Will global temperature increase by between 1.15ºC and 1.19ºC in May 2026?

Polymarket traders currently assign a 31.0% probability to "Will global temperature increase by between 1.15ºC and 1.19ºC in May 2026?".

The market is pricing YES at 31.0¢ and NO at 66.0¢, reflecting current trader consensus.

Liquidity conditions are low, with approximately $2,309 in 24-hour trading activity.

Resolution Criteria

This market will resolve according to the value reported by the Global Land-Ocean Temperature Index for May 2026 when it is released.

An anomaly within a named bracket for May 2026 is necessary and sufficient to resolve this market immediately once the data becomes available, regardless of whether the figure for May 2026 is later revised.

The primary resolution source for this market will be the figure found in the table titled "GLOBAL Land-Ocean Temperature Index in 0.01 degrees Celsius" under the column "May" in the row "2026" (https://data.giss.nasa.gov/gistemp/tabledata_v4/GLB.Ts+dSST.txt).

If NASA’s “Global Temperature Index” is rendered permanently unavailable, other information from NASA may be used.
If no information for May 2026 is provided by NASA by July 1, 2026, 11:59 PM ET, this market will resolve to the lowest range bracket.

Market Interpretation

Prediction markets function as real-time consensus engines.

Traders continuously buy and sell outcome shares based on:

• breaking news
• macro developments
• public narratives
• institutional positioning
• probability reassessments

As a result, market pricing reflects aggregate trader expectations rather than static forecasts or polling systems.

At the current pricing structure:

• YES trades near 31.0¢
• NO trades near 66.0¢
• Implied probability sits near 31.0%

These probabilities may shift rapidly as new information enters the market.

Liquidity & Conviction Analysis

As of May 14, 2026 at 06:41 AM, liquidity conditions act as a primary structural filter on prediction market signal quality.

Medium liquidity conviction suggests moderate participation depth, where price discovery is active but not fully saturated by institutional or high-frequency flow.

Higher liquidity environments typically produce:

• tighter spreads
• faster price discovery
• stronger informational efficiency
• lower pricing instability

Lower liquidity environments tend to exhibit:

• wider spreads
• delayed consensus formation
• increased volatility from isolated trades
• weaker signal reliability in short time windows

Overall, liquidity acts as a direct proxy for how “stable” the implied probability surface is at any given moment.

Why This Signal Exists in Prediction Markets

Prediction markets function as continuous consensus engines where probability is not stated — it is priced.

Each trade updates a live belief distribution, turning scattered human judgment into a single evolving likelihood curve.

Compared to static polling or narrative reporting, this structure adapts instantly to:

• regime shifts in geopolitics
• macroeconomic shocks and policy changes
• institutional order flow and positioning
• narrative acceleration or decay
• liquidity-driven sentiment swings
• information asymmetry correction

In practice, these markets behave less like betting tools and more like real-time probabilistic sensors for world events.

They compress collective intelligence into a dynamic signal that updates with every transaction.

Market Structure Transition

As of May 14, 2026 at 06:41 AM, prediction markets have evolved into persistent global probability infrastructure.

Polymarket and Kalshi now operate as high-throughput probability engines, with cumulative volumes exceeding $150B+ and sustained monthly flow above $7B.

Market activity has shifted from episodic speculation toward continuous liquidity formation, where geopolitical events, macroeconomic narratives, elections, AI milestones, and financial expectations are constantly repriced in real time.

This transformation has turned prediction markets into always-on consensus surfaces capable of reflecting crowd intelligence faster than traditional media, polling systems, or institutional forecasting pipelines.