On April 10, 2026, the Yes price for the 22°C option dropped quickly from 33.5c to 22.5c, as pre-resolution weather models slightly upwardly revised the expected high temperature center to the 23°C-24°C range. On April 8, 2026, the Yes price for 20°C plummeted from 30.5c to 10.5c, while the 24°C option rebounded from 15c to 25c, due to updated weather models ruling out stronger cold air interference and solidifying the warming trend.

Weather prediction is a relatively common category in prediction markets and traditional weather derivatives. However, betting on the exact daily high temperature of a specific city during a non-extreme weather period is somewhat niche, with participants relying almost entirely on meteorological forecast models.

From 2026-04-09 to 2026-04-10, the 'Yes' price for 11°C surged from 30.5c to 45.5c, as weather models solidified their forecasts around 11°C approaching the resolution date. From 2026-04-08 to 2026-04-10, the 'Yes' price for 9°C plummeted from 27c to 4.75c, driven by diminishing expectations of a cold front, drastically reducing the likelihood of such low temperatures.

There is a moderate interpretation risk. Key points: 1. **Post-analysis upgrades**: NOAA often re-analyzes data months after the season, upgrading a 'depression' to a 'named storm'. The market's strict settlement timeline (May 31/June 1) excludes these retrospective changes. If NOAA upgrades a May system in July, the market may have already settled incorrectly. 2. **Subtropical Storms**: While NOAA names subtropical storms (resolving 'Yes'), 'Subtropical Depressions' remain unnamed (resolving 'No'). Close attention to official NHC 'Public Advisories' vs. 'Tropical Weather Outlooks' is required for borderline systems.

Apr 7, 2026 - Apr 9, 2026, the price of Option_'Yes' surged from 32.5c to 45.5c, likely due to new long-range weather model runs again hinting at potential subtropical cyclogenesis, triggering speculative buying. Mar 29, 2026 - Apr 2, 2026, the price of Option_'Yes' surged from 12.5c to 40.5c, likely due to phantom subtropical cyclogenesis signals in long-range weather models (like the GFS, common in spring), triggering renewed speculative buying. Mar 27, 2026 - Mar 29, 2026, the price of Option_'Yes' plummeted from 40.0c to 12.5c, as previous model disturbances completely dissipated, causing a rapid reversion to the climatological baseline. Mar 20, 2026 - Mar 26, 2026, the price of Option_'Yes' fluctuated narrowly between 40.5c and 49c without a clear directional move exceeding 10c. This suggests the market has entered a stalemate, with traders waiting for new weather model signals and a lack of fresh catalysts. Mar 14, 2026 - Mar 20, 2026, the price of Option_'Yes' fluctuated narrowly between 49c and 50c without clear direction. This suggests the market has entered a stalemate following the mid-March volatility, with traders waiting for new weather model signals and a lack of fresh catalysts. Mar 10, 2026 - Mar 13, 2026, the price of Option_'Yes' rebounded from 39.5c to 48c. This movement likely reflects the market re-evaluating potential long-range model disturbances after a brief dip, or buying pressure in a low-liquidity environment, though it did not breach previous highs. Feb 27, 2026 - Mar 5, 2026, the price of Option_'Yes' consolidated narrowly between 40c and 41c, showing no volatility exceeding 10c. This indicates the market entered a 'wait-and-see' phase as the previous model threat was digested and no new signals emerged. Feb 22, 2026 - Feb 23, 2026, the price of Option_'Yes' surged from 31.5c to 49.5c before retracing. This was driven by speculative buying triggered by a short-term signal in weather models (likely GFS) suggesting subtropical genesis, a signal that subsequently faded without realization.

The market currently prices the probability of a pre-season named storm at 45.5%, which diverges significantly from meteorological consensus and historical climatological baseline (typically around 10-15%). This divergence is primarily driven by prediction market participants overreacting to unstable, noisy signals in long-range spring weather models, which are notorious for low accuracy at this time of year.