 I, for everyone who's here, thank you for attending and thank you for being here in like American time fairly early. CSDMS, the Community Surface Dynamics Modeling System has been hosting these webinars as a resource for the community. And today our speaker Anders Levermann, who is at Potsdam in Germany, sort of straddles this really interesting place where he looks at ice sheet dynamics and ice ocean interaction in modeling world and a lot of like of his students and collaborators also like work on like data sets etc. But then with a very clear perception of also thinking about policy implications sea level rise and so a lot of the research that has been going on in Anders. I guess like two decades already because it's been such an important topic over the last 20 years has been on like how do we bring this information about uncertainty and sea level rise and ice sheet dynamics to like things that are usable for policymakers and has been very successful with that. And we thought this was like really a timely topic to discuss again, since like quite a bit of unstabilities in the Antarctic ice sheets are being observed right now. And so it's interesting for for those people work on surface dynamics to sort of hear the perspective of what can we expect there. And what are sort of the big questions that's that community grapples with. Anders has a interesting position at University of Potsdam as head of a large Institute on like complexity and of climate dynamics which is like a far larger topic and some of the things that go on in his research group go far beyond what he will be talking about today. So with that, I would like to give the shared screen, I guess, in this case to Anders Levermann and thank you so much for joining us. Yes, thank you very much for having me I'm going to go through a few papers that we did on Antarctica and I'll always try to, you know, highlight obviously who are the co-authors because they are doing most of the work in most cases. So, I'm, I'm, I hope that that this can be of some interest. I will first go for long term sea level rise contributions from Antarctica and then go to shorter scales and I will actually switch from purely numerical simulations to a combination of some relations with so called a linear response theory in order to, you know, capture the uncertainty that's there and I'm really, I would really happy if we could have a lively discussion afterwards because as was mentioned before and I'm having the research department of complexity science and we are at least half of my work is on the propagation of extreme of this economic signal of extreme weather events along the global trade network, a complex network. And we, we are really in next to trying to do good research we're also interested in how to communicate this to the to governments to industry mainly and to the general public and this is something that's very interesting to discuss with, you know, for example you. But let's first go through the, the physics of the, of the talk. There, we, two years ago, they allowed us to have the cover of nature with our paper had by Julius Gabu is also listening in here as I saw earlier. The, you know, who was a PhD student of Ricardo Winckelmann on the histories of the Arctic ice sheet and I don't know how familiar you are with these physical concepts like histories and histories is kind of a memory of a system so if a system is undergoing a change due to a change in the internal perturbation or an external in the boundary conditions. And then, when you go the same path in the change in the boundary conditions backwards, again, and the system follows a different path than you have is to uses, and you can find this in the Arctic ice sheet similar to the agreement ice sheet. But let me first very briefly mention what kind of model is used here. You can see an article is really big right it's as big as North America from Mexico to Canada. It's a continent in the southern hemisphere around the South Pole and it has an ice sheet that's covered by the content is covered by an ice sheet of up to 4000 meters in height. At Pula and a jet ground from Alaska University built a model that was quite special in 2009 they built a hybrid model with two shallow approximations of the flow dynamics or the ice flow dynamics the ice flow dynamics are actually that the ice is actually not modeled as a solid because if you only you would only model it as a solid if you're interested in how it sounds but you don't want to know how it sounds under global warming or under the change of climate over the last millennia or even millions of years you are interested how it evolves its surface under the under change in boundary conditions such as warming on the surface warming of the ocean. And therefore you you model an ice sheet as a flow as a fluid with a highly nonlinear flow law. And there are two shallow approximations for ice sheet dynamics once the shallow ice approximation which is generally used for the ice sheet that is grounded that is, you know frozen to the bedrock. And then there's a shallow shelf approximation which is generally used for the shelf, which is ice that is floating on the ocean and I said floating on the ocean. And Euler and Brown had the idea that you could actually use the shell shelf approximation for the fast flowing ice streams in Antarctica, or actually on in Greenland, first of all, we kind of in demand during your PhD that she did with in my group. She adapted this model to Antarctica from Greenland to Antarctica. And then we did a number of changes over the years and we are co developers now together. Let's go up this model. And just to show you this is really an old similar in old animation just to illustrate, you know how these, these are snowflakes, you know, flowing along the flow lines of the of the model. And just to give you a hint of that we do in America simulations of these kinds. A typical sheet shelf system in Antarctica. You see a number of points here this is is you can see the shelf that is floating you can see the sheet that's grounded. You see the bedrock where it actually is grounded on a nice sheet and I don't know how familiar you are with these. The sheet is generally, you know, generated created by snowfall on to land and then it slowly is compacted to and to ice the snow and then, you know, it's growing over millennia, tens of millennia, even hundreds of millennia. This is what happened to Antarctica. Then this ice is flowing into the ocean and its own gravity and its own gravity. It's the pressure that is caused by by its own weight. It's flowing towards the side, following these, the so called Stokes equation, which is then which can be approximate by the two shallow approximations that I mentioned earlier. And since the the bet on it on which it is grounded generally eventually will become, you know, ocean floor, it will go very deep down and that means eventually the the ice that is, you know, generated on land and flowing into into this direction will become too thin and will not be supported by the ground and this moment becomes ice shelf and due to Archimedes principle, it has already displaced all the all the water in the ocean that that late that it will take later take it will take the place of the of this water so there's no more sea level rise after the ice has crossed the so called grounding line that you see. So this is, you know, this is just to give you some hint of what we are modeling and now I'll take a bit of time to show you the history. This is a relatively complicated figure, but what you should see is what you should concentrate on first is there's sea level the sea level equivalent of the ice volume in the Antarctic ice sheet plotted here on the y axis. You can see that, you know, at and on the y and the x axis there's the global mean temperature change, compared to the pre industrial and you see here this is the zero line. This is the regional surface temperature that is directly translated into global mean temperature change. And you can see this is the point where we start us know well that is where we are currently this small triangle here. The 55 meters of sea global sea level rise equivalent is stored roughly on Antarctica. And if we now increase the temperature of the Antarctic ice sheet around the Antarctic ice sheet then we follow this line here that the upper blue curve. The gray lines here are different model setups and middle different parameter. Set your age different parameter settings for the model. And if we do this gradually then we are going through quasi equilibrium states and we follow the path down here so and that at a temperature of about 10 degrees 11 degrees of global warming will have eliminated the entire Antarctic ice sheet basically at 14 where we had zero. And if we go back now starting from up from a situation without an ice sheet. And we go down down with the temperature. Again, then we'll follow another path and that is what's actually called the history is here that there's that we follow another path. A different path from the one that we actually followed when we went down and the difference between these two path is as the so called history is. If you really let the model run we change the temperature here very gradually. And you can see here the different speeds by which we change the temperature so one in a thousand one in 10,000 degrees Celsius per year. If you will let them let the ice sheet run into equilibrium you actually get the triangles here but there's still a history is the difference between the upper branch in the lower. And, you know, I would like just because it's nice to see I would like to show you this animation of. The simulation of one of these simulations, you can see at the top, the ice sheets and the ice thickness at different places so we're increasing the temperature on the on downwards here we can see the temperature increase over time and the blue curve here is on the left is the sea level contribution, and the purple line here gives the current seal ice loss in gigatons per year you can solve you can see that initially, and we'll start this again. Initially, the ice sheet is, as it is at the moment, fully intact the Western Arctic ice here the Eastern Arctic ice sheet, and at around two degrees of global warming. Now, you can see that the Western Arctic ice sheet becomes unstable and is this charging all basic you all its ice, all the ice that's that's grounded below sea level into the ocean then. The Eastern Arctic is quite stable for a long time then. Another instability occurs at Wilk is based here in Western Antarctica and, and then at a warming of about seven to eight degrees, we see another purge of ice, where the so called surface elevation feedback that you, there's also responsible for the. The amount of the green and ice sheet kicks in, and then basically all the ice is lost into the ocean. Now, I want to highlight here that in another study we using the same model. We associated these warmings with the amount of carbon that we put into the atmosphere and the basic statement is that if we burn all the coal that we found on the planet oil and gas at relatively small contributions the coal is the big part. If we burn all the coal that we found on the planet, we'll get an ice free Antarctica and thereby an ice free globe. That'll be 15 roughly 15 degrees of global warming. Now, if we go backwards if we follow the histories is the other, the other direction, the downward the lower branch, then you can see there's only slowly in the trans Antarctic mountains here. Ice is slowly developing by snowfall that is accumulated to become and slowly in ice sheet you can see high elevations here in the center of East Antarctica is also growing. And then there are temperatures where it suddenly goes goes up but overall the growth is more gradual and takes a longer time. I just let you digest this for a moment because it's. I'm talking very quickly. And then might be too much. Also, we want to see the full ice sheet. The temperature has remained, not at a temperature of zero degrees as above the present day, but actually at a temperature of pretty as well, but at a much lower temperature of about two degrees and negative two degrees or negative three degrees. Zoom into these two instabilities I mentioned this earlier the so called marine ice sheet instability is very important, especially in Western Antarctica because some research of 2014 indicates that this disability might have been already triggered and that we are now seeing the unfolding of this instability whether that is true or not remains to has to be further investigated, but our current state of understanding is that we have destabilized Western Antarctica in the Amazon sea. Now, you know some policymakers might think was that, well, the damage has already been caused so we don't have to reduce global warming because we already caused a sea level rise the instability in Western Antarctica and we'll get a sea level rise of at least three meters from that. Obviously, this is not the case that first of all it's not only sea level rise, we need to reduce carbon emissions, but obviously there are other and they're also for this, even with respect to sea level rise, East Antarctica for example has an instability. The same with the same dynamics in Wilco space and as you can see on the right hand side. So this is a numerical modeling and we can talk about this for a while but let me briefly indicate the implications of these long term results because the response both the response of the green and ice sheet and of the Antarctic ice sheet as well as the oceanic thermal expansion that is increasing sea level worldwide is on a multi millennial on the multi centennial to multi millennial timescale. So the sea level rise that we will that we have been seen in the last 100 years of about 20 centimeters and the sea level rise that we are expected to see of about of the order of the meter. And in this century is by far not everything that that that we have already caused. And that's why we introduced this the notion of of so called sea level commitment which is kind of the template the sea level that you will obtain in equilibrium on the long term when you elevate the temperature of the planet by one degree on the x axis here two degrees three degrees four degrees. This was in the last sea level in the last sea level chapter of the, not the last sea. But the one before that where was a co author. And you can see on the on the right hand side the different contributions. I mean, from the different components in the upper corner on the upper right hand side you can see the contribution by thermal expansion of the ocean. These are different, so called earth system models of intermediate complexity, and they give an immediate contribution of 0.4 to meters so roughly half a meter for every degree of warming you can actually the dots here in the center. These are not the median values of the model simulations, but these are the values that you get if you just take the observed temperature and salinity field of the world ocean and just add one degree everywhere in the ocean. And that gives you a very clear nice line, which is what happens to be at the center of the mark simulations. So one is the contribution from mountain glaciers these DC meters rather than meters so it doesn't really take a plain important role on the long term. And this, the center part here is in panel C you see the Greenland contribution really in equilibrium you can see here the step function that is caused by the so called surface elevation feedback and the histories of the Greenland ice sheet. This step smears out into into a continuous function without a step. If you take any fixed time frame so if you ask what's the sea level contribution after 1000 years or 2000 years or 3000 years. You will always get a smooth curve and not a step function only in equilibrium you get a step function, and the reason is so called critical slowing down near the threshold so the closer you are to the threshold, the slower the ice loss actually occurs. However, you can see the tipping point of the Greenland ice sheet is around half 1.5 degrees Celsius of global warming there's an uncertainty here obviously but somewhere in the Paris climate agreement range is this tipping point and the fourth contribution here is from an octica this is actually these are actually simulations carried out by David Pollard and what the contour in their nature simulations in the nature paper, I think 2008, where they can simulate the last 5 million years of an octica so it's a different model, a different set of simulations than we just presented but it's fully, it gives the same numbers as the history simulations that I just showed you which is quite, you know, quite nice. So we can actually, and that was one of the reasons why we consider the commitment of the sea level commitment, we can actually. In some cases you can make more precise statements or less uncertain statements about the equilibrium and thereby the long term evolution. Then the short term that's that's something that is interesting to discuss interesting to reflect on, because we are actually. It's a different approach to ask, what is the amount of ice that will survive a warming of one degree two degrees three degrees, then it is how will this evolve over time the evolution over time is much more complicated. So just a small side note with Ben Matsuyo and we computed how much the world cultural heritage will be underwater and at one degrees two degrees three degrees and four or five. You can see this here and you can also see that the number of World Heritage sites by the UNESCO will be that there are underwater is actually saturating, you know, somewhere around three degrees because everything that's near the coast is actually flooded. So also see in Potsdam or the Versailles castle of Louis Catois will not be flooded it's in the center of France. Now, a big question for policymakers and for adaptation purposes is not is not just how will see level evolve on the millennial timescale or even the centennial timescale, but how will how will the next decades look like. That is difficult. And what's what's important there to recognize is that what I just showed you were a number of simulations but a very finite number of simulations carried either carried out with either one numerical model and different parameter settings, or with an handful of models. But, and one set of boundary conditions that, however, that there obviously is large uncertainty, both in the model between different models between different ice sheet models, but there's also uncertainty with respect to the forcing. There's uncertainty with respect to how the global mean temperature responds to CO2 emissions, how this temperature is the global mean temperature is then transported to the southern ocean to the world around Antarctica. How this is transported underneath the ice shelves where it can actually hit the ice sheet, and then how these the ice sheet will respond that's again the ice sheet not send in order to capture these uncertainty we carried out. So, in a comparison project, and that is now tackling this is now something that that I did with the linear response theory and to this end I would like you to revisit linear response theory very briefly. The approach of a linear response theory is that you take a system and you put up the system with a delta function forcing. For example, the oceanic melting would you you increase the oceanic melting and around Antarctica for a short period of time and then you ask what how does the ice sheet respond to this. For example, if you have a table at the moment in front of you, you can knock your hand on the table. Not your hand, not your head please. I hope that my talk is not such that you want to knock your head on the table so your hand on the table and you will hear a sound. Now this is actually the response of the table to the delta function forcing of your knocking. The table will have a very specific response and if you hit double as hard with your with your knuckles you will get the same response only with a higher magnitude. And that is the linear. This is the assumption behind the linear response theory that you get a linear response not in the time evolution time evolution can be complicated as you can see here on the in the lower but in the linearity assumption is actually in the idea that if you if you if you're forcing is twice as large or three times as large then your response will also be two times or three times as large. So what we did now. We actually I ask. I think more than 20 ice sheet models. Well, I think, but sure 19, I don't something like this to to do one experiment and that is not to put a delta function warming or delta function melting underneath their ice shelves in Antarctica but actually to do a switch on experiment so to switch on the basal melt of one meter or actually of eight meters per year underneath the ice shelves and then observe the response of the ice sheet for 200 years and just report this number back to me. I can imagine that if I if I do a delta peak here I can get the response function if I do a switch on forcing here. I get the time integral of the response function and you know, by time, by the derivative of the of this of this result I will get the response function itself just quite easy. You can see so and and and once you have this response function you can actually and that is the big advantage you can actually compute under the assumption of a linear response, you can compute the response of the system to any temporal evolution of the forcing. Through this convolution of the forcing M of tau and the response function with a time delay and an inversion. This is nothing else but the super the linear superposition in the limit of infinite of infinitely small time steps. You know, of two different forcing to forcing time series. And that's what we did we did this switch on experiments for all the different models in five regions that you can see here. The Amundsen sea region is the one where we believe there's an instability that has already been triggered. There's the Antarctic Peninsula which is relatively small but still, you know reaches relatively far into the north so it's relatively warm, you know this Argentina here so it's even hot in the region. I'm just kidding, but it's, well, and there's there's the well see here with all the wonderful penguins that penguins everywhere, but a lot of here, it's actually a little penguin. I think the name of the region, then this huge bigger part of East Antarctica and then the West region here with another entrance to the Western Arctic ice sheet. And then we did different steps I will, I'm giving you here the example of the linear response of the ice loss for the Amundsen sea sector from these are I can you can see it 16 models like I could have actually memorized that it's 16 models and we did a linearity check it's not perfect but it's pretty much all right. And this alpha here which kind of gives you the you know the deviation from the linearity assumption, the further away from zero it is the, the, the, the worst it is. And we use this, these numerical simulations and fed them into a procedure in order to be able to capture the uncertainty of the sea level projections that arise from the different different sources of uncertainty. First, we have four different socioeconomic scenarios, these are just the carbon, the CO2 concentration pathways that have been used for a while now. And the sort of different socioeconomic assumptions. These are four choices in our case here that's RCP 2.6 all the way to RCP 2.6 is to do one here, all the way to RCP 8.5 in red. Then we used 600 emulations of the global mean temperature response to this. RCPs these are the same that are used by the IPCC that arrived from the so called magic model, which emulates different CMAP global climate models. This gives you an uncertainty in the global mean temperature. And then we, and then we used the, we use a number of CMAP simulations by by by, I think, nine ocean models. It's been a while and I forgot how many 14 or nine ocean models, a couple climate models, where we scale the temperature change in the, the temperature change in the subsurface ocean around Antarctica in the different basins. And we scale this with the change in the global mean temperature of the model. So there will be a time delay, you know, between the warming at the surface of global mean temperature in the surf global mean surface at temperature change, and the subsurface oceanic warming in the different regions around Antarctica. And as you can see in example, this is how the, the red the uncertainty in the red line here in the global mean temperature translates into a warming signal underneath in the Amundsen C sector in the subsurface at 200 meter depth. So it's even a bigger uncertainty here but also different magnitude because not all of the warming signal really reaches the subsurface in at time. We now used an observed interval between of sensitivity of the basal melt underneath the ice shelf, given a temperature change outside of the ice shelf that is in the in the region that this warming here and in the region where this warming occurs. And this is quite a large interval between seven and 16 meters per year of extra basal melt for every degree of warming out of the ocean outside of the cavity in the subsurface around Antarctica. So now we, we have the forcing we have the M of tau that I showed you earlier now we have the forcing that that we can feed into the linear response functions of the different models in the different regions of Antarctica these this is now where the ice sheet models comes in come to play. And this will then translate into C level response from this region from this model from this and the equations from this model for the future. And once we actually compare them to observations that is actually quite, quite good. Surprisingly good the contribution of an article is, even though it's not probably not well, you know, it's not for good reasons but the, the contribution over the last decades that we observed from an article is actually comparable to what these, you know, the models gives is how some models don't contribute in our industry sector at all. Some contribute quite strongly you can you know pick your favorite model. This is Belgium. This is England, you know if you want to attribute a country to it, you know, this is France, which is not a country Germany. So we have three for his models all different versions New Zealand, and so on and so forth. And if we take all this together then. Well, this is complicated and you don't have time for that now. But if we take all this together this would be get for the different RCP scenarios. So, the different aspects to these sea level contributions from an optical. First of all, there's surprisingly little difference between the different emissions scenarios and that is very simply due to the fact that there is inertia in the system as inertia between the temperature and the atmosphere on the planet. And then there's a time delay for this to reach the subsurface of the Antarctic of the Southern Ocean around Antarctica. Then there's a time delay of the ice sheet responding to the oceanic forcing. And that is why there's actually the sea level contributions from an article. I actually not as far apart for RCP 2.6 and RCP 8.5 as the temperature changes are in the left hand side you can see here the sea level change that's also an integration over time obviously of the sea level contribution which you see on the right hand side and in the sea level contribution that's the rate of sea level change in centimeters per decade. You can see already a bigger difference between RCP 8.2.6 and 8.5, especially then under 2.6 you can see some kind of saturation occurring here in the contribution, the annual contribution to global sea level rise. These numbers that we obtain from this are similar to other estimates, especially if you look at the median contribution so let's have a look here in the 2100 median contribution for the different ice sheets you can see something about 13 to 17 centimeters, which is also what the previous, not the last one, but the second but last one of sea level, sea level chapter of the IPCC came up with. The big contribution or if there is a contribution then the relevant contribution of this exercise here is to look at the uncertainty because that is what we can gain here, you know, you generally have the problem that if you do a model contribution then you have one forcing that you apply to a number of models. If you do a parameter study, then you have different for things different parameters that you apply to one model. Here we try to bring these different uncertainties together and that's why the important condition here is that under RCP 8.5 you can actually have a 5% chance that you end up with 58 centimeters of sea level contributions from Antarctica, which would be a very high number. A number that has not been obtained by Merkel modeling in either any of the other simulation apart from if you if you add the marine cliff instability by political contour, which is basically open and I really, I really appreciate this effort. I mean, the whole research line of research it's very important, but we're currently still struggling a little bit with with constraining these marine ice cliff instability. And yeah, and with this I would like to actually close my remarks and invite questions because I went through quite a bit of stuff and. I hope. I didn't lose you and hope that you have questions. Thank you so much on this this was incredibly interesting and I know that there'll be like a bunch of questions from the audience so I'll open it up I think we're a small enough group that we can. People can unmute and ask others a question. So, please do. This is Bob Anderson. That was a wonderful talk thank you very very much. I was inspiring to see the clever use of models and response times and so on. I wonder from now your decade at least of experience with these big models what you think the part of these models that we know the least. Where is the research opportunity where should we be focusing as a community on how these ice sheets respond to global change. I think you know there's there's all this as a natural. My prejudice I'm a physicist right so my prejudice towards physicists is to myself kind of is that we always try to solve the, the most difficult problem that we can solve. So a natural approach is to get better at simulating demand the ice dynamics. Because we know how to do that right we have the Stokes equation at the shallow consummations we get you know we can do this better and better however I think in ice sheet modeling the big problem is the physics that's not inside the models yet. And one aspect and that is again very complicated and then that's why it's kind of annoying is the basal conditions right we don't have a very good grasp on on how the ice is, you know is sliding or flowing across the base of the of the of the rock, and that's a big thing the other is that the, the fractures inside and a nice shelf in a nice sheet and the associated buff pressing associated with that that that's also the whole Milange world, right. And these are the two things where and then obviously the cliff instability is is a big unknown but at the moment we have shelves everywhere so I don't know what that's so important. How do you, what's your sense of how we're doing with, you know, the mental response to the changes in load. Well enough to that that's not an issue. It's something that I don't know. And that's why I had, you know that I have a natural tendency to say oh someone knows that. But if you tell me that we don't then then I would believe you. I feel that that that's important to take into account it's it's in Pism it's in the parallel sheet model right, but whether how well this is done I don't know. Okay, well thank you very much. We have time for another question or two, or even more. As a match you have your hand up do you want to speak up. Yes. First of all, thank you for putting this together and the brilliant presentation I loved it. My question is regarding the, you know, you show like 14 different models. You took the Amundsen region to as an example and my question is after that one yeah particular this one after in your next slide you put something. I guess like, as a result of the model into into comparison project you like, like guts or achieved a single result. Or that would somehow get the, I don't know, Michael, how did you do that how did you get one picture that this one out of 16 different models. Is it just the average of the. It's just the average. I, well it's not it's not really the average but it's, it's the median and that I put all the models together it's like, you know, it's a huge ensemble because we do like 50,000 computations, combining always one atmospheric model. In a sense that's the global mean temperature evolution one oceanic model. One selection of the observed sensitivity melt sensitivity and then one ice sheet model that gives you one curve, and you do just 50,000 random combinations of these, and then you get this right it said this is really straightforward. What's, what's at the core is this this response function part which is quite nice actually and it can be applied to a number of situations we can do this for the ocean. And so we did this exercise here and with with Riccata and climate dynamics way, you can actually derive an analytic response functions for mixing for for one dimensional diffusion equation. So it's, it's kind of a nice tool. Thanks for the answer. Albert you have your hand up. Yeah. So let's see thank you, thank you and there's that there was great. What, what I'm missing so so or, I think you touched upon this but I wonder if you have more comments about this. So I think somewhere last November or December wild came out with a paper about to age glacier, and it instability there and therefore sea level could rise. I think, within several decades or maybe two decades or something by another point six meters. And the slide actually where you're, you're right on now. I don't see that back in that, you know, as a as a response as a in this sea level change over time, if, if you look at you touch a little bit more upon that. No, we don't, we don't get these kind of numbers not not not with this with the release kinds of rates fully agree and and that's what I kind of meant earlier. We are still with them when we use the ice sheet models then we are constrained by the physics we have in the ice balls and that means we have no. We don't really have a good grasp on the, on the whole fracture world and that includes the carving dynamics, and we don't have a good grasp one on the basal conditions and, and you know, and observation lists have have a very good point when they emphasize this and say, Well, if that is fundamentally different from what you are actually modeling then this could go much faster. They could also be slow obviously quite but but generally the obviously the risk is that it's faster. There is something there's a puzzle that is actually related to Greenland that I think still is a puzzle. There was a paper by York Schaefer and colleagues, some years ago in in a nature where he had worked on a bill William method. And I don't understand it really but but in the William isotope method to determine when the base of Greenland in a specific location where they had drilled through the ice sheet and all the way into the bedrock. And this was how long over the past two million years so this was ice free. And his conclusion was that either it was ice free before the ice ages. Yeah, before the this this period, which was two million years ago so or it must have been ice free in almost every integration of the past million years. That means the integrations were typically to 1000 10,000 years long right so and our integration is now 10,000 years long so that I don't think that even if the integrations were slightly warmer than a present day I don't think that any ice sheet model that I know of could model an ice. I think it was a great meltdown of Greenland within this period with this kind of temperature increase, and that indicates that there's something wrong in the models. There's either something wrong with this bill your measurement. And I haven't followed up on the on the discussion there, or there's something wrong with the ice sheets, much ice sheet models. And yeah, that's, that's a big, big thing. Okay, thank you. Any other other questions still. And Rina, I think there are a few questions in the chat. Oh, I've been looking at the hands but maybe I didn't look at the chat so much. Let me check. Thank you. The first question by Santiago, I can answer. Yes, they are in there in the ice aesthetic adjustments are in there. The geothermal flux is not. It's not changed at least. And then there's a second question by Kobe that is a little further down into the whole climate system. Kobe's asked, are you reading it to understand. Yeah, yes, yes. So the question is whether there's whether we have included any kind of carbon sink measurements would know we have not not at all right there's not even. We don't have a cycle in this whatsoever we have. We don't even have a feedback on the global temperature or so we have a feedback on the, on the local temperature in the sense that if the ice goes down and elevation, then it goes into a warmer atmosphere and thereby is this is so called melt elevation feedback that also is responsible for the tipping of Greenland. But we don't have a, you know, any, any loop to the concept. We said that you have your hand up. I did. I'm not sure. I'm not sure if he just answered the question but it's sort of how to do with. Yeah. I guess feedback to temperature feedbacks how they're incorporated into the scenarios. I mean, is there any way to use like just past evidence from past. I guess you'd have to use past models of climate change to see how warming would affect temperature and. But but I mean how does air temperature, how do air temperature feedbacks affect the scenarios. The carbon cycle feedbacks and the air temperature feedbacks. Well, the carbon cycle feedbacks out in this because we prescribe the CO2 concentration in the atmosphere that's just a given so all the results that I'm showing you if I, you know, if I, if I do show you this that is given the RCP 8.5 carbon in the atmosphere, it's that because the RCP 8.5 is, is, is just giving a CO2 concentration pathway. It's not a carbon emission pathway. So the, yeah, so that's, that's number one. However, the temperature feedbacks they are included in, in the simulations through the different, different the uncertainty in, in this part here. Okay. Okay, and that's quite, quite a large range. Thank you. Are there any last questions. So, like, one more question. I think there's inspiring, or when like a modeling community and in your case it's like the ice sheet modeling community comes together and does does these like model into comparisons. Like one that's inspiring for other modeling groups right and so like it's maybe something that you can elevate to like oh we're doing, I don't know landslide modeling and modelers come together and do these like model into comparisons, and sort of the strategies that one group uses and another group uses is, is something to learn from to you. And so I thought by sort of following along with this perturbation that you imply in all the models and then see what are all the outcomes. Is it worth while and possible to look the other way then again and see like these are models like prism has dynamic calving in its like outlets and then some of the others may have a different algorithm for dynamic calving. Is it also possible to reason backwards with an experiment like this where you see like those models that really don't match the data then seem to be missing in these in these areas just because they don't incorporate or is that too far fetched. Well, that that is that that might be possible and I'm not sure whether that is actually a good, whether you would want to use the linear response theory for that. You should then directly compare to observations I would say you would have to go for this way right. Yeah, I was thinking the slide that you were showing with the like big panel that had the different countries different. So they have their realization and then they have in response to this perturbation. This is how much sea level rise we would get but you can for the first part of the time record, you could like compare to what has been happening. So then you go back to observations. Yes, that's true. And but we have to be careful obviously because, you know, as I learned from my paleoclimate colleagues, there's always the question did you get the right answer for the good reason, or did you get the right answer for for a bad reason and and we we know where the most of the sea level contribution came from in the past over the past decades, since we have satellite data, and that is the rest of Antarctica so you could actually go back and really ask if if I give it the right forcing in the in the right region do I get the right response there. But you would not be able to say much more about the rest of an article because you don't have a response there and what you could do is say, Well, I shouldn't have a response than also the model. Right. That's something you do. But you know if you're interested in modeling comparisons, there is something that mind. I mean, I just came to mind we have. Well almost 10 years ago now. The Potsdam Institute has started a model in the comparison for impact models and impact models is try to write, write variety of you know these are flood models and agricultural models and so on. So they have much less rigor than the physical models that we have, which means that they have to be very careful on the epistemic part of modeling. What is it you can actually say, using this model, and they have a model in the comparison already now in the third round. And they've really learned a lot, because it's a it's a highly heterogeneous modeling community. So if you are interested in model or if we are interested in modeling comparisons that that that might actually be a good link to do to learn from them because they really have quite different approach that they are more challenges. But they learn a lot from the physical community. Right. But I think they mature now enough to to give something back because they really have different, different problems, especially with respect to comparison to data. Yeah. I think that we that people are slowly signing off and questions are having been answered. I wanted to thank you Anders for like a really interesting talk. I think a lot of us feel like a bit more confident when friends will ask about the dark guy sheet and the instabilities there and what what sort of the science is telling us right now and that's like a big function of something like this. But also these insights and like what are like the current techniques that we are using and what are the like sort of gaps in the knowledge still so thank you so much. Yeah, thank you very much for having me. Thank you. Thank you.