| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| 44° to 45° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 46° to 47° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 43° or below | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 50° to 51° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 48° to 49° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 52° or above | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks which temperature range will be the highest recorded in Chicago on March 12, 2026, and matters for traders, event planners, and anyone exposed to weather risk in the region.
Early March in Chicago sits in a transitional season: large swings between cold and mild regimes are common, and a single synoptic feature can produce very different outcomes. Long-term warming trends, the urban heat island, and Lake Michigan interactions all shape variability on a given day.
Market odds reflect the collective expectation of participants about which temperature bin will be realized and update as forecasts, model runs, and observations change. Interpret them as a summary of current information, not a guaranteed forecast.
It covers the calendar day of March 12, 2026 in local Chicago time (00:00–23:59 local), as recorded by the market's designated official reporting source; consult the event rules for the precise timing and time zone used.
The market's event rules specify the official reporting station or dataset (for example an NWS station, airport observation, or specific weather observation feed); check the event page or rules to confirm which source is authoritative.
Large-scale tendencies can be seen a week or more in advance, but useful, actionable information for a single-day high typically emerges from short-range (0–7 day) deterministic and ensemble model guidance and high-resolution mesoscale runs in the 3–5 day window.
Yes — temperatures can vary across the metro due to elevation, urbanization, and lake proximity; the market will use the designated official station, so outcomes hinge on that reported measurement rather than neighborhood conditions.
New high-resolution model runs, shifts in frontal timing or storm tracks, official forecasts or statements from the National Weather Service, sudden changes in snow cover, or unexpected mesoscale features (like late-season convective clouds) can all prompt rapid market adjustments.