| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| 61° to 62° | 1% | 0¢ | 1¢ | — | $41K | Trade → |
| 63° to 64° | 99% | 99¢ | 100¢ | — | $37K | Trade → |
| 58° or below | 1% | 0¢ | 1¢ | — | $24K | Trade → |
| 59° to 60° | 1% | 0¢ | 1¢ | — | $13K | Trade → |
| 65° to 66° | 1% | 0¢ | 1¢ | — | $8K | Trade → |
| 67° or above | 1% | 0¢ | 1¢ | — | $6K | Trade → |
This market asks what the highest air temperature recorded in Chicago on March 8, 2026 will be; it matters for traders, event planners, utilities, and anyone monitoring short-term weather risk in the region.
March weather in Chicago is typically variable, with large day-to-day swings driven by passing synoptic systems and the moderating influence of Lake Michigan. Historical seasonal variability and a long-term trend toward warmer extremes provide context, but the realized temperature on a single date is dominated by short-term weather patterns.
Market prices reflect the collective judgment of participants about which temperature range will occur; higher prices indicate greater market confidence in a given outcome, while the contract rules define how the final reading is selected and settled.
The listed close time is TBD; the outcome will be determined after the official highest temperature recorded for the local Mar 8, 2026 observation period at the station and time window specified in the contract rules—check the market page for the final close and settlement times.
The market's contract rules specify the official observing station and data source (for example, a National Weather Service or ASOS/MAOS station); consult the contract on the KALSHI market page to see the exact station and dataset used for settlement.
The six outcomes are discrete, mutually exclusive temperature ranges (bins); the contract rules list the numeric boundaries for each bin—review those boundaries on the market page to understand which readings map to each outcome.
Watch short- and medium-range deterministic and ensemble model runs (operational models and their ensembles), National Weather Service forecasts and advisories, surface observations, lake-surface and ice conditions on Lake Michigan, frontal timing, and cloud/precipitation forecasts in the 72 hours leading up to the date.
Long-term warming shifts the baseline distribution and increases the background likelihood of warmer extremes over decades, but the realized highest temperature on a single date is primarily determined by short-term weather patterns—use climate context as background information rather than a direct short-term forecast.