#weatherforecasting
Live, measured metrics for the hashtag #weatherforecasting from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #weatherforecasting
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Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 08:47 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-27 08:47 UTCNo related tags with measured usage found for #weatherforecasting.
Live pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 08:47 UTCEverything below is measured over the latest 40 public posts (spanning ~10003 hours).
Posting hours (UTC) — busiest: 09:00
Languages: English (37) · German (2) · French (1)
Avg boosts / post: 1.2
Top of the latest posts
I work in this field and this paper captures the moment everything shifted. This is the first side-by-side comparison of ML-generated forecasts against operational NWP, initialized from identical conditions. PanguWeather matches the IFS for
The question I get asked most: do ML weather models break in a different climate? We tested AIFS, GraphCast, and Pangu-Weather across pre-industrial, current, and +2.9K warmer climates. The dynamics hold up -- skillful forecasts across all
This is literally my day job and it still blows my mind sometimes. ECMWF now shows ML weather forecasts from FourCastNet, Pangu-Weather, and GraphCast alongside the operational IFS on our public charts. Same verification, same standards. Pl
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