science

Meteoblue

Meteoblue is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Meteoblue rather than just read about it. In short: Meteoblue AG (stylized as meteoblue) is a Swiss weather forecasting company. It provides weather and climate services to consumers and to businesses in sectors including agriculture and renewable energy.

Key takeaways

Meteoblue belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Meteoblue to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Meteoblue from memory before moving on to harder problems.

Reference excerpt

Meteoblue AG (stylized as meteoblue) is a Swiss weather forecasting company. It provides weather and climate services to consumers and to businesses in sectors including agriculture and renewable energy. The service originated at the University of Basel, and the company was established as a university spin-off in 2006. Meteoblue uses artificial intelligence to combine forecasts from multiple weather models. In 2024, the weather service Windy acquired a majority stake in Meteoblue.

History In 1986, the Sandoz chemical disaster near Basel exposed gaps in cross-border meteorological analysis when Swiss, French and German meteorological services produced conflicting assessments of the direction in which potentially toxic smoke was moving. The disaster gave new impetus to regional climate research, and the University of Basel subsequently established the Institute for Meteorology, Climatology and Remote Sensing to improve local weather modelling. The forecasting work that became Meteoblue was developed at the institute. By 2005, meteoblue.ch was providing publicly accessible, high-resolution forecasts for Europe and had received the SWITCH Innovation Award. Meteoblue AG was established as an independent university spin-off in 2006. For the 2020 release of Microsoft Flight Simulator, developed by Asobo Studio, Meteoblue supplied global weather data used to simulate weather conditions in the game.

Services and technology Meteoblue produces weather forecasts using its own global and regional numerical weather prediction models together with forecast data from external providers. Its model families include NMM and NEMS. The company's Meteoblue Learning MultiModel (mLM) system combines output from multiple models with weather observations, radar and satellite data, using machine learning to produce location-specific forecasts. Forecasts are made available through Meteoblue's website and mobile applications. The company also supplies forecast and historical weather data through API and provides climate datasets.

References

External links http://www.meteoblue.com web site of meteoblue

Worked examples

Example 1 — a first encounter with Meteoblue

Start with the simplest possible case. Write down what Meteoblue claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Meteoblue before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Meteoblue ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Meteoblue

In research: Meteoblue appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Meteoblue in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Meteoblue is common in secondary-school and first-year university syllabi. It links to neighbouring topics Information technology companies of Switzerland, Meteorological companies, Meteorological organisations based in Switzerland, so understanding it makes those chapters shorter.
In everyday life: Look for Meteoblue outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Meteoblue in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Meteoblue means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Meteoblue out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Meteoblue in simple terms?

Why does Meteoblue matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Meteoblue?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Meteoblue.