… although it does still depend on which part of the world you live in. But such minor niggles aside, weather forecasting is now very, very good. Or so says the latest Our World in Data article:
Weather forecasting has been a hard won (and hard fought!) battle. Did you know, for example, that the HMS Beagle was famous for more than just the one obvious thing?
Vice-Admiral Robert FitzRoy FRS (5 July 1805 – 30 April 1865) was an English officer of the Royal Navy and a scientist. He achieved lasting fame as the captain of HMS Beagle during Charles Darwin’s famous voyage, FitzRoy’s second expedition to Tierra del Fuego and the Southern Cone.
FitzRoy was a pioneering meteorologist who made accurate daily weather predictions, which he called by a new name of his own invention: “forecasts”. In 1854 he established what would later be called the Met Office, and created systems to get weather information to sailors and fishermen for their safety
https://en.wikipedia.org/wiki/Robert_FitzRoy
But over time, forecasts the world over have become better and better, and today we can count upon real time forecasts being made available literally by the second:
Faster speeds are crucial: the Met Office now chunks the world into grids of smaller and smaller squares. While they once modeled the world in 90-kilometer-wide squares, they are now down to a grid of 1.5-kilometer squares. That means many more calculations need to be run to get this high-resolution map. The methods to turn the observations into model outputs have also improved. We’ve gone from very simple visions of the world to methods that can capture the complexity of these systems in detail.
The final crucial factor is how these forecasts are communicated. Not long ago, you could only get daily updates in the daily newspaper. With the rise of radio and TV, you could get a few notices per day. Now, we can get minute-by-minute updates online or on our smartphones.
https://ourworldindata.org/weather-forecasts
Well, most of us can, but all of us can’t:
And that, as it turns out, is a problem, because you are much more likely to work in agriculture in a low income country, and are therefore that much more dependent on accurate and timely weather forecasts. Alas, you are unlikely to get these forecasts, precisely because you are a poor agricultural worker.
So what can help? Take a wild guess:
A recent paper published in Nature documented a new artificial intelligence (AI) system — Pangu-Weather — that can perform forecasts as accurately (or better) than leading meteorological agencies up to 10,000 times faster.6 It was trained on 39 years of historical data. The speed of these forecasts would make them much cheaper to run and could provide much better results for countries with limited budgets.
https://ourworldindata.org/weather-forecasts
EconForEverybody 