on September 11th 2023 weather predictions in the northeast of the US sounded like this all eyes are on Hurricane Le the storm has strengthened back to a category 3 we're expecting it to make a northward turn over the next few days by September 16th after being downgraded storm Lee made landfall in Nova Scotia Canada flooding roads Downing trees and cutting out power for tens of thousands of people along the east coast at least 5 days before hurricane Lee struck land weather forecast had roughly predicted its trajectory but another forecast beat them 3 days before weather stations an AI model created by Google predicted the Cyclone's path the AI revolution has reached meteorology and it's at a time when we are responding to extreme weather more than ever we're about to find out if it'll help us prepare by bringing the future into Clear View predicting future weather more than a few hours out starts with creating a snapshot of Earth's current atmosphere scientists do that by collecting data from sources Like Satellites and weather stations and buoys located around the world taking pictures of clouds and measuring temperature and pressure and wind speed and humidity all that disperate data gets fed into computers which generate a 3D grid of boxes that represent the atmosphere both vertically and horizontally computers then do a lot of physics to determine how these conditions interact with each other and they produce a forecast I think any forecast has like 150 trillion calculations it's pretty amazing all that math requires some of the world's most powerful supercomputers the two big ones are run by the European Center for medium-range weather forecasts and the National Weather Service in the US to make a local weather forecast from this Global model meteorologists zoom in and ref find their own forecast with their local expertise like if they live in a hilly area or a flat area or near a lake they'll adjust those models and do their own professional interpretation based on their area no matter what this initial 3D grid of atmosphere is never going to exactly replicate reality there's too many gaps in the data we can measure that means forecasts get blurrier the further out you go which is why the big weather centers don't just generate one forecast they tweak the initial data and produce up to 50 forecasts it's called Ensemble forecasting and it helps meteorologists measure uncertainty if all 50 forecasts look similar there's a higher certainty in the prediction but if there's a lot of variation there's much less we got to kind of keep an eye to the sky there's a potential up under the storm in the works this one from 0% chance to 40% at 2:00 70% at 8:00 and at 11:00 we had a tropical storm weather centers only release their forecast every 6 hours because that's all today's computing power will allow but what if that limmit didn't exist before we explain that we'll hear from the sponsor of this video this episode is presented by Microsoft 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like hey you have terabytes of data I can learn how weather moves AI models learned how weather moves not through applying trillions of physics equations to the Earth's atmosphere but by being trained on a5's enormous historical data set researchers gave the models a snapshot of weather conditions asked them to make a prediction and then scored them on how closely that prediction matched what really happened after a while the models eventually got really good at this by 2023 the tech companies Google Huawei and Nvidia had developed models that rivaled traditional forecasting on variables like surface temperature humidity and wind speed and on some extreme weather events like the paths of tropical Cyclones atmospheric rivers and extreme temperatures these AI models still rely on the same observation data from the big weather centers the data that creates that initial 3D grid snapshot but they don't require anything close to 6 hours to produce a prediction huawei's pangu weather model for example can produce a week-long forecast in 1.4 seconds which means that we spent over a century figuring out the physics the atmospheric science and the computational skill to bring us our modern day weather forecast and now suddenly we have these AI models that have come out of you know the past 2 3 years and they're getting the same skill and now they run on a modest lap top despite the impressive results from these first AI models there's still lots of work to do Google's graph cast predicted hurricane Le's path faster than traditional models but it didn't prove it could predict A hurricane's intensity which is a trickier calculation to make these AI models are incentivized to get as many correct answers as they can through the scoring system if you swing for it swing for the fences right if it misses the model is penalized very large it says no you should never do that don't swing for the fences cuz the error is going to be huge but by prioritizing safer correct answers to boosta model score it could miss rare outlier weather events plus they are learning from 40 Years of history and historical weather has fewer extreme events than we do today or will have in the future due to climate change but a big reason for optimism with these AI models comes from their Ensemble forecasting instead of the traditional 50 Ensemble forecasts they can predict a thousand or more because they're freed from Computing and time constraints there's always going to be uncertainty in a weather prediction but larger ensembles will help us measure that uncertainty better that's extremely useful context to say you are a emergency manager down in Florida who's dealing with the very difficult decision are are you going to you know order an evacuation or not you want as much information about the uncertainty as possible large ensembles might also catch a rare weather event that a 50 member Ensemble would miss or measure the probability of weather events even further into the future than our 10-day forecast are we magically going to get a crystal ball that lets us foresee perfectly into the future probably not I think especially on like subseasonal time scales like multiple months out we're going to be able to frame the statistical question with a lot more specificity and probably a much better quantification of the uncertainty we do have a new winter storm warning that's been issued one thing we shouldn't expect to change anytime soon is the role of the meteorologist at least the ones you see on TV if only because we fundamentally have to communicate uncertainty and we have to walk through all the the various wh ifs and a human is the best tool that we have today to effectively communicate that and help somebody else make a decision AI forecasting models are still in an experimental phase but the European Center for medium-range weather forecasting has started publishing AI forecast alongside their traditional ones for the public to compare when we check the weather in the very near future it might be powered by AI instead of physics based models or a combination of the two and if we get things right we'll have a sharper view of the weather events that we need to prepare for the [Music] most