| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| 81° or below | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 82° to 83° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 84° to 85° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 86° to 87° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 88° to 89° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 90° or above | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks which temperature interval will contain the highest observed temperature in Austin on March 29, 2026. It matters for weather-sensitive planning (utilities, outdoor events, travel) and for traders who want to express views on a specific day’s weather outcome.
Late March in Austin sits in a transitional season that can produce anything from cool, post-frontal conditions to an early warm-up, so day-to-day variability is often large. Local factors such as Gulf moisture, passing fronts, and urban heat effects interact with synoptic-scale patterns to determine a single-day maximum. Long-term climate trends have increased the frequency of unusually warm days, but individual daily outcomes remain strongly driven by short-range weather systems.
Market prices reflect the collective, real-time judgement of participants about which temperature range will occur and incorporate observational reports, operational forecast models, and new information as it arrives. Treat prices as a summary of current expectations that can change rapidly as forecasts and observations update.
The market will use the official source specified in its rules to determine the daily maximum (typically an NWS/NOAA reporting station or another named observing site); check the market's resolution rules page to see which station and dataset are designated for this event.
The market’s closing time is listed on the event page; if listed as TBD, the market will announce a closing time and that closing time (or the observation window) governs trading cutoff and finalization—refer to the market page for updates.
Forecast models and ensemble guidance in the 1–4 days before the date are the primary drivers of changing expectations because they resolve fronts, cloud cover, and mesoscale features that strongly affect a single-day maximum.
Use historical late-March variability as context: the season is transitional and capable of large swings due to frontal passages, so climatology gives a baseline expectation but short-range dynamical forecasts usually dominate day-of outcomes.
Resolution procedures for missing or suspect data are defined in the market’s rules; common approaches include using provisional NWS data, an alternate official station, or a specified fallback dataset—consult the event rules for the exact protocol.