Empowering weather and climate forecast
How are we doing? We're collecting feedback. How useful are our apps and datasets? How easy is it to access them and work with them? Please take the time and complete our survey.
We will host our second workshop and second bootcamp next week at the premises of ECMWF in Reading, UK. We're thrilled to have gotten 242 registrations from 59 (!) countries on 6 continents!
This could become very influential:
Classical numerical models of the atmosphere exhibit biases due to incomplete process descriptions and they are computationally highly demanding. Recent AI-based weather forecasting models reduce the computational costs but lack the versatility of conventional models and do not provide probabilistic predictions.
The AtmoRep project asks if one can train one neural network that represents and describes all atmospheric dynamics. The FZJ team around Martin Schulz recently published a paper describing how this novel, task-independent stochastic computer model of atmospheric dynamics provides superior results for a wide range of applications: nowcasting, temporal interpolation, model correction, and counterfactuals.
Congrats to our MAELSTROM team members Bing Gong, Michael Langguth, Martin Schulz, and their FJZ colleagues!
Read the full paper here.
AtmoRep project page
We're approaching two major events before MAELSTROM turns into the home stretch! The registration for both our second Dissemination Workshop and our second Boot Camp are open. Be sure to reserve your place.
