 A kloedd gyda 10 a 5-n toth fy y gallwn ni i a ddoch chi'n gweithgareddau mewn cyfroeddennig, ac neu ddim ddim i'r byw sydd, felly gallwn ni ddim ddim yn enwedig, fel y gallwn ni'n credu amdano c Siw, a ddim yn rhyw bwysig, a dwi'n rhai, oherwydd mae wedi ansiwm gweithio gwaith y brosentau. gallwn ni wedi'i defnyddio chi'n gweithgareddau. Maelriírwynt ar gyfer Y Llyfrgell yn y cyfrafffyrddol, fel y cyfroeddon wedi ei ddysgu'r gwirionedd, felly chi'n gweld maDIw yma ar y cwm yn yr unaddod y mater, yw'r mwygrifennol a'r ymdauio sy'n gweld gwnaeth y mater, sy'n gweld dwy y mwyglwch ar y pwynghwytoni, a'i wneud ar y pwynghwytoniaeth angen amddangos i ddiwethaf nhw? Felly fyddo i'r brifiewn arnos. Dwy ddim yn gweld. Ond, yn y cwestiynau? Felly, yn yw donentsau sy'n gweld dwy? Mae'n dweud gyda'i cwestiynau. Felly, rym ni gyd yn ymdill, Ma' 我是 llawer to all the other systems we're talking about are in terms of the data of the MET models but its strikes me that the data flows into them are substantially less in the MET office so there is this timelag in terms of what you were doing 10 years ago is relevant for the Forestry Commission or whatever it might be. Oh i si, yes so we have different strwydd so we we ran the models in real time as you o leolwch ein darnas o'r ddweud, ond roeddan nhw'n golygu'n gweithio'n gwirio'r dweud a'r drafod o'r ddaeth yn y climio. Mae'n hyn yn wedi eu gwneud, diwn yn golygu'n gwirio. Yn gweithfarn ddaeth o y roodannol, ond os y byddwch gweithwyr wedi gweithio'n gwirio'r mightad, rydyn ni'n ceisio'r gwriadau arall i'w gwirio'r holl. Tym yn angen, y 24-7, i dechreuio llawd, natrygedd, mae gymryd y dyfodol. Mae hynny'n faddunol yn יdw meddwl y cwbl yn hynny, mae hynny'n dyfodol yn ganun. Ameri'u gair i'w Gymryd heddiw, James Copeland, cyn ym 피wn cyf 않아요. Rydym ni cerd bod nifer 55,000 rhan o'r gwaith o'r ddaf sydd o gyllideb yn gweithglyniad o'r ddeuethol y dinant. Yn ei ffodol y dyfodol, maelodau ar gyfer y llun o'r ddaf, ond o'n dod i'r cyffredin wedi'u cyd-agod. Roedd ydydd y gallwch chi'n gweithio y dynodau, y dynodau, a'r dynodau canol yn cael ei gweithio'r arddangos, felly dynodau ar gyfer y dynodau, y dynodau, y dynodau, y dynodau, y dynodau, y dynodau, yn cael ei gweithio'r dynodau a'r gael. Rwy'n dechrau'n gael ar gyfer dynodau, ond mae'n ddweud ydych chi'n gweithio'r dynodau ar gyfer dynodau. Mae'n ddirmwyd, ac mae drwci o'r dynodau, mae'n symud yn gwneud hynny, fyddwch bod fagorol fagorol eich cyfnodau dysgu yna, sy'n meddwl ychydig felly oes yn cyd-fyniadau? Yn ydych chi'n gweithio'r ichi ddweud nad oedd eich cyfnodau? Hefyd yn'r cyfnodau yma, a lefyn ardal y gallwn awrachau sy'n eich cyfnodau ac fellyn sy'n gweithio'r llaw. Rwy'n gyfnod pethau eich cyfnodau. those that don't have that background, and from our point of view, we are very much about providing a service to that community, so it's about getting warnings out in good time, and obviously where we do have an incident, we have staff working with the associated services on the ground, and obviously where there is an incident, we then take account of what has actually happened in addition to sort of the surveys we talk to, to stakeholders being flooded, find out what their experience was, if it was the warning time need, did it give them the right information, and we've learnt a lot by doing that, so you're absolutely right. How we communicate what we derive from our models is absolutely essential, because people have got to understand it, it's all very well that we can take weather data, do a forecast of what's going to happen in the river, and then issue a warning, but actually that's got to be meaningful for the end users, so they know that, do I really need to put that stuff upstairs, do I need to tell my neighbour, what do I need to do, and that communication is absolutely essential, because in a way nothing else matters, it's the people at the end that are most important, so we take that very much to heart. Transdisciplinary is actually critical here, and it was interesting that UN Secretary-General declared that warnings for all for everybody on this planet should be an endeavour, so we went to the Pacific Islands as part of that UN team, and we asked them what is it you need, and they said we need you to predict birds, and what he and she meant was that we rely on the movement of birds in order to protect ourselves, and what he was talking about El Nino, La Nina response, for natural response, and so therefore we now predict birds for the Pacific, and then they relate that and communicate in the way that they understand. They didn't want all this massive data, they don't want this detailed analysis, they just want simple language that they can take action. Another question. Did I see a hand over the back there? Yes, thank you. Thank you. Somebody earlier in a previous talk talked about integrating some of the work with Key Stage 3 GCSEs and A levels, and I'm just interested to know if any of you are actively considering how we make sure that school kids keep up with these vast changes and the speed at which technology is taking place. It's changing. And whether you're involved in schools. Thank you. Thank you. Very interesting question. Skills is key to this, isn't it? Paula, I wonder if you have some thoughts on that? Yes, it's funny you say that because that's part of our Sentinel project, our Sentinel treescape, where we're looking to take it in the future, is into schools and have these sensors in a school environment. Their private areas of land often have trees, so we can have tree talkers in that area. And it also creates engagement with the scientific community at an early age, puts them into cutting edge development, looking at okay internet of things, sensors. Obviously the curriculum is vastly different to when I was there with programming, et cetera, et cetera, being learned from my little daughters started looking at programming. So it is changing, but being able to work with that resource is something we're definitely looking at expanding with this PhD student and our Sentinel project. Because you're right, you need to keep at the grass roots, you need to keep at that level of the new scientists, the new brains. Well, we have to. Paul, thanks very much. Juan, you showed a range of incredible technology scanning in the words and time. How can we train the next generation to be aware of these technologies and to use them? What's the best? I think the next generation are very familiar with, or they have been growing in a digital environment. The problem is the analogic people that haven't had the same opportunity or they're struggling to understand some of the concepts. So as I was saying in the last wave wagons of this train of knowledge, there are people even waiting at the station, they haven't boarded the train yet. And these people that are important if we want to transform the British landscape the way we are planning. And it is important to get this key that will allow us to communicate better with them and then get their feedback because they will feel they are on board. Otherwise, well, it's going to be more challenging, more difficult. Thank you, Juan. May I just ask the microphone back, please, to the questioner? May I just ask your view as well, Chrissy, if you could just bring the mic back. Thank you. I agree. I think it's a very difficult question because things are changing so quickly and curriculums in schools are slowed to change. Or if they do change, sometimes they change too quickly and the teachers can't keep up with them. I mean, I'm old enough to remember pre-PC and so therefore I've seen a lot of these changes over time. But I think things like using Minecraft and getting people involved at really early ages is great because you get an enthusiasm and an interest in building systems. But how you take it from that simple way to some of the big data ideas. A challenge for us all. Yes, please. Thanks for mentioning that. My colleague Chris Skinner is involved in just that sort of project. In fact, using Minecraft and other gaming platforms to help encourage young people of all ages who have that interest in gaming to see it as a... ..a way of not just learning but also just interacting with them. He's developed his own set of YouTube videos as part of his research but it's also linked to some of the work that we've been doing in the environment agency. So he was one of our colleagues who was at the Science Museum last month giving demonstrations and so on. So I think you're absolutely right. It's engaging with the sort of technologies that are familiar to that part of the population. And maybe making better use of things like school level hackathons as well as competitive activities. Very good. Thank you. I think we have time for another one or two questions. Who'd like to put one forward please? Yes. Good afternoon. My name's Chris Baker from Rothamsted Research. So a few years back I saw Tim Berners-Lee give a presentation on this stage. He was a proponent of semantic technologies for data integration. So with respect to all of the advanced modelling that we're seeking to achieve, there are presumably some bottlenecks in integrating data. And I'm really trying to sort of get a handle on the extent to which standards, specifically semantic knowledge models, ontologies, et cetera, are critical to this endeavour of prediction. I mean effectively if you can't integrate the data, you can't reuse it, you can't make it an analytic thready or whatever you want to call it or fair data. So to what extent really are we still at a bottleneck with adoption of standards for integration of data versus our predictive capabilities or leveraging HPC? So I'll leave it there, but I'm interested to hear your thoughts. Thank you, Chris. Semantic technologies and standards being a bottleneck. Colleagues. Any thoughts on, Paul, what sort of standards are being used to deal with all this massive data that's coming in? Has it had to be a new science of standards as well as the... I guess that what we're working on at the moment that has a standard and has a policy derived from it coming in in November is the biodiversity net gain and using the naturally metric tool that's kind of forced us into that standard. I think our bottleneck, to look at the bottleneck side of your question and somebody alluded to it earlier in the question, on the panel is skills. People, skills as a remote sensor, you're doing remote sensing projects, you wanted to upscale them. You think I need more remote sensors, but actually no, you need more DevOps people, you need more data people, you need more people that have different skill sets to your traditional skill set. And that comes back to the educational piece, making environmental jobs a tech job. Making these technologies and these data scientists are really going to be hugely important. So that's our bottleneck, it's just the skill sets to use, free up this data. Thank you very much, Paul. What about a view from the Met Office on standards for the sort of data sets you're working with? Well, it's back in 1950 when we, as a global community under WMA, which is a UN special agency, we all got together 192 countries. And we agreed that we need to share observation data because we didn't. And if we don't have access to Brazil's data and they don't have access to ours, we can't produce a forecast. So we agreed the standard by which we can exchange observations. We have been stuck to that and we police that, we monitor that. So in that sense, we do that. One thing I would be interested in people's comments on this as well as we embark artificial intelligence machine learning. It's becoming ever increasingly important that the quality of the data and the algorithms which are used is a scientific endeavour and standards that need to be adhered to it. Because we're starting to see that people on, there's a misinformation coming through from some of the output that comes from that. And I welcome that sort of push that will standardise it and then show in the quality assurance of the interpretation of that information. It's really critical now. And maybe there's a bottleneck in that as well perhaps. I don't know, but I endorse your point about skills as well. I've noticed that a lot and my wife is a teacher. And one thing of trying to, the other question about how do you get the youth involved. We've sort of embraced the idea that schools have their own observation system in a business evens and screening to the garden and let them observe the weather. And then they may be more interested in understanding how it unfolds. And you start really small and really simple and let it grow. Thank you. Well, fantastic. Paul Brown, Kwansoaers, Martin Boethwick and Paul Davies, thank you very much for your presentations. A big round of applause for them, thank you.