Temperature prediction markets allow traders to assess and forecast the likelihood of specific weather conditions across different locations. Lowest temperature markets focus on predicting daily minimum temperatures in cities worldwide, creating transparent odds that reflect real-time expectations about meteorological conditions. These markets feature specific questions about daily low temperatures. Common predictions include whether Tokyo's lowest temperature will exceed 19°C or reach 18°C, and similar forecasts for Seoul at 18°C or 16°C on specific dates. Each market aggregates trader forecasts into a live probability that updates continuously as new information arrives. Several factors influence market prices. Seasonal weather patterns and geographic location set baseline expectations—winter months feature lower baseline temperatures, while spring and summer produce warmer forecasts. Historical climate data and local geography inform initial probabilities, while urban characteristics create location-specific variations. Short-term factors drive price movements. Weather forecasts from meteorological agencies, satellite imagery, atmospheric pressure systems, and approaching cold fronts can shift market sentiment quickly. Late-breaking weather alerts may trigger rapid repricing as participants update positions based on new conditions. Real-time trading activity itself provides valuable signal. As participants buy and sell positions, they collectively reveal expectations about temperature outcomes. This decentralized aggregation creates a transparent market that evolves continuously with incoming data and changing conditions, offering insights into how communities forecast weather.