Presentation
Towards Operational Data-Driven Forecasting at a National Weather Service
Presenter
DescriptionData-driven probabilistic forecasts have become a tangible possibility within just a couple of years, thanks to breakthroughs mostly driven by the tech industry and building on existing open datasets from the weather and climate community. National weather services play a crucial role in providing accurate and timely weather forecasts, essential for public safety and economic planning. The integration of machine learning (ML) presents transformative opportunities and challenges in enhancing predictive capabilities and providing novel products. We will showcase a few applications of ML which are already in operations, discuss some of the scientific and computing challenges which we have encountered, and present some early results from our efforts to build a regional data-driven forecasting model.
TimeMonday, June 314:30 - 15:00 CEST
LocationHG F 1
Event Type
Minisymposium
Climate, Weather, and Earth Sciences
Computational Methods and Applied Mathematics
