 Okay good morning everyone. It is very nice to see so many of you here. I would like to first of all really extend a very very warm welcome to Secretary-General of WMO, Mr. Michel Jarreau. We are very pleased to have you here at SEI. I also like to welcome of course all the people here at the seminar, all the friends that are looking at this through our webcast as well at SEI offices around the world and other guests. I also like to welcome David Molden here the Director-General of ECMOD which is really great to have you here. We also have friends from Stockholm University which is also very nice and other colleagues from WMO. So it's great to have you all here. You are right now at the Stockholm Environment Institute headquarters and the Stockholm Center which is the sort of main hub of SEI but we also have colleagues from quite a few other centers around the world. SEI just very briefly is an organization created in 1989 focusing on sustainable development, so an emphasis on environment and development of course, focusing on delivering science for policy and decision-making. So in many ways having a mandate which in some some respects is very similar to that of WMO. Of course we are an organization that relies very much on the work you do in the organizations. We are very interested to hear and vice versa and that's exactly what we are hoping to have that kind of discussion later on today. Just to briefly say the mandate of SEI is also very wide. Natural Sciences is of course a very important aspect of this but we also have very strong social sciences so we have that whole spectrum of different disciplines represented here. We have research that is broadly divided in four themes. Managing environmental systems which I think is also very relevant for this topic. Reducing climate risks, so climate is of course key but also atmospheric sciences are very important there. Transforming governance because we need that, we believe that this is very important and also rethinking development on the more long term. So this is what colleagues are working on in seven different continents or seven different countries around the world. So we are very interested to hear more about of course also what WMO is doing and not least related to the global framework of climate services. So a warm welcome. I'm going to hand over also to Magnus Bensi who from now on will moderate today's seminar. We don't have microphones like this or you know it's just for the webcast but we have to use these microphones if you're going to ask questions later on, wait for the microphone as well. So Magnus you will take over after the presentation but I'll now leave the floor to you and please give Michelle a warm applause. Thank you very much Johan and for this opportunity. I'm suddenly delighted to be here. It's not the first time I'm coming to Sweden. My first time was here now 41 years ago but it's the first time I'm coming to this place and when you contacted us I was very happy to say yes for many reasons to your invitation but one of them is precisely for the reason that you describe. When it comes to climate it is not, we're not dealing only with the traditional partnerships. We are dealing with new types of partnership and I will come to that in a minute which are very much multidisciplinary, which have to look at things from different angles which are not used to treat together. So you suggested that maybe because many of you know a little bit about WMO but maybe I can say a few things about WMO. So I decided to give you a little bit of, oops now I have to treat that with, well, to give a little bit of historical perspective but mostly linked with the climate issues. And when it comes to metrology there's been a realization actually for now more than 200, 250 years that no country can do it alone. We need to cooperate. It's obvious to say, I'm stating the obvious by saying that the weather doesn't stop at the borders but in practice it was so clear from the beginning that no country can do it alone therefore cooperation was essential and the cooperation led in the middle of the 19th century to the establishment of the predecessor of WMO. And it is, we are not the oldest international organization, we are only the second oldest. That's very interesting. The oldest international organization is the ITU, the telecommunion. And if you think about it it was necessary for the telecommunion to exist before we came to existence because what made the difference for internal cooperation metrology was the availability of telegraph that you could exchange observation in real time. Of course the definition of real time is a bit tighter now than it was at the time but still it allowed for the first time observation to be exchanged fast enough to be used for prediction. Not only compiling the logs of the ships when they came back to the harbor but in real time. And from the beginning the emphasis was on protecting life, protecting property, in particular ocean travel at the beginning. Not yet aviation for obvious reasons. It was remember 1873. But one of the first tasks was, and it's still very much valid, is to encourage observation, standardize observation, exchange of observation, quality control and that is still valid. It's still one of the main function, one of the main mandate of the organization. No country once again can do it alone. Right now we have this hurricane hitting USA, Isaac. You cannot predict the hurricane over the Caribbean if you don't have the observation over Africa. They start their life as what we call in our jargon, easterly waves over Africa and then they travel, they evolve, they interact with the ocean and now we get a hurricane. So cooperation is essential and all the big country need all the small countries and vice versa. It was an NGO actually, IMO. It was a collection of directors of Met Services, including Sweden, and they met to try to coordinate that thing. But after the Second World War it became obvious that it was not sufficient. It needed to become an intergovernmental organization. Government needed to commit to this cooperation. And in 1951 we became a specialized UN agency. On the climate issue, we organized three major conferences. The first, the second, the third world climate conference. The first world climate conference, 1979, led to several things, but in particular to the launch of the world climate research program. It was launched only in 1988. It took about nine years, but still that was the foundation for the world climate research program. It also led to the, sorry, in 1980. It led to the establishment of the IPCC in 1988. And the second world climate conference was the decisive conference between before the Rio Plus Zero, the original 1992, the Earth Summit. It also led to the creation of what we call now the global climate observing system, which is, so you can see the first world climate conference concentrated on the science. Great. But to say, we need more research. That was great. But the second world conference says, okay, by the way, to do science, we need more observation. We cannot do science if we don't strengthen our observations and our data for that. But even that was not sufficient. That's why we had the third world climate conference. So, yes, we have now more solid observation. We have made huge progress on the, on our scientific understanding. However, there's now huge gap between the scientific information and what decision makers have available to make decisions. So we need to bridge this gap. And it was the main purpose of this third world climate conference. And we'll come back to that because this is the main theme of my presentation, how to develop a framework to try to bridge this gap. What I should have mentioned, which is not there, is that in 1928, we created a commission for climatology. So it's not a new thing, this climate issue. So, but it took a bit of time, as you can see, to to collect enough evidence to understand how things are working and even more importantly, to convince decision makers. And there, as you know, we are still struggling a little bit. There's still here and there a few skeptics. And these a few skeptics are very vocal. And anyway, so maybe I'll use that one actually. Sweden, Sweden, lovely country. But also a wonderful, a very active country in our discipline. We have a price, we don't have a Nobel Prize for metrology, we have the IMO Prize. It's not quite as prestigious, but still, this is the highest distinction in our discipline. And you can see that six Swedish person got this prize. It was awarded only after 1951. So you there was nothing before before the Second World War. And all these people have played a major key role in our discipline. Hossby has really been one of the contributor transfer metrology into what it is now, dynamic metrology. All the research he did is still fundamental for numerical prediction for climate modeling. He left his name to the famous Hossby waves. So it really a key pillar of our discipline. And then you have a number and I could I don't want to go into too many details, because all of them left their names. Professor Bergeron, for example, is one of the many people don't realize that we are still struggling to understand our rainfall forms. How you get out of this water vapor, you can get this condensation, what is the mechanism. And he was, he left his name to what we call the Bergeron process. And I'm sorry, I pronounce his name in a French way. I'm sure you pronounce it differently. But he's Swedish, definitely. And he made a major contribution to understand the formation of raindrops and therefore rainfall, which is still very much used now. Professor Newberg was also playing. I think he was one of the president of the WMO Council as well. Professor Bolin, I'm sure many of you knew him personally. One of the father of the IPCC and many, many, many other things. And recently, Professor Bengton, who I happen to know very well, because he hijacked me twice from France to go to ECMWF. He was my head of research when I was a young scientist at ECMWF. And then when he was a director of ECMWF, I was his deputy. And so it was a particular pleasure for me. That was the last time I came to Stockholm to give him the IMO prize. So he's, and as I'm sure many of you know him, he's still very active in many, in many respects. So Sweden has played really a key, a key, has made a key contribution to our, to our discipline. Now, I, I'm not a great fanatic of mission and vision statement, but I felt it was useful to summarize what are the key things. We have three keywords. Weather, water, climate. Whether it's obvious, it is in the name. Well, metrological observation. Climate is, for us, is very much seen as the looking at the weather over a longer period over the evolution of the weather, the variability. Water, we are looking water and you organize the World Water Week every, every year. So water, you know, is a complex issue. So the contribution of WMO in the water is on the hydrological side and more specifically the, what we call operational hydrology. So that's, that's where our niche is in that. And we very much cooperate with all our partners on water, in particular under the umbrella of UN water, which I was, which I'm chairing for, for a while. So the mission of WMO is really to strengthen, to facilitate this cooperation across all, all countries. To, and it was still struggling with that, to, to make sure that the observation network, but not only the observation themselves are, are, are covering our uniform of the planet, but they can be exchanged. So you need the infrastructure for telecoms, for treating this information, transform that into, into application. We still need these very essential standards. And you know, when you talk about climate, there are still some of these polymica are linked to the way data are corrected, because things, context is changing urbanization, the instruments are changing. So we need to, to, this is still a very essential part of, of our activities. And to, to definitely encourage more research and more training, more capacity building. Unfortunately, not all countries are the same level by far. And I'm sure this is not a surprise to, to any of you. The priorities have been shifting over the years. And last year, we had the Congress, which is our sort of supreme body, where all the members of WMO meet every four years. By the way, we have now 189 members. Essentially, it's universal membership. In Europe, just to give you a few examples, those countries who are not a member of WMO, are countries like San Marino, like Vatican, but I guess they have a direct line of communication. And, and a few, and, and a few others like this. But essentially, it's universal membership. What are the priorities now? And if you look at the bottom right picture, observation, we still need to put more effort on observation and exchange. It's, it's, it's a constant struggle. We improve things, satellites are bringing better, but still we need to come satellite information, don't replace traditional observation. They complement each other. And because of many reasons, in particular financial reasons, many countries are struggling to maintain their observation network. Second priority, which is getting more and more critical, disaster prevention. Disasters are increasing. They are increasing in frequency, but they are also increasing in terms of impact. There will be good news. I will come to that in a, in a minute. But disaster prevention is a major, is a major priority. And I was very, for me, it's one of the very important positive outcome of the Rio Plus 20 conference is that now disaster prevention has been recognized as a key element of sustainable development, which it was absent from Johannesburg. It was absent from the Earth Summit. Now it is recognized that you cannot have sustainable development without disaster prevention. And just look at what happens in 18, a few other countries. I don't think anyone needs to be convinced of that, but it was not part of the international agenda and the connection between development and disaster prevention. We need capacity building. It is, again, a constant struggle for that. But, but for a long time, we wanted to, to close the gap and, and the gap has increased between developing and developed countries. So we should not give up on that one. There's, we're not allowed to give up. We need to do more in this, in this area. There is also some other, for a number of reasons, priority on aviation. But I don't want to bother you with that. It's, it's because of the requirement that services to aviation become ISO certified. So this is a technical priority, this one. And the, the one on the top is the GFCS. And I will talk about that. It's, how can we provide all the sectors which are climate sensitive? And that's essentially everything. With information which is suitable for making decisions. And I will come to, to that. Now, I said disaster. There are bad news. That's the top right diagram. What you see there is statistics from the CRED. You may know this database maintained by, it's a Center for Research on Epidemology of Disaster Basin in Belgium. So they collect statistics on, on disaster. We are working with them. We cooperate with them. And over the last decade by decade, over the last 50 years, you see on the top, the increase in the blue column. This is the increase in the cost in, say, billions of US dollars per decade of hydro metrological disasters. So they've increased dramatically in, in costs. Going from something like 10 billion per decade on average to now probably over 500 billion dollars per decade. It's not only due to the change in the economy. It's not only due, so it's a mixture of many things. Change in the economy. More people living in vulnerable areas. Change in demography and also increase in the number of some of these, some of these events. By the way, the, I don't know how you would call this color, this red brownish, well, like the color you put on your wooden houses in, in, in Sweden. So I don't know whether it has a name, this color. So these, these other ones are the geological disaster. And you can see that there are still, when you have an earthquake, it's spectacular thing. But on average, the cost is less than the hydro metrological disasters. So this is the bad news. The good news is the bottom and now I need to remove Rebekah driver and Lisa and Besson, if I can. No, no, no, no. Okay. Can I remove because it's fine. Thank you. It's an important message. So the same graph with the same color code is for the number of people who die from these disasters. And you can see a dramatic reduction of the blue, of the blue column. So we are saving more and more lives. Still too many people are dying of the order of over 200,000 per decade. But, but still, it's much less than it was 50 years ago. Why? Because of early warnings. Because now we are for the hydro metrological disasters on all timescale ranging from tornado to drought. We can provide better and better early warning. And these early warnings are better and better integrated in in decision making, evacuation, protection. So we are saving life. And you see quite a different story for the geological disaster, earthquake, volcanoes. Actually, it would include tsunami. The other one, the brownish, the brownish color. It's a different thing. Why? Because for most of these disasters, there may be many reasons. But one of them is that it's not yet possible to give proper, proper warnings. So this, this figure, I think is very, very interesting. And we want to, we want to do even better for the hydro metrological disaster with longer timescale, like drought, which we, we, we think of, of climate timescale. And I will come to, to that in, in a second. So Rio, Rio plus 20, I mentioned already briefly that I'm one of the person who came back from Rio with a pretty positive analysis. Of course, some people were disappointed, maybe because the expectation that different people had from Rio were different. The higher your expectation, of course, probably the more disappointed you are. That was one of the challenge in Copenhagen. That is, the expectation was so high, probably, and realistically high that, but in Rio there were many things which I feel are very encouraging. I mentioned that the reference to disaster, that's very encouraging. Also the decision, the reference to water is actually stronger than it was in both Rio plus zero and Johannesburg. There's still, there's a very explicit reference to the need for, of course, safe drinking water, for sanitation, but also to what do we do with wastewater? Also, there's an explicit connection between water and human rights. Water, access to water is a fundamental human rights. So all these are encouraging. There was also a decision, and we are working on that. It was a major subject of our discussion, UN Water in Stockholm this, sorry, last week, that we are working on the development of sustainable development goals. And that's very important because the millennium development goal, we're focusing mostly on eradication of poverty and related issue. The sustainable development goal will be relevant, should be relevant for everyone. And they will not be time bound. So it's something which concerns our planet, the global planet and the future generation. So this, in that respect, Rio Plus 20 has been a milestone conference. Some people say, yeah, but you didn't define these goals. It's a failure. No, it's good that we didn't define the goals, because if we had defined the goals in detail in a rush, we might have ended up with ill-defined goals and goals that we cannot measure. Some of you might have heard about the sort of polemica about the access to safe drinking water. One of a million different goal was to say by 2015, half of the world, we should reduce by half the number of people who don't have access to safe drinking water. Great. Who can be against that? But the problem are to measure it. So it was not possible to measure it. So what was decided was to measure it through proxy indicator. What is this proxy indicator? The proxy indicator is to say we can measure the number of people who have access to what we call improved water access. In other words, if you get water from a tap, it's not the same as taking it from a pond, which is shared with the animals, with these things. So this has improved water access. The assumption was that improved water access was a good indicator of safe drinking water. Take Bangladesh. Bangladesh, many underground water is contaminated by arsenic, by the way, in a natural way. If you get it through a tap or through a thing, it's still unsafe. So it is not good enough, but it was the best we could do. So it is important that we define goals in a proper way, with ambitious and sparsional goals. We can, but goals which are ambitious, but realistic and also measurable in an objective way. So I'm very happy that now this is what we shall do over the next 12, 18 months ahead of the of the period going from beyond 2015. Climate back to our favorite climate. Climate of course, as we know, is complex and climate is not only about about looking only at the atmosphere or the ocean. You see, many things interact with each other and they interact on different scale. The global scale interacts with the original local scales and the local scale actually influences the other scale. So it is, it is a complex issue. And one interesting point to illustrate that is the El Nino, the Enso. For literally centuries, fishermen knew Peru knew about El Nino because it affected the catchment of fish. So they knew there was an El Nino, which was very much a notion phenomena. Metrogies, our discipline is a bit more recent. We have known for quite some time about what we call the southern oscillation. If the pressure, atmospheric pressure in Darwin in Australia is lower than usual, it was higher than usual in Taiti and vice versa. So that is the CISO effect. We call it the southern oscillation. And it's only literally over the last about 30 years, maybe a little bit more than that, that we understood that the two were two facets of the same phenomena. So we don't have an El Nino, a southern oscillation. We have the El Nino is the ocean part of the, and the southern oscillation is the atmospheric part. And the two interact with each other. And you cannot predict one without getting the other. And this understanding has led us to now a position where we can indeed predict the onset, the evolution, and the decay of El Nino slash La Niña phenomena several months or several seasons in advance. And it is not perfect by far, but it is much better than what people used to do before. You see, this is since the 1950. You see some, I cannot call it periodicity, some fluctuation. And people struggle with statistical method to predict that. And of course it didn't work because it's not really periodic. And now we come to a situation where we can do much better than the traditional statistical method. And it is used already for major decision making in several parts of the world. So this is one of the tremendously successful scientific progress over the last 30 years. But it is not fully translated into things which is used in decision making. So that was just one example to illustrate. Now you have all seen this curve. This is from the IPCC report on the left. Now we are convinced there's near unanimous consensus that, well, sorry, a few things are factually, they cannot even be skeptics on that. The greenhouse gas concentration are increasing. We measure that. So I don't accept that anyone can dispute that. We measure it with great accuracy. We observe the temperature increase. And you have seen this polymica in particular around Copenhagen and later to say, well, maybe it's not true. Maybe you are measuring the effect of urbanization, this data. No, sorry. We know how we do. We know how to analyze this data. But this temperature increase, the question is, can we attribute it to human activities or not? Or is it part of some, some natural variability? And the last IPC, every IPC report from the first to the fourth went one step further in in stressing that indeed it was due to human activities. And the last one says it's beyond doubt. Every report will go further because the evidence gets stronger and stronger. And it's true for a long time, the signal was difficult to extract from these variability. But now, now we are, we are beyond that. And the challenge of climate change, whether many challenges, but one of the challenge is that it makes, how to put it, in the past, many of the decisions on, on, if you built a dam or something were based on statistics of the past. So you decided to dimension your things based on return period, like the Dutch are very vulnerable to storm surge because of the low lying things. So they decided, okay, let's protect against something which would happen every two, four, four, five hundred years. So you decide what is the, the level of protection you want and fine, you can do it. If you have the technology and the money to do it, you can do it. The problem is that the past now is not sufficient. What used to happen maybe every hundred years might happen every 10 or 20 years. So it's quite a different context. So to make decision, the past is no longer a good indicator for the future. And it's, it's very tricky to come to decision, to make decision making not only based on statistics, but also based on scenarios on content on it's, it's the decision making, it's a different way of, of, of doing it. So how do we identify the needs? Well, the needs, unfortunately are not the same for the various sectors. And then on the same, even in one sector, for the various levels of decision making. If you take agriculture, for example, the farmer will need some type of information, the farmer, but the person who is managing a dam, which is used for irrigation, needs a different type of information. So we need to, we need to really identify these various sectors, which covers essentially all socioeconomic sectors and to try to find what do we need and iterate, what can we do for that? It's a big challenge and we feel that it is, it would be unrealistic to try to address that all at once, that to say, okay, let's solve everything at once. This is not really realistic. But definitely we need to, we need to analyze that a bit more in detail. And clearly right now, in most countries, we don't have enough information available. So this is why, back to the Third World Climate Conference, we came to the conclusion that we need to establish a framework for providing these services in a way which can be used for decision-making to the various sectors. This decision, three years ago, was taken unanimously. Now, those of you who have participated in the COPS in various climate discussions, you know what our difficulty is to get a unanimous decision. This was unanimous. No disagreement. So how do we do it? We put in place a high level task force, which made proposal for the WMO Congress last year. And once again, Congress decided unanimously to develop that. Fine. All that is great. When I say unanimous, it didn't go without discussion. I can tell you, it was tough. It was but still, at the end of the day, unanimous decision to do it. And now we are in the process of translating that decision into concrete action. So we immediately put in place a special team. Felipe, he's somewhere. Felipe, he's the head of that team. So if you want any more question, any more detail, this is the man. This is the man. And he has a big task is to prepare for an extraordinary session of our Congress in a few, in a couple of months from now. When I say extraordinary, it's really extraordinary. It has never happened before. It's the first one in the old history of WMO, which would be focused on the development of these global framework. What do we do? What is the governance? How do we implement these things? And the way, as I said, we cannot do everything at once. So let's try to find out what are the priorities we should tackle. Definitely. And I will concentrate only on some of these, some of these boxes to do to do the purpose of this framework should be operational. The if you have a user, an operational user, he has to be, he has to be able to trust that the information will come. You cannot have something which is done sometimes or not sometimes. It needs to be operational services. It will have to be done on several scales, global, regional, national scale. Even the biggest country in Europe, no country can do it alone. The countries are getting together through various mechanisms. In Western Europe, there are many mechanisms where they cooperate with each other on satellite with UMEDSAT, on modeling with ECMWF and the UMED, there are many, many mechanisms, there are networks of universities. No country can do it, can do it alone. So we are going to establish some global structure, some regional centers, and of course, there will be national structure. We want to put the priority on the most vulnerable. And the most vulnerable are also the least developed countries because the two issues have definitely a connection. We identified, and I'm speaking, Philippe, correct me if I'm wrong, we identified through a survey 70 countries which right now have either absolutely nothing or very little and suddenly totally insufficient to provide even the basic services. It's a huge number. Out of 189, 70 countries have essentially nothing and very few countries, even in Europe, can say it's satisfactory. I would, I would even argue no country as, as enough right now. So partnership is essential because we are not talking only metrologists or or sonographers. We are talking, we are talking all coming, all kinds of communities, including communities which traditionally are not used to work with each other. Like, for example, when it comes to climate, demography is important. Normally metrologists will not talk to demograph, to demographic experts. Economy is important. And I could, I could, I could go on and on. So we need to establish new partnership which are not deep rooted in our scientific culture. Data exchange, we, I discuss with some of you before, before the presentation about the detection, it is a challenge. We have pretty good basis for metrological data exchange. It's significantly weaker in some other areas like hydrogy. It is non-existent in some, in some of the things which are, which are to be covered by this global framework. So there are many, many challenges to be addressed. And for the sectors, instead of trying to do everything, let's concentrate initially, and insist on initially because later we shall cover more on four priorities. We identified these four priorities as water, information for water management, food security, health and disaster risk reduction. They are not parallel, parallel issue because interact with each other. Water is also there in food security, in health, in disaster risk reduction. And disaster reduction is also there in water management and so on. These things interact with each other. We felt these were the four initial priorities. Why did we select those? We selected those because we wanted not to reinvent the wheel, but to map our priorities with those which were defined at the global level. Food security is one of the global issues. Water management, this is why this world, water week in Stockholm is so important, is a top priority. Disaster prevention, you can see these priorities are top global priorities. So when we discuss with governments, we don't have to convince them that health is important. Don't take it for granted. How do we do it? How do we get the link? So this is how we decided to set up these four initial priorities. To practically to implement that, we define five pillars or maybe, yeah, let's say four pillars and a foundation. The pillars, observation monitoring, we need to do more. It's not enough. Research, we need to do more. Second pillar, and these are really pillars, but we need to develop also an interface with a user because this interface often doesn't exist. And how do we afterwards develop products which can be concretely used for this in making? And this is the user interface platform. This is new. This doesn't exist in most countries. And all that has to be on solid foundation. And the solid foundation is capacity building. So we need to do all these, all these issues. Observation, just to illustrate that there are many gaps, but you know that, you know that. Research, no, I don't want to spend too much time on that because I'm so passionate about that that you would have to bear with me for many hours. I want to, I want to talk a little bit about that because initially we tried to present it as a matrix, two dimensional matrix, and clearly that's within managed. It's more complex. It has many more dimension. The minimum we managed to do with the three dimensional matrix and even that I think is a bit too simplistic. But we have to take the geographic scales into account. That's the top global, regional, national, local, the time scales. And the global framework will concentrate on time scales ranging from seasons to decades. Season like prediction of El Nino to decades. What do we do with the RPC scenario? How do we plan for the future? And we should have to deal with the various aspects of this data management analysis, monitoring, prediction, products, delivery. So this is sort of to try to structure our action. The user interface, because I said this is something new. So this is something where we would like to, we have to to do a bit more even conceptual work on on that one. Here you see the global, regional, national community, meaning local, local level and and many many aspects. We need to get feedback from the communities. And it's much more difficult than what you think. You have many conferences where we say, oh, we need to get the feedback from the health sector. And we invite a medical doctor. That's not one medical doctor. Doesn't mean that we have the feedback from the health sector. One farmer doesn't mean that we get the feedback. So we need to organize that in a systematic fashion and the needs of different different countries, different communities, different. So it is an incredibly complex issue. And we are now discussing with our partners, for example, for the health, we want to make full use of the networks of the World Health Organization. It's a priority. We would like WHO to lead that food security. We want FAO and the World Food Program and a few others to lead that disaster reduction. We have a structure in the UN system. ISDR. We want that to play a role and water. Well, we have UN water. So let's not reinvent the wheel. Let's make use of the existing mechanism. But there are many things you see beyond the dialogue. We need also a lot of advocacy outreach. So many, it is a challenging task. Let me give you just a few examples of what we mean by climate services. And it's based on things we are, which are being done now in an adequate way. But it's just to illustrate what can be done. Africa is probably the continent where we have made the best progress on structuring that. We organize for various sub-regions in Africa, what we call Regional Climate Outlook Forum. What is it? We get the experts from a sub-region. In this case, it's the Horn of Africa. And these experts get together and they elaborate ahead of the next rainy season. Consensus prediction of what is the likely, for example, here rainfall. Is it going to be above normal? What is the probability? You have three categories in this book. If you take the light blue, for example, it says that there is 40 percent probability that it would be above normal, 35 percent probability that it's near normal, and 25 percent that's below normal. It's a real example, this one. So it's not a theoretical one. It happened. And this is done in a consensus way. And they have access to all the information from all the major centers of the planet, all the experts are coming. And for many of this forum, we have also the key representative of the key user group. But you can see how difficult it is to use this information. It's useful, but it's limited and it's challenging. You see 40 percent, 35 percent, 25 percent? It's not easy to make a final decision with that. So how is that translated? And let's stay for a while on the Horn of Africa. On the top right, this is information which would be fed to organizations such as the, this case, the World Food Program. And you know the World Food Program is having quite a challenging role in when there was this drought in the Horn of Africa, because it's not just a matter of bringing food after you realize it's widespread. It's anticipating, prepositioning, getting, and it's not always easy even to, you see where Somalia is and the parasy in the thing to bring the food is by boat is a challenge, to bring it by plane is a challenge, to bring it by land is even more of a challenge. So there are lots of logistic issue and now they do use this information practically for their activities. And they're very, very happy. And that's an international organization. But also at the national level, the governments are using that more and more and Felipe could talk a lot more about it. For example, in Ethiopia, there's a very interesting scheme which has been developed with the government authorities together, I think with the World Bank and with the World Food Program as well, which is, you can think of it as a sort of insurance thing. Let's not wait for the drought to strike, but let's anticipate, let's say this kind of a financial instrument so that if some indicators are exceeded and the referee is the Ethiopian Metrogic Authority on precipitation, humidity, blah, blah, blah, temperature, automatically it gives access to some resources. And that means that it allows a much, much more effective response. It has been so successful that it's being replicated in Malawi, maybe Mali as well, or is it anticipated? It's a different thing, but in Malawi. So there are, this information is now translated, not only in traditional response, but also in linkage, linking with some financial instruments. Another example is on meningitis. You know, you see what is called the meningitis belt and meningitis happens to be more prevalent when it's dry, when you get these dust particles. And because of this little forecast, you can anticipate that. First of all, meningitis, one of the challenge is that you have vaccination, but the vaccination first of all is expensive. And it's limited, its effect is limited. So if you do it too late, it's too late. If you do it too early, it may be a wasted investment. So to optimize these activities, I'm not a medical doctor, so bear with me that what I say could be misleading, but what the message I'm trying to get is that you can optimize this action by linking it. And it's done right now. There are similar things done for malaria as well. So we can use this information provided it's organized in a proper way. So it's now, how do we how do we see the next steps? Definitely, we want to to to define the framework because you cannot have cooperation based just on ad hoc bilateral agreement. It has to be a global agreement. You need to structure that if you want to be effective, not to waste investment, you need to have a structure. You need to define national mandates who will be responsible for that at the national level. Some it should not be just a collection of good will. Good will is essential, but I'm sorry, it's not sufficient. It has to be organized. You need to strengthen capabilities in the all the key areas I've I've mentioned. We need to find a way that these various communities, climate, agriculture, food security, just to take an example, they can they can talk more to each other, health and climate. Some of I'm I'm coming from a country which was badly affected by the severe heat wave in 2003. The World Health Organization estimates that in Western Europe, in 2003 between difficult to know, but between let's say 50 and 80,000 people died out of the heat wave. Think about it. It is a major natural disaster. 52 to 80,000 people dying from a disaster. What went wrong? Well, actually, it's fascinating. The health system was good. The metrological warning were good. And still in France alone, 35,000 death out of that. So something went wrong. What went wrong was the connection between the two, the two disciplines which were not enough connected. Of course, lessons are learned. But you know human nature often lessons are learned only after a disaster. But what we want is to make sure that we don't have to wait for even worse disasters so that lessons will be learned. So it's not a new problem for developing country. I took on purpose an example in a developed country to show it is all countries will benefit from that. So in order to test, we are not very maybe innovative, but it's a very effective way. We want to have a few pilot projects. And we selected the pilot projects so that they correspond to, first of all, the four initial priorities, but also country with special things. And Philippe in the question could tell you more about the pilot project. I think there's one in Chad. And that is Nizhe. OK. OK. So we are trying to find a number of pilot projects. So that's that is what we shall do. And that's it. So this is my conclusion that many shoes are interrelated to each other that we cannot look at sustainable development without looking at these other aspects, climate change, disaster prevention. And now we want to map our action using the framework of the development of the SDG, the Sustainable Development Goals. But to do that, we need to really put more efforts and capacity building on multidisciplinary partnership. Capacity building to come back to that. I'm not the only one to say that I know it's almost stating the obvious. But unfortunately, the obvious is not sufficient to attract resources. Should be seen as an investment, not as an expenditure. And the framework is really a key opportunity to to do that. So fun thing. And I hope I will not get lawyers upset by misusing the logo. So I try to combine the WMO logo with with something. Thank you very much. Susan Tak. Thank you very much indeed, Michelle, for a fascinating presentation with with lots of content, lots of content that's very relevant to the work that we do at SCI, where we also try and translate science into policy and support decision making. Because that was nice and long, the presentation will go straight to some presentations from SCI staff. And first of all, Richard Klein, who leads our reducing climate risk theme. Good morning. And thank you very much, Michelle and other WMO colleagues for joining us here at SCI. And thank you for a very inspiring and fascinating presentation. I don't want to undermine the importance of your message at all, but I would like to add something to that. And that is you've emphasized the importance of climate data, climate information for decision making. But I would submit that climate data and climate information are necessary but not sufficient to provide climate services. Why do I say that? Based on some of the work that we've done here at SCI, and I'll give a few examples, we found that the model by which people tend to think about climate services is one that's very linear. It is the assumption is that as long as you've got the right information at the right place, action will happen. Decisions are being made. And what we found in research on adaptation, on research in other fields in environmental studies that this is social science that is a very complex process, even if the information is available, even if the information is presented to presumably the right kind of people. Decisions are often very complex. They aren't made, or there is a series of trade-offs with things that have nothing to do with climate change to start with. For example, a program that SCI is working on together with the Swedish Meteorological and Hydrological Institute and several other partners funded by the Swedish Foundation for Strategic Environmental Research. Sweden, which stands for Swedish Climate Impact and Adaptation. The role of SCI in that work has been to investigate factors that influence people's decisions to act or not to act in a phase of climate risks. And it's been in-depth research with stakeholders first here in the Stockholm region. And now there's an in-depth case study in the forestry sector in Sweden where we found that people, first of all, are very different perceptions of risk, but also respond quite differently when presented with climate information. Climate information comes from the climatologists the climate modelists here in Sweden. What we found is that they operate, obviously, on different timescales that the information might be at a level of position or detail that they find very difficult to relate to their day-to-day activities and that their day job is one in which they have to juggle many different responsibilities and climate is one of them. So in order to put climate services that they were basically presented with, the climate information that they were being presented with to good use requires an additional step. A second example is the recent IPCC report on extreme SRECs which a colleague of mine Lisa Shipper and myself were lead authors of. And that report has a strong section on climate extremes on projections of climate extremes under different scenarios. But the majority of the chapters are actually dealing with how does one actually address those disasters? How does one use the kind of information? And you already mentioned the 2003 heatwave in France. An interesting example or an interesting comparison was that in that same year there was also a big heatwave in India. Whereas the people in France and you said all the information was available, the people there who were most affected and most vulnerable were those that the elderly who lived alone and who were even more isolated because family might have been on holiday and weren't able to respond in the way they could have respond. The people who were most affected in India were landless laborers who had no choice but to work on the land of others until they literally dropped dead. So the vulnerability is very different to a similar meteorological event. And that also suggests that the kind of information you need to respond effectively to reduce people's vulnerability goes beyond just the climate information. This is about issues of development, equity, rights and so on. Hurricane Katrina is a similar example. The disaster that took place in New Orleans wasn't primarily due to the strength of the hurricane or even the failing of the levees. It was an issue of social inequality within the city that affected one particular group in particular. Third and final example of work that we're doing within SCI is linked to the global program of research on vulnerability impacts and adaptation, PROVIA, which some of you might be familiar with, which has been set up as a counterpart to the World Climate Research Program that you've already mentioned. If you think of climate science or climate research in IPCC terms, World Climate Research Program focuses very much on the physics and the heart science of climate change of the IPCC working group one kind of research. And we felt that there was something missing that represents the working group two kind of research on vulnerability impacts and adaptation. So UNEP about three years ago took the initiative also in collaboration with WMO and UNESCO to set up a counterpart of WCRP to encourage coordination and dissemination of research globally on vulnerability impacts and adaptation. And I'm part of the scientific steering committee of that. And one of the issues that we found is that to reduce vulnerability effectively and support adaptation, one needs to go beyond identifying the issue. In other words, to go beyond providing the climate date and climate information that is of course essential, but what we say not sufficient. One of the activities that we're involved with is the revision of guidance to be used by countries developed and developing or also sectors to assess their vulnerability impact and adaptation. The current guidance that exists was provided by the IPCC back in the 1990s which very much took a linear approach. These are the climate models. These are the climate scenarios. And this leads to an understanding of what could be your climate impacts. And once you know what your impacts are, then you'll automatically adapt to that. Well, we know from a lot of research that that's not how it works. That even if the information is available, there needs to be an additional step also beyond capacity building that's part of it to ensure that climate services are indeed being put to good use. In fact, some researchers Maria Lemos in Brazil wrote an interesting article recently that suggests that the availability of climate services or climate information and climate data could actually increase inequality in Brazil. She gave an example where in agriculture, the commercial farmers in northeastern Brazil were able to benefit from the climate information that was made available. But the small hold of farmers, the non-commercial ones, actually were either lost. They were outcompeted. And this is one of the aspects that needs to be taken into account. Now, in your presentation, you emphasized the need for partnership within the global framework of climate services. And I would argue that Provia is very much ready and with Provia SEI is very much ready to step in and ensure that climate data, climate information is complemented with social science and other information that ensures that climate services are being put to good use to those who need it. Thank you very much. Thank you, Richard. And what we'll do, we're going to take one more presentation from SEI. And then, Michelle, we'll give you a chance to respond, if you like, to these presentations and then open up for questions from the floor or even from anyone joining from the webcast from overseas. But we're very lucky to have Maria Escobar, who's from our US Center, another benefit of having this talk during World Water Week. So, Maria. Yeah, I have this. Do I have to turn it on or it's fine? OK, so thanks for the opportunity to present the work that our team is doing. I work at the California Office of SEI. I am a hydrologist, a civil engineering environmental engineer. And I've been working for five years with SEI with some projects in California. But most of our work right now is in Latin America of my work. So I'm going to present a few case studies to to show how some tools that we are using require climate information and the way in which we are using them as well. So I'm going to talk about WIP, which is the tool that we develop and work with is the water evaluation and planning system. I'm going to describe some of those projects that we are developing and how we use meteorological data for those analysis. So this is a team work and David Perky, Jack Sever, who develops and does all the WIP programming is here. Then there's Laura Forney also that does agri-economic analysis and Vishal Mehta, who is doing some of the more urban related work. So these two here are the numbers of users of WIP in the different countries in Latin America. So there's a user base that are already using this software for doing water analysis in their countries. We don't know exactly what all of them are doing, but we develop some of our projects through those networks. And many times they contact us and tell us what they need and what are the type of projects they want to do. So that's what we are working on with this user base. This is the interface of WIP. This is a model of La Paz, El Alto in Bolivia. All the watersheds that provide the water to the cities, which are the red dots in the model and the rivers that go to the Titicaca Lake. So we are trying to represent the system. In particular, I'm going to talk about that project. And I also have a more detailed description of the projects here if you want to pass that around. The different elements that we model then are here on this upper screen, you know, the rivers, the canals, the reservoirs, the demand sites, and the catchments, which are climate-driven rainfall runoff elements. So all of these areas are the supply areas. It also includes glaciers, of course, because there are anti-unglaciers here. And then how the wire moves through canals, then goes to the cities and all the availability of water, whether or not is enough for the demand. There are also some agricultural demands up here that we are also trying to represent. So that's what we do with this tool, trying to represent the watersheds and the supply and demand interactions and the management of the infrastructure. So the different projects that are in the handout, we have some analysis of special ecosystems like glaciers and paramos and ecosystem services as well. We try to provide information to do some wire-benefit sharing analysis as well. In Bolivia, that's the project that I was talking about. I'm going to talk more. Now, it's technical support to create a decision tool so to make decisions about the future infrastructure so they can keep up with the growth of the demands. And this is tied to the climate investment funds and PPCR programs. So the idea is to be able to produce information and create scenarios that, so this infrastructure that are built in the future can really integrate climate into its planning. Then we have the KITO vulnerability study that's being done with Lisa Shipper. It also incorporates climates. It's not only on the vulnerability of water but other sectors as well. And in Colombia, we have several projects right now being founded by USAID. And the focus of this is to create and build capacity also for climate planning. So some common points of all these different projects and this is the city of Pereira in Colombia. This is a watershed in Peru in Pura where there are many users and including agricultural users and this is the city of La Paz. You can see how there are some urban and rural dynamics going on in all the different projects. There's also the conservation versus use of the resources interactions. So either the conservation of these ecosystems that provide the services that control and regulate the water in the watershed. And finally, the climate impacts on provision of the hydrologic ecosystem services. So how the climate is affecting the provision of these ecosystem services like glaciers and paramount. So the way in which you use all this information for these different projects is weep in these elements that are the catchments which represent areas of rainfall runoff. There's some data associated to each of those elements and we create databases where we input that information and manage that information so it can be put into the models. So the data that we use and meteorological data needs and what we have discovered through these projects is that we need historical precipitation, temperature, relative humidity, wind speeds, DMs, land cover type and stream flow as input data for the hydrologic models. We need the development of data processing procedures that are validated by meteorological organizations to reduce the uncertainty and increase the confidence of observed data. So it's very common that the different meteorological organizations, they have observations, they have collected the data for a number of years but many times they don't even trust their data or the processes, the way in which they process data. So we have discovered that it's important that there are some procedures that are validated. There's also the need for filling the gaps and comparing observed data with global data sets because it's common to find gaps in the data so it would be very important also to be able to fill in those gaps with global data sets. We also need future climate scenarios that are validated with observations and scales that are useful for specific analysis. A notion of uncertainty associated with the scenario so that this can be factored into planning and decision making. So since the data not necessarily are validated, then we need to have a good understanding of that uncertainty for the history but also for the future climate. And we need tools for processing the data to fit the models at different temporal and spatial scales because as you were pointing out there are different global, regional and local scales at which these analysis are happening so we need to know better. So the idea is that I think there are many connections with what you were saying and I think we can also help making those connections with the local people that are really using these for planning on their climate uncertainty. And that's all I had to say. Thank you very much, Maria. Now I wonder, Michelle, whether we could invite you back up to the front to take questions and so those watching in can see you and whether you want to reflect on either of the presentations and first of all. Maybe just very quickly on the last one because indeed what was raised about the quality of the data is indeed a serious issue, not always easy. We have standard, we have procedures to do that. However, even for the quality control it is not always, it has not always been done in a consistent fashion. Sometimes even the metadata which would be required to do that are not always available but there are standards actually. And when you talk about meteorological organization I assume you are talking about the various national met services, yeah, yeah. So they follow normally the WMO guidelines but there's something else I would like to add to what you say because it's even more challenging in many countries, including Latin America. There's a number of very precious record which are in paper form, which are not yet that digitized. Sometimes we don't have the proper metadata we don't know, for example, temperature with which instruments they were made or wind measurement we don't know always exactly the location, the height, the context but still it is valuable information. And we are promoting this data rescue and data recovery because much of this data is, well, it's not always stored in good conditions so the paper in many country can, so it's very important to protect this data. But we'd be very happy to liaise with you on that. Sorry. Okay, before we go to the floor for questions I thought I might just ask one general question and in your presentation which had a lot of content Richard also asked about the partnerships. Now delivering climate services is an extension of the WMO's role. We look at the history from hard science to supporting users and specifically in the research community what opportunities are there for SCI and other research partners to engage with WMO within the framework. Yeah, the partnership indeed and I can confirm you mentioned Povya we are very much in contact with of course UNEP and essentially you can consider that all the key United Nations system partners in this domain are part of it. And if you look at the various pillars the Povya would fit more into the data, the user interface platform and user and that's what you mentioned. When it comes to research there are again many actors but I think we have to look at the research not only in the traditional WCRP, the World Climate Research Program because as you mentioned the research is not only about the physical thing it's also research into the application it's research into also how to make decision in the context of uncertainty. It's research from in economy, in health, in so it's multi-faceted research and we are going to leverage on the research activities of the various partners in the UN but beyond that for example a key partner a strategy been IXU, the Internal Council for Science we still use the old acronym IXU and this has been bringing us a very interesting thing because they are multidisciplinary. They cover not only the sort of physical research activities but they go into the economics, they go into the social science, the human dimension so that is also something that we are going to elaborate. So back to your specific question are the SEI could contribute? We are building this research pillar they are consultation and at this stage when we define the process maybe Philippe you could say more I would like Philippe to answer in more detail because they are consultation we very much welcome your feedback. I don't know, I think maybe Philippe could... Thank you Michel, Philippe we'll use the microphone for the webcast. I'd like to start by kind of reacting to some of the comments in terms of the additional need of having more than just the climate information. I come from a part in the world where I came across that particular thing. In 1997 I went to speak to a particular community leader because we were introducing a color coded warning system and I said well now you have the benefit of you'll see the flags being raised when a tropical cyclone is coming. And his reaction was well I would not consider what you are trying to tell me or to give me. And I said but we have the best science we could tell you that a tropical cyclone is going to come your way within 48 hours and you have enough time to evacuate. And he says well son I'm 7, 8 years old if I'm to die I'd rather die by a tropical cyclone. And I said but I still don't understand what you mean. So well what I mean is if you tell me to evacuate and I evacuate I'll die anyway. I said but how would you die anyway because you've already evacuated. I said no by the time I come back my assets would have all gone and I'm too old to start a life all over again. So there was a very special need. His assets were in a sense more valuable to his life. He was saying well you can give me a good warning but I will not evacuate because there's a social problem which I would not ensure that when I come back I have to go back to my life. And I think from that there's a very good and successful case which is the Bangladesh case. In Bangladesh they've learned throughout the years that by building cyclone shelters was not enough because people still not evacuate. So what they did was they built cyclone shelters and the bottom floor or the bottom part of the shelter is for animals that when people can evacuate they bring along the animals and because animals were one of the reasons why they never evacuated they wouldn't leave them behind. So I think there are good lessons to learn and the point towards the fact that that is probably quite complicated because of the specific nature of, in local nature of the way people are going to react to warnings. So I'd like to now make a bit of publicity about something we are doing and I think that knowledge on how do you integrate other elements in addition to climate service should come through what we're trying to establish now through the user interface platform which is one of the main and the innovative components of the global framework for climate service. We're going to have a conference in October, 26 to 27 of October, which will focus exactly on the user interface platform. How can these platforms be established and how they should facilitate understanding specific needs and basically orienting not only research but also observations and other needs that would help responding to those specific needs. So I'd want to invite you all to attend. We could send you specific information on that so you could also share the type of findings you have from your research. Now going back to the question of how we are developing these implementation plans, the global framework for climate services. The way we devised to develop the implementation plan was to make it a very bottom-up initiative in the sense that the framework could have to be developed to respond to specific needs. And one of the first activities we did was to conduct consultations, consultation meetings under the main pillars of the framework, which are those five to which the Secretary General talks, but also under the priority areas which are the four priority areas. And those provided the basic element that would have to be taken into account in developing the framework, but also helped in identifying experts who could contribute to the process of the development of the implementation plan itself. We've just ended on the 19th of this month, the last round of review. Hopefully some of you might have contributed to the review process. And after that we're going to have the document finalized, in fact, it's Friday this week when we have to finalize the document and then submit to the Extraordinary Congress that's going to be held in October. So in a sense, there was a bit of always trying to engage as many people as possible. Those who have not had the opportunity to contribute to the review process would invite them to also come to the Extraordinary Congress and eventually share their own perspectives as part of the whole initiative. Thank you, Philippe. We'll now take some questions from the floor. Yeah, I'm David Perkey. I manage the water group within the US Center of SEI where we develop the WEAP software which Jack Sieber has been programming and I work with Marison, the activities in Latin America as well. You had a point in your slide which was, we can always assume that the historical climate patterns will be good points of reference for the future. I don't know about in health and other sectors, but in water that's like a fundamental pillar of the way water planning has been done. And so a lot of our research is really getting at this question of how do you make decisions about water management, about infrastructure investment, about environmental flows in the face of deep uncertainty and we're nesting our WEAP software within some very innovative decision support frameworks such as robust decision making developed by the RAND Corporation. And a question that always comes up when you're talking with water planners about this new paradigm about decision making under uncertainty is there still always wanting to have this sort of probabilistic assessment of what, okay, we know that it's uncertain but try to tell us what the most likely outcome is. And in my work and in our research and I think being influenced by RAND's robust decision making approach is that we really can't provide that information. Really what we need to look at is sort of solutions that are robust across the whole spectrum of possible outcomes. Do you have an opinion about whether we should be talking to our end user community about the probability of future climate conditions or now and perhaps in the future or is this idea of looking for solutions that are robust across the full spectrum really the wise way to proceed? Thank you. Actually, this is one area where there's a significant amount of research which is being initiated now. There was not much research on exactly what you described but there is some research which is emerging and I would like to encourage more because it's not always possible to answer your questions. When you talk about the water sector, indeed it is an interesting sector for this application because the time scales are somewhat different than they are in several other sectors. Indeed it is one thing where you invest in infrastructure, it is the time scale considered are often of the order of decades which is not always the case in other sectors. You have many other sectors where the time horizon is of the order of years, sometimes months and sometimes even less than that. So water is particularly interesting. There are a few sectors. It's not the only sector but it's one of the sector where the people are already used to probabilities to uncertainties. So in a sense we don't start from scratch, there is a lot of expertise. Indeed what people would like is to have the most probable and the reason why they would like that, they would like to use this information in a way similar to one that I use, deterministic thing. I want to have one, tell me what is the most likely and then I will be, well it's not that simple because as you know you need to have in this, even if you have one scenario you need to have this if you simplify this typical thing, what is the cause of action, of not action, what happens if I do it and doesn't happen, et cetera. You have this and you have to weigh that with the probability of each thing to happen or not to happen. But when it comes to longer time scale, it's even more complicated because it's not, sometimes the average of the most likely scenario may not be the most important one because it could be that the least likely scenario, even if it's only 10%, could have a huge consequence or it could be that there are bifurcation, that you have two or three things. So it's really a different way to make decisions for some of these big decision makers. It's a lot easier for when I say big decision makers, talk about water, for example, the link between water and energy. If I'm the manager of a dam, there are many applications you can use the water in the dam for. One application is to produce electricity. One application is for flood management. Another application might be for irrigation and many other. Let's concentrate on these three applications first. And I'm going, bear with me, that I'm going to exaggerate for the sake of the argument. If I'm an electricity producer, what I want is as much water as possible. The more water, the more electricity, the more revenue. If I'm a flood manager, and again, I'm exaggerating, I want as little water as possible because if the flood is coming, I can absorb more water. So if I'm a farmer irrigation, I don't really care whether there's a lot or not enough water, but I know that if I don't irrigate now or in the next two days, my crop will die. So these three sectors often at the national level come under different decision-making authority. You might have a minister in charge of energy. You probably have a minister in charge of agriculture. You may, you are probably going to have a structure on disaster prevention. And very few countries as a way in this case to make a higher level decision where you have to arbitrate at a pretty high level because you know, if you lower the level of the water, you know exactly how much money you are going to lose in terms of lost revenue. You may not know whether the flood, it will be only a probability of a flood coming. So it's a tough decision, you are, and if you don't do that, and again, Philippe has been living in Mozambique quite dramatic experience of that where his country was affected by decision-taken upstream beyond the control of Mozambique. And so it is not only even a national coordination which is required in some cases. It is sub-regional or even international cooperation. So back to your question, I think we need to really look at, that's why I cannot have a simple answer, but it's a very important question you are asking. And we have to look as part of that how we can encourage countries to use this and it's easier to make this high-level decision than the individual farmer will have to make the decision you want. He wants to know what is the most likely, unless back to the Ethiopian example, there is a sort of protection, which is at a higher scale, which can spread the risk so that the individual farmer doesn't have to bear the old risk of his individual decision, but it can be shared. But it's a different way for all these disciplines to interact with each other. I don't know whether I guess. Hi, my name is Vishal Matha. I'm also with the US Center of SEI. I've been working on urban systems in India in the last couple of years, among other things, and building online platforms for communication access, I mean, easy access to information on demography and water supply. And also building online tools where people can build their own scenarios for the future of the city and see what might happen in terms of water supply into the future. One of the problems with urban centers in places like India is that the data on how people use water and where it's coming from is very scarce because pipe water supply is only like less than half of what people use. So people have hundreds of thousands of wells and so on. So what I'm exploring and I'm coming to the question through this roundabout way is public participation in collecting this data and building a knowledge base on urban systems. Is WMO thinking about that idea as well, the use of public participation and public collection of data? Actually, it goes much beyond WMO because in WMO, the data which come under the authority or coordinating umbrella of WMO are probably amongst the easiest to coordinate. When you come to atmosphere in most countries, this is under the authority of government authorities. Every country has a national med service of some sort. And there are a few others on pollution on things which may not fall under that. But actually, it's pretty easy. It's a lot more complicated when you come to water data and water not being only hydrology, water data in general. Actually, some of you might have because as part of the World Water Week, there was a very interesting seminar yesterday organized under the umbrella of UN water to address this kind of issue. And definitely for many of these data, we need to have also... We need to have different types of partnership. And there's also the question which is extremely difficult to solve is about the ownership, the sharing of these data which is... Because often the data are taken in a particular context and they can be either commercial consideration but it can be also nationalistic or a safety or security consideration. There can be many, many considerations. It is an incredibly challenging area. Thank you. James Gao from China Clean Water Alliances. Thank you for the both speakers. I have three points to mention about the keywords. One, you mentioned this disaster risk reduction, which is quite important. I have a fresh case in China. Actually, in the middle of July, I was in Kumamoto. It's a Japanese, one of the safest old city. But then the chaotic situation happens. It's raining, flood, then several people died. So when I go back to China to Beijing, the very evening there's a rainstorm but something happened is in the city, in the second ring road, city center, someone drying a Jeep and drowned. It could never happen before, but it happened. But another road is also in Beijing, 170 cars drowned on the highway. It could never happen. So it has something to do with climate changes but also has something to do with whatever, corruption, whatever, doesn't matter. But what's relevant to our point is how do we anticipate these kind of things? Because in cities, that's a heat island effect and that's corruption for the under sewage system which is lower quality and for someone has some diluted project, we occupy the land, have misuse, whatever could happen. But I think that is issue now. I mean for China now, I think SEI and quite a few other organizations or they shift that focus to other countries. China is big, so they have bigger problem. This is number one. Number two, like you mentioned, dam. Dam still, it is issue. I still remember when Clean Water Alliance announced its establishment, then quite a few UN people in China on their personal basis refused to participate if three gorgeous people participating and sponsoring the ceremony because they are against it because still it's debatable now. Personally I visit some of the upstream of three gorgeous where because there's no dynamic of the water when you have big pool, so they already lost the self-cleaning function and then quite a few algae and quite a few pollution happening. And also there's garbage as a sand, many, many problems. So how to weigh the balance. And China now I'm also in the Sino-Mienma Association. Still for the environmental project, we are not doing Myanmar for international society because of sanction, but Myanmar should be next on the list. China has problem with the Mee Song Dam because it's first time in Myanmar's history, probably everyone is against it, everyone. The left, the right, the official and the people. So it's really how to carefully weigh and balance in the issue. This is the last one. The last one is about this water and food security. Today one of my colleagues is addressing the issue that's how to use sewage water to irrigate the vegetable agriculture and what's the impact of that. And the impact is obvious, so. Thank you, maybe we'll take a couple more questions just to wrap up and then we can get your reflections one while we're over here. Michelle, you mentioned a couple of times the concept of index-based, weather index-based insurance. And that's come up quite a lot in relation to particularly poor farmers because as a mechanism the insurance company, if you're not familiar with it, the insurance company doesn't pay out on the actual loss of the farmer. They just pay out if certain parameters go above or below thresholds. So it's much cheaper system to administer for the company and therefore the premiums are much cheaper. It's a product designed for low-income farmers but the insurance companies have always argued that the main barrier to such a product is the availability of really local scale climate data because even at the valley level. So I'm interested in, Philippe, you also mentioned several examples where it's been up and running now. What the main barriers are to getting meteorological data at that local scale, is it simply a cost or is there some sort of historical legacy that also prevents that sort of really local scale meteorological data? We'll go take the mic from this way and we'll go through it. Do I answer now, what do you say? No, no. There's a, okay. So first of all, you asked four questions and I would not answer the second one because I don't feel quite competent to answer it. I would like to cover briefly the three aspects of your question. The first aspect had to do with something which is not unique to China, which is in many of the big towns and we are back to the point you were raising about is the infrastructure in the town dimension in a way which can cope with the current and future evolution of the climate and in many cases, the answer is no because either in many countries, there was no planning. Let's face it, if you go to two places like Manila, the evacuation system was not based on planning. It was, it developed in its own way. And, but even if there was planning, the planning was based on past data and the frequency of extreme events and in particular what is critical in this particular case you mentioned is floods and rainfall, heavy rainfall has not been taken into account. So it's important to take into account this for the future. The second thing you mentioned was Myanmar. And Myanmar, I want to mention something interesting and it's not a direct answer to your question but it's an opportunity for me to mention something. You know, they were hit by this cyclone with the associated storm surge which killed many people. And I don't want to comment on what was the political regime in Myanmar because, but what I want to say is that for Myanmar it was an incredibly exceptional situation. We couldn't find in our record any situation where a tropical cyclone would have this, well maybe in this action they need to do it the other way around. Which normally they would curve and this one went straight west to east and hit a place where there was no precedent of such a cyclone to hit that place. Now Myanmar is a bit like, the Philippines was managing Bangladesh. It's a bit like Bangladesh. You have a delta, this part of Myanmar, there was a delta, people are living in the branches and the warnings by the way were good. The warnings were good, the plane company got the warning, they could protect the planes, the people, et cetera. The problem is the people living in this delta. They got the warning. But what do you do with the warning? Evacuate, okay, thank you. There's no bridge to evacuate. You need to evacuate with a boat. But you don't take the boat if you're in the middle. So the challenge was daunting. In Bangladesh there are shelters. In Myanmar there was no shelter. Can we blame them or not for not having shelters if it has never happened in this place? There are many challenges. So if you invest, you still need to decide what is the risk you want to cover. So I think it was, Myanmar is a very interesting example and we should take the sort of emotion out of whether we like or not like the political regime. That's a different issue. But practically it's a very interesting challenge out to cope with these things which were completely out of the Gaussian curve. So I wanted to answer the fourth part of your question but now it just escapes me. What was the fourth question you asked? No, that was the second question. Okay, maybe it will come back. Yes, thank you. That's right. The sewage water, this is where I feel encouraged also by the Rio plus 20 conference. Because if you look at Rio plus zero and Johannesburg, the emphasis for water was on two things. Access to safe drinking water and sanitation. And there was no reference to wastewater. And now this is now identified as part of the Rio plus 20. I don't have, no one is the answer to what is the best approach to that but it's a problem that is to be addressed. Then yeah, you were asking the, but to some extent it was a common to some extent. Yeah, for these weather linked instruments, indeed they need to have enough data. Now, one of the limitation and that was the case in Ethiopia, the historical data are not enough to cover, to get this local scale. So as part of that, it is seen now as an investment including by the insurance companies that it is in their own interest to support that they should be better data. So definitely it's another incentive to strengthen this data network. For the past, you cannot replace those data which are not there, but you can to some extent have some proxy information. It's not as good. And the way which is being done, the best way which is being done is to reconstruct some of the past data through sophisticated data simulation. It doesn't have the same local scale, but still for example, many countries in Europe, in USA are working on what we call reanalysis. Actually Europe and USA are probably the most advanced in these things where you go back to all the data and you go through very sophisticated techniques how to reconstruct. And these instruments are very, very powerful to the point that actually, in a sense, it's a beauty of the way the atmosphere works. Because the information one point tend to influence, you can think of it of going backwards. If you know the atmospheric situation, you can sort of work backwards and recreate some observation. And by merging that sophisticated way, let me give you some example. We think now we could reconstruct maybe not perfect by far, not even very good, but good global maps of the weather maybe going back before we had many observations, 200 years, why? Take a ship log and you make a surface observation. Now the system is so sophisticated that this information in a way which is consistent with the basic law of physics can affect what happens in the upper atmosphere. So we can get a feeling out of a few scattered information. We can get a feeling about the global thing. It's fascinating the research which is taking place there. It will not be perfect, but that will give us some indication of some of these fluctuations. Fascinating research. Thank you very much. I think we've got time for one more question. There's one at the back. If this one's quick, we'll see if we have time for the next one. I'll ask the question quickly. I don't know how quick the response is, but maybe it's quick. I'm interested in the climate prediction part of your story and presumably there's a lot of modelling involved in that. Now the IPCC is doing a lot of modelling, but that's more assessing what's there. The area of work which I'm working on, the short-lived climate forces, there are lots of questions over say the South Asian monsoon, rainfall patterns, the interaction between climate change and then local pollution particles, sulfate, all of those things together. And I was just interested to know to what extent WMO is trying to develop and coordinate research or whether that's under another forum. I will give you the short answer and I would be happy to give you a longer answer, but that will be too long. The answer is this is coordinated mostly under the umbrella of the World Climate Research Program. There are a number of modelling centres in the planet. When it comes from the short metrological time scale to the long climate scale, the impact on the modelling is twofold. One is because of the longer scales, the resolution of the model is getting coarser and coarser. So that's a sort of negative aspect. But at the same time, the complexity of the model has to be more and more. You don't need a notion model to predict the next 20 minutes, but definitely you need a notion model on monthly to seasonal to multi-decadelle time scales. And you need to integrate more and more elements. Now all these models are of their own strength and weaknesses. And what is being realised is that to capture the uncertainty, one of the most powerful technique now is what is called multi-ensemble because of the different techniques. So there is under this umbrella of the World Climate Research Program, there is a lot of effort on this multi-ensemble. In other words, to get, you know, the way we try to capture the uncertainty is to run not only to have one run of the model, but to have maybe 100 run of the model with slightly different initial condition, physical package, blah, blah, blah, to modify that. And then you get a spread. You get and you try to derive from this spread probabilities. But what is even more powerful is to do that with different centres, different models. This is why we call it multi-ensemble model. And this is coordinated under WCRP. But it's not only WMO is playing a key role, but it's very much also with UNESCO, in particular the Intergovernmental Security Commission UNESCO and IXU. These are the three key partners of that programme. But more and more, we need now to include even some other dimensions, which were not covered in the original WCRP. For example, IPCC, you are right, IPCC doesn't do research, doesn't do modelling, that's the assessment. So in order for IPCC to do its job, we need to have something to assess. So this is where we encourage these, I think, but we need to integrate through the scenario, for example, even the economic perspective, the demographic perspective, the other perspective. Michelle, thank you very much indeed for coming to visit SEI. It's been a fascinating conversation. There's a lot of interaction, two ways I think with SEI as Marisa outlined. We are a user of information from WMO, but hopefully also a provider of insights from our research on how climate services can be used to support decisions. For those of you heading to World Water Week, there is a bus leaving from SEI at 11 o'clock. The fun bus will be leaving at 11 o'clock. But the last thing is just to thank you again, Michelle, a round of applause.