A weather model is a sophisticated computer program that uses mathematical equations to simulate the physics of the atmosphere and predict its future state. These algorithms analyze current atmospheric conditions, such as temperature, pressure, and wind speed, to project how the weather will change over time. Because the atmosphere is constantly evolving, models require periodic updates, known as “runs,” to remain accurate for forecasting. The timing and frequency of these updates are determined by the model’s purpose, geographical scope, and computational demands.
The Six-Hourly Cycle of Global Models
The largest and most comprehensive weather models cover the entire globe and provide the foundation for long-range forecasts. These models adhere to a standardized four-times-a-day update schedule, known internationally as 00Z, 06Z, 12Z, and 18Z. The “Z” refers to Zulu time, which is the same as Coordinated Universal Time (UTC).
This synchronized schedule ensures that all major global forecasting centers initialize their models with a consistent starting point. The 12Z run is typically the primary morning initialization, while the 00Z run is the main evening initialization in North America. These four updates per day provide continuous oversight of atmospheric developments, extending forecasts out to 16 days or more.
The Role of New Data Assimilation in Updates
Scheduled model updates rely on data assimilation, a complex process that integrates real-world observations into the forecast. Every model run must begin with the most accurate representation of the current atmospheric state, known as the initialization. Without this accurate starting point, small errors quickly magnify in the chaotic atmospheric system, rendering the forecast useless.
Between each six-hourly run, a massive volume of new data is collected from a variety of sources to feed into the assimilation process. This includes measurements from orbiting satellites, ground-based weather stations, radar systems, and weather balloons. The assimilation system takes these new, real-time observations and mathematically blends them with the previous model’s short-range forecast. This continuous cycle acts as a course correction, ensuring the model remains closely aligned with reality.
High-Resolution Models and More Frequent Updates
While global models provide the broad picture, specialized high-resolution models are designed to update much more frequently to capture localized, short-term weather details. These models focus on smaller geographical regions, meaning they require significantly less computational power to complete a full run. This reduced domain allows them to produce new forecasts every hour or every three hours, rather than every six.
This rapid update cycle is particularly valuable for forecasting rapidly evolving weather events, such as severe thunderstorms, flash floods, or localized snow bands. Some models update hourly, incorporating the latest radar and satellite data into the new forecast. These short-range models typically project weather conditions only 12 to 18 hours into the future. Their high frequency and fine detail make them indispensable for short-notice preparedness.