| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| 54° or below | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 55° to 56° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 57° to 58° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 59° to 60° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 61° to 62° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 63° or above | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks what the highest air temperature recorded in Minneapolis on March 26, 2026 will be; it matters for short-term planning (energy, travel, outdoor events) and provides a focused way to trade on a specific weather outcome.
March in Minneapolis sits in the spring transition period and can produce both late-season cold outbreaks and early warm spells; historical records show substantial day-to-day variability, while multi‑decadal warming has shifted the seasonal distribution modestly. Single‑date outcomes are driven primarily by the synoptic weather pattern present on that day rather than long‑term trends alone.
Market odds express the collective assessment of traders given current forecasts and observations and will update as new model runs and observations arrive; treat prices as a realtime consensus signal, not a guaranteed meteorological forecast.
The market will settle to the official maximum temperature reported for Minneapolis on March 26, 2026 by the data provider/station specified on the KALSHI event page; if the event description does not name a station, consult the event rules or contact KALSHI support for the designated observing source (typically an NWS/NOAA official station).
Settlement occurs after the chosen data provider publishes the daily maximum for March 26, 2026; exact timing depends on that provider’s publication schedule and any platform settlement window—check the event page for KALSHI’s stated settlement timing.
Each of the six outcomes corresponds to a specific temperature bin or range defined in the event listing; traders should review the event’s outcome labels and boundaries on the page to know which range matches a given forecast.
Short‑range numerical model forecasts (0–5 day runs), radiosonde/upper‑air observations, surface station reports, changes in snow cover or cloud cover forecasts, and official NWS updates are the primary information types that typically change market expectations in the days and hours before the target date.
Long‑term warming shifts the baseline distribution and makes warmer outcomes relatively more probable over decades, but for a single calendar date the dominant influences are day‑to‑day weather patterns and the specific synoptic setup—use climate context as background, not a substitute for short‑range forecasts.