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# Weather drones are filling the data blind spot that armies and traders both need

**[The Next Web](https://daily.dev/sources/tnw)** · 4 min read · 0 upvotes · 0 comments

## Summary

As radiosonde balloon launches decline worldwide, including reduced US National Weather Service launches following 2025 federal staff shortages, drone makers like Switzerland's Meteomatics are stepping in with reusable 'Meteodrones' that sample temperature, humidity, pressure and wind in the lower atmosphere. Meteomatics delivered operational drone data to the US National Weather Service for the first time this year as part of a NOAA push to integrate drones into routine forecasting. The push matters because AI weather models from Google DeepMind and Swiss startup Jua depend on fresh, high-quality observational data to stay accurate, and energy traders and militaries are among the biggest beneficiaries of sharper low-altitude readings.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://thenextweb.com/news/weather-drones-forecasting-traders-military>

## Questions this post answers

### Why are weather balloon launches declining and what is replacing them?

Radiosonde balloon launches have declined partly due to staff shortages after federal layoffs, which pushed the US National Weather Service to suspend or reduce launches at a string of upper-air stations. Reusable drones, such as Meteomatics' Meteodrones, are filling the gap by climbing several kilometers to sample temperature, humidity, pressure and wind, then landing to fly again, unlike single-use balloons.

_Engineers building on weather and sensor APIs can follow infrastructure shifts like this on daily.dev._

### Why do AI weather forecasting models need more low-altitude atmospheric data?

AI weather models, including Google DeepMind's forecaster, are only as accurate as the observations feeding them, and the lowest few kilometers of the atmosphere is where most weather happens. Without fresh ground-truth readings from that layer, even the most advanced neural network is essentially guessing about current conditions rather than genuinely forecasting them.

_Developers working on AI forecasting pipelines can track data-quality stories like this on daily.dev._

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---

Tags: [#ai](https://daily.dev/tags/ai), [#data-science](https://daily.dev/tags/data-science)

[View this post on daily.dev](https://daily.dev/posts/weather-drones-are-filling-the-data-blind-spot-that-armies-and-traders-both-need-apma3jhbt)

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