 I'm not moving though. Right. So I start off with this figure that is coming from our chapter, chapter 12. And the results of chapter 12 and summarized in the summary for policymakers in figure SPM 9. Here, I think Alex also showed this yesterday. I think Alex has got lost in his running today. Oh, he's here. OK. Welcome, Alex. OK. So here, we tried to summarize everything that we found for all of our 33 different climatic impact drivers in the different categories. As you can see here, heat and cold, wet and dry, wind, everything. And here on the y-axis is the number of regions where we have high or medium confidence. So the purple and pink bars indicate high confidence or medium confidence increase. The dark purple showing high confidence and the medium purple or pink showing medium. And the orange-yellow colors show high or medium confidence decreases. And the number here basically indicates the number of regions in which these changes are projected to occur by this period. So with a 2 degree global warming compared to a similar period within 19, 6, 20, or 18, 15, 19 hours. So it's a bit complicated. But anyway, so it's with about 2 degree warming or 2050. So what I want to draw your attention to here in my talk today is this block. These are the coastal and ocean CIDs. So we have relative sea level rise, coastal flooding, coastal erosion, marine heat paves, and ocean acidity. And you can see already from this block that all these coastal CIDs are projected to increase with high confidence in most of the regions of the world, almost all. So why did we pick these CIDs? So again, like Alex and Erica both explained yesterday, we didn't just pull these out of there. So we looked at a lot of literature and also connecting with the sectoral aspect in working group two. We picked these CIDs due to these reasons. So relative sea level change can lead to permanent inundation. So once the relative sea level goes up, it's permanently underwater, which could lead to forced migration. Coastal flooding can lead to damage to property and infrastructure, and also in extreme cases, loss of life. Coastal erosion can also lead to damage to property infrastructure and also lead to forced migration if it's continuously eroding or episodic erosion happening all the time, people don't want to live in such places. Marine heat paves can cause coral breaching and shifts of large parts of the marine species. And ocean acidity can affect fish and health reproduction, fish health and reproduction, and also cause algal blooms. So these are the reasons why we picked these CIDs. But today I will limit my presentation to only these three CIDs. I don't have a lot of time, 20 minutes. It's not a long time. Now, when we talk about tacking these CIDs or how they will change, we have to also pick indices that are used commonly. So that's what we looked at in our chapter. And we had to identify the indices that are used commonly. So for relative sea level change, usually what is used is pretty straightforward. We people either refer to the magnitude of relative sea level change by 2050 or 2100, or the percentage relative to GMS LR, that the global mean sea level like Amy mentioned, the 20%. When we come to coastal flooding, the flooding due to the 1 in 100 year return period extreme sea level is commonly used for planning purposes and adaptation. So here, when we were doing AR6, now these data sets are becoming available. But we didn't really have data sets that showed us projections of coastal flooding per se. So we use this extreme total water level as a proxy for coastal flooding. So the impacts due to coastal flooding would be on, for example, the estimated annual damage in terms of euros or dollars, or the extreme annual population affected, that's the number of people affected. So we use this ETWL as a proxy. And that's defined as, in Chapter 9, that's defined as the addition of the relative sea level change, tide, storm surge, and wave set up. Depending on which of these components are combined, there are different terms. So for example, if you don't consider wave set up, then it is called extreme still water level. But we, in Chapter 12, looked at all these things. So we use throughout this ETWL. Coastal erosion, usually, again, in decision making or looking at sectoral impacts, people use the meters of shoreline retreat projected by 2050, 2100, something like that. And also for more storm erosion type decision making, people use the 50 to 100 year return period erosion volume. We did not have this kind of projections at the time of AR6 with global garbage. I don't think we still do. It would be quite a challenge to make such a database. But we did have information on the chronic shoreline retreat. So that's the more long-term shoreline retreat, mostly due to sea level rise. But in the absence of additional sand supply to the coast or any physical barriers. So there is that caveat always. In anything we say in AR6, when we refer to shoreline retreat, it is in the absence of additional sand supply or any physical barrier shoreline retreat. In places where these things are there, these projections would be different. So it's important to note that. So why these indices? As I said, they are the most commonly used indices in coastal zone management, port and harbor design and insurance industry. That's why. Now, one of the main results that we have in Chapter 12 are the CID tables. Again, you had a sample of that yesterday. So I have here just taken out the coastal and oceanic CIDs that I mentioned earlier. And this is for Africa. So we have projects. We have the CID tables, which are subdivided into the different IPCC regions. So here is Africa, all these different regions, including also the African part of the Mediterranean. And you can see it's dark blue. This whole block is dark blue, which means high confidence of increase. The red dots mean emergence. I think this means red means already emerged in the historical period. Yes? If there's no circle, that means there's no emergence. And the caveats, there are caveats. Throughout these CID tables, there are caveats. So here you can see for coastal erosion, we have these caveats. Number four, the what I mentioned earlier, along sandy coasts. So not in rocky or muddy coasts, and in the absence of additional sediment sinks, sources, or any physical barrier shoreland. And then here, it's also five there for eastern Southern Africa and Madagascar, southern moats past. So there are some conditions to its validity. So it's important to, when you're looking at these CID tables, not just look at the colors, but also look at the caveats. We went to a lot of trouble to make it as accurate as possible. A lot of people just look at the headline statements and make loud comments. But I think we have been really precise in the way we have presented this information. So like this for Africa, we have similar tables for every region of the world. And you can see almost everywhere where there's ocean, it's dark blue. High confidence of increase. IPCC Confidence Language, this was covered yesterday. So there's different lines of evidence. I will not go into this again. But I must highlight that process understanding is also something that really comes into play when we come up with confidence statements. We covered this yesterday. This is how we come up with confidence statements and likelihood statements. Now some projected changes. This is from chapter nine. This is about extreme still world level. So not quite extreme total world level. It doesn't have the web setup component. And this is based on measurements at 634 tide gauge locations. And based on these measurements, chapter nine came up with projected changes in the frequency of extreme still world level. Here you see 2050, 2100 for different scenarios, low to high. And so the basic thing you see here is that by 2100 everything becomes dark blueish, which means the frequency increase, frequency amplification of greater than 100. So that means that, for example, the one year annual probability event today will become 100 times or more frequent. So the one year, 1% annual probability event will become at least an annual event at 31% of tide gauge locations by 2050 and 82% of tide gauge locations by 2100 under this high emission scenario. So that's a very big change. Imagine an event that happens today one time. So that has a chance of happening once in 100 years. By 2100, that happens many times a year, more than once a year. That's a very big change. You will not be able to live in such areas. So it's just not statistics when you think about the reality of the situation. Then in chapter 12, we have magnitudes of projected change in extreme total water level. So this is one of our main figures in section 12.4. We have two scenarios, 4.5 and 8.5, and we have 2050 and 2100. So again, you can see here, compare the 8.5 for mid-century and in-century. You can see by mid-century, the increases projected are about 0.2 meters or so, between 0.2 and 0.4. When we go to 2100, the increases are around one meter. So that's again a big increase in the extreme total water level. All of these changes are relative to a baseline period in the beginning of this century. Shoreland retreat, we have such figures that show the projected shoreland retreat. Subject to those caveats I mentioned. So this is by 2100 for RCB 8.5. Again, this is for Africa. Negative is erosion. Positive is accretion. So dark red means more than 100 meters, for example. And then we also have these uncertainties for each of the regions. As you can see, in some regions, there's large uncertainties. And we have produced such figures also for Asia, Australia, and Central and South America. We don't have a global map. So that is all about the direction of change, though. So in the CID tables, we are only talking about direction of change. We don't talk about the magnitudes. We don't say the tables only indicate the confidence we have in the increase or decrease. So if you also want to see the numbers and assess confidence level on the magnitudes of change, we have that in the text. So here, for example, in 12.4.5, which is for Europe, that's the section that Erica handled personally, with Robert. So if you look at the text, we will first have, so if you take the text for coastal erosion, we will have something about observed changes, right? So then we see here, from the papers that we find the literature, we have this kind of text about the rate of observed change. And then in the next paragraph, we will have text about projections. So here, it's retreated by 25, 60 meter long sandy coast in certain regions. So if you want the numbers, you have to go into the text. Not only look at the maps. In fact, it's a bad idea to get anything from the maps because these are all done with very large scale global studies. So course grid and under a lot of assumptions. So if you look at a map, a dot in your town and take that number, that's probably gonna be wrong. So because a lot of local poses are also operating at any local scale. And that's why when we give numbers, it's all average for a whole region because some places, the models are good, some places, they are bad, so it balances out, that's the idea. Coastal CIDs that we have not assessed in AR6, mostly due to lack of data at this point. So maybe if you wanna think about doing studies in these topics, that'll be helpful for the next assessment report. We haven't looked at salt water intrusion in a global sense, it's very important actually when salt water intrusion increases, as it does, and there'll be a lot of implications into like drinking water extraction from rivers. I know from where I am from Sri Lanka, there's a couple of rivers that people take drinking water and now in the last 20 years or so, they have had to move the water extraction point upstream three times because salt water keeps coming up. We also didn't look at compound coastal flooding, so that's like things like the combination of storm surge and flu wheel flooding, or it could be also the addition of flu wheel flooding, again, due to lack of literature. So that's I think is a major research gap that can be addressed actually with available tools. We did not look at extreme waves in AR6, but since then now there have been a couple of studies that have come up with these projections. We also didn't look at the groundwater table effects on the coastal zone, which does have a effect. So where to find the coastal CID data is assisting AR6 working group one. Amy talked to you about one, so the relative sea level change can be found from this really nice tool maintained by NASA. I will not go into that, play around with it. All the other data sets, we have put in this tool called Coastal Futures, which is maintained by us at ICDAL. So there we also have the regional sea level change that Amy talked about, but only the median values. We don't want to repeat, but just for sake of completeness, we have that, just the median values, not all the bells and whistles that are available in the NASA tool. We have also extreme sea level. We have now I think three data sets there. Three different data sets produced on extreme sea levels. Two by scenario and one by global warming. Coastal flooding, also we have now two data sets, one with current coastal protection measures and one without. For shoreline change, we have only one data set at the moment, that's the same one that we used extensively in AR6. And extreme waves, also we have a data set that became recently available, but we are in the process of also adding mean wave projections to that, that should also be available within a couple of weeks. I was initially thinking of doing a little demonstration of this, but given that we are already running a bit late, I will not. You can find this, the link is there and you can just search for it on Google also. We don't have a data download facility here because all the data sets that we use here, by definition, is one thing we do in coastal futures is we only put up published data sets that are freely available. So in each one of these pages, we have provided links to the original papers that you can go and download all the data. But if you need any of these data sets for a particular region and if you don't wanna be bothered with navigating through global data sets, you can always email us and we'll try to help you, okay? So limitations of our assessment, I think that's also a very important thing to bear in mind. It's that all of the coastal CID projections are based on relatively close, close resolution global scale studies. So they are useful to identify regional scale patterns or potential hotspots at national or continental scale, but not to inform local scale adaptation. I would advise not to take any of those numbers that we have in these maps and use it for adaptation study in Danang Beach in Vietnam or Manila in Philippines. That is not the purpose of this data. If you wanna do something like that, then you need to do detailed higher resolution studies. Usually for coastal studies, it can be 10 to 100 meter resolution. Maybe 100 meters is even still too close and then you had to do the hazard impact risk modeling. All that whole cycle has to be done with detailed modeling. So then you end up with maybe research like this. So for here, here this is a flood risk study that we did in Kanto, very detailed. Also this is a flood risk for a 100 year event that combines the river flow and the storm surge and this is without subsidence. This is with subsidence. You can see the effects of subsidence is far outweighs anything else. And this is the result of a coastal risk study that we did. The colors indicate the yearly risk in Australian dollars per square meter going from light to dark reds with high numbers. So the dark red areas are high risk areas and these black and blue lines are the coastal set back lines that we calculated from the study. So to do these kind of things, you cannot do this with our AR6 results. Then you really have to go into detailed modeling. These are very high resolution model results. I think that's it from me. Yes. So I can take one quick question or we can move on to Jose up to you.