Weather models constantly churn out updates, each predicting the future at different lead times. Think of Day 0 as latest forecast close to measurements, Day 1 as a glimpse 24 hours back, and Day 2 as a 48-hour rewind. Each day further back forecasts longer into the future and, typically, increases volatility. Data jumps become wilder past Day 6 or 7, highlighting the inherent challenge of long-term forecasting.

This data serves multiple purposes, including answering questions such as "what did yesterday's forecast predict for today?" or by comparing past forecasts with real-time observations, we can assess a forecast's accuracy and volatility. When combined with machine learning techniques, models can be trained specifically to enhance forecasts for the next 2 or 3 days.

The frequency of model updates varies, ranging from hourly to every six hours. For local models with shorter prediction horizons (2-5 days), we naturally have access to a shorter "time machine" of past predictions (2-5 days).

Weather Models Sources: The Previous Runs API uses the same models as available in the general weather forecast API. Please refer to the Forecast API documentation for a list of all weather models and weather variables.

Data Availability: Data is generally available from January 2024 onwards. Exceptions are GFS temperature on 2 metre, which is available from March 2021 and JMA GSM + MSM models which are available from 2018. More data from previous runs can be reconstructed on request (depending on data availability from official sources).