Polymarket Weather Markets Guide
Last verified: 2026-06-18 PDT
Polymarket weather markets look simple because the titles are concrete: a temperature range, a city, a date, or a weather event. The trap is that the title is only the headline. Weather contracts can depend on the exact station, the source URL, date boundaries, units, precision, and whether later data revisions count.
In the live Gamma API sample checked on 2026-06-18, an active Los Angeles temperature market listed Wunderground's Los Angeles International Airport station as the resolution source. The description specified the date, Fahrenheit precision, when the next day's first data point matters, and how revisions are considered. That is the lesson: weather markets are not just "will it be hot?" They are data-source contracts.
Weather markets in plain English
A weather market asks whether a measurable condition will happen. Examples can include a maximum temperature range, rainfall threshold, snowfall total, hurricane category, or city-specific event. The price still works like other binary markets: a 0.32 Yes price can be read as roughly a 32% implied probability before spread and liquidity.
But weather markets add a special layer: measurement. You are not debating vibes. You are comparing a contract to a specific source's recorded data.
The resolution checklist matters more than the forecast
Before reading price, identify the measurement rules:
| Rule | Why it matters |
|---|---|
| Location | Airport station vs city center can change the value |
| Source | The listed source controls settlement |
| Date window | Local date, UTC date, and publication timing can differ |
| Units | Fahrenheit vs Celsius must be clear |
| Precision | Whole-degree rounding can decide close markets |
| Revisions | Some descriptions say when later changes stop counting |
A forecast can be useful research, but the market resolves on its own criteria. If the listed station reports a number that differs from another weather app, the listed station is the source that matters.
Example: turning a temperature price into a review
Suppose a market asks whether a city's high temperature will be 90°F or above on a specific date, and Yes trades at 0.44. The beginner read is: the market implies about a 44% chance. The better read is:
- ▸Which station decides the high?
- ▸Does the market use whole degrees or decimals?
- ▸When is the final datapoint available?
- ▸Is the current best ask meaningfully above the displayed midpoint?
- ▸How much liquidity is available if you need to exit?
- ▸What forecast sources are you comparing, and how reliable are they for that station?
Common weather-market mistakes
- ▸Using the wrong station. A city can have multiple stations with different readings.
- ▸Ignoring precision. A 0.4-degree difference may not matter if settlement uses whole degrees.
- ▸Assuming all forecasts agree. Models and apps can diverge close to the event.
- ▸Trading after the edge is gone. Weather markets can move quickly when updated forecasts drop.
- ▸Forgetting revision timing. Read when the market stops considering altered data.
Bucko framework: source, spread, scenario
Weather markets reward process. Use this three-part framework:
- ▸Source. Copy the exact resolution source into your notes.
- ▸Spread. Record best bid, best ask, and available size before entry.
- ▸Scenario. Define what forecast update or data publication would make you review the position.
Bucko can help organize this as a research note, checklist, journal entry, and post-event review. The goal is disciplined probability work, not prediction-market hype.
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Sources and last-verified notes
- ▸Polymarket Gamma API active-market sample, last checked 2026-06-18, included a Los Angeles temperature market with Wunderground KLAX as the listed resolution source.
- ▸Polymarket docs, market data overview, last verified 2026-06-18: public market data is available through public REST endpoints without an API key.
- ▸User-provided Bucko/Polymarket partner offer: code BUCKO, $50 deposit bonus for eligible U.S. app downloads.