| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| 51° to 52° | 18% | 17¢ | 19¢ | — | $2K | Trade → |
| 48° or below | 46% | 44¢ | 47¢ | — | $2K | Trade → |
| 49° to 50° | 26% | 25¢ | 26¢ | — | $1K | Trade → |
| 53° to 54° | 8% | 8¢ | 9¢ | — | $1K | Trade → |
| 57° or above | 2% | 1¢ | 2¢ | — | $1K | Trade → |
| 55° to 56° | 2% | 2¢ | 3¢ | — | $518 | Trade → |
This market concerns the maximum air temperature recorded in Philadelphia on March 5, 2026. It matters because same-day temperature extremes influence energy demand, transportation, and local business operations and provide a focal point for short-term weather trading.
Early March in the Mid-Atlantic is a transitional period between winter and spring, so day-to-day temperatures can swing between winterlike cold and unseasonably mild conditions depending on synoptic-scale patterns. Climate trends and year-to-year variability both shape typical outcomes, and precise resolution depends on the official observing site and procedures defined by the market contract.
Market odds reflect the collective expectations of traders at any given moment and should be read as relative signals that update as new weather model output and observations arrive. For final determination, rely on the contract’s specified official data source and timing for the daily maximum temperature.
The market will resolve to the highest official air temperature as defined in the contract’s resolution text; check that text to see which observing station, network (for example an NWS or cooperative station), and time standard are used for the daily maximum.
Resolution typically occurs after official daily observations for Mar 5 become available per the contract’s timeline; because publication times vary by data source, consult the contract for the exact post-event settlement window.
Use climatology to set a baseline expectation—early March is historically variable—then overlay recent model trends and forecast anomalies; historical context helps identify whether a particular model run implies an unusually warm or cold departure from typical conditions.
Traders commonly watch global and regional deterministic models (e.g., ECMWF, GFS), high-resolution convection-permitting runs, ensemble forecasts for spread, National Weather Service guidance, surface observations, satellite/radar for cloud/precip timing, and model-derived temperature probability fields.
Urban heat island effects can raise daytime maxima within the city compared with surrounding rural areas; a sea-breeze or onshore flow can moderate highs near the river/coast; recent snow cover or saturated ground tends to limit daytime warming—so local surface conditions and wind direction on Mar 5 will materially affect the observed maximum.