 As we know the future is inherently uncertain and scenarios or tools that have been used by the research community for more than 30 years to help think about what the future could look like understanding it's not one future it's a whole range of possible futures. And to be able to inform decision makers we need to look at that full range of possibilities. Well academies were critical to this process there was a meeting early on in this process I think it might have been in this room but Brian you might remember better than me. I was during snowmageddon in DC, and we were all sitting in the room intensely talking about scenarios and developing this new process. And I think it was a great offer who was the predecessor Jim ski rushed into the room at one moment and said they're closing the airport and ran out. It was, it was dramatic. It was quite a dramatic meeting but it is a process that's been going on for more than a decade. And we do have a slightly different approach today than what's listed on some of the agendas. We're going to start with Brian O'Neill who's been absolutely critical to the process of developing the shared socio economic pathways. When we look into the future, as I said inherently uncertain. We want to look into the future in ways that we can assess the results across regions across sectors. And scenarios are used to look at developing projections where you do have some consistency and you can then aggregate the results. We want to look at the risks going into the future. We want to look at the responses the effectiveness of those responses, and we need to integrate. We need to integrate within a region we need to integrate for a sector across the world. And so these are tools that are used for those processes. These studies that have tried to disaggregate where are the major sources of uncertainty in our projections. The smallest source of uncertainty is in the climate modeling. Although that's where the bulk of the funding has gone is into the climate modeling. The second source of uncertainty, which is larger than the climate modeling is the impact modeling of how do we understand what kinds of risk could arise under what conditions, when we have the what ifs the major source of uncertainties what we think about in terms of socio economic. How do we understand human behavior how do we understand policy making and governance, and those critical factors that will determine the magnitude and pattern of risk. So building on the work that was done for the special report on emissions scenarios this process was started more than a decade ago, with two major elements are supposed to be three but mostly there's two. One are the representative concentration pathways that talk about emissions going into the future. And the other are the socio economic pathways that talk about possible ranges. Brian's going to set that up for us first, and then we're going to hear from Jim ski the co chair for working group free of the nearly completed ar six congratulations Jim on getting the synthesis report approved that was fantastic. Well then here from Wolfgang Lutz from IASA talking about demographics and demographic change the drivers thereof. Heinrich Carlson is going to talk about some of the work that he's done on more downscaled kinds of approaches to using these scenarios were set up at a global scale. Primarily because there was really no funding for all of this and so set up at a global scale and he's going to talk about some of his work in communities and then Casper cock is going to be talking about the work he's done in Europe. Also on downscaling. Another quick comments is you'll notice there's not a lot of diversity in the speakers. That's because number one the major funding source has been in Europe that's why most of the speakers are European. Also, there's been an effort over the years to try and increase diversity in people engaged in scenarios. There was early funding from the State Department to try to increase diversity. It's a little challenge because with limited funding, we're asking people to volunteer a lot of time. And as you know researchers in low and middle income countries just don't have the privilege of being able to do so. So with that as a stage is there's something else I'm supposed to say here Steven, just get started. Good to go. So Brian, you're up first. Everybody has about 12 minutes and then we'll have five minutes for clarifying questions, and then we'll have a longer discussion at the end. Brian, take it away. Thanks Chris and let me share my screen here. Okay. You should be able to see that. Again, for that introduction and as Chris said I'm going to talk about the SSP RCP scenario framework, introduce it, talk about what it is, how it works. I think many people will be referring to it so we thought it would be good to make sure we're all on the same page before getting into deeper details. This may be familiar to some of you, maybe to many of you. But again, probably not to all. So, so in the interest of starting from a common base. Here, here we go. Let's start with the the RCPs. The RCPs are a set of what we're at the time pre existing concentration pathways that were drawn from the literature around the year 2010. There were four of them and they were intended to span the range of scenarios in the literature at that time, and that range is indicated here in gray so you can see they, they do span that that full range. So those concentration pathways were used in the CMIP five modeling exercise to produce earth system model simulations, which of course produced all kinds of spatially explicit earth system variables. This is showing here that the global average temperature outcomes but the full set of results were then available for use in studies of impacts or adaptation or mitigation. So that's, that's the RCPs these climate futures. The SSPs or shared socioeconomic pathways are a set of five societal futures. And these were produced to provide the important societal inputs to to integrated studies and they consist of two types of information, qualitative narratives that is text descriptions in broad terms of the logic of how the world may unfold in the coming periods along several different dimensions, as well as quantitative elements at the national level for a number of key variables population GDP, urbanization education. You see here there were five SSPs that were developed and you might ask, you know, why, why these five and how do we know when we've got a set of scenarios that we want that's sufficient. Well, the, the idea is that at the beginning of the process. The point of the scenarios was defined upfront and that was decided to be that we want to span a range of uncertainty, and we want to span uncertainty in two dimensions. The aspects of society that make it harder or easier to adapt to climate change and aspects of society that make it harder or easier to mitigate. So these were explicitly climate focused and climate response focused. And so the way the scenarios were then the SSPs were then developed to fill different parts of this space. So SSP one is in the lower left corner, where it's a world that, according to the way that many of the various social demographic economic trends evolve, it's a world that has relatively low challenges to either adapt or mitigate SSP three in the upper right is the opposite where those challenges are both high. SSPs four and five are scenarios in which one type of challenge dominates the other and SSP two is our middle of the road scenario. So the way the SSPs and RCPs are brought together are in this, this sketch of the overall framework here and the, the point of this framework is that it's designed to facilitate the production of integrated scenarios and studies studies that bring together the societal futures and the climate futures to understand impacts potential adaptation potential mitigation. So that's why that's in the middle. That's the point of the whole framework is to facilitate those kind of studies, the elements arranged around the outside circle, you can think of as ingredients basically to a recipe for creating those integrated studies. It can be combined in different combinations, depending on the nature of the study that you're doing. So at the top you'll see the RCPs and SSPs, which we just talked about the RCPs are concentration pathways again, they, as we said, were run in the same at five exercise to produce climate model simulations to use in integrated studies. The SSPs are the societal futures. Important to point out here is that the SSPs by themselves don't include climate don't include climate impacts or adaptation or mitigation. They don't include these types of policies, you can of course combine policy assumptions with the SSPs to look at mitigated futures or adaptation, and to help organize policy assumptions there are also a set of so called SPAs or shared policy assumptions that are available for the community to use, to use as one of the ingredients in their analyses if they'd like. Excuse me, so that's how these different elements are brought together for integrated studies. Now you see at the bottom right branch here, there's one more feature which is that the SSPs themselves were used to develop new scenarios of emissions and land use and concentrations in integrated assessment models. And those emissions and concentration pathways have already been used in the next round of climate modeling the CMIP-6 exercise to produce climate model simulations as well. So at the moment you can combine societal futures with either the CMIP-5 or the CMIP-6 climate model simulations, both are now available. In producing these integrated studies it's been found by researchers that oftentimes it's necessary to extend the SSPs to include information that was not included in the basic set that came with the original SSPs, the narratives, the population GDP urbanization scenarios. A lot of times you need additional information and so the research community has produced a lot of it that then is available for other researchers to use in their own studies. So some examples is that income distributions within countries have been produced for example to look at issues of climate change and poverty. Spatial population projections have been produced to supplement the national level population projections that were part of the basic SSP information. This has been used in many exposure and impact studies. Global spatial urban land projections consistent with the SSPs have also been produced to inform urban studies. Even indexes of governance have been produced consistent with the SSPs at the national level to inform studies of vulnerability and so on. These are the extensions in many different sectors that have facilitated studies in those areas and in addition there have been some sort of downscaling of scenarios which we'll hear more about later to different regions in the world. So the SSPs are in wide use have been since they came out at last count, which ended about a year and a half ago there's more than 2000 papers in the literature that use the SSPs. Many of those also employ the RCPs in their analyses and they cover a wide range of fields. You see here from this figure that about half of them in the dark blue are on impacts and or adaptation across a variety of sectors. Maybe a third are on energy, land use, emissions, including mitigation studies. So they cover a wide range and the framework has been used in some prominent assessments, including in the IPCC, including in the last US national climate assessment. So we're going to hear lots more about use and challenges for in assessments, as well as in research. So, so Chris, I was going to stop here and then maybe come back later to talk about research needs. If, if that turns out to be useful either way, I'll leave that up to you. Thank you, Brian. That was really very helpful. And yes, the plan is to come back to you at the end to talk about research needs. The one point I'd like to expand on is when you look at the SSPs is they were designed as spaces. And so it was explicit from the beginning that there can be a whole range of scenarios that look like SSP one or SSP two or SSP three. And so that it is a way to start categorizing the diversity of scenarios that are produced in the literature. With that, Jim, I apologize that I didn't say that you're going to be up next Jim's been running around the world doing really. I've seen a few very exceptional presentations about work on scenarios, and all that he contributed to moving scenarios to the co-chair of working group three. Jim. Okay, thanks very much, Chris. I hope you can see my screen, you know, at this point, and just to flag up that I'm not actually an active model or anymore it must be 25 years since I wrote a computer code in earnest. The bigger role has been in either specifying or interpreting scenarios, both at the global level, but also at the national level I spent more than 10 years as a member of the UK's committee on climate change and spent a lot of time kicking kicking scenarios around. Obviously, you're going in a US direction, I necessarily take a global perspective and an IPCC perspective, and it will focus more heavily on mitigation. I'm just figuring out how to move my screen. Now, this is a slightly provocative slide, which I'm asked more to borrow than any other slide I have ever produced. To flag up a very strong message we've had from governments in IPCC is that they would like to see a simple set of scenarios to help them illuminate their policy choices. And when we approved the working group one report in IPCC in this cycle, they reduced it to the ultimate level of simplicity. They wanted very low, low, intermediate, high and very high scenarios. Scientists are also I think really interested in the issue because scenarios are a really good integrating device for pulling together different scientific domains, the physical sciences, mitigation, impacts, adaptation and vulnerability. And as a result of this, we have derived a number of different concepts that try to bring things together, but it is proving difficult for governments, I think in policymakers to always you stay in tune with this. I noticed that in the background material for this meeting that there was a bold definition of scenarios and pathways. Just to flag that the IPCC glossary definition says that the term scenarios and pathways are used almost interchangeably, which is not a very helpful way forward. But I think it's important to realize there is a lot of ambiguity in the terminology that you that's actually used. Now, one thing also that I want to flag up is that often people refer to IPCC scenarios, there are no IPCC scenarios, there are scenarios produced by the community that are assessed by IPCC. 25 years ago IPCC was producing its own scenarios, the so called stress scenarios, the special report on emissions scenarios, but there was a very active decision taken by IPCC around 2005 that IPCC should not own its own scenarios, but its own scenarios, which should only facilitate the development of new scenarios in the community. And as a response to that, there was a new body, for example, created the integrated assessment modeling consortium, and there were pre existing kind of bodies, especially related to the concept that Brian has mentioned that pre existed this decision by IPCC. So I think just to be very clear, most of this activity IPCC does not produce scenarios, most of the activity is taking place in the community. And this, this really illustrates scenario design scenario production the development of the modeling tools lies with the scientific community IPCC's job is to assess the results of the scenarios that got have gone into the literature. But to fulfill this full facilitation objective. There are many bodies that are effectively intermediaries, and I would include the integrated assessment modeling consortium, the CMIT world climate research program process and iconics which I think Chris and Brian are both involved with, which is more covers more the impacts adaptation vulnerability vulnerability side, but it's very clear there is a kind of feedback because the community is often working towards scenarios that can ultimately be assessed by IPCC and feed into global processes. Now, very obviously, you can think of you can conceptualize this in terms of a kind of causal chain that does not go working groups one two and three for IPCC. It goes working groups three, one, two, because causally you can obviously think of your emissions taking place which is working group three domain working group one and kind of activity takes this through to climatic conditions, which can be downscaled then to particular parts of the globe. And then this moves on to working group two, which can assess various kind of indicators that are relevant to you to vulnerability climate impact so we have this kind of causal chain moving through in a particular direction. But this is not the approach that the community has taken since about 2005. The sequential approach was used back in the time of the stress scenarios, but there was a very active decision about 2005 to follow this so called parallel approach, which Brian has touched on here with the idea of the representative concentration pathways as something that could be done to guide the work that was carried out both in the working group one world with the climate models, and in the working group three world with the integrated assessment models. And what this did very obviously was by starting in the middle of the causal chain was that allowed people to work in parallel, and it got over some of the issues around timing that were there as we waited for the emission scenarios to be produced. And just to flag that to relate this to policy process, the reason for focusing on concentrations goes back to article two of the Convention on Climate Change, which talks about stabilizing greenhouse gas concentrations at a level that will prevent dangerous anthropogenic interference. And it's very interesting with the Paris agreement we've much more focused on the question of warming levels as the as the most important sort of policy guide. So building on exactly what Brian has said and thanks to Brian's presentation, I don't need to go into detail here, but we have the combination of the representative concentration pathways on the shared source economic pathways, which you can use to produce this kind of matrix at the bottom right and corner, because different different shared source economic pathways can be associated with different warming levels on the same warming level might be associated with different socio economic pathways. So you can produce this kind of matrix here but the community decided to identify so called tier one scenario classes, which are illustrated by the dark blue there, because it is quite clear that some combinations of SSP and RCP are more plausible than others so we have this kind of picture. And so far, the sixth assessment report in working group one, it was the five scenarios that are through which this red line passes that were chosen as the key scenarios that were portrayed in working group one and which the government signed off as very low, low, intermediate, high and very high, and that was the kind of background to them. Now one thing going into the working group three domain particularly is the importance of the carbon budget or cumulative carbon dioxide emissions as a concept. And this follows from the strong AR five conclusion that there is a very strong quasi linear relationship between cumulative carbon dioxide emissions and the level of warming. Therefore, if you want to limit warming to a particular level, as implied by the Paris agreement, then you should also be looking to limit cumulative carbon dioxide emissions in the same way. And in many cases the integrated assessment models I should say in many cases not always they have been run so as to meet a cumulative level of carbon dioxide emissions throughout the 21st century. And this then inevitably with the way that models work, attempting in most cases to minimize costs that this results in the kind of net emissions trajectory that you can see in this diagram marked in black. So you tend to see agriculture forestry and land use emissions going negative during the 21st century energy sector emissions going to zero sometime mid century and substantive reductions in emissions from the demand side and buildings, transport and but never actually getting to zero. And that is then complemented by negative emissions. For example, bioenergy with carbon capture and storage and emissions avoided through fossil fuel carbon capture and storage. This is inevitable way of it's put together. If you're going to limit cumulative emissions, and if you're going to discount future costs. This is the inevitable kind of outcome that you get from from these scenarios. I want to flag that some some of the colleagues in a European Union funded project actually were responded to a lot of criticism about negative carbon dioxide emissions by trying a kind of two stage approach to setting budgets throughout the 21st century. The first carbon budget is set to the point of net zero carbon dioxide emissions, but then you set a zero carbon budget out to the year 2100 after that. And basically, the pink kind of scenarios on this is the slide or a one stage carbon budget. The two stage budget is rep and represented by the blue stage, the blue scenarios, which stop reducing somewhere around mid century, and then grow greenhouse gas emissions in aggregate, continued a roughly constant level for the remainder of the century and never reach net net zero. We are flagging that many countries have criticized these blue scenarios, because they say it's not compatible with article four of the Paris agreement which looks between a balance of sources and sinks of greenhouse gases. To say, in working group three, there have been two kind of approaches for making sense at the many, many hundreds of scenarios that are assessed here. The first approach is to pick out a small number of so called illustrative mitigation pathways. This is shown on on the right hand side it's showing the characteristic of emissions and sinks at the point of net zero carbon dioxide emissions, which is basically telling the story that it is still possible to get to net zero, but there are different strategies for getting to net zero, which has different balances of removals and different balances of emissions in particular sectors. And the other way of being doing it is to take these hundreds of scenarios and try to bend them or allocate them into particular categories and then perform any statistical analysis on the outcomes of these scenarios for things like changes in the energy sector changes in land use. So what happened, our colleagues at the International Institute for Applied Systems Analysis, where Wolfgang is based, have created a database for these scenarios, and they have filtered them many of the scenarios this time were national or sectoral. So they've taken out included only the global ones, they've vetted them for compatibility compatibility with historic trends, and they've checked them to see if they actually have enough information to run through reduced complexity climate models. And as a result, 1200 scenarios in all were categorized, according to the warming level by the end of the century, and the likelihood with which that level would be adhered to. So quite a complicated process and there were lots of decisions taken there about how these scenarios should be vetted and characterised. So just the novelty in AR6 was that for the first time they were national, regional, sectoral scenarios included in this assessment and the database. And there was a much bigger effort to enhance transparency, for which the scenario community had been criticised in the past. So the scenarios database for the sixth cycle has input assumptions as well as model outputs, which is a novelty. And we also included an annex on scenarios and modelling methods in an attempt to explain just what the basis for the models and the scenarios were. And worthwhile flagging on that, the aim from my view was to communicate it to non-modelers and users. I think it's much more successful actually at the end of the day in explaining it to fellow modellers what's going on. So personally, I think there's a little more work on transparency needed. Well, let me skip this one because I think it'll come on. But one of the issues I think that we do need to address is the question of the inclusiveness and diversity of the scenarios that were assessed. Of the 1,202 scenarios in the global scenarios in the AR6 database, more than 90% were based on the middle of the road shared socioeconomic pathway. A very small percent based on SSP1, sustainable development and even smaller amounts on the other SSPs. There is also a big bias in terms of the different models or modelling families that are included in the database. So you can see that more than three quarters of the scenarios in the database were accounted for by only five models. And these models happen to be all models supported by the European Commission, I should say. So very interesting issues on diversity there which we do need to work on. So I think these are the kind of issues that we have with the scenario process at the moment that we will be addressing in a workshop which I'll just come on to as a final slide. Concentration in a small number of models and modelling teams. The question of inclusivity in scenario design and scenario architecture. And I noticed Brian, you picked up the issue of how the qualities are dealt with in the SSPs. And this is something which we got a lot of brutal commentary on from governments, some governments during the Working Group 3 approval. The boundary between what is research belonging to the community and what is assessment belonging to IPCC does get blurred. And for example the vetting process I just mentioned for scenarios took place inside the IPCC fence. You could argue that that should have been done outside subject to full peer review. And we also have some more administrative issues around the database. It was a big administrative burden for modelling teams to submit to the scenarios database in the last cycle, which I think partly explains the big concentration for particular models. Also a very short time between the cutoff date for literature and our final government draft submission. So only six or seven weeks time for the actual authors of the particular chapter to assess all the scenarios. I'll just do a little kind of advertisement to address many of these issues. Next week there is going to be a workshop on scenario IPCC workshop on scenarios which will take place in Bangkok that has a mixture of scientific aims which you're on the screen. I can leave the presentation behind and I'm very happy for people to have that. But also, for example, to consider the degree to which the RCP SSP framework is still serving as well, because some governments in particular would argue that it doesn't cover the fuel range of possibilities, especially in relation to equity. It also has process aims. We're also be thinking about developing cross working group collaboration further. I should say it was absolutely excellent on scenarios between working groups one and three in the last cycle. Work in progress on working group two sorry Chris and Neil in terms of the Brian in terms of the scenarios to think about the institutional mechanisms, thinking about how the scenario data is being curated. And to think about getting increasing further the diversity of contributors to scenario building process. So I'll call it to halt there and I know that there are several people on the call who will be in Bangkok next week so look forward to seeing you there. Thank you. Thank you very much Jim that was really excellent. So I put in the chat we just have time for one question. If somebody online or in the room has a question for Jim. We will have a longer period for discussion at the end. Brian I didn't ask for questions on your presentation because you're going to talk again later and I was going to combine the questions at that point. Anybody have any questions, I don't see a hand raised run. Jim, it was extraordinarily surprising and meaningful I think that 90 plus percent of the SSPs were number two modeling was about number two. What explains that I mean that that's that almost undermines the entire idea of spanning a space. I was so disappointed when we got to the stage to see this concentration on on one set of SSPs. I think the explanation is that a lot of a lot of these were based on modeling enter comparison projects that were supported by the European Commission. And the question the policy relevant questions that were asked didn't touch on comparing the different socioeconomic backgrounds. They were asking other questions about timing about the degree to which there was involvement in in sort of global efforts on climate change how inclusive it actually was. And I think the message has gone through. I mean I've been at meetings in Brussels since then about which we've talked about these very issues. But I think it really is a call for diversity and letting a thousand followers grow as it were in terms of scenario development and utilization is important because for me it was very disappointing to see that we we could have we had more SSP ones in particular that we could have developed much stronger evidence around some of the lines and findings in the IPCC report. Thank you Jim I think another issue was there was a process funded by the German government that provided consistency in terms of using for example some of the climate modeling data, but then only used SSP to demographic data and there's been a there's been a diversity since then but there were initial processes that really limited the the broad applicability of the SSPs to questions of relevance for policymakers. With that, I would like to turn to Wolfgang and Wolfgang you have multiple hats. I know that you're what the temporary interim executive director to yasa you, you run a demographic modeling group and other illustrative things, which I hope you'll articulate much better than me. Greetings from Vienna. So I've been for 25 years heading the world population program at yasa and currently service scientific director for the whole Institute. Now let me try to share the screen. I think it's worthwhile stepping back a little and when we talk about demographic trends. Ask ourselves first, what it is that we are looking at because most people think it's only population size or it's only the age structures of the classic definition of our discipline. So the scientific study of changing population size and structures, and not that structures is stated in plural, referring to multiple structures and not just the age structure. So we developed this concept that we called a mighty dimensional demography where we study population structures, of course, age and sex which are the primary demographic dimensions, but other characteristics of people as well such as place of distance, educational attainment level, labor force participation, ethnicity or in the US would use the words race. What are the variables where these are all the variables that have been traditionally collected in census sense, or if you have a survey that I sort of in a demographic Spock's what do you want to know about this interviewed person. So we try to show that this multi dimensional approach really makes the study of changing population structures, much more relevant for sustainable development than the more conventional limited focus only on population size or age structure. So, let's just look at the world population in 1950 you see here in the back. So what we did essentially is just add to the well known education pyramid where you have women on the right and men to the left sorted by age you see 1950 the word really looked like a pyramid. We added color as the third dimension in dark red meaning men and women who have no education whatsoever they never had the opportunity to go to school and then the light the pink one is primary education some primary light blue some secondary. And in 1950 was very little with post secondary education. Now, on the right hand side you see the total population as of 2020 so that in the meantime he has reached 8 billion, where it was 2 and a half billion in 1950. And you see that the first of all the age structure has changed a bit we have fertility has now started to decline and the pyramid is a bit more narrow at the bottom, but in particularly education has expanded tremendously, but we still have about a billion people in dark red that is what Paul Collier called sort of the bottom billion and then you have sort of a little more than a billion people ready with post secondary education. Well this is the global pattern that hides a significant regional differences and I just like to show you this fascinating pyramid for South Korea, which really had the world's most rapid education expansion and also one of the most rapid demographic variations. So this is Korea 1960 it was a really very poor developing country at that point, you see fertility all under recently there had been about six or seven children so the pyramid is very wide at the bottom. And you see in dark red that virtually every woman above the age of 35 was without any education. For me and it had this education expansion started a little earlier this is a very typical pattern. But what you also really see is this inter cohort differences while the elderly people are without education, the young ones have already benefited from the rapid education expansion and for the 15 to 19 year old, more than half already had some secondary education. But then these more educated courts move step by step up the age pyramid. And here you see Korea and 2020 it looks like a completely different country. And, well we don't have time to talk about all the other social and economic consequences of this rapid increase in human capital body was precisely when these more educated young adults came into the main working ages that you had this very rapid growth rate in the Asian Tiger countries and particularly in Korea. So what you see that today, fertility is very low the age pyramid is very narrow at the bottom because Korea now has the world's lowest the fertility rate, just around 0.7 children per woman, which is about a third of the so called women's level. And you see that almost half of the young court, both of men and women are these days, having some post second year tertiary education and this is part of the reason why the fertility is so low because under these traditional family norms, a educated women choose to have a professional career rather than to stay home with having children. What you also see here is that the elderly, particularly women you still have some of these women who were at the school age in the 1950s when Korea still didn't have a functioning school system. So this process of complete societal change through the cohort replacement we call also demographic metabolism. This is boring when we look into the future so I chose a somewhat more extreme country Nigeria and here. I'm not using SSP to bother use the two more extreme scenarios SSP one, which in the social terms we call sort of the rapid social development and SSP three, a stall social development. We've reconstructed this for all countries in the world is education and age structures back to 1950. So you see the historical trend. And you see, yeah, up until recently in Nigeria, you had the half of the adult population is still in dark red meaning no education whatsoever. You still have many children that's the gray area below under the age of 15, but then education expansion has also kicked in. But Korea, Nigeria is still sort of the crossroads they have their fertility rate declined from more than seven to at the moment somewhere around 4.5. And it's not sure that it will continue rapidly along the demographic transition it may well be that there's a stall development in Boko Haram the Islamic movement in the north of Nigeria were actually translated Boko Haram means that education is thin. But take over then the population expands still very rapidly. There's still many young children. And if the school enrollment rates are only constant or you can go down, then we may see what is there in SSP three then the population may increase too close to a nearly end of the century. See, it was just 50 million by in 1950 or below 50 million, and they're very rapid development SSP one still season increase to somewhat below 400 million so there will be population growth. And of course the right hand side the SSP three will be twice as big the country and much more vulnerable because as you see, actually an absolute number even of uneducated people will continue to expand there and there will be a much lower level. So this brings me now to my most important the actually only slide originally intended to show that gives you this circular relationship between the human population and global climate change. So, there are several main messages here the first message is that in these we humans we are the ones throughout greenhouse gas emissions who cause the climate change. But we will also be affected by climate change so it's the vulnerability the adaptation to already unavoidable climate change that needs to be of concern. The second main message here is that in the you see two pyramids here in the population the one is time t that is the current time. And that is where we are through our consumption behavior, cause the greenhouse gas emissions, and then the population at time t plus X at some point in the future will be vulnerable and affected by these climate changes. And the important thing here is that the climate is changing, but the human societies are also changing and this is often forgotten I've seen so many studies where sort of people try to assess. The additional malaria deaths due to climate change in East Africa what they did is take the climate let's say of the year 2070, but match it with today's population today's public health capabilities, today's societies and this of course is makes no sense. The question is, what tools do we have to anticipate social change. And here this multi dimensional population modeling, in particular with respect to education, offers a very powerful tool that as we've seen also we can with quite some certainty, look 60 or more years into the future, because if you know how many 20 year old women have sort of high school graduation today, we know well about how many 80 year old women, 60 year down the road will also have high school graduation and this is associated with better health, and very different institutional settings and so on so we don't have time to discuss all the benefits of education but it is a very forceful way of forecasting in one analytical handle on modeling a society's future. Coming back to the circle. It is not only our consumption behavior that is also impacted by the size of the population age structure was a labor force participation, and as well as education higher education typically resulting in higher income and in higher income in higher consumption, but it's also the technology or the development of green technologies that depends, particularly on the human capital of these populations we are looking at. We are causing the problem but to some degree, we are also the ones that develop the green technologies that then can help to mitigate or through other behavioral changes and mitigate climate change. Now let's look at the, the right hand side. It's already quite clear that there is some climate change is going on and some more it seems to be inevitable. So how does it affect the human population. Well, there is of course some direct effects on health and mortality is will be faster death or whatever. The more relevant issue also is the impact on livelihoods. And that has also impacts then on starving people if there's a drought and a famine, but very important aspect here is the migration is sort of climate change induced migration. This is a very big research topic at the moment, both in terms of internal migration as well as international migration. And of course you have the mortality, you have the migration and then fertility, that is a bit more controversial, how much climate change will have impact on the future birth rates and there are currently many studies going on and the opinions differ quite significantly. The key message again is that we are when we look at the vulnerability of future populations. We really need to try to anticipate what is the adaptive capacity of these future populations and the economist has recently reviewed some of these evidence and put it into a night short design that climate change is harder on less educated people. I think I'll stop with this. Thank you. Thank you very much Wolfgang that was really excellent. You're, you're a bit kinder than I am about the health sector. Three quarters of the projections assume the world, everything in the world stays the same only temperature changes. It's actually problematic. It's also a bit problematic with some of the migration work, because it's doing exactly the same thing. And as we sit here one of the people in the room is the head of the national climate assessment and thinking about migration and how important migration is but we really have to understand what's happening outside our borders in terms of demographic change. So in some ways this will be incredibly interesting and useful going forward. We have time for just a couple of questions. Sarah did you have a question. Of course. Thank you. Thank you Chris and thank you Wolfgang. It's great to. Thank you after many years. I had a couple questions about how you've been thinking around, and I loved your multi dimensional approach, and really appreciate that. I was just wondering about how you've been thinking about temporal dimensions of your of these changes you know how you mentioned briefly cohort replacement and I was just wondering how you think we should be thinking about time frames and, and, and that, as well as downscaling and thinking about sub national or even smaller local community modeling of demographic dynamics in in your approach. These are, these are very relevant questions indeed the temporal dynamics is really sort of set by the sort of the length of the human lifespan which is in most countries above 70 years now. So if we know how many babies have recently been born we have a good analytical handle about how many 7080 year olds will be living in 7080 years in the future. And as I said also the educational attainment is something that is typically acquired at young age. And so if we know as I said how many men or women got high school graduation now we really can also project, at least for these cohorts, the educational attainment in the longer term future with all the positive consequences and other consequences. So if for place of residence urbanization of course there's a bit more moving back and forth and we sort of are projecting the stock and it changes then only through the flow at the margin. In other words this process that it had been called by the, the Princeton, the marker for Norman writer demographic metabolism is this cohort replacement which I should say it's moving slowly, but steadily and with great predictive power so this is really sort of a slow moving process because of the inertia and this long average length of the human lifespan. Now what you just said about the spatial dimension that is of course a big challenge. The SSB is at the moment still have the urbanization projection, not yet fully integrated with these age sex and education projections and and that is something that we are now working on to have it better integrated. And then we've done this for individual countries such as in India we have it for all the states and within each state urban rule. And then of course we want to downscale to do even much smaller spatial units, but then it becomes a data problem at the same time. We want to maintain the rich multi dimensionality there are many downs can effort as you know for just total population size but having a full age structure having a full education structure. That is more of a challenge but we are moving in the direction and clearly in the future what we'd like to see if something that is multi dimensional and very spatially explicit. Thank you very much Wolfgang and in the interest of time we are going to move on to Heinrich. Are you ready to present. Indeed I am Chris thank you try to share my screen here should be this one. It's still in present it's still like this. That's okay. Can you see the screen. That's great thanks. Okay, so here I go. Thank you organizers for the opportunity to share some thoughts on on on scenarios and now we will dig a little bit deeper and and the point of departure will be more on the sub national scale compared to the previous talks. So I will try to go into impacts and adaptation studies primarily from a scenarios point of view and focusing on the sub national scale will also have some outlook to the global scale. So, so how how is local adaptation contextualized in both socio economic and climate scenarios that's the sort of starting point here for what I'm, I'm trying to talk about today. And the approach that we take the community that by itself and I'm sure that Casper will go along similar lines after me is that we are often working on the ground in sub national locations to study impacts and adaptation. One of the things that we are doing is to try to develop scenarios together with stakeholders and problem owners so this is, this is key for us to work together with stakeholders and developing scenarios. And there is a big and I think quite important distinction that I would like to make upfront and this is between creating new knowledge based on existing scenarios versus producing new scenarios. And the first case here and producing new knowledge based on existing scenarios that is usually what you what we see on the global level that people are trying to interpret the scenarios and using the scenarios for global studies. What we do mostly often in local impact sanitation vulnerability studies is to produce new scenarios, sometimes based on for example the SSPs, but the important starting point is that we start bottom up and not top down. So, why should such studies, local impact sanitation studies care about global social graphics. This is the question. Not only me but the community has pointed up on these questions for for quite some time now. And one of the design parameters for the new scenario architecture the RCP SSP architecture was actually to increase comparability across based on this regarding impact, mostly impacts but also vulnerability studies. Because this is as as both Wolfgang and Chris has alluded to this is a big problem in in mostly in working group to I would argue that we have some problems in accumulating new knowledge based on case study after case study. Because of this simple fact that that Chris and Wolfgang mentioned that people use perhaps the same climate signal but they do nothing regarding that the socio economic development in some in most cases. Society stays as it is. And in other cases, scenarios are developed, socio economic scenarios are developed independent of any comparability across different regions of the world. So this is one very important and driving force because behind the work that I'm trying to do. And one that has been raised sometimes is methodological guidance. It is difficult, it's complex, and I'm consuming it's it eat up your resources quite quickly when doing these kind of development of scenarios together with local stakeholders. And some methodological guidance from the global level down to the local and sub national levels would be good in order to increase uptake of scenario development processes. The third point for increased legitimacy. Well, sometimes I hear that people are happy to work within in the framework of a global architecture sometimes not so I'm not so sure about this. I will come back to this in an example later on. So, combining climate and socio economic data, where to put the emphasis. As I said, it's very, very complex to build those integrated scenarios at the at the sub national scale. And this figure here is quite old now Hawkins and Sutton going back to 2009. It's a good starting point, I think in order to discuss where to find your resources when it comes to handling the uncertainty. This figure shows the relative uncertainty on the vertical axis as a function of lead time on the horizontal axis with regards to the climate signal only. And you see, for example, I think you quite quickly realize that the green area here represent emission uncertainty. You see that in the near term emission uncertainty is quite narrow. And as was said before that it's important to try to to make some assessment what are the key uncertainties that we need to deal with in different time perspectives. And I think this figure can be used in order to draw some conclusions with regards to how to study impacts and annotation. Can you imagine that we have at the bottom of the figure a time axis. And the shortest time perspective we consider in the in the typical probably could be something like one generation. I really like to work with this one generation to generation framework on the same 10 years 20 or 30 years. People tend to understand better what I mean when I'm talking about generations but let's imagine that we have three different time scales in one generation into the future two generations into the future. We have a long the lines of 100 years, which is really the case regarding impacts and adaptation studies but but for the example here. So if one work in near term one generation time perspective. I think it's fair to say that based on the on the previous figure that they are certainly will regard to mission is quite low relatively low. So the proposal is to work with one emission scenario and the space regards to socio economic uncertainty more than the emission uncertainty. So in this case we get for integrated scenarios with the two arrows meet these are the. The so called integrated scenarios combining climate futures with social futures and moving into the future now going into two generations 50 60 years into the future something like that. I think it's fair to increase the amount of resources just spend on spanning the uncertainty space with regards to emissions so here I propose working with two emissions and ours. And then to not make things too complicated narrowed down the, the, the number of social economic futures to work with. You can argue the more longer into the future we look the more uncertain the social development is. So you should everything else equal work with more so she can maximize going into longer into the future. But I think it's also especially working together with stakeholders important to work with a limited number of scenarios to get the message. And the argument goes those on like this. I think when talking about the RCP dimension and the SSP dimension generally I think this this aspect of the time perspective that we are interested in is a little bit under discussed so I think one should put some more emphasis in in trying to figure out what are the key uncertainties in relation to the time perspectives we are interested in. I would like to mention just a few criteria for good scenario development. And the usual ones is on your left and relevance possibility and representativeness or representative. And the interesting thing is, I think is that relevance and possibility applied to individual scenarios in a set all scenarios should of course be relevant for the question we are studying. The scenario should if not being likely or we don't usually attach probabilities to scenarios. They should at least be plausible. Whereas representative, that's a property of the set of scenarios. This is not a property that you can tag to individual scenarios. This is a property of the set of scenarios if you work with three four five and six scenarios. Let's try to illustrate this. So imagine that we use this. Yeah, okay scenarios and store lines are used interchangeable that was mentioned before but I think it was Jim. I used the term store line in this simple matrix but it's similar to social futures. Let's imagine that we have three strategies that we assess across those four store lines A, B, C and D. And according to what we see here study one or two is something that we would prefer. Even those four store lines that we assess the strategies. But what if now we forgot or for some reason we missed out some store lines or some scenarios that makes study one and two perform very, very badly. Then the pictures is totally different than we should probably go for strategy number three. The conclusion for this from this very simplistic reasoning is that it's important when trying to represent a huge number of possible scenarios to try to span the space as much as possible and this was also mentioned I think it was Robert to When someone showed that only as most most I am so using SSP to and this goes directly in country to the idea of spanning the space of possibilities. So instead of doing the merging everything into the middle we should of course try to span the space and pick those scenarios that are on their outer edge here so together they span a bigger area. And what kind of of area this is is of course dependent on what kind of scenarios we're discussing could be simple, simple, simple one dimensional measures but this could also be multi dimensional measures. For example, if you study different dimensions with different states for for spanning the space of socio economic possibilities. But they, there are methods out there now that can help in trying to span the space in the mathematical sense as much as possible and I think, even the turbulent times we are living in I think this, this notion of spanning the space of possibilities. It's becoming more and more important. Okay. Just something that minutes left. Three minutes left. Yep. How many five or three. Wow. Okay, I will go to an example then. I will talk a little bit about cross border impacts of climate change because I think this illustrates very very clearly the importance of the social economic signal when studying impacts of climate change. Since we have known for quite some time now that the causes of climate change is a truly global problem, whereas the effect of climate change has mostly been studied in isolation in each and every country, not taking imported climate risks into account. This is the usual picture that we see over and over again that the vulnerability looks something like this. And you can really ask yourself, do we learn anything new, if we for example, plot those count all countries against climate vulnerability on one axis and human development index on the other one. And we see that they nicely align the screen line like this. And I think in an increasingly globalized word, this is perhaps not the whole story. So the bottom line is that in traditional assessment of climate impacts, the impacts every response take place more or less in the same region, whereas when it comes to cross border impacts of climate change, their impacts happens in one region. And the response happens somewhere else, and this is what has been called cross border impacts of climate change. So this Thailand flooding of 2011 was perhaps the primary example so far about what can happen with extreme weather events and disruptions to global supply chains. But in Kenya, trying to understand and using global scenarios in order to understand what are the global development that influences the future impacts of climate risks that might impact Kenya. And we described and built social economic scenarios bottom up as I described earlier on, and focusing on those climate risks that are not from Kenya itself but are imported. So we link those scenarios to global RCPs and SSPs. And we used also some globally global modeling and created what we call scenario packages trying to describe the situation in Kenya in relation to those climate risks that are imported so that we could develop adaptation options and assess adaptation. So what we did when developing the scenarios was first using only stakeholders and trying to identify drivers of importance to understand future vulnerability in Kenya. And then after that we introduced a global scenario so we started with not using the global scenarios, and we use them instead of trying to interpret the different drivers in Kenya given different global context as described in the different SSPs. In the last slide we laid out skeletons for local scenarios that were compatible with the global storylines. And I think when going from studying localized impact and adaptations to studying impacts of climate change that cross borders, I think this the case for global socioeconomics is even stronger. In order to understand the future threats to Kenya, you need to understand the socioeconomics in Kenya, you need to understand the socioeconomic development globally, and you also need to understand the socioeconomic development from which those countries you import climate risks. So this extra I skip in interest of time, this is about AI and scenarios, which is perhaps important to discuss sometimes. I'm sorry this was a bit rushed, but this was what I had to say. Thank you. Thank you very much, Heinrich that was really great. Apologies to have to rush you but we only have limited time and we've got two more presentations and then we're going to open up for general discussion. Casper, are you ready. I see you're online but ready when you are. We're ready. Looking forward very much presentation. Thank you so much for joining. I hope the whole audience is still ready. I noticed that I getting kind of at the tax of how much information I can take in, which is so let me see which screen should I share. The one that's useful for this. Why not. There we go. And I have heard most of those stories before and I'm still kind of at the limit of what I can take in so I hope you have room for one more. Somehow it doesn't want to go in presentation mode. Let me try this way. Yes. That's better is it. That's better. Thank you. Hello, so my name is Casper and I also want to thank everybody Chris especially I think for inviting me to speak at this meeting. When preparing this presentation I realized I weigh too much and of course my way of doing is putting it all in one presentation and rush it all through and I'm sure you don't. I won't be able to follow all that but I think there's just simply so much going on at the non global level of SSP development that is worthy of at least touching upon that I that I did need to leave it all in. And that includes actually a little bit of the scale concept I decided to focus only on multi scale scenarios that's been my kind of red thread throughout my career either using multi scale models or multi scale scenarios or multi scale stakeholder workshops. I think there's a lot to be said on how to do that best and I tried to give you some highlight of it. There is a little bit of backgrounds and then there's a tiny bit of time for best practice examples and I'll highlight one particular project that both me and Henrik have been involved in, and then summarize all of that in a minute or so. I hope, but please correct me if I have less time than I think I have why starting with ecological theories, not to give you a lecture but multi scale scenarios have been around almost as long as scenarios have been around and I think it's it's good to realize that it's not necessary. In my view to do multi scale scenarios. If you talk at any theme on any issue at any scale that is not global, called here a focal level. There is a larger scale above where there are slower processes happening over larger scales, and there are smaller processes happening over much shorter time time scales part of that already Henrik touched upon, and to understand what's happening at any scale you need to understand that these somewhat happens at the scale above and at the scale below. There's beautiful books written ecology about it and some of that transfers to integrated systems some doesn't. I'll skip it for now there's also a dozen of these kinds of diagrams around that kind of plot out space and time, and you, you roughly see a diagonal, which the very, very large scale processes be it climate change or economic crisis you see this figure somewhat old one that was in play you can add the pandemic. If you want to understand spatial planning at, at state level, for example, but then you know household income might also be important to to take into account. There's two animals here that tried to get all my attention. Well, they shouldn't. Okay, this particular paper is 15 years old and I think it's been underused. It's been written in the aftermath of the millennium ecosystem assessment, which is later on followed up by the IPS on biodiversity and ecosystem services, it's worth revisiting. So all the time. This paper lays out the foundation of how to set up a scenario development process was written for global assessments but it applies to different scales with the top half tells you what kind of scenarios at different scales do you want to reach and how comparable how similar should those be from completely complimentary to completely the same, which they call equivalent. The bottom half tells you what type of process you should embark upon in order to get those scenarios. Very conceptual but it's it's something that that a lot of people haven't thought about until they're in the middle of the process realizing they're not doing it the right way. So that's just saying that that paper is worth reading. This is 10 years later when we were asked to, to, to give input to the new process of global scenario development for the IPS. I came up with a little paper that was supposed to be a cock and cock paper simply because I know somebody else with my surname, because many other people joined the party. There we laid out three different options for it best itself, where one was use existing scenarios in this case that the global SSPs to was developed completely new scenarios, and three is use local scenarios, build a database and use all those to create a global set of scenarios. They both had all three of them have strengths and weaknesses I don't have time to go into it. It's worth simply reading what it says there because they all come with pros and cons and you can't avoid all of them. In a way, the best in the end took option two, because they didn't want scenarios that were kind of what if what if what if we span the uncertainty space, they said we want normative scenarios that all that all gear around protecting nature. So they came up with their nature futures framework, which is another set of global scenarios that are more on system transformations than they are on spanning uncertainty spaces so there might be important reasons to do something else than what the SSP set out, even though I'm here to advocate the use of the SSPs. This I can skip because Brian introduced it. It's just to highlight again that the word scenarios can really mean a lot of things to different people and particularly in the in the community that Henry can I operate in. So those are often local regional national type of scenario processes narratives become much more important than the actual model input or output. When we talk about scenarios they might well simply be only stories and nothing else. So it's good to keep that in mind. Well Brian also talked about this that at some point integration needs to come because the SSPs are very powerful as a product in its own right but in the end certainly when you when you're in the climate change arena. There is more than just socioeconomic change and we highlighted how it can be important certainly in the in the shorter in the shorter run, but at some point that does need to be integrated with climate change impact signals. And this particular figure here in the bottom was shown already where you know a set of global emission levels were matched with certain SSPs in tier one and hopefully more will come later. So one thing about to say about that I think later, if I have time, just a reminder that that's that's always somewhere needing to happen as well. Now there are different ways in which scenarios can be downscaled. And so we have the existing bit which are global narratives and the global models and are plenty of them. The key of downscaling is to downscale stories first. So you actually develop regional stories, continental stories, national stories and those then can be translated to model inputs and can then run a set of models that will give you both global and regional models. To say I will directly downscale models, or I have global models that give us outputs and that output can directly be used by regional models and give you the regional model outputs, skipping the narratives. And if you wish you can use then those regional model outputs to create your own set of regional stories. Those are by and large three ways in which you could reach sets of narratives and or models at regional scale. So I'm realizing though, some of the things I just said is that I think there's two fundamental choices that need to be made. And the first one really is you're going to do downscaling or you're actually going to do upscaling. So is this going to be a top down process, starting with global SSPs, then developing in Europe, many times to the European SSPs and you have national ones and local ones that can be multi tiered downscaling, where the global scenarios are kind of used as boundary conditions, or do you want to start bottom up with regional scenarios that can then later on be matched for some other way linked to global level developments. And the other thing that also Henry touched upon in my own work of scenario development, almost every, every case has some degree of a stakeholder participation. And that's often tied with more qualitative scenarios narratives cartoons or kinds of other types of outputs could be derived. But it is a choice, whether you want to have stakeholder input in the actual development of the scenarios, or you want this to be more model based and let's say quote unquote expert driven, where scenarios can perhaps be more consistent with global models, but you might lose some of that local specificity because you haven't included the stakeholder knowledge. I think both of those do need to be discussed and you have to make very clear the clear decisions on what it is you want to do. Right. I think Brian touched upon that first one I think he said the word 2000 so there are two systematic review initiatives that try to keep track of who's been using the SSPs and been been documenting about it. I say he is 1600 I think Brian said had the number 2000 so it's a very rapidly increasing database of papers and and other documents that that tell you how SSPs have been used. So there's a first one that's also published I don't have didn't have the DOI number with me but that's also freely accessible through I think the iconic website. And then there's a second one and I'll focus a bit more on that one that's just been finished. We focus on a subset of that entire body of evidence and it's focuses on those papers that have downscaled the SSP somehow and that also have something of a narrative component. And that database has roughly about 160 papers, from which I can conclude two things. 90% of all papers that use the SSPs are global and quantitative. Yes, we have a lot of papers but do we have a lot of papers that are really modeling papers. Even so 90% out of 2000 leaves us about 200. So that also means that there are literally hundreds of examples of those studies that have regionally extended SSP narratives in some way or another. So that's a that's a huge body of evidence as well. We have some figures that look a bit different they cover a bit the same indicators as that Brian already showed of this regional set of 160 papers. So I think the first conclusion we can draw from that is the same as what what Brian already concluded from the big database. The SSP extensions cover a large range of different sectors, and not surprisingly the largest one is the water sector but that's only 18% of all the papers and agriculture is the second one urban is the third land uses the fourth one. It's a similar similar breakdown as for the whole the whole set. You seem to see here and I think that differs from also the earlier question that was raised is what SSPs have actually been used. And you see that, although by far the largest class of papers only 35% of the papers use all five SSPs. And you see almost any type of combination. If you break it down by individual SSP actually SSP to does not stand out, if anything it's been used less than the other ones. So I think at regional level spanning the diversity as a use of the SSPs has been much more important, partly because modeling has been a bit less important there. And actually that stands out completely is SSP for which is hugely under represented and a and a big reason for that is that the, the CMIP six model into comparison that span the whole range of uncertainty for emissions, do not span the entire space for socio economic development. SSP for was not included in that first set of SSPs. And that's why many non global projects are now saying we shouldn't use SSP for because CMIP six hasn't used SSP for. So you see a consistent under representation of SSP for then for the, the, the, the, the skate the scaling methods that were being used. You see that about half is strictly top down, which also means that about half includes some kind of bottom up element. So you see that becoming quite important in regional studies, even though predominantly a lot of studies are at first top down, starting from global or continental SSPs, they, they do have bottom up elements in them. Yes, that's what I want to say about the database, explore it yourself you want to have other findings as lots of other material coming out soon. You're just a flavor of different downscaling methods that you could use. So that actually said, let's not do narratives, but let's start from tables that have trend indications and use those kind of as a structured way to look across different SSPs. So you actually have mostly trends with very short stories. And that actually say now let's only do models or first do models so there were global models that were downscaled those were fed to regional models and that was used as an input to stay called the workshops, but mostly driving driven by by model information. We only do narratives. So here's quite quite well well cited study on European agricultural SSPs that was that was a set of narrative stories only. And then you can do the one example project I have a few more slides on which was the impressions project, which focused on high end scenarios so we only had a higher level RCPs. We excluded actually SSP to in our set for a variety of very good reasons we didn't like SSP to. We had narratives and models, all based in in the end to feed into a regional integrated assessment model that we developed for Europe only. There's a website there with has lots of more information. Not to explain everything but when you start talking about downscaling loads of different things come into play and you see global SSPs feeding into European SSPs feeding into case study scenarios. All with arrows that have different words. And they all mean different they actually tie back to the Zurich and Henry's paper where you use downscaling in a different way where you where you make the link between SSPs at different scales, either stronger or weaker. But the main overall approach of impressions was that approach of first producing narratives and downscaling the narratives and feeding back to models and then it iterating that back and forth to get more consistency between stories and models at all the different scales. Asper if you can move to that conclusions. I can move to the conclusions. You can also integrate if you do workshops. Don't forget about the RCPs that come in integrations. Two slides. Can I have two slides of conclusions. I can. Yes, people use the SSPs. I think that's by and large the big conclusion that I draw from all the material that's available there are many and they increase only by the day. Also on those that do regional studies. It's super heterogeneous in what theme what sector, how to design the multi scale approach, which method they actually use to develop scenarios with SSPs they use, but they also have common characteristics. So as Henry was already pointing out very often in the end this is about the IVA community. This is about climate change mitigation and adaptation options. These scenarios serve to contextualize that discussion. So it's actually a means to an end very often stakeholders are very often involved in co production methods are a big chunk of the whole methodology of developing scenarios, even though and don't underestimate very often I hear that you know local people that you only do qualitative scenarios, these people couldn't be more wrong. Many studies have very good models on board and do very good local modeling studies. They use quantitative models. Three key points that I want to give the community. Please don't reinvent the wheel. I think there's so much scenario develop and I think the part of the reason we talk here is that exactly that reason but I think I just want to reiterate that the concepts exists the approaches exist and there is really a multitude of different methods methodologies and tools that are readily available to be taken from the shell. So any of that I think you need to look at that key set of methodological questions. This is going to be top down a bottom up. You want to involve stakeholders or not if so at what point are you aiming for model output are you aiming for narratives or aiming for both. What's the time horizon, you know, Henry's talking about generations, very often 2100 is very, very far, the more local you go and the more difficult it gets to extend scenarios, all the way until the end of the course. But my bottom line one liner is that the SSPs are an excellent starting point to do scenario development for any study at any scale. I'm sorry I'm taking too much time. So thank you very much. We're going to turn back to Brian who's going to try and summarize all of the research needs that we heard. And after Brian we're going to take a two minute break while everybody online and in the room can formulate questions, then we'll have 30 minutes for q amp a. So Brian, good luck with summarizing all of the research needs thanks. Thanks Chris. So, yes, rather, rather than trying to summarize the research needs that were presented in these talks. You'll see some of these messages reflected but what I wanted to go through is just a relatively short list of research challenges that have been identified by the research community and in particular have sort of been discussed and come to the surface in a couple of fairly large conferences that have been held on the scenarios topic and the most recent one was just last year at yasa. And so, so these are our challenges that the community has identified itself you will see some of the themes that we talked that have been talked about today reflected here. So the first one is simply keeping scenarios up to date. The, the SSPs in particular were developed quite some time ago. And the both the base year information, the sort of starting points of GDP of population of current energy systems, so on, are now somewhat out of date. As are some of the near term outlooks for example there's been kind of widely publicized, unexpectedly rapid change fall in costs for some renewable technologies that were not anticipated at the time the SSPs were developed. And these need to be updated as well. So this is a process that is underway I believe the population and education projections have just been updated, and other elements are in the process of being updated at the moment. An important challenge here is though to make this somehow sustainable and repeatable over time, so that we don't have to just wait, you know, five, six, seven, eight years till it becomes a crisis and then scramble and figure out how to get them updated and how to keep a set of scenarios up to date and relevant over time. An additional challenge is that as we talked about in the beginning, the so called reference scenarios or kind of starting point for an analysis is the SSPs at the moment. And as we discussed right those don't have impacts or policy in them. And then the idea is that when you do a study, you introduce climate change or you introduce policies and you study what the effect of those are on this counterfactual scenario in which they don't exist. And it's been noted that this the the relevance of a counterfactual in which there are no impacts and policy in a world that is beginning to experience impacts and policy doesn't make as much sense as maybe it used to it still can play a methodological role, but for credibility of scenarios probably want to move towards reference scenarios that do include some degree of climate impacts and policy in them in the first place. There is of course the question of do we need new scenarios do we need new SSPs different SSPs are some of them no longer useful and should be dropped. A couple of important topics of discussion here are the high end scenario. The, the highest one was RCP 8.5 or the SSP five without any mitigation that also produces eight and a half watts per meter squared of forcing this high scenario has been critiqued as maybe being implausibly high and should perhaps be retired and a new high scenario chosen. There's also a lot of discussion of the need for additional scenarios in which temperature exceeds a given level and then later comes down and meets it at some later point in time. This has become especially relevant since it appears that we will most likely be exceeding the one and a half degree target. Who knows maybe the two degree target as well. And maybe we should have scenarios that exceed those targets and then come down later in temperature change and meet it at a later time. But there's also a discussion underway and this was reflected in some of the comments about broadening the framework, because as we discussed right it's sort of organized conceptually around these challenges to adaptation challenges to mitigation it's not change focused and that was a very explicit intentional choice at the time, but it has made it harder to make these scenarios as useful as they could be to studies of other issues in particular biodiversity ecosystem services. As Casper mentioned the biodiversity community has developed another framework and nature futures. There are some sustainable development issues that a broader framework that was sort of reframed to include not just climate change but other issues may be important and useful. In addition, the idea of developing new kinds of community scenarios, which reflect the outcomes of all this work has been put on the table as well. So we're talking about SSPs RCPs, they're a starting point right there one of these ingredients around the outside of the circle that are used to create the integrated studies that then reflect how the world may actually look when there are impacts when there is adaptation or mitigation policy. We don't have scenarios of those outcomes we have large numbers of scattered studies, and these have not been pulled together to say for example what doesn't SSP to world with climate change and potentially with some kind of policy look like what is that scenario. We don't have such a thing that's a scenario of the outcomes of this whole process. This is the potential for moving scenarios in a way that would incorporate outcomes and maybe plan for them from the beginning, rather than taking this approach of the counterfactual without impacts or policy and then adding them in later studies. Finally, and the CMIP process the round the next round of climate model simulations to follow up CMIP 5 and CMIP 6 is now being planned the process has started for the next round of climate model simulations, based on on SSPs of some type. Right and so what a current challenge is to select what should we be doing next in terms of earth system model simulations of scenarios. Obviously, we want them to be up to date, but should we be simulating new reference scenarios that have impacts in them. Do we not want to do the high scenario anymore. Do we need overshoot scenarios. If so, what should they be as part of the mix of considerations for designing those experiments is that it appears that the climate model emulation has advanced a lot since the last time around. And it may be possible to replace a lot of earth system model simulations with fewer simulations and use model emulators to fill in the gaps. So that's a representative sample of questions that are on the table. There are other challenges that have been referred to in the talks here, but plenty to work on and plenty to be doing. I'll stop there. Thank you very much Brian that's a very useful summary. There's another issue that often comes up is the SSP RCP framework was designed as a toolkit and the whole communication to policymakers. It's not exactly a research question but it is something that the community is aware that more work needs to be done in that space. We are exactly on time. I want to thank all of the speakers for just remarkable presentation.