Do One-Minute Observations (OMO) Give You an Edge? We Backtested a Year.

This is an educational article about weather data and how a daily-high model uses it. It is not financial, investment, or trading advice, and nothing here is a recommendation to do anything. It's just meteorology and data.

There's a persistent belief in temperature markets: the edge is faster, finer data. One-minute observations (OMO). The 5-minute high-frequency METAR feed. The old ASOS one-minute phone line. The logic is intuitive — if you see the temperature more often than everyone else, you'll catch the daily peak first.

We wanted to know if that's actually true, so we tested it: a full year of one-minute observations for seven cities, millions of readings, checked against the official settled highs. The answer surprised us twice, and it's worth walking through — because it changes what "an edge" even means here.

What OMO actually is

One-minute observations (OMO) are exactly what they sound like: the ASOS station's temperature reported every minute, instead of the roughly hourly cadence you see in a standard METAR. It sounds like a strict upgrade — 60× more resolution on the temperature trace.

There's a catch that matters a lot: OMO temperature is reported in whole degrees Fahrenheit. More often, but coarser. Hold that thought — it's the whole story.

First test: OMO looks like a cheat code

Compare one-minute obs against a plain hourly METAR and OMO looks incredible. Because it samples so much more often, it "catches" sub-hourly peaks the hourly reading walks right past — often a degree or two of daily high that an hourly-only view never sees.

If you stop here, you conclude OMO is a must-have and go chase the feed.

But hourly METAR is the wrong thing to compare against. A good daily-high model doesn't run on hourly obs. It already ingests the 5-minute ASOS feed, the METAR 6-hour maximum group (the precise sub-hourly record), and the eventual CLI. Against that, the picture changes.

Second test: so is precision the edge? Also no.

Our next guess was that precision would be the real winner. The METAR remark T-group reports temperature to a tenth of a degree Celsius, every hour. OMO is only whole degrees. Surely precise-but-slower beats fast-but-coarse?

The year of data said no. The official daily high is itself a whole-degree number, and the coarse-but-frequent OMO feed predicted that settled number about as often as the precise feed did — sometimes more. Neither "faster" nor "more precise" was an edge on its own. Both tidy stories were wrong.

What actually held up

Two findings survived the full year:

1. The precise 5-minute observations a good pipeline already ingests predict the settled high with essentially zero bias. For practical purposes, they already are the settlement. There isn't much headroom above that for a new feed to claim.
2. Every single raw feed has a failure mode. The OMO archive has multi-week gaps and the occasional bogus sensor spike (one city's file had a 53°F jump that never happened). The hourly feed systematically under-reads. The precise T-group is unbiased but fuzzy right at the rounding boundary — where markets settle. Lean on any one feed and you inherit its blind spot.

Put those together and the conclusion isn't "OMO is useless." It's subtler: no single feed wins, because each one is wrong in its own way.

The real edge: fusion and calibration

If no feed is the answer, what is? The thing that fuses them.

A daily-high model that's worth anything doesn't pick a feed — it reconciles them. It takes the tenth-of-a-degree T-group, the whole-degree obs, the 6-hour maximum group, and the official climate report, notices where they disagree, and resolves the conflict. Then it does the part that actually matters for a market that pays out on a bracket: it turns that reconciled picture into a calibrated probability — how likely the high crosses a given threshold, whether the peak is already in, and how confident to be — tuned so that "90%" means it happens about nine times in ten.

That's the same reason a model firms up in the afternoon rather than the morning (When Daily-High Temperature Models Firm Up During the Day), and the same machinery that explains oddball settlements like Chicago Midway settling 88°F when the report said 87°F. A single fast feed can't do any of that. Reconciliation and calibration can.

The trader's read

• A faster feed is not automatically an edge. More frequent readings of a coarser signal don't beat a model that already fuses the precise ones.
• A more precise feed isn't automatically an edge either. We tried to prove it and the data didn't cooperate.
• Every feed lies to you somehow — gaps, spikes, under-reads, boundary fuzz. The value is in combining them, not in owning the fastest one.
• The edge is the honest probability on top of the data, not the data itself. Feeds are a commodity; a calibrated model is not.

A quick note on intellectual honesty, because it matters: our cleanest test against the exact number the market settles on is still a small sample — good archived history is short. So read this as "no single feed beat a fused model in our data," not a mathematical law. We kept the backtests, and we'll revisit as more settled days accumulate. If a feed ever earns its keep, we'll write that up too.

See it live

WeatherEdge runs a fused, calibrated daily-high model in real time — combining the precise and coarse feeds, tracking the 6-hour maximum record, and publishing a live uncertainty range for every market it covers. You can watch it tighten through the day and check it against the final CLI yourself. New accounts get a 7-day free trial with every station unlocked, no credit card.

Once more: this is an explainer about weather data and modeling, not financial or trading advice. It describes how a model uses observations — nothing more.