[Script Info]
Title: 
[Events]
Format: Layer, Start, End, Style, Name, MarginL, MarginR, MarginV, Effect, Text
Dialogue: 0,0:00:00.00,0:00:12.82,Default,,0000,0000,0000,,{\i1}rC3 preroll music{\i0}
Dialogue: 0,0:00:12.82,0:00:19.67,Default,,0000,0000,0000,,Herald: It is with much pleasure that I\Ncan now introduce our next speaker, so
Dialogue: 0,0:00:19.67,0:00:26.50,Default,,0000,0000,0000,,it's just started raining outside, but\Nthis heavy rain is not at all probably the
Dialogue: 0,0:00:26.50,0:00:32.98,Default,,0000,0000,0000,,extreme weather effects that we will hear\Nabout right now. The weather, the talk
Dialogue: 0,0:00:32.98,0:00:40.54,Default,,0000,0000,0000,,that we are being presented next will deal\Nwith extreme weather effects and how they
Dialogue: 0,0:00:40.54,0:00:45.18,Default,,0000,0000,0000,,are linked with climate change and how we\Neven know about that. Our speaker today
Dialogue: 0,0:00:45.18,0:00:51.80,Default,,0000,0000,0000,,is Fredi Otto. She's associate director of\Nthe Environmental Change Institute of the
Dialogue: 0,0:00:51.80,0:00:57.76,Default,,0000,0000,0000,,University of Oxford, and she's also the\Nlead author of the upcoming IPCC
Dialogue: 0,0:00:57.76,0:01:04.64,Default,,0000,0000,0000,,assessment report, AR6. And without with\Nno further ado, I give you the stage
Dialogue: 0,0:01:04.64,0:01:07.35,Default,,0000,0000,0000,,Fredi, please.
Dialogue: 0,0:01:07.35,0:01:12.28,Default,,0000,0000,0000,,Frederike Otto: OK, thank you. Yeah. Hi.\NIt's stopped raining here in Oxford, just
Dialogue: 0,0:01:12.28,0:01:16.28,Default,,0000,0000,0000,,about, but it's definitely flooded, so\Nthat might actually be something to come
Dialogue: 0,0:01:16.28,0:01:24.67,Default,,0000,0000,0000,,back to and talk about with respect to\Nclimate change. So. Whenever we hear or
Dialogue: 0,0:01:24.67,0:01:31.74,Default,,0000,0000,0000,,whenever today an extreme weather event\Nhappens, we hear about hurricanes,
Dialogue: 0,0:01:31.74,0:01:39.78,Default,,0000,0000,0000,,wildfires, droughts, etc., the question\Nthat is immediately asked is, was this,
Dialogue: 0,0:01:39.78,0:01:47.83,Default,,0000,0000,0000,,what is the role of climate change? And to\Nanswer that, for quite a long time,
Dialogue: 0,0:01:47.83,0:01:55.58,Default,,0000,0000,0000,,scientists gave an answer that we cannot\Nattribute individual weather events to
Dialogue: 0,0:01:55.58,0:02:07.72,Default,,0000,0000,0000,,climate change. But… Sorry, OK. But this…\NBecause the first, the one answer that
Dialogue: 0,0:02:07.72,0:02:14.65,Default,,0000,0000,0000,,people were giving were that, well, you\Ncan't attribute individual weather events
Dialogue: 0,0:02:14.65,0:02:20.95,Default,,0000,0000,0000,,or they were saying in a world where\Nclimate change happens, of course, every
Dialogue: 0,0:02:20.95,0:02:25.12,Default,,0000,0000,0000,,extreme weather event is somewhat affected\Nby climate change. And the latter is
Dialogue: 0,0:02:25.12,0:02:30.96,Default,,0000,0000,0000,,attributed too, but that does not\Nobviously provide much information,
Dialogue: 0,0:02:30.96,0:02:34.94,Default,,0000,0000,0000,,because it doesn't say anything about\Nwhether the event was made more likely or
Dialogue: 0,0:02:34.94,0:02:42.21,Default,,0000,0000,0000,,less likely or what the role of climate\Nchange was. And the first answer that you
Dialogue: 0,0:02:42.21,0:02:49.36,Default,,0000,0000,0000,,can't attribute individual events is not\Ntrue any longer. And this is... why that has
Dialogue: 0,0:02:49.36,0:02:55.13,Default,,0000,0000,0000,,changed and how that has changed. And what\Nwe can say is what the content of this
Dialogue: 0,0:02:55.13,0:03:03.70,Default,,0000,0000,0000,,talk will be. So ultimately, every weather\Nevent, extreme or not, is if you
Dialogue: 0,0:03:03.70,0:03:10.59,Default,,0000,0000,0000,,absolutely boil down to it is unique and\Nthey all have many different causes. So
Dialogue: 0,0:03:10.59,0:03:16.73,Default,,0000,0000,0000,,there is always the role of just the\Nnatural chaotic variability of the climate
Dialogue: 0,0:03:16.73,0:03:22.28,Default,,0000,0000,0000,,system and climate and weather system that\Nplays a role. There's always a causal
Dialogue: 0,0:03:22.28,0:03:28.42,Default,,0000,0000,0000,,factor in where the event\Nhappens, whether it's over land, over a
Dialogue: 0,0:03:28.42,0:03:37.01,Default,,0000,0000,0000,,desert, over a city or a forest, but also\Nman-made climate change can have an
Dialogue: 0,0:03:37.01,0:03:46.62,Default,,0000,0000,0000,,influence on the likelihood and intensity\Nof extreme weather events to occur. And so
Dialogue: 0,0:03:46.62,0:03:52.28,Default,,0000,0000,0000,,what we can say now, and what we mean when\Nwe talk about attribution of extreme
Dialogue: 0,0:03:52.28,0:04:00.06,Default,,0000,0000,0000,,weather events to climate change is how\Nthe magnitude and likelihood of an event
Dialogue: 0,0:04:00.06,0:04:07.43,Default,,0000,0000,0000,,to occur has changed because of man-made\Nclimate change. And in order to do that,
Dialogue: 0,0:04:07.43,0:04:14.30,Default,,0000,0000,0000,,we first of all need to know, what is\Npossible weather in the world we live in
Dialogue: 0,0:04:14.30,0:04:21.16,Default,,0000,0000,0000,,today? So say we have a flooding event in\NOxford and the question is, was this
Dialogue: 0,0:04:21.16,0:04:27.29,Default,,0000,0000,0000,,climate change or not? So the first\Nquestion is we need to find out what type
Dialogue: 0,0:04:27.29,0:04:34.24,Default,,0000,0000,0000,,or what kind of event is the heavy\Nrainfall event that leads to the flooding.
Dialogue: 0,0:04:34.24,0:04:39.80,Default,,0000,0000,0000,,So is it a 1 in 10 year event? Is it a 1\Nin 100 year event? And in order to do
Dialogue: 0,0:04:39.80,0:04:44.78,Default,,0000,0000,0000,,that, you can't just look at the observed\Nweather records because that will tell you
Dialogue: 0,0:04:44.78,0:04:50.34,Default,,0000,0000,0000,,what the actual weather that occurred is.\NBut it doesn't tell you what the possible
Dialogue: 0,0:04:50.34,0:04:55.70,Default,,0000,0000,0000,,weather under the same current climate\Nconditions are. And so we need to find out
Dialogue: 0,0:04:55.70,0:05:02.68,Default,,0000,0000,0000,,what is possible weather. And to do that,\Nwe use different climate models. So we
Dialogue: 0,0:05:02.68,0:05:07.63,Default,,0000,0000,0000,,simulate under the same climate conditions\Nthat we have today, possible rainfall
Dialogue: 0,0:05:07.63,0:05:14.75,Default,,0000,0000,0000,,events in December in Oxford. And we might\Nfind out that the event that we have
Dialogue: 0,0:05:14.75,0:05:23.21,Default,,0000,0000,0000,,observed today is a one in 10 year event.\NAnd so if you do this, look at all the
Dialogue: 0,0:05:23.21,0:05:27.52,Default,,0000,0000,0000,,possible weather events, you get a\Ndistribution of possible weather under
Dialogue: 0,0:05:27.52,0:05:33.31,Default,,0000,0000,0000,,certain conditions, which is shown in the\Nschematic on the slide here in the red
Dialogue: 0,0:05:33.31,0:05:40.34,Default,,0000,0000,0000,,curve. And then you know that when it\Nrains above, say, 30 millimeters a day in
Dialogue: 0,0:05:40.34,0:05:45.14,Default,,0000,0000,0000,,Oxford, then you have a real problem with\Nflooding. So you define that this is your
Dialogue: 0,0:05:45.14,0:05:49.75,Default,,0000,0000,0000,,threshold from when you speak about an\Nextreme event. And so you have a
Dialogue: 0,0:05:49.75,0:05:57.65,Default,,0000,0000,0000,,probability of this event to occur in the\Nworld we live in today. Of course, that
Dialogue: 0,0:05:57.65,0:06:02.70,Default,,0000,0000,0000,,does not tell you the role of climate\Nchange, because in order to know that, you
Dialogue: 0,0:06:02.70,0:06:07.95,Default,,0000,0000,0000,,would also you will also need to know what\Nwould the likelihood of this event to
Dialogue: 0,0:06:07.95,0:06:15.29,Default,,0000,0000,0000,,occur have been without man-made climate\Nchange, and so. But because we know very
Dialogue: 0,0:06:15.29,0:06:22.31,Default,,0000,0000,0000,,well how many greenhouse gases have been\Nintroduced into the atmosphere since the
Dialogue: 0,0:06:22.31,0:06:27.91,Default,,0000,0000,0000,,beginning of the industrial revolution, we\Ncan actually remove these additional
Dialogue: 0,0:06:27.91,0:06:34.33,Default,,0000,0000,0000,,greenhouse gases from the climate models\Natmospheres that we use and simulate a
Dialogue: 0,0:06:34.33,0:06:41.30,Default,,0000,0000,0000,,world that would have been exactly as it\Nis today, but without the greenhouse gases
Dialogue: 0,0:06:41.30,0:06:46.57,Default,,0000,0000,0000,,from the burning of fossil fuels. And in\Nthat world, we can then also ask the
Dialogue: 0,0:06:46.57,0:06:54.44,Default,,0000,0000,0000,,question, what are possible heavy rainfall\Nevents in December in Oxford? And we might
Dialogue: 0,0:06:54.44,0:07:00.54,Default,,0000,0000,0000,,find that the event that we are interested\Nin is in that world, not a one in 10 year
Dialogue: 0,0:07:00.54,0:07:06.76,Default,,0000,0000,0000,,event, but a one in 20 year event. And\Nbecause everything else is held the same,
Dialogue: 0,0:07:06.76,0:07:11.66,Default,,0000,0000,0000,,we can then attribute the difference\Nbetween these two likelihoods of
Dialogue: 0,0:07:11.66,0:07:19.07,Default,,0000,0000,0000,,occurrence of the extreme event in\Nquestion to man-made climate change. And
Dialogue: 0,0:07:19.07,0:07:26.39,Default,,0000,0000,0000,,so with this fake example that I've just\Nused, we would then say climate change has
Dialogue: 0,0:07:26.39,0:07:31.83,Default,,0000,0000,0000,,doubled the likelihood of the event to\Noccur because one that was one in 20 year
Dialogue: 0,0:07:31.83,0:07:41.68,Default,,0000,0000,0000,,event is now one in 10 years. So that is\Nbasically the whole theoretical idea
Dialogue: 0,0:07:41.68,0:07:47.71,Default,,0000,0000,0000,,behind attributing extreme events and this\Nmethod can be used. And so, for example,
Dialogue: 0,0:07:47.71,0:07:53.11,Default,,0000,0000,0000,,with our initiative that's called World\NWeather Attribution, we have looked this
Dialogue: 0,0:07:53.11,0:08:02.71,Default,,0000,0000,0000,,year at the extreme heat in Siberia, the\Nbeginning of this year that, among other
Dialogue: 0,0:08:02.71,0:08:08.31,Default,,0000,0000,0000,,things, led to temperatures above 38\Ndegrees in the city of Verkhoyansk, but
Dialogue: 0,0:08:08.31,0:08:16.78,Default,,0000,0000,0000,,also let to permafrost thawing and large\Nwildfires. And that event was made so much
Dialogue: 0,0:08:16.78,0:08:23.19,Default,,0000,0000,0000,,more likely because of climate change that\Nit's almost would have been impossible
Dialogue: 0,0:08:23.19,0:08:29.54,Default,,0000,0000,0000,,without climate change. So when we did the\Nexperiments that the models it's a one in
Dialogue: 0,0:08:29.54,0:08:34.99,Default,,0000,0000,0000,,80 million year event in a world without\Nclimate change. And it's still a
Dialogue: 0,0:08:34.99,0:08:40.57,Default,,0000,0000,0000,,relatively extreme event in today's world,\Nbut it is possible. So this is the type of
Dialogue: 0,0:08:40.57,0:08:46.74,Default,,0000,0000,0000,,event where climate change really is a\Ngame changer. Another event that we have
Dialogue: 0,0:08:46.74,0:08:56.69,Default,,0000,0000,0000,,looked at is Hurricane Harvey that hit the\NHouston and Texas in 2017 and caused huge
Dialogue: 0,0:08:56.69,0:09:05.19,Default,,0000,0000,0000,,amounts of damage with the rainfall\Namounts it brought. And several attribution
Dialogue: 0,0:09:05.19,0:09:11.65,Default,,0000,0000,0000,,studies doing exactly what I've just\Ndescribed found that this type of, so this
Dialogue: 0,0:09:11.65,0:09:16.68,Default,,0000,0000,0000,,extreme rainfall associated with a\Nhurricane like Harvey has been made three
Dialogue: 0,0:09:16.68,0:09:22.77,Default,,0000,0000,0000,,times more likely because of climate\Nchange. And colleagues of mine, Dave Frame
Dialogue: 0,0:09:22.77,0:09:29.76,Default,,0000,0000,0000,,and his team, have then used these studies\Nto figure out how much of the economic
Dialogue: 0,0:09:29.76,0:09:36.08,Default,,0000,0000,0000,,costs this hurricane can be attributed to\Nclimate change, and found that of the 90
Dialogue: 0,0:09:36.08,0:09:43.54,Default,,0000,0000,0000,,billion US dollars that were associated,\Nthat were associated with the flood damage
Dialogue: 0,0:09:43.54,0:09:51.09,Default,,0000,0000,0000,,from Harvey, 67 billion can be attributed\Nto climate change, which is in particular
Dialogue: 0,0:09:51.09,0:09:58.72,Default,,0000,0000,0000,,interesting when you compare that to the\Nstate of the art economic cost estimations
Dialogue: 0,0:09:58.72,0:10:05.90,Default,,0000,0000,0000,,of climate change in general, which had\Nestimated only 20 billion US dollars for
Dialogue: 0,0:10:05.90,0:10:12.67,Default,,0000,0000,0000,,2017 in the US from climate change. And of\Ncourse, not every year is an event like
Dialogue: 0,0:10:12.67,0:10:19.60,Default,,0000,0000,0000,,Harvey, but it shows that when you look at\Nthe impact of climate change in a more
Dialogue: 0,0:10:19.60,0:10:24.49,Default,,0000,0000,0000,,bottom up approach, so looking at the\Nextreme events, which are how climate
Dialogue: 0,0:10:24.49,0:10:30.42,Default,,0000,0000,0000,,change manifests and affect people, you get\Nvery different numbers, as if you just
Dialogue: 0,0:10:30.42,0:10:39.42,Default,,0000,0000,0000,,look at large scale changes in temperature\Nand precipitation. But of course, not
Dialogue: 0,0:10:39.42,0:10:45.85,Default,,0000,0000,0000,,every extreme event that occurs today has\Nbeen made worse because of climate change.
Dialogue: 0,0:10:45.85,0:10:51.56,Default,,0000,0000,0000,,So this is an example of a drought in\Nsoutheast Brazil that happened in 2014,
Dialogue: 0,0:10:51.56,0:11:00.09,Default,,0000,0000,0000,,2015, where we found that Climate change\Ndid not change the likelihood of this
Dialogue: 0,0:11:00.09,0:11:07.85,Default,,0000,0000,0000,,drought to occur, so it was a one in 10\Nyear event in 2014, 2015, and also without
Dialogue: 0,0:11:07.85,0:11:14.14,Default,,0000,0000,0000,,climate change, it has a very similar\Nlikelihood of occurrence. However, what we
Dialogue: 0,0:11:14.14,0:11:20.33,Default,,0000,0000,0000,,did find when we looked at, OK, what else\Nhas changed? Why has this drought that has
Dialogue: 0,0:11:20.33,0:11:27.08,Default,,0000,0000,0000,,occurred in a very similar way earlier in\Nthe 2000s and also in the 1970s with much
Dialogue: 0,0:11:27.08,0:11:33.11,Default,,0000,0000,0000,,less impacts. We looked at other factors\Nand found that the population has
Dialogue: 0,0:11:33.11,0:11:38.87,Default,,0000,0000,0000,,increased a lot over the last or over the\Nbeginning of the 21st century, but in
Dialogue: 0,0:11:38.87,0:11:45.53,Default,,0000,0000,0000,,particular, the water consumption in in\Nthe area and the water usage has increased
Dialogue: 0,0:11:45.53,0:11:54.27,Default,,0000,0000,0000,,almost exponentially. And that explains\Nwhy the impacts were so large. So this is
Dialogue: 0,0:11:54.27,0:12:00.68,Default,,0000,0000,0000,,what I've just said is sort of basically\Nthe the very basic idea and and how in
Dialogue: 0,0:12:00.68,0:12:09.78,Default,,0000,0000,0000,,theory these studies work and how and some\Nresults that we find. In practice, it is
Dialogue: 0,0:12:09.78,0:12:14.60,Default,,0000,0000,0000,,usually not quite as straightforward,\Nbecause while the idea is still the
Dialogue: 0,0:12:14.60,0:12:21.65,Default,,0000,0000,0000,,same, we need to use climate models and\Nstatistical models for observational data
Dialogue: 0,0:12:21.65,0:12:25.99,Default,,0000,0000,0000,,to simulate possible weather in the world\Nwe live in and possible weather in the
Dialogue: 0,0:12:25.99,0:12:31.23,Default,,0000,0000,0000,,world that might have been. That is, in\Ntheory, straight forward, in practice,
Dialogue: 0,0:12:31.23,0:12:37.08,Default,,0000,0000,0000,,it's often relatively difficult, and what\Nyou see here is how the results of these
Dialogue: 0,0:12:37.08,0:12:42.98,Default,,0000,0000,0000,,studies look when you don't use schematic\Nand if you're not a hydrologist, this
Dialogue: 0,0:12:42.98,0:12:49.93,Default,,0000,0000,0000,,might be a bit of an unfriendly plot. But\Nit's it's basically the same as the
Dialogue: 0,0:12:49.93,0:12:57.47,Default,,0000,0000,0000,,schematic that I've showed at the\Nbeginning, but just plotted in a way that
Dialogue: 0,0:12:57.47,0:13:03.22,Default,,0000,0000,0000,,you can see the tails of the distribution\Nparticularly well, so where the extreme
Dialogue: 0,0:13:03.22,0:13:09.28,Default,,0000,0000,0000,,events are. So on the X-axis, we have the\Nreturn time of the event in years on a
Dialogue: 0,0:13:09.28,0:13:18.03,Default,,0000,0000,0000,,logarithmic scale and on the Y-axis, you\Nsee the magnitude of the event and that
Dialogue: 0,0:13:18.03,0:13:27.59,Default,,0000,0000,0000,,defines what our extreme event is. And\Nthis is actually a real example from heavy
Dialogue: 0,0:13:27.59,0:13:35.70,Default,,0000,0000,0000,,rainfall in the south of the U.K. And you\Ncan see here in red, each of these red
Dialogue: 0,0:13:35.70,0:13:43.20,Default,,0000,0000,0000,,dots that that you see on the red curve is\Na simulation of one possible rainfall
Dialogue: 0,0:13:43.20,0:13:49.40,Default,,0000,0000,0000,,event in the South of the U.K. in the year\N2015 in the world we live in today with
Dialogue: 0,0:13:49.40,0:13:57.28,Default,,0000,0000,0000,,climate change and the dashed line\Nindicates the threshold that led to to
Dialogue: 0,0:13:57.28,0:14:04.74,Default,,0000,0000,0000,,flooding in in that year. And on the\NX-axis, when you go down from the dashed
Dialogue: 0,0:14:04.74,0:14:10.08,Default,,0000,0000,0000,,line, you can then see that this is\Nroughly a one in 20 year event in the
Dialogue: 0,0:14:10.08,0:14:15.52,Default,,0000,0000,0000,,world we live in today. And all the blue\Ndots on the blue curve are simulations of
Dialogue: 0,0:14:15.52,0:14:22.53,Default,,0000,0000,0000,,possible heavy rainfall in the South of\Nthe U.K. in 2015, in a world without man-
Dialogue: 0,0:14:22.53,0:14:28.29,Default,,0000,0000,0000,,made climate change. And you can see that\Nthese two curves are different and
Dialogue: 0,0:14:28.29,0:14:33.47,Default,,0000,0000,0000,,significantly different, but they are\Nstill relatively close together. And so
Dialogue: 0,0:14:33.47,0:14:38.72,Default,,0000,0000,0000,,the event in the world without climate\Nchange would have been a bit less likely,
Dialogue: 0,0:14:38.72,0:14:45.63,Default,,0000,0000,0000,,so we have roughly a 40 percent increase\Nin the likelihood. But still other factors
Dialogue: 0,0:14:45.63,0:14:52.30,Default,,0000,0000,0000,,like, yeah, just the chaotic variability\Nof the weather and also, of course, than
Dialogue: 0,0:14:52.30,0:14:57.66,Default,,0000,0000,0000,,other factors on the ground where houses\Nbuild in floodplains and so on play an
Dialogue: 0,0:14:57.66,0:15:07.62,Default,,0000,0000,0000,,important role. So this is the\Nactual attribution step. So when we find
Dialogue: 0,0:15:07.62,0:15:13.04,Default,,0000,0000,0000,,out what the role of climate change is,\Nbut of course, in order to do that, there
Dialogue: 0,0:15:13.04,0:15:20.66,Default,,0000,0000,0000,,are a few steps before that are crucially\Nimportant and absolutely determine the
Dialogue: 0,0:15:20.66,0:15:27.72,Default,,0000,0000,0000,,outcome. And the first step, the first\Nthing to find out is what has actually
Dialogue: 0,0:15:27.72,0:15:32.09,Default,,0000,0000,0000,,happened, because usually when we read\Nabout extreme weather events or when we
Dialogue: 0,0:15:32.09,0:15:39.13,Default,,0000,0000,0000,,hear about extreme weather events, you see\Npictures in newspapers of flooded parts of
Dialogue: 0,0:15:39.13,0:15:47.17,Default,,0000,0000,0000,,the world. And so you don't usually have\Nobserved weather recordings reported in
Dialogue: 0,0:15:47.17,0:15:53.36,Default,,0000,0000,0000,,the media. And the same actually is\Ntrue for us. So when we are, so we work a
Dialogue: 0,0:15:53.36,0:16:00.66,Default,,0000,0000,0000,,lot with the Red Cross and they ask us:\NOK, we have this large flooding event, can
Dialogue: 0,0:16:00.66,0:16:05.20,Default,,0000,0000,0000,,you do an attribution study? Can you tell\Nus what the role of climate change is?
Dialogue: 0,0:16:05.20,0:16:09.91,Default,,0000,0000,0000,,Then we also just know: OK, there is\Nflooding. And so the first step is we need
Dialogue: 0,0:16:09.91,0:16:15.39,Default,,0000,0000,0000,,to find out what is the weather event that\Nactually caused that flooding. And that is
Dialogue: 0,0:16:15.39,0:16:21.92,Default,,0000,0000,0000,,not always that straightforward. And this\Nis what you see here on this map, on this
Dialogue: 0,0:16:21.92,0:16:29.100,Default,,0000,0000,0000,,slide is a relatively stark example, but\Nnot an untypical. So it's of an extreme
Dialogue: 0,0:16:29.100,0:16:35.44,Default,,0000,0000,0000,,rainfall event on the 10th of November\N2018 in Kenya. And on the left hand side
Dialogue: 0,0:16:35.44,0:16:41.08,Default,,0000,0000,0000,,is one data product of observational data,\Nof observational rainfall data that is
Dialogue: 0,0:16:41.08,0:16:49.65,Default,,0000,0000,0000,,available and on the right hand side is\Nanother showing the same event. And the
Dialogue: 0,0:16:49.65,0:16:57.96,Default,,0000,0000,0000,,scale which I failed to to say on the\Nslide in millimeters per day. And so on
Dialogue: 0,0:16:57.96,0:17:03.79,Default,,0000,0000,0000,,the left hand side, you have extreme\Nrainfall of above 50 millimeters per day,
Dialogue: 0,0:17:03.79,0:17:10.78,Default,,0000,0000,0000,,which is considering that, for example, in\Nin my home town of Kiel in Schleswig-
Dialogue: 0,0:17:10.78,0:17:17.94,Default,,0000,0000,0000,,Holstein, there is about 700 millimeters\Nof rainfall per year. You can see that 50
Dialogue: 0,0:17:17.94,0:17:24.05,Default,,0000,0000,0000,,millimeters in a single day is very heavy\Nrainfall, whereas in the other data
Dialogue: 0,0:17:24.05,0:17:32.42,Default,,0000,0000,0000,,product, you don't see as much rain. You\Nstill see large rain, but it's not in
Dialogue: 0,0:17:32.42,0:17:39.86,Default,,0000,0000,0000,,the same magnitude, and it's also not\Nexactly in the same place. And so given
Dialogue: 0,0:17:39.86,0:17:44.99,Default,,0000,0000,0000,,that most countries in the world do not\Nhave an open data policy, so you can't
Dialogue: 0,0:17:44.99,0:17:50.89,Default,,0000,0000,0000,,actually get access to the observed\Nstation data, but you have to use
Dialogue: 0,0:17:50.89,0:17:56.49,Default,,0000,0000,0000,,available, publicly available products\Nlike the two have shown here, you have to
Dialogue: 0,0:17:56.49,0:18:03.84,Default,,0000,0000,0000,,know and you have to work with experts in\Nthe region to actually know who hopefully
Dialogue: 0,0:18:03.84,0:18:08.64,Default,,0000,0000,0000,,has access to the data to actually find\Nout what has happened in the first place.
Dialogue: 0,0:18:08.64,0:18:15.04,Default,,0000,0000,0000,,But of course, if you don't know that or\Nthere is not always a perfect answer, then
Dialogue: 0,0:18:15.04,0:18:21.41,Default,,0000,0000,0000,,if you don't know what event that is. It's\Nvery difficult to do an attribution study.
Dialogue: 0,0:18:21.41,0:18:27.36,Default,,0000,0000,0000,,Assuming though you have found a data\Nproduct that you trust, the next question
Dialogue: 0,0:18:27.36,0:18:34.22,Default,,0000,0000,0000,,then is what is actually the right\Nthreshold to use for the event? So if you
Dialogue: 0,0:18:34.22,0:18:39.29,Default,,0000,0000,0000,,have flooding that was pretty obviously\Ncaused by one day extreme rainfall event,
Dialogue: 0,0:18:39.29,0:18:43.87,Default,,0000,0000,0000,,then that would be your definition of the\Nevent. But it could also be that the
Dialogue: 0,0:18:43.87,0:18:50.92,Default,,0000,0000,0000,,flooding has been caused by a very soggy,\Nrainy season. So actually, the really the
Dialogue: 0,0:18:50.92,0:18:57.85,Default,,0000,0000,0000,,real event you would want to look at is\Nover a much longer time scale or if the
Dialogue: 0,0:18:57.85,0:19:02.36,Default,,0000,0000,0000,,flooding occurred mainly because of some\Nwater management in the rivers and has
Dialogue: 0,0:19:02.36,0:19:08.05,Default,,0000,0000,0000,,actually flooded further upstream, your\Nspatial definition of the event would be
Dialogue: 0,0:19:08.05,0:19:13.77,Default,,0000,0000,0000,,very different. And so and what you see\Nhere on this plot is an example of a heat
Dialogue: 0,0:19:13.77,0:19:22.43,Default,,0000,0000,0000,,wave in Europe in 2019. And there, what\Nusually makes the headlines is the maximum
Dialogue: 0,0:19:22.43,0:19:27.58,Default,,0000,0000,0000,,daily temperature. So if records are\Nbroken, so you could use that as a
Dialogue: 0,0:19:27.58,0:19:32.80,Default,,0000,0000,0000,,definition of the event that you're\Ninterested in. But of course, what really
Dialogue: 0,0:19:32.80,0:19:38.86,Default,,0000,0000,0000,,causes the losses and damages from extreme\Nevents is not necessarily the one day
Dialogue: 0,0:19:38.86,0:19:43.77,Default,,0000,0000,0000,,maximum temperature, but it is when heat\Nwaves last for longer, and especially when
Dialogue: 0,0:19:43.77,0:19:49.19,Default,,0000,0000,0000,,the night temperatures are also high and\Nnot just the daytime temperatures. So you
Dialogue: 0,0:19:49.19,0:19:54.77,Default,,0000,0000,0000,,might want to look at an event over five\Nday period instead of just the maximum
Dialogue: 0,0:19:54.77,0:20:02.79,Default,,0000,0000,0000,,daily temperatures. Or, and this is sort\Nof why I have shown the pressure plot on
Dialogue: 0,0:20:02.79,0:20:06.43,Default,,0000,0000,0000,,the right hand side, which is really just\Nan illustration, it's not terribly
Dialogue: 0,0:20:06.43,0:20:11.43,Default,,0000,0000,0000,,important what's on there. But there are,\Nof course, different weather systems that
Dialogue: 0,0:20:11.43,0:20:18.12,Default,,0000,0000,0000,,can cause heat waves, especially in the\Narea here in the south of France. It could
Dialogue: 0,0:20:18.12,0:20:26.58,Default,,0000,0000,0000,,be a relatively short lived high\Npressure system bringing hot air from the
Dialogue: 0,0:20:26.58,0:20:32.47,Default,,0000,0000,0000,,Mediterranean. Or it could be something\Nthat is caused from a long time stationary
Dialogue: 0,0:20:32.47,0:20:38.73,Default,,0000,0000,0000,,high pressure system over all of Europe.\NIf you want to take that into account,
Dialogue: 0,0:20:38.73,0:20:44.80,Default,,0000,0000,0000,,obviously also your event is different.\NAnd there is no right or wrong way to
Dialogue: 0,0:20:44.80,0:20:50.50,Default,,0000,0000,0000,,define the event because there are\Nlegitimate interests in the maximum
Dialogue: 0,0:20:50.50,0:20:57.92,Default,,0000,0000,0000,,daily temperatures, legitimate interest in\Njust a specific type of pressure system
Dialogue: 0,0:20:57.92,0:21:04.60,Default,,0000,0000,0000,,and interest in what actually causes more\Nexcess mortality on people, what would be
Dialogue: 0,0:21:04.60,0:21:11.26,Default,,0000,0000,0000,,the three day or longer type of heat\Nwaves. But whichever definition you
Dialogue: 0,0:21:11.26,0:21:19.27,Default,,0000,0000,0000,,choose, it will determine the outcome of\Nthe study. And here are some typical
Dialogue: 0,0:21:19.27,0:21:28.06,Default,,0000,0000,0000,,results of attribution studies when you\Nlook at them in a slightly more scientific
Dialogue: 0,0:21:28.06,0:21:33.87,Default,,0000,0000,0000,,way and slightly less just the headline\Nway as the ones that I've shown earlier.
Dialogue: 0,0:21:33.87,0:21:39.62,Default,,0000,0000,0000,,Because, of course, what also is important\Nis not only how you define the event,
Dialogue: 0,0:21:39.62,0:21:44.76,Default,,0000,0000,0000,,depending on the impacts and depending on\Nwhat you're interested in. The extreme
Dialogue: 0,0:21:44.76,0:21:48.95,Default,,0000,0000,0000,,event and what observational data you have\Navailable. But of course, there's also
Dialogue: 0,0:21:48.95,0:21:53.95,Default,,0000,0000,0000,,then the question of what models, what\Nclimate models do we have available? And
Dialogue: 0,0:21:53.95,0:21:58.56,Default,,0000,0000,0000,,there's always some tradeoff between what\Nexactly caused the event and what we can
Dialogue: 0,0:21:58.56,0:22:04.60,Default,,0000,0000,0000,,meaningfully simulate in a climate model.\NAnd then all climate models are good for
Dialogue: 0,0:22:04.60,0:22:10.74,Default,,0000,0000,0000,,something and bad for other things. So\Nthere always need to be a model evaluation
Dialogue: 0,0:22:10.74,0:22:15.13,Default,,0000,0000,0000,,stage. So where you test if the models\Nthat you have available are actually able
Dialogue: 0,0:22:15.13,0:22:20.69,Default,,0000,0000,0000,,to simulate in a reliable way the event\Nthat you're interested in. But even if you
Dialogue: 0,0:22:20.69,0:22:26.98,Default,,0000,0000,0000,,have done all this, it can sometimes be\Nthat the models and the observations that
Dialogue: 0,0:22:26.98,0:22:34.19,Default,,0000,0000,0000,,you have show very different things. And\Nso the heat wave in Germany in 2019, which
Dialogue: 0,0:22:34.19,0:22:39.52,Default,,0000,0000,0000,,was also on the slide before,\Nis an example of that. When we
Dialogue: 0,0:22:39.52,0:22:48.31,Default,,0000,0000,0000,,look at the long term observations of\Nextreme, of high temperatures and see how
Dialogue: 0,0:22:48.31,0:22:55.19,Default,,0000,0000,0000,,they have changed over time, we find that,\Nbecause of the change in climate, we have
Dialogue: 0,0:22:55.19,0:23:02.68,Default,,0000,0000,0000,,observed, the likelihood of this type of\Nheat wave has increased more, yeah, about
Dialogue: 0,0:23:02.68,0:23:10.41,Default,,0000,0000,0000,,300 times. So you see this\Nin the black bar, the black bar in the
Dialogue: 0,0:23:10.41,0:23:14.90,Default,,0000,0000,0000,,middle of the blue bar, on the left hand\Nside, at the very top where it says DWD
Dialogue: 0,0:23:14.90,0:23:19.77,Default,,0000,0000,0000,,obs, that's the Deutscher Wetterdienst\Nobservations and we see that where this
Dialogue: 0,0:23:19.77,0:23:25.24,Default,,0000,0000,0000,,black bar is about, again, a logarithmic\Nscale, about 300 hundred times more
Dialogue: 0,0:23:25.24,0:23:30.80,Default,,0000,0000,0000,,likely. But of course, because we have\Nonly 100 years worth of
Dialogue: 0,0:23:30.80,0:23:38.51,Default,,0000,0000,0000,,observations and summer temperatures\Nare extremely variable, there is a large
Dialogue: 0,0:23:38.51,0:23:43.82,Default,,0000,0000,0000,,uncertainty around this change. And so we\Ncannot, from the observations alone, we
Dialogue: 0,0:23:43.82,0:23:50.30,Default,,0000,0000,0000,,cannot exclude 100.000 times change in the\Nlikelihood of this heat wave. But
Dialogue: 0,0:23:50.30,0:23:55.91,Default,,0000,0000,0000,,similarly, also not a 20 times heat wave.\NBut what the main point is, that in all
Dialogue: 0,0:23:55.91,0:24:01.76,Default,,0000,0000,0000,,the climate models and all the red bars\Nthat you see on there are the same
Dialogue: 0,0:24:01.76,0:24:08.33,Default,,0000,0000,0000,,results, but for climate models where we\Nhave compared today's likelihood of the
Dialogue: 0,0:24:08.33,0:24:13.20,Default,,0000,0000,0000,,event to occur with the likelihood in the\Nworld without climate change, and you see
Dialogue: 0,0:24:13.20,0:24:18.18,Default,,0000,0000,0000,,that the change is much lower. And of\Ncourse, climate change is not the only
Dialogue: 0,0:24:18.18,0:24:23.94,Default,,0000,0000,0000,,thing that has changed and that has\Naffected observed temperatures. But other
Dialogue: 0,0:24:23.94,0:24:30.82,Default,,0000,0000,0000,,factors like land use change and things\Nlike that are much smaller in the size
Dialogue: 0,0:24:30.82,0:24:36.26,Default,,0000,0000,0000,,than the climate signal. So they cannot\Nexplain this discrepancy. So this means
Dialogue: 0,0:24:36.26,0:24:42.86,Default,,0000,0000,0000,,that the climate models we have available\Nfor this type of study have obviously a
Dialogue: 0,0:24:42.86,0:24:51.39,Default,,0000,0000,0000,,problem with the extreme temperatures in a\Nsmall scale. And there are effects that we
Dialogue: 0,0:24:51.39,0:24:56.32,Default,,0000,0000,0000,,don't yet understand. And so we can't say:\NOK, this heat wave was made 10 times more
Dialogue: 0,0:24:56.32,0:25:03.53,Default,,0000,0000,0000,,likely. But we can only say, that with our\Ncurrent knowledge and understanding, we
Dialogue: 0,0:25:03.53,0:25:07.28,Default,,0000,0000,0000,,can say that climate change was an\Nabsolute game changer for this type of
Dialogue: 0,0:25:07.28,0:25:14.35,Default,,0000,0000,0000,,heat wave, but we can't really quantify\Nit. On the right hand side is a much nicer
Dialogue: 0,0:25:14.35,0:25:21.11,Default,,0000,0000,0000,,result on the top one, which is for\Nextreme rainfall, in Texas 2019 and nicer
Dialogue: 0,0:25:21.11,0:25:27.66,Default,,0000,0000,0000,,result I mean now for a scientist and\Nin a scientific way. So we have in blue
Dialogue: 0,0:25:27.66,0:25:35.53,Default,,0000,0000,0000,,two different types of observations from\Nthe heavy rainfall event, and they both
Dialogue: 0,0:25:35.53,0:25:43.65,Default,,0000,0000,0000,,show pretty much exactly the same result.\NAnd also the two climate models that we
Dialogue: 0,0:25:43.65,0:25:51.50,Default,,0000,0000,0000,,had available that passed the model\Nevaluation tests show an increase in the
Dialogue: 0,0:25:51.50,0:25:56.64,Default,,0000,0000,0000,,likelihood of this event to occur. That is\Nvery similar to that in the observations
Dialogue: 0,0:25:56.64,0:26:04.19,Default,,0000,0000,0000,,in terms of order of magnitude. And so in\Nthat case, we can just synthesize the
Dialogue: 0,0:26:04.19,0:26:09.76,Default,,0000,0000,0000,,results and give an overarching answer,\Nwhich is that the likelihood of this event
Dialogue: 0,0:26:09.76,0:26:18.25,Default,,0000,0000,0000,,to occur has about doubled because of man-\Nmade climate change. And the last example
Dialogue: 0,0:26:18.25,0:26:27.08,Default,,0000,0000,0000,,that I, that is here is for drought\Nin Somalia in 2010, where not only the
Dialogue: 0,0:26:27.08,0:26:32.85,Default,,0000,0000,0000,,observations are extremely uncertain. So\Nfrom the observations, you could say we
Dialogue: 0,0:26:32.85,0:26:37.54,Default,,0000,0000,0000,,could have both an increase in likelihood\Nor a decrease in likelihood by a factor of
Dialogue: 0,0:26:37.54,0:26:45.33,Default,,0000,0000,0000,,10. But also the climate models show a\Nvery, very mixed picture where you can't
Dialogue: 0,0:26:45.33,0:26:51.72,Default,,0000,0000,0000,,even see a sign that that is conclusive.\NSo in that case, you can say, we can
Dialogue: 0,0:26:51.72,0:26:59.74,Default,,0000,0000,0000,,exclude that climate change made this\Nevent more or less than 10 times, more
Dialogue: 0,0:26:59.74,0:27:05.72,Default,,0000,0000,0000,,than 10 times or less than 10 times more\Nlikely. But we can't say anything more. So
Dialogue: 0,0:27:05.72,0:27:09.56,Default,,0000,0000,0000,,we can exclude that it's a complete game-\Nchanger like we have for heat waves, for
Dialogue: 0,0:27:09.56,0:27:14.03,Default,,0000,0000,0000,,example. But that's about the only\Nthing that you can say for a result
Dialogue: 0,0:27:14.03,0:27:24.05,Default,,0000,0000,0000,,like this. So this was sort of the\Nmost detailed scientific stuff that I
Dialogue: 0,0:27:24.05,0:27:29.78,Default,,0000,0000,0000,,would like to show, because I think it's\Nimportant to get some background behind
Dialogue: 0,0:27:29.78,0:27:35.31,Default,,0000,0000,0000,,the headline results that would just\Nbe climate change doubled the likelihood
Dialogue: 0,0:27:35.31,0:27:42.84,Default,,0000,0000,0000,,of this event. So there are always four\Npossible outcomes of an attribution study
Dialogue: 0,0:27:42.84,0:27:51.78,Default,,0000,0000,0000,,a priori. And that is because\Nclimate change affects extreme weather in
Dialogue: 0,0:27:51.78,0:27:58.38,Default,,0000,0000,0000,,two ways basically. One way is what we\Nwould call the thermodynamic way, which
Dialogue: 0,0:27:58.38,0:28:02.17,Default,,0000,0000,0000,,means that because we have more greenhouse\Ngases in the atmosphere, the atmosphere
Dialogue: 0,0:28:02.17,0:28:07.16,Default,,0000,0000,0000,,overall gets warmer. So you have, on\Naverage, an increase in the likelihood of
Dialogue: 0,0:28:07.16,0:28:12.38,Default,,0000,0000,0000,,heat waves decrease in the likelihood of\Ncold waves. A warmer atmosphere can also
Dialogue: 0,0:28:12.38,0:28:17.55,Default,,0000,0000,0000,,hold more water vapor that needs\Nto get out of the atmosphere as rainfall.
Dialogue: 0,0:28:17.55,0:28:24.27,Default,,0000,0000,0000,,So on average, from the warming alone, we\Nwould also have more extreme rainfall. But
Dialogue: 0,0:28:24.27,0:28:28.24,Default,,0000,0000,0000,,then there's the second effect, which I\Ncall the dynamic effect, and that is
Dialogue: 0,0:28:28.24,0:28:33.50,Default,,0000,0000,0000,,because we've changed the composition of the\Natmosphere, that affects the atmospheric
Dialogue: 0,0:28:33.50,0:28:38.78,Default,,0000,0000,0000,,circulation. So where weather systems\Ndevelop, how they develop and and how they
Dialogue: 0,0:28:38.78,0:28:44.23,Default,,0000,0000,0000,,move. And this effect can either be in the\Nsame direction as the warming effect. So it
Dialogue: 0,0:28:44.23,0:28:51.99,Default,,0000,0000,0000,,can be that we expect more extreme rainfall,\Nbut we also get more low pressure systems
Dialogue: 0,0:28:51.99,0:28:57.35,Default,,0000,0000,0000,,bring rain to get even more extreme\Nrainfall. But these two effects can also
Dialogue: 0,0:28:57.35,0:29:03.38,Default,,0000,0000,0000,,counteract each other. And so you\Ncan expect more rainfall on
Dialogue: 0,0:29:03.38,0:29:07.86,Default,,0000,0000,0000,,average. But if you don't get the weather\Nsystems that bring rain, you either have
Dialogue: 0,0:29:07.86,0:29:13.58,Default,,0000,0000,0000,,no change in likelihood and intensity or,\Nif the dynamics win, you have actually
Dialogue: 0,0:29:13.58,0:29:19.45,Default,,0000,0000,0000,,decrease in the likelihood of extreme\Nrainfall in a particular season or region.
Dialogue: 0,0:29:19.45,0:29:24.55,Default,,0000,0000,0000,,And so this is why a priori, that can\Nalways be four outcomes: It can be that
Dialogue: 0,0:29:24.55,0:29:29.01,Default,,0000,0000,0000,,the event was made more likely. It can be\Nthat it was made less likely. It can be
Dialogue: 0,0:29:29.01,0:29:34.33,Default,,0000,0000,0000,,there's no change. Or it can be that with\Nour current understanding and tools, we
Dialogue: 0,0:29:34.33,0:29:46.76,Default,,0000,0000,0000,,can't actually answer the question. And so\Nthis has been possible to do now for
Dialogue: 0,0:29:46.76,0:29:52.86,Default,,0000,0000,0000,,about a decade, but only in the last five\Nyears really have many, many people or
Dialogue: 0,0:29:52.86,0:29:57.38,Default,,0000,0000,0000,,many scientists started to do these\Nstudies. And so there is actually a
Dialogue: 0,0:29:57.38,0:30:05.37,Default,,0000,0000,0000,,relatively large, there are\Nlots of attribution studies on different
Dialogue: 0,0:30:05.37,0:30:12.15,Default,,0000,0000,0000,,kinds of extreme events. And what you can\Nsee on this map here is what the news and
Dialogue: 0,0:30:12.15,0:30:17.51,Default,,0000,0000,0000,,energy outlet CarbonBrief has put all\Nthese studies together. And you can see in
Dialogue: 0,0:30:17.51,0:30:22.40,Default,,0000,0000,0000,,red where climate change played an\Nimportant role, and blue where climate
Dialogue: 0,0:30:22.40,0:30:33.93,Default,,0000,0000,0000,,change did not play a role. And in gray,\Nthat was an inconclusive result. This is
Dialogue: 0,0:30:33.93,0:30:39.75,Default,,0000,0000,0000,,very important, though, that this is not\Nrepresentative of the extreme events that
Dialogue: 0,0:30:39.75,0:30:46.58,Default,,0000,0000,0000,,have happened. This is just represents the\Nstudies that have been done by scientists
Dialogue: 0,0:30:46.58,0:30:59.56,Default,,0000,0000,0000,,and they are, of course biased towards\Nwhere scientists live
Dialogue: 0,0:30:59.56,0:31:05.28,Default,,0000,0000,0000,,and also towards extreme events that are\Nrelatively easy to simulate with climate
Dialogue: 0,0:31:05.28,0:31:12.78,Default,,0000,0000,0000,,models. So there are lots of heat waves in\NEurope, Australia and North America
Dialogue: 0,0:31:12.78,0:31:21.31,Default,,0000,0000,0000,,because that is where people live. And on\Nthis next map, I have tried to
Dialogue: 0,0:31:21.31,0:31:26.39,Default,,0000,0000,0000,,show the discrepancy between the extreme\Nevents that have happened and those for
Dialogue: 0,0:31:26.39,0:31:33.85,Default,,0000,0000,0000,,which we actually do know the role of\Nclimate change. So here in red are deaths
Dialogue: 0,0:31:33.85,0:31:39.57,Default,,0000,0000,0000,,associated with extreme events since 2003.\NSo since the first event attribution
Dialogue: 0,0:31:39.57,0:31:49.34,Default,,0000,0000,0000,,study. And it's death from heat waves,\Nstorms, heavy rainfall events and droughts
Dialogue: 0,0:31:49.34,0:31:54.94,Default,,0000,0000,0000,,primarily in different parts of the world,\Nthe bubble is always on the capital of the
Dialogue: 0,0:31:54.94,0:31:59.82,Default,,0000,0000,0000,,country. And the larger the bubble, the\Nmore deaths due to extreme events in those
Dialogue: 0,0:31:59.82,0:32:07.60,Default,,0000,0000,0000,,years. And in black overlaying that are\Nthose deaths for which we know the role of
Dialogue: 0,0:32:07.60,0:32:11.30,Default,,0000,0000,0000,,climate change. So that doesn't mean that\Nthe deaths are attributed to
Dialogue: 0,0:32:11.30,0:32:17.25,Default,,0000,0000,0000,,climate change, but it means that there\Nwe do know whether or not to what
Dialogue: 0,0:32:17.25,0:32:23.38,Default,,0000,0000,0000,,extent climate change played a role. And\Nyou can see that most of the European
Dialogue: 0,0:32:23.38,0:32:28.78,Default,,0000,0000,0000,,countries, the black circle is almost as\Nlarge as the red one. So for most of the
Dialogue: 0,0:32:28.78,0:32:32.44,Default,,0000,0000,0000,,extremes or most of the deaths associated\Nwith extreme events, we do know the role
Dialogue: 0,0:32:32.44,0:32:39.74,Default,,0000,0000,0000,,of climate change. But for many\Nother parts of the world,
Dialogue: 0,0:32:39.74,0:32:44.47,Default,,0000,0000,0000,,there are no or very small black circles.\NSo for most of the events and the deaths
Dialogue: 0,0:32:44.47,0:32:49.09,Default,,0000,0000,0000,,associated with them, we don't know what\Nthe role of climate change is. And I've
Dialogue: 0,0:32:49.09,0:32:52.95,Default,,0000,0000,0000,,used death here not because I'm\Nparticularly morbid, but because it's
Dialogue: 0,0:32:52.95,0:32:58.64,Default,,0000,0000,0000,,an indicator of the impacts of\Nextreme weather that is relatively good
Dialogue: 0,0:32:58.64,0:33:05.99,Default,,0000,0000,0000,,comparable between countries. So this\Nmeans that with event attribution methods
Dialogue: 0,0:33:05.99,0:33:12.13,Default,,0000,0000,0000,,that we have developed over the last\Ndecade, we now have the tools available to
Dialogue: 0,0:33:12.13,0:33:19.95,Default,,0000,0000,0000,,do, to provide an inventory of the impacts\Nof climate change on our livelihoods. But
Dialogue: 0,0:33:19.95,0:33:25.68,Default,,0000,0000,0000,,we are very far from having such an\Ninventory at the moment because most of
Dialogue: 0,0:33:25.68,0:33:30.00,Default,,0000,0000,0000,,the events that have happened, we actually\Ndon't know what the role of climate change
Dialogue: 0,0:33:30.00,0:33:37.96,Default,,0000,0000,0000,,is. And so we don't know in detail on\Ncountry scale and on the scale where
Dialogue: 0,0:33:37.96,0:33:46.71,Default,,0000,0000,0000,,people live and make decisions, what the\Nrole of climate change is today. There's
Dialogue: 0,0:33:46.71,0:33:56.53,Default,,0000,0000,0000,,another slightly related issue with that\Nis, that the extreme events that I've used
Dialogue: 0,0:33:56.53,0:34:01.51,Default,,0000,0000,0000,,to create the map are shown before with\Nthe death of climate change, with the
Dialogue: 0,0:34:01.51,0:34:07.67,Default,,0000,0000,0000,,death of extreme weather events. They are\Nfrom a database called EM-DAT, which is a
Dialogue: 0,0:34:07.67,0:34:16.29,Default,,0000,0000,0000,,publicly available database where losses\Nand damages associated with disasters
Dialogue: 0,0:34:16.29,0:34:20.31,Default,,0000,0000,0000,,technological disasters, but also\Ndisasters associated with weather are
Dialogue: 0,0:34:20.31,0:34:31.29,Default,,0000,0000,0000,,recorded. But, of course, they only can\Nrecord losses and damages if these losses
Dialogue: 0,0:34:31.29,0:34:36.59,Default,,0000,0000,0000,,and damages are recorded in the first\Nplace. And so what you see on this map is
Dialogue: 0,0:34:36.59,0:34:44.64,Default,,0000,0000,0000,,in grey and then overlayed with different\Nwith different circles are heat waves that
Dialogue: 0,0:34:44.64,0:34:50.58,Default,,0000,0000,0000,,have occurred, they have occurred between\N1986 and 2015 on this map. But you could
Dialogue: 0,0:34:50.58,0:34:56.33,Default,,0000,0000,0000,,draw a map from 1900 to today, and it\Nwould look very similar. And that shows
Dialogue: 0,0:34:56.33,0:35:03.51,Default,,0000,0000,0000,,lots and lots of heat waves reported in\NEurope and in the US, India, but there are
Dialogue: 0,0:35:03.51,0:35:09.17,Default,,0000,0000,0000,,no heat waves reported in most of sub-\NSaharan Africa. However, when you look at
Dialogue: 0,0:35:09.17,0:35:17.42,Default,,0000,0000,0000,,observations, and also we see that extreme\Nheat has increased quite dramatically in
Dialogue: 0,0:35:17.42,0:35:24.32,Default,,0000,0000,0000,,most parts of the world and a particular\Nhotspot is sub-Saharan Africa. So, we know
Dialogue: 0,0:35:24.32,0:35:29.40,Default,,0000,0000,0000,,from when we look at the weather that heat\Nwaves are happening, but it's not
Dialogue: 0,0:35:29.40,0:35:35.20,Default,,0000,0000,0000,,registered and it's not recorded. So we\Nhave no idea how many people are actually
Dialogue: 0,0:35:35.20,0:35:41.06,Default,,0000,0000,0000,,affected by these heat waves. And so we\Nthen, of course, don't do attribution
Dialogue: 0,0:35:41.06,0:35:46.08,Default,,0000,0000,0000,,studies and don't find out what the role\Nof climate change in these heat waves is.
Dialogue: 0,0:35:46.08,0:35:52.75,Default,,0000,0000,0000,,So in order to really understand the\Nwhole picture, we would also need to start
Dialogue: 0,0:35:52.75,0:36:01.82,Default,,0000,0000,0000,,recording these type of events in other\Nparts of the world. And so my very last
Dialogue: 0,0:36:01.82,0:36:08.70,Default,,0000,0000,0000,,point, before, I hope that you have\Nquestions for me, is: Of course,
Dialogue: 0,0:36:08.70,0:36:14.27,Default,,0000,0000,0000,,everything I've said so far was talking\Nabout the hazards, so talking about the
Dialogue: 0,0:36:14.27,0:36:19.76,Default,,0000,0000,0000,,weather event and how climate change\Naffects the hazard. But of course that is
Dialogue: 0,0:36:19.76,0:36:25.79,Default,,0000,0000,0000,,not the same or translates immediately\Ninto losses and damages, because whether
Dialogue: 0,0:36:25.79,0:36:32.12,Default,,0000,0000,0000,,or not a weather event actually has any\Nimpact at all is completely driven by
Dialogue: 0,0:36:32.12,0:36:38.44,Default,,0000,0000,0000,,exposure and vulnerability. So who and\Nwhat is in harm's way. And I've already
Dialogue: 0,0:36:38.44,0:36:46.16,Default,,0000,0000,0000,,shown, I've already mentioned the example\Nearly on with the drought in Brazil, where
Dialogue: 0,0:36:46.16,0:36:52.11,Default,,0000,0000,0000,,the huge losses and damages were to a\Nlarge degree attributable to the increase
Dialogue: 0,0:36:52.11,0:37:01.63,Default,,0000,0000,0000,,in water consumption. And thus,\Ntherefore, in order to really find out how
Dialogue: 0,0:37:01.63,0:37:07.95,Default,,0000,0000,0000,,climate change is affecting us today, we\Nnot only need to define the extreme events
Dialogue: 0,0:37:07.95,0:37:14.93,Default,,0000,0000,0000,,so that it connects to the impacts, but\Nalso look into vulnerability and exposure:
Dialogue: 0,0:37:14.93,0:37:21.52,Default,,0000,0000,0000,,What is changing, what's there and what\Nare the important factors. But we can
Dialogue: 0,0:37:21.52,0:37:28.33,Default,,0000,0000,0000,,do that. And so we have really made a lot\Nof progress in understanding of how
Dialogue: 0,0:37:28.33,0:37:35.01,Default,,0000,0000,0000,,climate change not only affects global\Nmean temperature, which we have known for
Dialogue: 0,0:37:35.01,0:37:41.83,Default,,0000,0000,0000,,centuries, and how it affects large\Nscale changes in temperature and
Dialogue: 0,0:37:41.83,0:37:46.87,Default,,0000,0000,0000,,precipitation, which we have also known\Nfor a very long time. But we now have
Dialogue: 0,0:37:46.87,0:37:52.11,Default,,0000,0000,0000,,actually all the puzzle pieces together to\Nreally understand what climate change
Dialogue: 0,0:37:52.11,0:37:58.74,Default,,0000,0000,0000,,means on the scale where people live and\Nwhere decisions are made. We just need to
Dialogue: 0,0:37:58.74,0:38:07.19,Default,,0000,0000,0000,,put them together. And one lens or one way\Nof where they are currently put together
Dialogue: 0,0:38:07.19,0:38:16.62,Default,,0000,0000,0000,,is, for example, in courts. And so because\Nit's obviously people who experience
Dialogue: 0,0:38:16.62,0:38:23.01,Default,,0000,0000,0000,,losses and damages from climate change.\NAnd so one way to address that is going
Dialogue: 0,0:38:23.01,0:38:28.91,Default,,0000,0000,0000,,through national governments, local\Ngovernments, hoping for adaptation
Dialogue: 0,0:38:28.91,0:38:35.07,Default,,0000,0000,0000,,measures to be put in place. But if that's\Nnot forthcoming quickly enough, there is
Dialogue: 0,0:38:35.07,0:38:40.51,Default,,0000,0000,0000,,the option to sue. And so this is one\Nexample which is currently happening in
Dialogue: 0,0:38:40.51,0:38:53.82,Default,,0000,0000,0000,,Germany where a peruvian farmer is suing\NRWE to basically pay their share of a
Dialogue: 0,0:38:53.82,0:39:01.10,Default,,0000,0000,0000,,adaptation because of largely increased\Nflood risk from glacier melt in the area.
Dialogue: 0,0:39:01.10,0:39:09.36,Default,,0000,0000,0000,,And they want RWE to pay from their\Ncontribution to climate change, where
Dialogue: 0,0:39:09.36,0:39:16.26,Default,,0000,0000,0000,,their emissions and then have some funding\Nfor the adaptation measures from them. And
Dialogue: 0,0:39:16.26,0:39:21.97,Default,,0000,0000,0000,,that is one example of where these kind of\Nattribution studies can be used in a very
Dialogue: 0,0:39:21.97,0:39:29.22,Default,,0000,0000,0000,,direct way to hopefully change\Nsomething in the real world. And with
Dialogue: 0,0:39:29.22,0:39:36.35,Default,,0000,0000,0000,,this, I would like to end and yeah, leave\Nyou with some references, and hope you
Dialogue: 0,0:39:36.35,0:39:39.01,Default,,0000,0000,0000,,have some questions for me.
Dialogue: 0,0:40:01.13,0:40:14.91,Default,,0000,0000,0000,,Herald: Sind wir durch? So, ja. Herzlichen\NDank für den Vortrag. Ich hab, bevor wir
Dialogue: 0,0:40:14.91,0:40:20.78,Default,,0000,0000,0000,,zum Q&A kommen muss ich einmal mich im\NNamen der Produktion bei den Zuschauern
Dialogue: 0,0:40:20.78,0:40:25.38,Default,,0000,0000,0000,,entschuldigen, ich glaube ihr hattet etwas\NProduktionssound auf den Ohren, das sollte
Dialogue: 0,0:40:25.38,0:40:34.20,Default,,0000,0000,0000,,natürlich nicht so sein. Gut, wir haben\Njetzt keine Fragen aus dem Chat bisher.
Dialogue: 0,0:40:42.14,0:40:50.94,Default,,0000,0000,0000,,Aber vielleicht eine Frage von mir, das\Nletzte Beispiel war ja ein Fall
Dialogue: 0,0:40:50.94,0:41:00.66,Default,,0000,0000,0000,,einer Klage über Ländergrenzen hinaus\Nquasi, ist das ein Ansatz, den man, den
Dialogue: 0,0:41:00.66,0:41:06.56,Default,,0000,0000,0000,,wir in Zukunft öfter sehen würden, das\Nheißt, dass über Ländergrenzen hinweg
Dialogue: 0,0:41:06.56,0:41:13.54,Default,,0000,0000,0000,,Menschen oder Organisationen sich\Ngegenseitig versuchen quasi über den
Dialogue: 0,0:41:13.54,0:41:20.49,Default,,0000,0000,0000,,Klageweg auf den richtigen Weg zu bringen.\NFO: Also es ist tatsächlich ein, eine
Dialogue: 0,0:41:20.49,0:41:31.94,Default,,0000,0000,0000,,Ausnahme, dass das im Fall RWE und Lliuya\Nfunktioniert, denn das deutsche Recht
Dialogue: 0,0:41:31.94,0:41:36.33,Default,,0000,0000,0000,,sieht vor, dass Firmen, die in Deutschland\Nansässig sind auch verschieden
Dialogue: 0,0:41:36.33,0:41:39.34,Default,,0000,0000,0000,,verantworlich sind, die nicht in\NDeutschland stattfinden.
Dialogue: 0,0:41:39.34,0:41:44.75,Default,,0000,0000,0000,,H: So sorry to interrupt. I just realized\Nthat we are still in English talk. Sorry
Dialogue: 0,0:41:44.75,0:41:48.81,Default,,0000,0000,0000,,for that.\NFO: OK. No worries. So your question was
Dialogue: 0,0:41:48.81,0:41:56.12,Default,,0000,0000,0000,,if we're going to see more\Ninternational court cases where across
Dialogue: 0,0:41:56.12,0:42:03.04,Default,,0000,0000,0000,,countries, across nation states we have\Nclimate litigation. And this type of
Dialogue: 0,0:42:03.04,0:42:07.37,Default,,0000,0000,0000,,litigation that I've just shown as\Nthe example is in so far an
Dialogue: 0,0:42:07.37,0:42:13.87,Default,,0000,0000,0000,,exception, as in German law, a company is\Nalso responsible for the damages caused
Dialogue: 0,0:42:13.87,0:42:20.06,Default,,0000,0000,0000,,outside of Germany. Which is not the case,\Nfor example, for companies in the US
Dialogue: 0,0:42:20.06,0:42:30.15,Default,,0000,0000,0000,,or so. So, and this is why Lliuya sued RWE\Nand not, for example, ExxonMobil. But
Dialogue: 0,0:42:30.15,0:42:40.78,Default,,0000,0000,0000,,these type of cases, where this\NLliuya case is an example. We see a lot of
Dialogue: 0,0:42:40.78,0:42:48.38,Default,,0000,0000,0000,,a lot of them, an increasing number of\Nthem each year. And they are difficult to
Dialogue: 0,0:42:48.38,0:42:57.94,Default,,0000,0000,0000,,do across nations because this, the German\Nlaw is exceptional on that case. But there
Dialogue: 0,0:42:57.94,0:43:03.34,Default,,0000,0000,0000,,are other ways, like, for example, why are\Nhuman rights courts that can be done
Dialogue: 0,0:43:03.34,0:43:11.23,Default,,0000,0000,0000,,across nation states and that is also\Nhappening. So it's at the moment, it is
Dialogue: 0,0:43:11.23,0:43:18.56,Default,,0000,0000,0000,,still legally not super straightforward to\Nto actually win these cases, but
Dialogue: 0,0:43:18.56,0:43:24.32,Default,,0000,0000,0000,,increasingly a lot of lawyers working on\Nthat so that we will see a lot of
Dialogue: 0,0:43:24.32,0:43:31.58,Default,,0000,0000,0000,,change in that in the coming years.\NH: OK, thank you. In the meantime, there
Dialogue: 0,0:43:31.58,0:43:37.86,Default,,0000,0000,0000,,appeared some questions from the chat and\Nfrom the Internet. I will go through them.
Dialogue: 0,0:43:37.86,0:43:42.91,Default,,0000,0000,0000,,First question is: are the results of the\Nindividual attribution studies published
Dialogue: 0,0:43:42.91,0:43:50.45,Default,,0000,0000,0000,,as open data in a machine readable format?\NFO: {\i1}laughter{\i0} So all the studies that
Dialogue: 0,0:43:50.45,0:43:57.62,Default,,0000,0000,0000,,we do that that I've done with my\Nteam, with world weather attribution. So
Dialogue: 0,0:43:57.62,0:44:03.02,Default,,0000,0000,0000,,there all the data is\Navailable, and it's available on a
Dialogue: 0,0:44:03.02,0:44:11.00,Default,,0000,0000,0000,,platform that's called Climate Explorer.\NSo that should be machine readable. So and
Dialogue: 0,0:44:11.00,0:44:17.79,Default,,0000,0000,0000,,this is deliberately because yeah, because\Nwe want to make it as transparent as
Dialogue: 0,0:44:17.79,0:44:23.76,Default,,0000,0000,0000,,possible so everyone can go away, use our\Ndata, and redo our studies, and find out
Dialogue: 0,0:44:23.76,0:44:29.45,Default,,0000,0000,0000,,if we made any mistakes. But this is not\Nthe case for all the studies that exist,
Dialogue: 0,0:44:29.45,0:44:34.83,Default,,0000,0000,0000,,because most of them or many of them are\Npublished in peer reviewed journals and
Dialogue: 0,0:44:34.83,0:44:39.07,Default,,0000,0000,0000,,not all peer reviewed journals have\Nopen data and open access policies.
Dialogue: 0,0:44:39.07,0:44:45.95,Default,,0000,0000,0000,,But increasingly, journals have.\NSo if you, for example, go to the
Dialogue: 0,0:44:45.95,0:44:51.41,Default,,0000,0000,0000,,CarbonBrief website and look at the map of\Nstudies, there you have links to all
Dialogue: 0,0:44:51.41,0:44:56.33,Default,,0000,0000,0000,,the studies. And a lot of them have the\Ndata available.
Dialogue: 0,0:44:56.33,0:45:05.00,Default,,0000,0000,0000,,H: OK, maybe a follow up to this one. The\Nnext question is, are the models somehow
Dialogue: 0,0:45:05.00,0:45:11.91,Default,,0000,0000,0000,,available or usable for a wider interest\Npublic or is APC required? I'm not quite
Dialogue: 0,0:45:11.91,0:45:18.02,Default,,0000,0000,0000,,sure what APC means.\NFO: So the model data is publicly
Dialogue: 0,0:45:18.02,0:45:25.78,Default,,0000,0000,0000,,available from–and this is one reason why\Nwe have been able to do these studies
Dialogue: 0,0:45:25.78,0:45:31.28,Default,,0000,0000,0000,,because until relatively recently, model\Ndata was not publicly available and only
Dialogue: 0,0:45:31.28,0:45:36.39,Default,,0000,0000,0000,,scientist working in a specific country\Ncould use the model developed in that
Dialogue: 0,0:45:36.39,0:45:44.81,Default,,0000,0000,0000,,country–but now all the model data is\Nshared publicly and people can use it. So
Dialogue: 0,0:45:44.81,0:45:50.83,Default,,0000,0000,0000,,it's definitely there and usable. It just\Nrequires some expertise to make sense of
Dialogue: 0,0:45:50.83,0:46:00.00,Default,,0000,0000,0000,,it. But it's, yeah, people can use it.\NH: OK, the next question is: to what
Dialogue: 0,0:46:00.00,0:46:05.45,Default,,0000,0000,0000,,certainty can you set up counterfactual\Nmodels, which are an important reference
Dialogue: 0,0:46:05.45,0:46:12.92,Default,,0000,0000,0000,,to your percentage value, and what\Ndata are the basis for these models?
Dialogue: 0,0:46:12.92,0:46:19.76,Default,,0000,0000,0000,,FO: So the counterfactual simulations are-\Nthe climate models we use are basically the
Dialogue: 0,0:46:19.76,0:46:23.97,Default,,0000,0000,0000,,same models that are used also for the\Nweather forecast. They are just run in
Dialogue: 0,0:46:23.97,0:46:30.52,Default,,0000,0000,0000,,lower resolution. So, which I guess most\Nof this audience knows what that means. So
Dialogue: 0,0:46:30.52,0:46:36.67,Default,,0000,0000,0000,,the data points for the part, so that it's\Nnot so computing intensive. And these
Dialogue: 0,0:46:36.67,0:46:43.39,Default,,0000,0000,0000,,models, they are tested against observed\Ndata. And so that is how we do the model
Dialogue: 0,0:46:43.39,0:46:48.60,Default,,0000,0000,0000,,evaluation. So that is some simulations of\Nthe present day. And for the
Dialogue: 0,0:46:48.60,0:46:57.43,Default,,0000,0000,0000,,counterfactual, we know extremely well how\Nmany greenhouse gases have been included
Dialogue: 0,0:46:57.43,0:47:02.01,Default,,0000,0000,0000,,into the atmosphere since the beginning of\Nthe Industrial Revolution, so that there
Dialogue: 0,0:47:02.01,0:47:07.74,Default,,0000,0000,0000,,is some very large certainty with that\Nnumber and we remove that from the models'
Dialogue: 0,0:47:07.74,0:47:13.08,Default,,0000,0000,0000,,atmospheres. So the models have exactly\Nthe same set up, but the lower
Dialogue: 0,0:47:13.08,0:47:16.72,Default,,0000,0000,0000,,greenhouse gases, lower amount of\Ngreenhouse gases in the atmosphere, and
Dialogue: 0,0:47:16.72,0:47:24.58,Default,,0000,0000,0000,,then are spun up and run in exactly the\Nsame way. So, they, but of course, we
Dialogue: 0,0:47:24.58,0:47:33.62,Default,,0000,0000,0000,,can't test the counterfactual. And so that\Nmeans that we assume that the sort of the
Dialogue: 0,0:47:33.62,0:47:40.51,Default,,0000,0000,0000,,the weather was still the same, physics\Nwill still hold in the counterfactual. And
Dialogue: 0,0:47:40.51,0:47:45.80,Default,,0000,0000,0000,,that the models that are developed\Nusing present day represent the
Dialogue: 0,0:47:45.80,0:47:48.88,Default,,0000,0000,0000,,counterfactual. Which is, which is an\Nassumption.
Dialogue: 0,0:47:48.88,0:47:51.82,Default,,0000,0000,0000,,But it is not a completely\Nunreasonable assumption, because of
Dialogue: 0,0:47:51.82,0:48:00.74,Default,,0000,0000,0000,,course, we have now decades of model\Ndevelopment and have seen that, in fact,
Dialogue: 0,0:48:00.74,0:48:05.99,Default,,0000,0000,0000,,that indeed climate model projections that\Nhave been made 30 years ago have actually
Dialogue: 0,0:48:05.99,0:48:13.11,Default,,0000,0000,0000,,come… come to… have been realized, and\Npretty much the same way on a large scale
Dialogue: 0,0:48:13.11,0:48:18.98,Default,,0000,0000,0000,,that they have, as they had been predicted\N30 years ago. And so that assumption
Dialogue: 0,0:48:18.98,0:48:24.89,Default,,0000,0000,0000,,is not, yeah, it's not a big assumption.\NSo the counterfactual itself is not a
Dialogue: 0,0:48:24.89,0:48:29.70,Default,,0000,0000,0000,,problem. But of course, also the present\Nday model simulations, they are
Dialogue: 0,0:48:29.70,0:48:34.99,Default,,0000,0000,0000,,not… they are very far from perfect. And\Nthere are some types of events which state
Dialogue: 0,0:48:34.99,0:48:41.04,Default,,0000,0000,0000,,of the art climate models just can't\Nsimulate. And so, where we can- what
Dialogue: 0,0:48:41.04,0:48:46.56,Default,,0000,0000,0000,,we can say very little. So well, for\Nexample, for hurricanes, we can say
Dialogue: 0,0:48:46.56,0:48:51.73,Default,,0000,0000,0000,,with high certainty about the\Nrainfall associated with hurricanes, the
Dialogue: 0,0:48:51.73,0:48:56.67,Default,,0000,0000,0000,,hurricane strength itself and the\Nfrequency of hurricanes is something
Dialogue: 0,0:48:56.67,0:49:01.97,Default,,0000,0000,0000,,which is very difficult to simulate with\Nstate of the art models. So our
Dialogue: 0,0:49:01.97,0:49:12.64,Default,,0000,0000,0000,,uncertainty there is much higher.\NH: OK. And then, well, some, one question
Dialogue: 0,0:49:12.64,0:49:20.17,Default,,0000,0000,0000,,that emerges from all of this is,\Nof course, if we know this much and way
Dialogue: 0,0:49:20.17,0:49:26.72,Default,,0000,0000,0000,,more than in the past, how are\Npoliticians still ignoring that
Dialogue: 0,0:49:26.72,0:49:34.94,Default,,0000,0000,0000,,information? And how can we\Nconvey that into their minds?
Dialogue: 0,0:49:34.94,0:49:39.88,Default,,0000,0000,0000,,FO: Well, if I knew the answer to that, I\Nwould probably not be standing here,
Dialogue: 0,0:49:39.88,0:49:49.48,Default,,0000,0000,0000,,but actually doing politics. But I\Nthink it takes a frustratingly long time
Dialogue: 0,0:49:49.48,0:49:56.85,Default,,0000,0000,0000,,for things to change and things should\Nchange much faster. But we actually- the
Dialogue: 0,0:49:56.85,0:50:03.51,Default,,0000,0000,0000,,last two years have shown huge progress, I\Nthink, in terms of also putting climate
Dialogue: 0,0:50:03.51,0:50:11.83,Default,,0000,0000,0000,,change on the agenda of every politician.\NBecause, and that's largely due to the
Dialogue: 0,0:50:11.83,0:50:17.74,Default,,0000,0000,0000,,Fridays For Future movement, but also to a\Ndegree, I think, due to the fact that we
Dialogue: 0,0:50:17.74,0:50:23.80,Default,,0000,0000,0000,,now actually know that the weather that\Npeople experience in their backyard–and
Dialogue: 0,0:50:23.80,0:50:29.40,Default,,0000,0000,0000,,pretty much independent of where their\Nbackyard is–is not the same as it used to
Dialogue: 0,0:50:29.40,0:50:37.43,Default,,0000,0000,0000,,be. And so people do experience today\Nclimate change. And I think that
Dialogue: 0,0:50:37.43,0:50:42.70,Default,,0000,0000,0000,,does help to bring a bit more urgency.\NAnd, of course, I would have said everyone
Dialogue: 0,0:50:42.70,0:50:47.63,Default,,0000,0000,0000,,has climate change on their agenda, which\Nwas very different even two years ago,
Dialogue: 0,0:50:47.63,0:50:52.14,Default,,0000,0000,0000,,where there were lots of people who\Nwould never talk about climate change and
Dialogue: 0,0:50:52.14,0:50:57.88,Default,,0000,0000,0000,,their political agendas has played no\Nrole. It doesn't mean that it
Dialogue: 0,0:50:57.88,0:51:05.79,Default,,0000,0000,0000,,has the right priority on that agenda,\Nbut it's still a huge step forward that
Dialogue: 0,0:51:05.79,0:51:18.71,Default,,0000,0000,0000,,has been made. And so I think we do know\Nsome things that do work, but we just have
Dialogue: 0,0:51:18.71,0:51:28.08,Default,,0000,0000,0000,,to just keep doing that. Yeah, I don't\Nthink I can say more. I don't have a magic
Dialogue: 0,0:51:28.08,0:51:35.20,Default,,0000,0000,0000,,wand to change it otherwise.\NH: Maybe some other point of impact.
Dialogue: 0,0:51:35.20,0:51:40.14,Default,,0000,0000,0000,,One of the question is, is it possible to\Nturn the results of attribution studies
Dialogue: 0,0:51:40.14,0:51:47.92,Default,,0000,0000,0000,,into recommendations for farmers and\Npeople who are affected in a financial way
Dialogue: 0,0:51:47.92,0:51:53.36,Default,,0000,0000,0000,,by extreme weather and how to change\Nagriculture to reduce losses from extreme
Dialogue: 0,0:51:53.36,0:51:56.58,Default,,0000,0000,0000,,weather effects?\NFO: Yes, absolutely. So that is
Dialogue: 0,0:51:56.58,0:52:03.73,Default,,0000,0000,0000,,one of the most useful things of these\Nstudies is well, on the one hand, to raise
Dialogue: 0,0:52:03.73,0:52:07.96,Default,,0000,0000,0000,,awareness. But on the other hand, if you\Nknow that a drought that you have
Dialogue: 0,0:52:07.96,0:52:16.93,Default,,0000,0000,0000,,experienced that has led to losses is a\Nharbinger of what is to come, then that is
Dialogue: 0,0:52:16.93,0:52:22.63,Default,,0000,0000,0000,,incredibly helpful to know how\Nagricultural practices might need to be
Dialogue: 0,0:52:22.63,0:52:29.88,Default,,0000,0000,0000,,changed. Or that insurance for losses from\Nagriculture might need to be changed. And
Dialogue: 0,0:52:29.88,0:52:36.01,Default,,0000,0000,0000,,so this is exactly why we do these\Nattribution studies. Because not
Dialogue: 0,0:52:36.01,0:52:42.77,Default,,0000,0000,0000,,every extreme event has always\Nshows the fingerprints of
Dialogue: 0,0:52:42.77,0:52:47.99,Default,,0000,0000,0000,,climate change. And if you know\Nwhich of the events are the ones where
Dialogue: 0,0:52:47.99,0:52:53.92,Default,,0000,0000,0000,,climate change is a real game changer, you\Nalso do know where to put your efforts and
Dialogue: 0,0:52:53.92,0:53:00.49,Default,,0000,0000,0000,,resources to be more resilient in the\Nfuture. And for financial losses, it
Dialogue: 0,0:53:00.49,0:53:06.07,Default,,0000,0000,0000,,is on the one hand, yeah, you can use\Nthese studies to find out what your
Dialogue: 0,0:53:06.07,0:53:12.93,Default,,0000,0000,0000,,physical risks are for your assets. And\Nhow they, and of course, everything that
Dialogue: 0,0:53:12.93,0:53:17.71,Default,,0000,0000,0000,,I've said, comparing the counterfactual\Nwith the present we can do, and we do this
Dialogue: 0,0:53:17.71,0:53:23.95,Default,,0000,0000,0000,,also with the future. So you can also see\Nhow in a two degree world, the events,
Dialogue: 0,0:53:23.95,0:53:29.22,Default,,0000,0000,0000,,the likelihood and intensities are\Nchanging. And of course, you can then
Dialogue: 0,0:53:29.22,0:53:35.25,Default,,0000,0000,0000,,also, in a less direct way, use this kind\Nof information to see, to assess what
Dialogue: 0,0:53:35.25,0:53:42.88,Default,,0000,0000,0000,,might be other risks from- where might be\Nstranded assets, what are other risks
Dialogue: 0,0:53:42.88,0:53:48.91,Default,,0000,0000,0000,,for the financial sector,\Nfor the financial planning.
Dialogue: 0,0:53:48.91,0:53:57.19,Default,,0000,0000,0000,,Where could liability risks be and how\Ncould they look like. So there is, because
Dialogue: 0,0:53:57.19,0:54:02.45,Default,,0000,0000,0000,,extreme weather events and their changes\Nin intensity and magnitude is how climate
Dialogue: 0,0:54:02.45,0:54:10.36,Default,,0000,0000,0000,,change is manifesting, it really connects\Nall these aspects of where the
Dialogue: 0,0:54:10.36,0:54:21.92,Default,,0000,0000,0000,,impacts of climate change are.\NH: OK, last question for today. I hope I
Dialogue: 0,0:54:21.92,0:54:30.02,Default,,0000,0000,0000,,can get that right. I think the question\Nis if there are study, if there are
Dialogue: 0,0:54:30.02,0:54:40.52,Default,,0000,0000,0000,,studies on how we cultivates fields\Nand agriculture. How does this impact the
Dialogue: 0,0:54:40.52,0:54:48.95,Default,,0000,0000,0000,,overall climate in that area? The example\Nhere is that only an increase in water
Dialogue: 0,0:54:48.95,0:54:57.85,Default,,0000,0000,0000,,consumption was directed to São Paulo. Or\Nmight there also be a warm world created
Dialogue: 0,0:54:57.85,0:55:06.44,Default,,0000,0000,0000,,by monoculture in central Brazil?\NFO: So, yeah, I don't know details, but
Dialogue: 0,0:55:06.44,0:55:13.46,Default,,0000,0000,0000,,there are, but land use changes and land\Nuse does play a role. On the one hand, it
Dialogue: 0,0:55:13.46,0:55:20.21,Default,,0000,0000,0000,,affects the climate. So if you have, if\Nyou have a rainforest, you have a very
Dialogue: 0,0:55:20.21,0:55:26.94,Default,,0000,0000,0000,,different climate in that location as if\Nthere is a savanna or plantation. And
Dialogue: 0,0:55:26.94,0:55:35.23,Default,,0000,0000,0000,,also, of course, if you have monocultures,\Nyou are much more, your losses are
Dialogue: 0,0:55:35.23,0:55:42.10,Default,,0000,0000,0000,,larger usually as if you have different\Ntypes of agriculture. Because
Dialogue: 0,0:55:42.10,0:55:46.83,Default,,0000,0000,0000,,in a monoculture everything is in\Nexactly the same way vulnerable and
Dialogue: 0,0:55:46.83,0:55:52.03,Default,,0000,0000,0000,,so that, yeah. So that does,\Nland use change plays a hugely important
Dialogue: 0,0:55:52.03,0:55:59.39,Default,,0000,0000,0000,,role with respect to the impacts of\Nextreme weather. And that is one thing to
Dialogue: 0,0:55:59.39,0:56:03.57,Default,,0000,0000,0000,,look at. When I was saying, talking about\Nlooking at vulnerability and exposure, and
Dialogue: 0,0:56:03.57,0:56:08.52,Default,,0000,0000,0000,,of course also changes in the hazard are\Nnot just because of climate change, but
Dialogue: 0,0:56:08.52,0:56:12.61,Default,,0000,0000,0000,,also because of land use change. And you\Ncan use exactly the same methods, but
Dialogue: 0,0:56:12.61,0:56:17.04,Default,,0000,0000,0000,,instead of changing the CO2 or the\Ngreenhouse gases in the atmosphere of your
Dialogue: 0,0:56:17.04,0:56:22.79,Default,,0000,0000,0000,,model, you can change the land use and\Nthen disentangle these different drivers
Dialogue: 0,0:56:22.79,0:56:29.87,Default,,0000,0000,0000,,in and hazards.\NH: OK, Fredi Otto thank you very much for
Dialogue: 0,0:56:29.87,0:56:37.29,Default,,0000,0000,0000,,your presentation and for the Q&A. It was\Na pleasure to have you with us. And yeah,
Dialogue: 0,0:56:37.29,0:56:43.80,Default,,0000,0000,0000,,if you have any questions, any more\Nquestions, I guess there are ways to
Dialogue: 0,0:56:43.80,0:56:47.25,Default,,0000,0000,0000,,contact you.\NFO: {\i1}laughter{\i0}
Dialogue: 0,0:56:47.25,0:56:52.54,Default,,0000,0000,0000,,H: I think your email address and contact\Ndetails are in the Fahrplan for all the
Dialogue: 0,0:56:52.54,0:56:58.93,Default,,0000,0000,0000,,viewers that have way more questions. And,\NI don't know, do you have access to the 2D
Dialogue: 0,0:56:58.93,0:57:05.52,Default,,0000,0000,0000,,world and do you explore that?\NFO: Given that I don't know what you mean,
Dialogue: 0,0:57:05.52,0:57:07.35,Default,,0000,0000,0000,,probably not, but…\N{\i1}laughter{\i0}
Dialogue: 0,0:57:07.35,0:57:12.07,Default,,0000,0000,0000,,H: OK.\NFO: That can also be changed.
Dialogue: 0,0:57:12.07,0:57:20.95,Default,,0000,0000,0000,,H: Yeah, it's the the replacement for\Nthe congress place itself. But anyway,
Dialogue: 0,0:57:20.95,0:57:26.70,Default,,0000,0000,0000,,if you viewers and you people out there\Nhave any more questions, contact Fredi
Dialogue: 0,0:57:26.70,0:57:32.93,Default,,0000,0000,0000,,Otto. And thank you again very much for\Nyour talk. And, yeah. Have a
Dialogue: 0,0:57:32.93,0:57:35.33,Default,,0000,0000,0000,,nice congress, all of you.
Dialogue: 0,0:57:35.33,0:57:39.08,Default,,0000,0000,0000,,{\i1}rc3 postroll music{\i0}
Dialogue: 0,0:57:39.08,0:58:13.96,Default,,0000,0000,0000,,Subtitles created by c3subtitles.de\Nin the year 2020. Join, and help us!