Daily Dew Point is a free forecast tracking and prediction tool for daily high temperature markets. We aggregate multiple weather forecast sources, track how they change throughout the day, and use a proprietary machine learning model to predict which temperature bucket is most likely to win on Kalshi.
Our model is trained on hundreds of days of historical forecast data and years of atmospheric observations. It learns patterns in how forecasts miss — for example, certain atmospheric conditions that cause forecasts to consistently overshoot or undershoot. The model retrains daily to incorporate the latest data.
The model outputs a probability distribution across temperature buckets, not just a single number. This lets us show confidence levels and identify when the model is uncertain.
Currently available for New York City (Central Park) and Los Angeles (LAX). More cities may be added in the future.
Weather prediction is inherently uncertain. Our model improves over time as it trains on more data, but it will not be right every day. The bucket picks should be one input in your decision-making, not the only one. Always do your own research.
Questions or feedback? Email support@dewdropventures.com.