People working in logistics know how much weather affects operations.
Wind, heavy rain, heat, ice and flooding change journey times, access routes, crane windows, construction sites and safety decisions. AI-supported models can calculate these developments with increasing speed and detail.
The European Centre for Medium-Range Weather Forecasts, ECMWF, has operated its own Artificial Intelligence Forecasting System since 2025. In May 2026, it was updated to version 2. It provides individual forecasts and ensembles of possible developments up to 15 days ahead.
Such a system still faces uncertainty. It can show possible developments earlier and indicate how uncertain they are.
Operational teams can turn a forecast into specific questions:
- Does a time window need reassessing?
- Does a heavy transport need an alternative route?
- Should a crane appointment be confirmed or postponed?
- Which construction site is particularly exposed?
- Who decides which threshold triggers a response?
Many companies already have weather data. A useful next step is to agree on a process for how and when to respond to it.
AI know-how for logistics professionals in 2 minutes
What is an ensemble?
An ensemble calculates many slightly different possible developments. Similar results indicate a relatively stable forecast. Large differences indicate greater uncertainty.
For logistics, that uncertainty may matter more than an individual number. A system should help answer:
- What is the range of possible outcomes?
- Which operational threshold could be exceeded?
- Which transports or construction sites are affected?
- Which decision does a person need to make, and by when?
AI can support an early-warning system that connects relevant forecasts with specific operations.
At ViMoKi, we are interested in connecting external signals with orders, documents and open decisions. Responsibility remains with the people involved.