From 23d84a8149f6f832d348d023fca39cd8aa684f75 Mon Sep 17 00:00:00 2001 From: Peter Ling Date: Thu, 7 Mar 2024 12:42:13 +0000 Subject: [PATCH] Add line breaks --- ...the-Wind--Weather-Forecasting-in-the-Age-of-AI.md | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/_posts/2024-03-06-Something-in-the-Wind--Weather-Forecasting-in-the-Age-of-AI.md b/_posts/2024-03-06-Something-in-the-Wind--Weather-Forecasting-in-the-Age-of-AI.md index ea79c3607b..cb3ba3f633 100644 --- a/_posts/2024-03-06-Something-in-the-Wind--Weather-Forecasting-in-the-Age-of-AI.md +++ b/_posts/2024-03-06-Something-in-the-Wind--Weather-Forecasting-in-the-Age-of-AI.md @@ -22,6 +22,8 @@ Talking about the weather: it’s a national obsession. And why not? It changes In this blog post, I’m going to dive into some of the technology that we use to predict the weather, and look at an exciting new development that could revolutionise the field of meteorology: artificial intelligence. +
+ ## A Brief History of Weather Forecasting Since the beginning of time, people have tried to predict the weather. At first, with nothing more than prophecy and superstition (and perhaps some rituals to change any unfavourable outcomes). Aristotle was the first to put a bit of critical thinking into his predictions, but it wasn’t until the 17th century that the ideas and inventions of the Renaissance came together to give us the first scientific understanding of the weather. Fast-forward another couple of centuries, and Lewis Fry Richardson throws a bit of maths into the mix to give us our first glimpse of Numerical Weather Prediction. Then, in the 1950s, computers get involved and forecasting as we know it today really takes off. @@ -34,6 +36,8 @@ So what will come next in the world of weather forecasting? More complex numeric Unless you’ve been off [measuring the weather on Mars](https://mars.nasa.gov/msl/mission/weather/) for the last few years, you will have noticed that artificial intelligence is *the* hot topic in tech right now. Here at Scott Logic, we’ve kept a keen eye on [what’s going on](https://blog.scottlogic.com/category/ai.html). We’ve [built chatbots](https://blog.scottlogic.com/2023/07/26/how-we-de-risked-a-genai-chatbot.html); we’ve looked at the [sustainability of training large language models](https://blog.scottlogic.com/2023/11/24/llm-mem.html); we’ve analysed [what businesses need to deploy AI](https://blog.scottlogic.com/2023/11/22/capabilities-to-deploy-ai-in-your-organisation.html) and [how it might impact architecture](https://blog.scottlogic.com/2023/06/06/how-ai-may-impact-software-architecture.html). So what are the prospects of using AI for predicting the weather? +
+ ## Introducing GraphCast Turns out, it’s looking quite promising. In the last few months, [Google have announced GraphCast](https://deepmind.google/discover/blog/graphcast-ai-model-for-faster-and-more-accurate-global-weather-forecasting/): an AI model that they claim can make medium-range weather forecasts with more accuracy than traditional NWP methods. @@ -94,6 +98,8 @@ Start by collating recorded weather observations from around the world, going ba *Data Assimilation fills in the missing pieces to create a complete picture of the weather over the past 80 years. Image credit: Copernicus ECMWF [https://youtu.be/FAGobvUGl24](https://youtu.be/FAGobvUGl24)* {: style="font-size: 80%; text-align: center;"} +
+ ## Changing the World, One Forecast at a Time Whenever I come across a new application for AI, my initial thought tends to be, “that’s pretty cool…but does society really need this?” We’re living in a volatile time, and AI seems to be giving us more problems than solutions: deepfakes, copyright infringements, job insecurities. But using these techniques to predict the weather is something I can get on board with. I described at the start of this post just how important weather forecasting is, and using AI promises us more accurate results as well as more advanced notice of extreme weather events. Not only do the results improve, but we also see a dramatic decrease in energy demands. @@ -102,8 +108,12 @@ The initial training can be pretty intensive (Google used 32 of their Tensor Pro With less reliance on their supercomputers, forecasting agencies may need to invest in some new data engineering infrastructure. This could be an ideal opportunity for them to migrate to the cloud (pun very much intended) and perhaps to overhaul some of their legacy systems. +
+ ## This is the End +
+ ### The End of Supercomputers? Clearly not, but there are other high-performance computing applications that could take advantage of machine learning. We’re already seeing this kind of progress in fields such as computational chemistry and drug discovery, astrophysical simulation, computational fluid dynamics, and structural mechanics. @@ -117,3 +127,5 @@ With the dawn of AI-based forecasting, will we see the end of Numerical Weather Now this one is certain. We’ve seen what currently goes into forecasting the weather, and how artificial intelligence is making waves towards advancing and perhaps revolutionising the process with its potential to improve on both accuracy and energy consumption. Given humanity’s desire and need to predict the weather, I look forward to seeing how this area of development evolves over the coming years. Let’s keep talking about the weather. + +