| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| 82° to 83° | 1% | 0¢ | 1¢ | — | $8K | Trade → |
| 84° to 85° | 77% | 81¢ | 88¢ | — | $6K | Trade → |
| 81° or below | 1% | 0¢ | 1¢ | — | $5K | Trade → |
| 86° to 87° | 13% | 13¢ | 19¢ | — | $4K | Trade → |
| 88° to 89° | 1% | 1¢ | 2¢ | — | $2K | Trade → |
| 90° or above | 1% | 0¢ | 1¢ | — | $1K | Trade → |
This market asks what the single highest air temperature recorded in Houston on March 6, 2026 will be; it matters to traders, energy managers, and weather-sensitive businesses because temperature swings affect demand and operational risk. The outcome is determined by an official observation source specified on the market page.
Houston’s weather in early March sits in seasonal transition between winter and spring, so temperature outcomes can be influenced by either lingering cool fronts or early warm surges. Historical variability on this date reflects influences from large-scale patterns (e.g., troughs/ridges, Gulf moisture) and local effects like urban heat and sea-breeze interactions. The market lists six discrete outcome buckets that cover a range of possible high temperatures for that calendar date.
Market odds summarize collective expectations about which temperature bucket will be highest, but you should interpret them as real‑time trader sentiment rather than fixed forecasts. For precise resolution mechanics and which observing station is used, consult the market's official rules on the KALSHI event page.
The market’s resolution source is listed on the KALSHI event page; resolution typically relies on an official National Weather Service or other designated station/observation, so check the event rules to confirm the exact station and dataset used.
The six outcomes are distinct temperature buckets that cover increment ranges for the day’s highest temperature; the specific numeric endpoints for each bucket are shown on the market page under outcomes or rules.
Model changes begin to materially affect expectations roughly 2–5 days before the date, with the highest sensitivity in the 24–48 hours prior when mesoscale features (fronts, sea breezes) are better resolved.
Historical values provide climatological context—how warm or cool the date typically is—and can help identify whether a given outcome would be anomalous; consult a reliable climate record (NOAA/NCEI or local NWS climatology) for exact past highs.
Participants usually include independent weather traders, energy and utility hedgers, agriculture and logistics firms, and prediction market speculators who use weather forecasts and model output to take positions ahead of the event.