Understanding How Surface Weather Observations Become the Numbers People See Every Day
The temperature on tonight's news, the daily high in tomorrow's newspaper, the historical record posted on a city's climate page — all of these begin as raw observations from automated sensors at airports across the country. The path from sensor to public number is interesting, has many subtle steps, and is rarely explained in a way a non-specialist can follow. This research program aims to document that path through three connected studies, with findings published as accessible educational content for students, weather enthusiasts, journalists, and anyone curious about how the weather information they see every day is actually made.
Why this matters
Most people interact with weather data dozens of times a day — checking an app before leaving home, watching a forecast during dinner, reading about a heat wave in the news. The numbers in these products are the end of a long chain that starts with sensors, passes through quality-control software, and arrives at the public through different channels at different speeds. When two weather apps show slightly different temperatures for the same city, or when the official daily high doesn't match what a thermometer in the backyard recorded, the explanations live in this chain. This program produces written content explaining each link of that chain, in language a curious general reader can follow.
Three Proposed Studies
How Quickly Does Weather Data Reach the Public?
When you check the weather, how recent is the information you're looking at? This study documents the journey from sensor to screen.
Study 02 · ProposedWhy Two Apps Can Show Different Temperatures
How a sensor's quick blips and its smoothed averages produce different reported values for the same moment in time.
Study 03 · ProposedHow Much Do Consumer Weather Apps Disagree?
The apps people actually use — measured side by side, for the same place at the same moment, to see how far off they are from each other.
What Each Study Aims to Produce
Each study is designed around a question a curious general reader might ask, and the planned output for each is an accessible written explanation suitable for non-specialists.
- Study 01 — A clear explanation of how weather observations travel from sensor to public, with measured timing showing how recent the weather you're seeing actually is.
- Study 02 — A plain-language guide to why averaging windows matter in temperature reporting, helping readers interpret apparent discrepancies between different weather products.
- Study 03 — A comparison of the major consumer weather apps people use every day, measuring how much they disagree about the same location at the same moment, and explaining what causes the spread.
Who This Research Is For
The findings are intended to be useful for several audiences:
- General readers and weather enthusiasts who want to understand how weather data they encounter daily is actually generated.
- Students and educators in earth science, atmospheric science, and data communication courses.
- Journalists and science communicators who report on weather and climate and want grounded explanations of source provenance.
- Software developers who build weather-related tools and want to understand the public observation system they're building on.
- Climate-curious citizens who want to interpret historical records, daily summaries, and forecast products with a clearer mental model.
Sources of Information
This program draws on publicly available data and documentation from:
- The NOAA Meteorological Assimilation Data Ingest System (MADIS)
- The NOAA Aviation Weather Center public service
- The NOAA Telecommunications Gateway public file distribution
- The Iowa Environmental Mesonet community archive at Iowa State University
- The NOAA published daily weather summaries
- The NOAA Federal Meteorological Handbook and ASOS User's Guide documentation
Compliance & Attribution
All raw observational data is consumed internally for analysis. Educational content published from this research includes appropriate NOAA attribution, does not redistribute raw observational data, does not present a public-facing real-time data API or dashboard, and does not constitute a commercial weather service. The data is used to learn about and document the public observation system itself.
Selected References (used across studies)
- NWS Phoenix, High-Resolution KPHX ASOS Data. weather.gov/psr/HiResASOS
- Sun, B. and B. Baker (2005). A Comparative Study of ASOS and USCRN Temperature Measurements. Journal of Atmospheric and Oceanic Technology, 22(6).
- NOAA, Federal Meteorological Handbook No. 1: Surface Weather Observations and Reports.
- NOAA NWS, Automated Surface Observing System (ASOS) User's Guide. weather.gov/media/asos
- Iowa Environmental Mesonet. Wagering on ASOS Temperatures (technical commentary).