121–130 of 310 posts
Are there any experts around that can chime in on the possible impacts of this technology if widely adopted?
In case someone is looking for historical weather data for ML training and prediction, I created an open-source weather API which continuously archives weather data. Using past and forecast data from multiple numerical weather models can be combined using ML to achieve better forecast skill than any individual model. Because each model is physically bound, the resulting ML model should be stable. See: https://open-me…
Based on historical data!
In case someone is looking for historical weather data for ML training and prediction, I created an open-source weather API which continuously archives weather data. Using past and forecast data from multiple numerical weather models can be combined using ML to achieve better forecast skill than any individual model. Because each model is physically bound, the resulting ML model should be stable. See: https://open-me…
I'm used to working with different weather stations, e.g. seeing different snowfall prediction at the bottom of a mountain, halfway up, and at the top, where the coordinates are quite similar.
What are the similarities between weather forecasting and financial market forecasting?
What are the similarities between weather forecasting and financial market forecasting?
Beyond the difficulty of running calculations (or even accurately measuring the current state), is there a reason to believe weather is unpredictable? I would imagine we probably have a solid mathematical model of how weather behaves, so given enough resources to measure and calculate, could you, in theory, predict the daily weather going 10 years into the future? Or is there something inherently “random” there?
What you're describing is effectively how climate models work; we run a physical model which solves the equations that govern how the atmosphere works out forward in time for very long time integrations. You get "daily weather" out as far as you choose to run the model. But this isn't a "weather forecast." Weather forecasting is an initial value problem - you care a great deal about how the weather will evolve from t…
In case someone is looking for historical weather data for ML training and prediction, I created an open-source weather API which continuously archives weather data. Using past and forecast data from multiple numerical weather models can be combined using ML to achieve better forecast skill than any individual model. Because each model is physically bound, the resulting ML model should be stable. See: https://open-me…
Is there somewhere to see historical forecasts? So not "the weather on 25 December 2022 was such and such" but rather "on 20 December 2022 the forecast for 25 December 2022 was such and such"