The meteoblue Learning MultiModel (mLM) is our unique post-processing technique, which trains the output from numerical weather prediction with measurement data. It uses AI (Artificial Intelligence) - since 2018, long before the entire world (and Basel Fasnacht) started to talk about AI.
mLM uses current weather measurement data and 10-20 different weather models to select and weight the model with the most accurate simulation for the local downscaled forecast.
The new mLM version was developed over several months by adding computation power and mathematics. This version now delivers even better and more complete probability distributions for each forecast hour and station. This data is then used to calculate temperature, dewpoint temperature and wind speed predictions. It also enables us to continue adding many more weather stations, as we did recently for France. In addition, the number of outliers was significantly reduced. During development, we have carefully validated the new mLM version, resulting in an accuracy improvement of more than 5% compared to the previous forecast data, making this the weather forecast with the highest publicly documented accuracy worldwide. We will soon publish a detailed validation study on our verification pages.
The mLM uses measurement data as input for model training. Consequently, we also improved the quality of the input measurement data by implementing various new quality control algorithms, ensuring a high quality of the measurement data.
We hope that you notice the forecast improvement in your daily operations or systems, and will continue to work on improvements based on your feedback.
