Every week someone emails us some version of the same question: “I need the temperature history for a list of zip codes, and everything I find is either a station ID I don’t recognize or an API I don’t have time to learn.” This guide explains how temperature history actually gets recorded, what “by zip code” really means, and the fastest routes to a usable file, including the free ones.
Where temperature records actually come from
No agency records “the temperature in 60614.” Temperatures are measured at weather stations, airports, water plants, volunteer observer sites, and each station reports a daily maximum, minimum, and average. NOAA’s National Centers for Environmental Information (NCEI) archives those observations going back decades.
A zip code dataset is built on top of that: each of the roughly 41,000 US zip codes gets matched to nearby station records, so a lookup for Chicago’s 60614 resolves to real observations instead of a citywide estimate. That matching step is where most do-it-yourself projects stall, because station coverage is uneven and stations open, close, and move.
What temperature history looks like in practice
Numbers make the differences obvious. In January, Buffalo’s 14201 typically sees average highs right around freezing with lows in the teens, while Phoenix’s 85001 runs highs in the mid-60s and rarely touches frost. Miami’s 33101 has never recorded a freeze in the modern record. If your sales, claims, or enrollment data varies by location, joining it to temperature history at this resolution is what makes the weather signal visible.
Resolution matters as much as geography. Daily history shows heat waves and cold snaps; monthly history shows seasonality; long-term averages describe what is normal for each month. A demand forecaster usually wants daily, a market analyst comparing regions is often better served by monthly, and a event planner mostly needs the long-term averages.
The free route, and what it costs you in time
NOAA’s Climate Data Online portal will give you daily station summaries at no charge, and for a single location that is often enough. The friction shows up at scale: you select stations rather than zip codes, orders over a size limit have to be split, gaps appear where stations were offline, and mapping thousands of stations to your zip list is a genuine data-engineering task. We wrote a step-by-step walkthrough in our guide to getting NOAA weather data into Excel if you want to try that route first.
If you only need one long-term value per zip code, grab our free historical average temperature by zip code dataset — every US zip code, no purchase required.
What the data looks like
| Zip Code | City | State | Period | Avg temperature (°F) |
|---|---|---|---|---|
| 98101 | Seattle | WA | Jul 2016 – Jun 2026 avg | 53.7 |
| 97201 | Portland | OR | Jul 2016 – Jun 2026 avg | 55.4 |
| 89101 | Las Vegas | NV | Jul 2016 – Jun 2026 avg | 70.8 |
| 85004 | Phoenix | AZ | Jul 2016 – Jun 2026 avg | 77.1 |
| 80202 | Denver | CO | Jul 2016 – Jun 2026 avg | 53.3 |
| 73301 | Austin | TX | Jul 2016 – Jun 2026 avg | 69.5 |
| 64101 | Kansas City | MO | Jul 2016 – Jun 2026 avg | 58.1 |
| 60601 | Chicago | IL | Jul 2016 – Jun 2026 avg | 53.5 |
| 55401 | Minneapolis | MN | Jul 2016 – Jun 2026 avg | 47.2 |
| 33101 | Miami | FL | Jul 2016 – Jun 2026 avg | 78.2 |
| 30301 | Atlanta | GA | Jul 2016 – Jun 2026 avg | 62.5 |
| 14201 | Buffalo | NY | Jul 2016 – Jun 2026 avg | 50.5 |
| 10001 | New York | NY | Jul 2016 – Jun 2026 avg | 56.5 |
| 02108 | Boston | MA | Jul 2016 – Jun 2026 avg | 53.1 |
Real rows from our free average-temperature dataset, shown to one decimal. One long-term average per zip code, 40,000+ US zip codes covered.
The ready-made route
Our datasets do the station-to-zip mapping and gap-filling once, for every US zip code, and deliver a flat Excel or CSV file you can open immediately. For temperature history specifically there are three tiers: 10 years of daily temperature data (about 3,650 observations per zip code), 10 years of monthly temperature data, and long-term average temperature by month. Each is a one-time purchase, no subscription or API key, and the pricing page compares them side by side.
If your project involves rainfall or snow instead, the same approach applies and we cover it in the precipitation data guide and the snowfall data guide.
Checks worth doing before you commit to any source
Whatever source you choose, run three checks with a sample before building on it. Confirm the temperature units and whether values are highs, lows, or averages. Spot-check a few zip codes you know personally against your own memory of that climate. And test one join against your business data early, because key mismatches (zip-plus-four, leading zeros dropped by Excel) surface fast and are cheap to fix at the start. Questions about a specific region or time span? Email contact@weatherdatabyzipcode.com, we answer these directly.
Temperature history also drives agronomic planning — see growing degree days by zip code.
Get free data: our four overall-average datasets (temperature, rainfall, snowfall, and humidity — every US zip code) are free to download here.