Outdoor air feeds: where the outside numbers come from

The Terrestream sensor measures what is in the room. It does not measure what is outside. For outdoor conditions the dashboard depends on third-party data feeds: temperature, humidity, pressure, wind, precipitation, ozone, NO₂, SO₂, ammonia, PM₁₀, PM_2.5, aerosol optical depth, UV index, pollen species counts, and mold-spore forecasts. The combined picture (indoor sensor + outdoor feed) is what lets the AI advise on opening windows, running HEPA, closing the house up, or scheduling outdoor activities.

There are three providers. The weather side is Open-Meteo, an open-data weather API that aggregates multiple upstream models: ECMWF (the European reference forecast), NOAA GFS, regional models like ICON-D2 and HRRR, and station observations from METAR and national networks. The air-quality side is the Google Air Quality API, which reports pollutant concentrations (PM_2.5, PM₁₀, ozone, NO₂, SO₂, CO), a universal AQI, and the local US EPA AQI, drawn from government monitoring networks and atmospheric models. The pollen side is the Google Pollen API, which forecasts tree, grass, and weed pollen by region.

Update cadence and accuracy. Current-condition weather refreshes every 15 minutes. Air quality refreshes hourly. Pollen forecasts update daily during the active season. The forecast horizon is several days with declining accuracy past day 3; the dashboard uses the next 24-48 hours for most "open a window?" decisions. Spatial accuracy is best near urban monitoring stations and degrades in rural areas where the model leans more on simulation and less on observations. Ozone forecasts are generally good in summer because the inputs are well-characterized; SO₂ is rougher because point-source events (volcanic eruptions, refinery upsets) are not well-predicted by regional models. See where do the numbers come from for the indoor side of the same question.