Context
Open-Meteo now offers Google DeepMind WeatherNext 2 — a 64-member global AI ensemble (0.25°, 6-hourly, out to 15 days) via the Ensemble API endpoint (different from our forecast endpoint). It rides our existing paid Open-Meteo subscription — confirm no extra cost before building.
Most of this model is not for FastWeather: a 64-member ensemble is a meteorologist's tool, and a 64-line "spaghetti plot" is exactly the decoder-ring UI this app avoids (see WAM/simplicity principles). This issue is scoped to the one on-brand idea, not adopting the model wholesale.
The idea: an accessible confidence signal on the 16-day forecast
The value an ensemble adds over a single deterministic model is uncertainty — how much the members agree. Our 16-day forecast currently shows day 14/16 with the same visual authority as tomorrow, which quietly overstates certainty; single-model forecasts that far out are close to noise.
Use ensemble spread (Open-Meteo already exposes ensemble mean + standard deviation) to surface confidence in plain language, e.g.:
"Next 3 days: high confidence. Days 8–16: forecasts disagree — treat as a rough outlook."
This is the same principle behind the air-quality work (#94): never present a number as more certain than it is.
Hard scope guardrails
Open questions
- Cost/quota impact of the Ensemble API endpoint on our plan.
- Whether to derive confidence from WeatherNext 2 specifically or a blend of ensembles Open-Meteo offers.
- Portability of the confidence logic to the web and Windows apps.
Priority
Backlog / exploration — explicitly not a detour from finishing the air-quality feature. Captured so the framing isn't lost.
Context
Open-Meteo now offers Google DeepMind WeatherNext 2 — a 64-member global AI ensemble (0.25°, 6-hourly, out to 15 days) via the Ensemble API endpoint (different from our forecast endpoint). It rides our existing paid Open-Meteo subscription — confirm no extra cost before building.
Most of this model is not for FastWeather: a 64-member ensemble is a meteorologist's tool, and a 64-line "spaghetti plot" is exactly the decoder-ring UI this app avoids (see WAM/simplicity principles). This issue is scoped to the one on-brand idea, not adopting the model wholesale.
The idea: an accessible confidence signal on the 16-day forecast
The value an ensemble adds over a single deterministic model is uncertainty — how much the members agree. Our 16-day forecast currently shows day 14/16 with the same visual authority as tomorrow, which quietly overstates certainty; single-model forecasts that far out are close to noise.
Use ensemble spread (Open-Meteo already exposes ensemble mean + standard deviation) to surface confidence in plain language, e.g.:
This is the same principle behind the air-quality work (#94): never present a number as more certain than it is.
Hard scope guardrails
Open questions
Priority
Backlog / exploration — explicitly not a detour from finishing the air-quality feature. Captured so the framing isn't lost.