 degrees south. So everyone knows that the pole is 90 degrees. So it's public lecture by the way. So I'm trying to um so we have eight degrees that we still have to go. Um and so there's a gap and so there's kind of some smoothing that goes on. Uh a lot of smoothing goes on with alimemetry basically radar alimemetry. Um especially where there's no data. Um and so but where there is data around the edges um you see a lot of interesting information. And now this is a really useful map. In fact, Matia, I think it was, showed this this morning as an input into a model. Um, having uh these um these DEMs is super important because it helps determine where the ice flow goes um and all of that. Uh but what you need to do is really figure out how accurate that height measurement is, like how true it is to where the actual surface is. So, there's a photo of me there. um because turns out in the end I uh did stay on and work on the the kind of science that Chris Rapley was doing.

[00:30:16]Um but I didn't do it at UCL. I actually moved to um Australia and did my PhD in Hobart. Um and by then there had been three years of of ERS1 data. I I had no clue this was going to happen really, but it was quite good because it meant that three years of uh data had already been collected. I didn't have to sort of wait for the data. Um and then we actually went to validate the data and so went to Amory Ice Shelf um to do a validation survey with Scudoo um and these are our uh GPS antennas and we're driving around and we're testing out the actual or trying to get the accurate height um of the surface. So you can compare that with the altimeter um and this is what came out of that work which was mentioned in Shin's generous citation earlier. This was the first map of marine ice under Amry ice shelf that we got from uh the ERS1 uh map digital elevation model and we actually differenced it from radio echo signing data that had been collected in the 1980s. Um so that was a really um very nice uh result that we've that we managed to get from integrating the satellite data with the radar um airborne radar. Um and that kicked off a um research program called Amaz Ocean Research. Um and these sites were drilled along the bull hole. So this is actually thick marine ice. We still use rainbow color scales in these days. So this forgive me. Uh so this is 190 meters of marine ice along a flow line and that's underneath the ice shell. So that's actually observing something that you can't observe directly. It's an indirect observation. Um and yeah, we were able to then go and drill along these flow lines and and make measurements and find out more about what's going on uh underneath. Okay.

[00:32:04]Um okay. So um during this time as well, people use these data to difference with time um or or look at height changes versus time. Um, so this was early day uh height change maps um to show us where the ice sheet is changing because if you know the height and you know the height has gone down then you know you've lost ice. If the if the height's gone up then you've gained ice. So it's that simple. Um it's not actually that simple. There are many other things but that's the bottom line principle. And so again ugly color maps not my fault but you do see that changes over here. This is a change. This is height going down.

[00:32:42]This is height going down. This is height going down. Uh Duncan Wingham, Jay Wally, Andy Shepard, all sort of pioneers in this technique and showing us how to use alimmetry um to show us where the ice sheet is changing um and um point us to places to go. I need to do a time check.

[00:33:02]I don't have Huh.

[00:33:04]>> Hello.

[00:33:05]>> Thank you. Okay. Um so I um also wanted to show you results of um TOPEX.

[00:33:14]Basically this is a sort of place we were at with Topex at the same time. Um so TOPEX this is from this institution David Samuel may or may not be here. Um and so he used TOPEX um to give us global C4 topography. So the the sort of two branches that split off each led to really cool things in the different areas. Um and in the end they sort of come together and I'll show you that uh soon. Um, also ERS1 um was able to give us some of the first CI thickness mats.

[00:33:48]And this is my dear former mentor Seymour Laxon um the late Seymour Laxon um who was very uh instrument like very foundational to me in my career of huge mentor um and he actually came up with a technique for retracking to get sea ice thickness measurements very accurately.

[00:34:05]Um, and so that it was able to tell us how much ice we're losing, how much sea ice we're losing in the Arctic. Um, and we're working on this still for the Antarctic. Um, and then going in to um a little bit more back in time using the ERS1 sort of uh 1990s to to 2000 era data and then comparing backwards in time to sees. So this gave us a good like 20-year time series to really try and understand. Okay, so we know the ice is changing in a in a few places, but can we take the record back far enough by going to Seesat to try and figure that out? And we had a paper had a paper with uh Lori Pabin, another dear wonderful colleague who I think is online. Um and he and I came up with this is one of the first papers we wrote together maybe, maybe not. Um and this actually showed us changes in ice thickness with time over the whole peninsula going back all the way to the the 17 1970s. Um, and then this is the work that was referred to, I think, in the citation. Um, some of the work that we've seen today at this meeting. Um, this is changes in the eye shelves from long-term records, basically stitching together a lot of radar altimeter data in one. ISA did a fantastic thing by launching these missions so that they overlapped and we had this seamless data set of height change from June 1991 until now. Cryat is still up there giving us and they've got crystal coming down the line. So there they have this seamless welloiled uh data set from radar ultimatry and we use these data for uh for this one over here on the right. This is Fernando Paulo who was a graduate student here um now works at Global Fishing Watch. Um but he learned a lot here to take it to to that other useful uh thing that he does. Um and then over here I set um Hamish Pritchard came and spent some time here at Scripps um in 2011 and did this work looking at um ice shelf height with time. And we plotted it on a map of ocean temperature and what you see there is where the ice is um going down thinning the red is where the water is red. So we this was the early sort of time and Eric had had published his paper at this before then as well and we kind of knew this uh basil melting is driving the changes and the ocean is driving the ice shelf changes and so this was sort of seeing it all coming together from this one um instrument. Um and then uh we did a little bit more which is going into this is back to Bry's technique that she was talking about earlier today if any of you saw it but using uh once ISAT was up ISAT was kind of the next thing where okay so radar alimemetry is is great but um radar alimemetry struggles because of the fact it's a large footprint and and and uh laser alimemetry is very very um uh it's a it's a much shorter wavelength It's a laser. Um, it has a few uh cons of course because you can't have all pros. Um, it is affected by clouds at that wavelength, but uh the pros are that the footprint is a lot smaller. So, the height ends up being a lot more accurate. And we were able to look at changes with time over the grounding line um and pull out this flexure uh this this flexing uh area that u that Bry was talking about earlier.

[00:37:30]And that is where we went into the side quest.

[00:37:35]Um so the side quest was mentioned in the citation as well. Um so when I was looking at the grounding line of Ross I shelf um one of the first tracks actually was right here track 53 my favorite track of ISAT. And what we found was right upstream of um the grounding line there was this crazy signal that everybody looked at and said oh no that can't be right. No, you must have made some problems. You've got some problems there. No, couldn't possibly have uh like 10 meters of draw down or change in in that. But anyway, long story short, it wasn't wrong because we uh we actually looked at all the cross tracks and the same signal was there.

[00:38:16]This is the discovery of the active sublacial lakes from laser alimemetry. I have to say I was not the first person to do this. Um there was actually radar altimeter looking at using crossovers looking at some lakes upstream at Adventure Trench and then before that actually Lawrence Gray had used SAR to identify some lakes but it was the first sort of active system of lakes found underneath an ice stream and the fact it's under an ice stream is super key because that can change the sort of glacial hydrarology and the flow dynamics and that interaction. Uh and I love the whole concept of this because it was a new process we didn't know about before and also not a climate change. It's not oh you know this thing is changing because of climate is actually a process that was new that we discovered. So um that triggered another uh whole load of fieldwork. There's two sets of field work for this one actually. So Wizard, some of you remember that and then Salsa. I'm not going to spin off those acronyms. Um but anyway, they were drilling projects into these subglacial lakes on Will's ice stream. Um and a whole lot of people involved in this really super interdicciplinary project. Um I've given like a whole hour lecture just on this alone. So I'm not going to spend much more time on this, but super exciting.

[00:39:30]There is actually a movie, The Lake at the Bottom of the World, um about the Salsa project. Um very exciting, uh project to be part of. Um but it was definitely a side quest for me. I I'm not really in lakes anymore. I'm back to ice shelves. Um I enjoyed it for a decade. Um but ice shelves are kind of my my thing. Um I think it's hard to to get away from them. Um okay, so um in the sort of 2010 era, um we have these new missions. So I already told you about ISAT a little bit and then also Cryasat. So Cryasat was big new thing, shiny thing. So two big new shiny instruments um had had sort of been operating. ISAT was earlier in 2003.

[00:40:12]Cryat um well the first Cryasat wasn't so successful. This is actually Cryat 2 but got rebranded. Um and so what why why were these so innovative? Well, Cryat um was able to kind of improve the resolution of the footprint and give us better information along track uh by using a very clever interferometric processing technique that Duncan Wingham wrote lots of papers about and lots of people don't understand them but it's very very smart and produces really great data. We've seen some this week actually. Um and then ISAT, this laser altimeter from NASA. Um and then ISAT 2 came along um in 2018. So these are the sort of uh sequences of of instruments that I've been working on. In fact, the whole reason I came to the US was to work on ISAT. It hadn't been launched yet. Um but I came as a posttock to work here at scripts with Bernard Minster. He was on the science team. Um so this mission actually brought me from uh Hobart to San Diego to work on the new data because radar automatry you know there were flaws. We really thought ISAT was going to like solve all our problems and it sort of did but you know this then it brought others. Uh so yeah Cryat um Cryat has done a lot. I didn't want to miss out Cryat. Cryat's just a fantastic instrument but I haven't spent so much time in my career working on that. So but I didn't want to to miss it out. Um we have still been looking at a lot of long time series. This is some early work that Sashil did when he was a student here. Uh you've just heard from Sashil today. So um so yeah looking again at long time series of these all of these radar alimters put together to try and understand the processes driving the changes and then going into more I don't think did Sashil show this map? I can't remember. I actually had to duck out for a minute. This was his his amazing map of basal melt rates and a lot of people have been talking about this at this meeting. Um and so the next step from just looking at height versus time is actually convert that into something that can be useful for modeling. We actually talked to Sophie Nikki and asked her at a sea level change meeting um here at scripts actually like what do you guys need from us and she said Sophie Nikki is an ice sheet modeler runs the ISMIT program and she said we need melt rates. We need melt rates on a plate. I said, "Okay, we'll give you melt rates on a plate."

[00:42:28]I'm like, "Can't you just take the heights and multiply them by the ice shelf areas?" She's like, "No, no, we want melt rates." So, so Sashil worked out a way to give melt rates. And this is our melt rate map um that um that that they have subsequently used. And I know it's not the only melt rate m rate [clears throat] map, but it's one of them. Um and so it's really um sort of shows you what you can do with a long time series of data. um other data sets went into it of course but um but the ultimatry was the sort of driving force for this particular uh melt rate map and then on the right we've seen this map a little bit as well at this meeting um this is what happens when you difference um the later ISAT mission the ISAT 2 mission from ISAT so this is um 16 years of change from one mission to the other in this map we've actually used a intuitive time intuitive scale people have started using this much more intuitive scale, which is red is loss, which is hot. It's just like your faucet or your tap on your sink. Very easy. So, red is loss and blue is gain. Blue is cold, red's hot. Um, and so this is the New York Times rendition. Actually, the color scale is different to the one we had um of the map from the Smith at al uh paper. So, this is now showing us where the ice is coming off and touching the most uh where the height is going down the most. and we can focus on where the changes are. And you'll notice that it's all around the edges. Um, which is going to bring me into uh the next part uh which is the final part. Um, so this it says I've been going for 53 minutes, but that's not right.

[00:44:08]Okay, good. Thank you. Okay, so the game just kicked off. I'm fully aware.

[00:44:13][laughter] Don't tell me the score.

[00:44:16]Okay. Um, and so ice is being lost around the edges of Antarctica. And why does that matter? Okay, so on the left you see sea level contribution um how it's changed with time. The little color uh colors in the pie chart tell you the where it's coming from because sea level change doesn't just come from uh the melting of ice sheets and glacias. It also comes from thermal expansion. So the red is thermal expansion. This is with um increasing with time. the size of the circle is increasing with time because the whole signal is increasing with time but so is the proportion of Antarctica um to the whole. So by this time period we have 10% of the ice loss of the sorry 10% of the signal of sea level rise coming from the ice sheet the Antarctic ice sheet whereas back in the 70s it was a really small amount. Um, and so we know that we've got uh this possibility for that to become a very large number. Um, we've heard about this today and and and Matia actually already showed one of the figures I'm about to show. And a couple of people talked about this. Eric talked about recovery having a huge um uh sea level potential. I mean, the darker the blue on that map, the more sea level is behind it. So, you really want to worry about the dark blue areas in Antarctica.

[00:45:33]I'm not saying you don't want to worry about the West Antarctica, but for me, East Antarctica is is is a focus of of of huge concern because of the potential sea level coming from it. This is a map that Matia showed, actually slightly different version, but from a paper we had um last year now um showing how the future is very uncertain in terms of how much ice will be lost from Antarctica.

[00:45:57]So, we have to learn it, we have to understand it better, we have to observe it better. Back to the map. Why is it so tricky? Okay, so around the edges of Antarctica, edges, margins, where all the changes are happening, this is what it looks like. It's a hot mess. Okay, well, it's a cold mess, but it's a mess. And basically, an altimeter is going to really struggle over this area. Even a laser altimeter that is able to like um get a small footprint and it's still going to struggle um because there's a lot going on. There's a lot of topography you got to try and unravel.

[00:46:30]Those height changes with time are now getting really complicated. Okay, so you've got to try and capture all of this and very hard. And these are the scales of change. We already talked about grinding zones today and all these things, pinning points. They're all super important, but we don't map them at the right spatial and temporal scales to understand them to be able to put them into models because we just don't have that information yet. Um, and so yeah, I'm not going to show this, but this is another map that was well, I am going to show it, I guess. Uh this is another map that was in our science papers showing like the the mass loss processes from Antarctica, the carving and the melting are all getting down to time scales and spatial scales that we don't yet observe at things that we've heard about like today in this meeting like turbulence and eddies and things like that are just not captured. Um, and so, you know, if you're if you're observing features that are responding to processes like that, then you're not going to be able to sample them um well enough to to fully understand them. Um, and so this is the problem. So, here we have uh basically your typical uh sort of ice shelf with lots of rifts and things. ERS1 wide swath is set a little bit wider. I set two a little bit smaller than that. Smaller they get smaller, but they still encounter a lot of topography. And basically you're gonna struggle. The altimity the altimery noisy data does get really noisy. I'm trying to go fast because I know about the England game. Um and so um ISAT did solve a lot of problems. It gave us some really useful um like data over risk. ISAT 2 even better because the uh ISAT 2 sort of uh innovation was to go from a single beam sampling um which is just one strip going around is a red laser um and so I the analogy I like to use is like it's like u wrapping a piece of cotton around a ball that was 2 um we realized we needed more information across the across the track um so ISAT 2 used um split the data into six beams. It was three pairs of beams.

[00:48:34]Um, and that's a bit like having three uh sets of well, six sets of say wool, thicker going also going around the around the ball. Uh, you're going to map more, you're going to get more information, but you're still going to have a lot of gaps. Um, I'll tell you about edge when we get to edge. Um, and so even but 2 was great and is great.

[00:48:55]It's still collecting a lot of data. Um, and we have a lot of information and a sort of like a hint at processes that we could learn more about if we were able to sample at higher spatial and temporal resolution. For example, this is a whip round. So, hold on. Um, this is a ice shelf, favorite ice shelf, um, before and after carving from Isatu.

[00:49:17]Information about rifts, information about Milange, all sorts of things in there. Uh, Suji Wang at Penn State has done some amazing work with um, with Isatu over rifts. Um this is some of her work also on Amory. Um the details of the riffs here is beautiful. Um but you know there's just this limitation in how much you sample because of the gaps in the data. Um Suji Wang again lots of information here. I'm not going to talk about it but basically to tell you that is 2 is very good at giving you um information where there is data but there are a lot of gaps in the middle where you want to just fill in but you can't just interpolate. um greats uh really nice uh data here looking at pinning points because we know pinning points are super important we've heard about those today as well mapping those how they're changing with time um and this was Bert's um pinning points uh paper that we've heard about as well learning and looking at pinning points how they're changing you need the the the high spatial resolution um and it's really good where you have it but there are gaps um Katherine's paper looking at conga Glenn's eye shelf over here near Shackleton um made use of a lot of ISAT 2 data as well giving us some knowledge and getting us to understand the processes but just not quite giving us enough we just the gaps so here are the gaps so here's ISAT 2 gaps there's like more gaps than data right like I shouldn't go on about the gaps because 2 is amazing um but we need better sampling um and so basal channels also really important we've heard about these today and 2 is able to give us some really nice data um looking at changes in basal channels with time and the channels actually funnel the melting and give us higher uh melt rates and we can look at that um and so she'll talked about this as well um but you know the the spatial resolution again is is the issue um I'm going to jump over that price 2 also does basal melt rates um 2 does one thing the edge is not able to do um and that's because it's a green laser and it penetrates through water um and so we got some very nice information about melt lake uh features from ISAT 2 which is um yeah just sort of still a bit of a work in in in publication but um it's a very nice data set if you want this data set let me know uh we can get it to you uh and then work with Roland Warner who I think is online um looking at a do line on Amory again uh told you favorite eye shelf um and this is very nice also looking at eyesight too but pointing to the this limitation in spatial and temporal sampling Um so you know we really want to understand the ice shelf region very well around the edges at the margins.

[00:51:57]The grounding zone is really important as well. We heard this all morning from the sessions. Um and grounding zones are very well sampled as well by ISAT 2. We heard this from Brian. Um and I had showed you earlier from the ISAT. And so ISAT 2 has been able to pull out some really nice information about title migration. This is a 10 or so uh kilometer tidal migration that Bry talked about earlier. This is a lifting of the ice shelf with uh with ocean tide. Um and then this other work that Bry started uh has started and talked about today which is the the viscous bump um at the granning line which tells us um about basil drag and ice viscosity as well. So this is all coming from ISAT 2. I'm going to just jump through this.

[00:52:41]This is information about lakes. We have a lot of data from ISAT 2 telling us about lakes as well. This is from uh Matt Sefrieded um and Mike showed this earlier this week, but the really improved sampling is great um but not quite not quite at the place where we need to be to understand. So I'm going to tell you about edge in a minute. Um atmospheric rivers uh is 2 gets uh data from the top of the snow which is uh very nice because it tell you actually can pull out snowfall events. So these atmospheric rivers which are becoming uh what we think is more frequent over the iceat 2 period are adding to the mass um overall on the ice on the the whole ice sheet and we can pick that up with ice 2. Um so iceat 2 does not just do ice it also does a lot of other things. Um so this is kind of the the whole new way that NASA is kind of being split up into the cryossphere and the biosphere and other things. So um we obviously do a lot in the cryossphere. We also do a lot in the biosphere as well because ISAT 2 um is able to give us um information over the forests and the trees uh and vegetation. Um it also gives us bethimemetry and it also has been able to monitor human reservoirs. So the point being the key thing here is it's monitored changes across the full earth system. Um there's also in parallel another instrument on board the international space station called Jedi.

[00:54:05]And why am I talking about Jedi? Well, you'll find out in a minute. Uh, Jedi is a great instrument. It's um at the infrared wavelength. So, it's not the same as 2, but um it's on the space station, so it's constrained in its orbit because the space station does not go around the poles. It just goes to 50 north and south. Um, so we are working with the Jedi team. But before I get there, I'm going to show you the highlights of ice set 2 and do another time check.

[00:54:38]15 minutes left. Okay. So, this is the movie of Isatu and showing us how the data build up with time. This is the I showed you the still of this at the beginning. Um, but this is I think an amazing visual showing us how you can use these data to understand how these different parameters change uh have changed with time in the Earth system from the launch date of uh of ISAT 2 in 2018. Um, and this goes until 2024. So, you can actually get this from the NASA science visualization uh studio. This is mean forest height on top of mean terrain height because you can extract the tree height from that. Um, okay. So, I got to move along because I got to get to edge. Um, what have we learned? Okay.

[00:55:22]So, from the ocean alimos, we've learned that sea level is going up with time, right? We know this. This is Topex Jason uh the Capernacus mission set Michael Frick satellite. Um this is an increasing signal. It's actually accelerating. These are all the ocean altimeters and this is the signal that they have uh produced. Um at the same time we've had this parallel branch of altimeters mapping change in ice with time. And we made this map. Uh Jennifer is here made this amazing map that kind of went together with the uh the the oceanmetry one to show us the uh change in uh ice with time. This is just the uh the altimery contribution from IMBI.

[00:56:05]IMBI also brings together the the SAR the input output method and the grace.

[00:56:10]It's a fantastic um sort of consortium of all the different techniques that all work together to complement each other.

[00:56:16]Um but my point here is to show you that these different altimeters have shown us sea level rise in parallel with ice sheet melt. Um but different uh different instruments independent but all coming from the same technique um and the sea level change team is a great group um a really a big NASA sort of interdicciplinary team where you can go at sea level.nasa.gov and you can get these metrics of like what is happening with sea level now, ocean mass, reland mass change, Antarctic mass. I encourage you to go to this. It's a fantastic resource. Um I'm going to jump through this. You you all know about SWAT. Uh SWAT has basically done a lot for understanding uh processes around the edges of the uh the ice sheets in the in the ocean. If not, if you don't know about SWAT, you should. And I think Tasha is probably going to talk about Squat um uh next tomorrow or Friday. Um there's also some really great data over the ice shelves as well. But this is the sort of next generation ocean altimeter um that kind of comes along with Isac 2 and Jedi.

[00:57:18]We're sort of where we are right now, the current state-of-the-art. So I'm going to talk about the future for about maybe eight minutes and then we'll be done. Uh so the future is bright hopefully. Um, so coming down the line from issa, we have this mission called crystal. Um, not the celibate crystal crystal. It's actually got an I in it, not a Y. Um, and Crystal, I can't remember what it stands for, but anyway, um, it's coming and it's going to be great. It's a dualband, uh, radar altimeter. Um, and it will be launched in, well, the website currently says 2027. Um, so next year. Um, so that's great. So issa have something in the pipeline. So what is next for NASA, you might ask? Well, I'll tell you. Um, in February, we were selected um Edge was selected um for implementation. Um, it went through a two-step process uh with NASA. Um, a lot of work, a lot of work.

[00:58:13]Um, I kind of didn't do much else uh for a long time. Um, and um, basically, it's a joint project between the terrestrial ecosystem group and the ice elevation group that you talked about. It's kind of like bringing Jedi together with ISAT 2 and moving it into a freef flying uh orbit, a free so freeflying instrument in a free orbit, polar orbit. Um and so I can't do that by myself because you know I only do is telemetry. So um obviously don't do the instrumentation either. So uh we um of course need to go to the gurus for this. So at NASA Godard we have Brian Blair who leads the Elvis um facility and then Scott Lusky who's a Geodys guru and uh just all around amazing human. These these guys are amazing. Um works on so many different missions. Um and then John Armst also amazing. It's probably online. Um this John is the deputy PI for ecosystems. He works on Jedi and you know I needed help. I love trees but I don't know much about them. So I needed the help and and so we are we are the team. We are an interdicciplinary team. We would we were interdicciplinary from the get-go. Edge was designed to be a community instrument for the entire earth system.

[00:59:26]Well, starting with just ecosystems and ice. Okay. So, I'm going to give you a very quick very quick lightning talk of what edge is. So, edge is kind of it's evolution. You have to you have to show evolution with NASA, but it's also continuity because we really do need the continuity. I think I've told you or or like given you the reason why we need to keep monitoring the ice sheets with alimemetry. Well, we are going to continue doing that, but we're also going to innovate by going way way higher resolution. Edge is a multi-be uh sorry, a swath mapping um instrument.

[01:00:00]It's an imaging uh so Jedi and ISAT 2 are multi-beam and edge is a swath mapping. It's basically like an imaging LAR. So, it takes things to the next level. So here's our um this is our cotton. This these are our wool going around the earth. This is like ribbons.

[01:00:16]Ribbons going around the earth. You can you can uh change you can cover cover the ball very quickly with ribbons and that's what edge is going to do. Um and so how does it work? Well, it's basically got five lasers and each of those lasers is split into eight beams.

[01:00:30]And so on the ground these are 120 m wide and in between the strips that we call the mini swats there's 1.2 km. So, it's a really big swath and the coverage is amazing. Um, basically it takes away the whole need for really repeat tracks because you have so much coverage. Um, and we're going to be able to show show a lot about what's happening around the edges of the ice sheets. We have this sort of strategy behind our implementation. We're teaming up with what used to be Maxar. They're now they went through a couple of name changes.

[01:01:01]Now they're intuitive machines up in PaloAlto. It's the same spacecraft that's used for the world world view legion uh uh high resolution imagery.

[01:01:10]It's stable. You need a stable, precise platform, high accuracy. It's agile. Uh and we do that. We need that because we have a capability to target. It's the first time that that's been a possibility for a for an altimeter like this. Um and I'll show you that in a second. And the orbit is sun-synchronous. We've gone back to sunsync. We are not going all the way to 88 like ISAT 2 and Cryat. Um and that's okay because what we do is we actually place the highest density tracks over the edges of Antarctica. Haha. Um so the margins. So yeah, I mean in the end you get better spacing in the places where you need it the most. And so that was kind of in the end a really nice um thing that came out of this collaboration with the vegetation group.

[01:01:56]Um and we also have the lowest altitude over the equator because you have thick uh tropical rainforest there and you need dense uh you need uh to improve the link margin. Um these are our modes. I won't go through this. I can definitely talk a lot more about edge if people want to know more but we do have um the first time uh sort of rapid targeting.

[01:02:14]We can dwell. We can spend longer on a place. If you love a glacia we can spend more time there for you. Uh who knows what you're going to want in 2031. Uh maybe we'll be back here even in five years. uh and you can tell me um transformative science um well okay so we're kind of going for the major issues this was in the slide deck right from the beginning of when we first started working on edge in 2021 uh you know forest fire sea level rise super important I already showed you the tipping points the uh the tipping points are really well sampled uh by edge we actually get all of these things we get the boreal which Jedi couldn't get um and we just able to increase the coverage by the width of this hourglass tells you the coverage. I set to as you can see super thin uh edge really thick. So yeah much much much better sampling and we will because of that I'm going to jump through this but trust me it's all grounded in the decal survey which we heard about from Britney. Uh we have possibility to do fire and carbon and snow and perafrost but this is now a big a big whiz through because I really want to get to the end. Um, so measurement gaps were thought about for a long time by the science team. We thought about what we have up flying now. We have Jedi and ISAT 2 that are flying at the moment. What can they sample with what they do, right? Their sampling is limited, but they are able to do a lot.

[01:03:38]They tell us a lot, but there's some things they can't get. Like for example, I'll just look over on this side because you're all familiar. So the rifts and the ice fronts are undersampled. Uh, the grounding zones are undersampled. The basil channels are all under sampled by ice 2. But Edge is going to get them all. And let me show you. Um, so this is actually the best way that we've come up with to show you how amazingly wow factor edge sampling is going to be. So look at these two circles. They're 20 kilometers in diameter. Jedi on the left over the Amazon and ice 2 um on the right over the Cook eye shelf at 68 degrees uh south in East Antarctica.

[01:04:15]Super important glacia. Uh but look at all the white space on the ice too. And now look at what edge will do. fills in everything. Wow, all those creasses pop out and um it's kind of amazing. And it's similar story in the Amazon where you can now start to see a forest emerging. Things you can do with that I won't go into but trust me forests are needed for habitat which are needed for animals which is megapora and we have orangutans in the edge proposal. Um we also have this fantastic capability to be able to bring all the swath together and u map at very high resolution along uh spatial resolution with a mega swath um along the coastal corridors.

[01:04:54]Um the ice well we've heard about the basil channels I already showed you. Um basil channels are just going to be amazing in edge. So you can't even tell that there's tracks under here because the edge data is so good. Uh we use gold for edge in the proposal because we're going for the gold standard science.

[01:05:09]Some of you know what that means. Um, right. So, we kind of went for that. Um, so the gold is under here. The ISAC 2 is in blue. Um, not not very good coverage.

[01:05:18]So much better information with um with the edge data. We're going to be able to understand the the the the pattern and the change change and the shape of the rifts and the and the interacting with the basil channels as they're forming um in a really really coherent way as edge is flying. Um, and the same over here again rift and how it's really well sampled with edge. Um, we also have baby penguins. Um, so yeah, sea ice, uh, again, it's really really great for picking out the, um, the leads. Um, much much improved, uh, sampling, um, improved lead detection and all the information that's needed for, uh, sort of CIS modeling. I'm going to jump through. I do have a movie, but I don't know if I have time for it. Uh, yeah, maybe I do. Five minutes. Um and this is basically showing you the targeting mode of the instrument. Um which is just we actually made this for the AGU meeting and we we uh ended up showing the region where AGU was held. U you'll notice a red, white and blue spacecraft.

[01:06:23]Um yeah. So anyway, I think I won't show this whole thing. Uh if you're interested, I can show it to you another time but not right now.

[01:06:33]Okay. But what have I done? What have I done?

[01:06:37]Okay. Um, so there's a thing at NASA now. It's all about Earth action, right?

[01:06:42]And so the data that we are going to collect by edge is what we call actionable. That means it does something useful for society. Um, it's kind of a commitment to and you might wonder how on earth did they get this selected right now? Well, this was the kinds of things we talked about because everybody needs to understand the height of the earth and how it changes with time. No matter what side of the aisle you sit on in politics, you need to understand this. And so situational awareness, uh national security, food security, resilience, all of these things, we had over 70 letters of commitment um for the mission. Um and we sort of argued that uh it will help the US but also the world um efficiently manage resources and safeguard our citizens. Um many many um incredible um applications here. Just look at this middle one, which is colorcoded by how quickly people need the data. So, if it's in a dark gold color, you need that data pretty quickly because flooding happens pretty fast.

[01:07:39]Whereas insurance and things like that, maybe you can wait a little bit longer.

[01:07:43]Um, but all of these um sort of agencies and outcomes and stakeholders will use the data eventually. High value to the nation. We talked about this yesterday.

[01:07:51]You need to be able to show uh return on investment for uh for NASA emissions.

[01:07:56]And this is a um the wonderful Jim Garvin who's a Da Vinci PI did this study for us um using an AI based approach to show us the return on investment as the data are sort of up the uptake in data um after the launch in 2030 which I think I didn't tell you all September 2030 um and so by in 8 years time the return on investment is modeled to be 50 to one which is a huge uh value okay so I'm nearly finished um this is the 50 years of laser alimmetry on a sort of full family tree. Um, starting with that Williamstown report going to the Gio set, all these branches split. We come down all the ones we know now. I set two Jedi. Here's Edge. Here is where it all fit. Crystal as well.

[01:08:38]Um, and I thought I'd throw in the timing of the ice the IGS meetings because that's kind of interesting. Last IS meeting, we didn't have I set two flying even. So, that's kind of amazing.

[01:08:50]Um, and by the next one, um, hopefully, well, here we are now. um because we have this gap of course um you know edge is like now about to be uh well we're starting to build it um in four years time it'll be launched so the next world cup will be actually ready uh to launch and by the time we have the next meeting here we should have been on launch for six months so you guys need to keep me in check on that one um okay so we've learned a lot this is our sort of we call this the knowledge steps um ISAT sort of was a pathfinder showing us a little bit of info and we're learning more we're learning more I love this way of thinking about it because we really sort of think about what we've gained and things that we can actually do with the data once we understand the processes better by observing it better.

[01:09:33]Um I have a poster on this that you can look at more. So I'll just wrap up um with this. We need to be able to um like tell the community the work that we work on like right this is so important. We are very uh lucky to work in the field that we that we work in and we need to communicate our results. This is an incredibly important statement by Jane Lchenko. If you don't know her work, please go and and have a look at some of her papers because she talks about the sort of stewardship that comes with being an earth scientist. Um I am going to quickly say don't get distracted by the false promises of geoengineering. Um if you want to see um a paper on that, we have a paper uh led by Martin Seager that came out. But this is there's a poster outside which shows what I call the action wheel. this is kind of the things that the community kind of probably needs to focus on in the future and these are the distracting things like diverting attention and all these things. Um this is kind of the the where I think personally the value is. Um so we can argue about that but I'll finish with this which is a summary. Um obviously we've got this incredible record. We've learned a lot about the earth's vital signs since the 70s. Um, we've just had a lot of people involved in all of this, collaborations and missions that have been planned for years and led to some incredible data sets that have all just led to this advance of understanding. Future missions will probably hopefully improve things even more. And I'm going to end with a thank you. And please tell me what the score is. [laughter] I should say thank you to everybody for everything because you know this is all a massive team effort and friends, family, colleagues, you're all amazing and just keep going because you know we're doing important stuff. So yeah, thank you.

[01:11:33]>> Thank you very much.