WeatherForecastModels

WeatherForecastModels are computer simulations used to predict atmospheric conditions. They solve a set of equations that describe fluid motion, thermodynamics, and moisture on a discretized grid of the atmosphere. Forecasts typically include temperature, wind, precipitation, and pressure for hours to days ahead.

Modern weather forecast models are numerical weather prediction (NWP) models comprising a dynamical core that advances the atmosphere in time, physical parameterizations for subgrid processes (radiation, convection, clouds, surface interactions), and data assimilation systems that ingest observations to update the initial state. Forecasts start from a best estimate of current weather and are produced on regular cycles.

Forecasts can be deterministic or probabilistic. Deterministic models produce one forecast; ensemble forecasting runs multiple members with perturbed initial conditions and/or physics to quantify uncertainty. Models vary by resolution and domain, from global to regional. Resolution affects detail in features like storms.

Examples of widely used models include global systems such as the ECMWF Integrated Forecast System and the US Global Forecast System (GFS); regional models include the UK Met Office Unified Model, Germany’s ICON, and the WRF. These models are run at many centers worldwide and are often used in combination through ensemble systems and post-processing to produce products for users.

Applications and limitations: They support weather forecasting, aviation, agriculture, disaster preparedness, and climate research. Limitations include imperfect physics, model biases, data gaps, parameterizations for clouds and precipitation, and high computational costs.

History: The concept emerged in the mid-20th century with early computer-based NWP efforts, reaching operational maturity in the 1960s and 1970s and continuing to advance with higher resolution and better data assimilation.