Your backyard has better weather data than the airport

Your backyard has better weather data than the airport

The official weather observation for my town comes from an airport 23 miles away, at an elevation 600 feet lower than my house, on the other side of a ridgeline. When it says "partly cloudy, 72°F," I have no idea whether that applies to me. Half the time, my yard is in fog while the airport is in sunshine. All winter, the airport sits above the inversion layer and reports temperatures 15°F warmer than anyone in the valley actually experiences.

Meanwhile, my neighbor has a $280 Davis Vantage Pro weather station sitting on a pole in their backyard. It reports every 5 minutes. It's 400 feet from my kitchen window.

Which one do you think knows whether it's going to rain on my kid's soccer game?

The citizen weather network that already exists

There is a staggering amount of weather data being collected by non-government sources right now, and almost none of it shows up in mainstream weather apps.

• PWS networks (Personal Weather Stations): WeatherUnderground, PWSWeather, and Ecowitt.net host hundreds of thousands of homeowner-operated stations globally. Most are consumer-grade ($150–$500), some are research-grade ($2,000+).

• CWOP (Citizen Weather Observer Program): A ham radio and enthusiast network with 9,000+ quality-controlled stations feeding NOAA.

• Mesonet / IEM (Iowa Environmental Mesonet): An aggregation of 45+ regional mesonets (agricultural, university, state DOT, research) typically at 5-minute cadence with calibrated sensors.

• Soil sensors: Agricultural networks tracking soil temp, soil moisture, and leaf wetness at depth. Wildly useful for frost prediction and growing-degree-day math.

• OpenSenseMap / Netatmo: Urban citizen science sensors, often in schoolyards and parks.

Any given suburb has dozens of these within a 5 km radius. Your actual official weather station has one airport METAR every hour.

Why most apps ignore all of this

Because raw PWS data is noisy. A station in direct sun over asphalt reads 10°F high. A station under a tree reads 3°F low and never sees rain. An Ecowitt unit that lost its Wi-Fi last Tuesday is still showing last Tuesday's conditions.

The usual shortcut is "just don't use them." Mainstream apps stick with airport METARs and global models because those are uniform and predictable, even when they're uniformly wrong about your specific location.

What we actually do with it

DewLogic pulls from all of the above and then does the work of making them trustworthy:

• HardwareTier bonuses. A professional sensor (Davis, Campbell Scientific, Vaisala) gets a +5 fidelity bonus. A consumer sensor gets 0. Unknown/ambiguous gets -5. This lets the blending engine trust better equipment more without kicking out the cheap ones.

• Anomaly rejection. If your reading disagrees with the reference by more than 3°C, you're excluded from this blend cycle. No one station can hijack the answer.

• Recency penalties. Stale data gets dropped. A sensor that hasn't reported in 30 minutes doesn't vote on current conditions.

• IDW blending. What survives gets weighted by distance and tier and combined into a single Virtual Station reading at your exact coordinates.

The result: your app's "current temperature" is the consensus of every well-sited, currently-reporting sensor within range, not one guess from 23 miles away.

A real example

Last winter, during a heavy lake-effect squall, the nearest METAR showed "light snow, 28°F, wind 10 mph NW." Three PWS within 2 km of my house were showing 27°F, wind 32 mph with 48 mph gusts, visibility under a quarter mile. The airport was 20 miles downwind of the squall band. The backyards were inside it.

A single-source app would have told me to go for a walk. The Virtual Station told me the truth.

If you run a PWS yourself and want your station weighted into your own Virtual Station, we support that. Drop your station ID in a reply.