| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| 70° to 71° | 99% | 99¢ | 100¢ | — | $20K | Trade → |
| 68° to 69° | 1% | 0¢ | 1¢ | — | $18K | Trade → |
| 72° to 73° | 1% | 0¢ | 1¢ | — | $13K | Trade → |
| 67° or below | 1% | 0¢ | 1¢ | — | $10K | Trade → |
| 74° to 75° | 1% | 0¢ | 1¢ | — | $10K | Trade → |
| 76° or above | 1% | 0¢ | 1¢ | — | $5K | Trade → |
This market asks which of six discrete outcomes will contain the highest temperature recorded in Denver on March 2, 2026. It matters for traders and anyone with weather-sensitive exposure because it aggregates short- and medium-range weather expectations for that specific date.
Denver’s weather in early March is seasonally variable: it can still experience winter chill and snow, or warm up rapidly under downslope (Chinook) conditions. Synoptic-scale features—Pacific storms, the Pacific jet, and upper-level ridging or troughing—have historically driven large day-to-day swings in March temperatures at Denver-area observing sites. The market currently shows active interest (source: KALSHI) and closes and official resolution details are listed on the event page.
Market odds reflect traders’ collective assessment of which temperature bin is most likely given available information; they update as new forecasts, observations, and model runs arrive. Interpret prices as relative market sentiment among the six discrete outcomes rather than fixed forecasts.
Close time is listed on the KALSHI event page as TBD; consult the event description there for the precise close and official resolution criteria, which typically specify the observing station and time window used for the daily high.
The six outcomes are discrete temperature bins or labeled ranges shown on the event page; check the market interface for the exact boundary values and any inclusivity rules (e.g., whether endpoints are inclusive).
Major moves usually follow new runs of global and high-resolution models, ensemble shifts, public National Weather Service forecasts or watches, updated satellite and radar analyses, and significant changes in observed upstream conditions that alter expected temperature trends.
Denver’s elevation, proximity to the Front Range, and urban/suburban land cover influence daily maxima; local downslope warming, valley positions, and recent snow cover can all produce substantial differences between nearby observing sites and between morning and afternoon highs.
Participants include weather traders using model-based forecasts, local meteorologists, event speculators, and businesses hedging weather exposure; motivations range from short-term speculation on forecast changes to hedging operational risk tied to temperature outcomes.