Lowest temperature in San Francisco on May 30, 2026?

Prediction market odds on Kalshi reflect real-money trader expectations for San Francisco's lowest temperature on May 30, 2026, and often diverge from traditional meteorological forecasts. While weather analysts rely on numerical models and historical patterns, prediction markets incorporate collective trader judgment and incentivize accuracy through financial stakes. Comparing Kalshi odds to National Weather Service or private meteorology firm forecasts can reveal whether markets are pricing in more optimistic or pessimistic temperature scenarios than expert consensus, offering a complementary perspective on likely outcomes.

On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. On Kalshi, the lowest temperature in San Francisco on May 30, 2026, is priced as a set of binary or range-based contracts, each reflecting the probability traders assign to specific temperature thresholds. Prices move based on order flow and new information, such as seasonal climate patterns, El Niño conditions, or updated long-range forecasts. Traders buy contracts at lower prices if they expect cooler outcomes or sell if they anticipate warmer conditions, with the contract price directly representing the implied probability of that temperature band occurring.

The market resolves on May 31, 2026, after May 30, 2026, concludes and the lowest temperature for that day is recorded. The outcome is determined by official temperature data from a designated weather station or source, ensuring an objective, verifiable settlement. Traders holding contracts aligned with the actual lowest temperature recorded will receive payouts, while misaligned positions expire worthless. The resolution process is final once the official temperature reading is confirmed and locked into the market system.

Several factors could shift odds for San Francisco's lowest temperature on May 30, 2026. Major climate patterns such as changes to the Pacific jet stream, development of El Niño or La Niña conditions, or unusual high-altitude pressure systems can alter seasonal temperature expectations. Updated long-range forecasts from meteorological agencies, anomalous spring weather patterns, or volcanic activity affecting atmospheric conditions may also influence trader positioning. As May approaches, near-term weather models become more reliable, potentially triggering sharp repricing as traders gain confidence in specific temperature ranges.