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Weather reconnaissance aircraft, such as this WP-3D Orion, provide data that is then used in numerical weather forecasts.. The atmosphere is a fluid.As such, the idea of numerical weather prediction is to sample the state of the fluid at a given time and use the equations of fluid dynamics and thermodynamics to estimate the state of the fluid at some time in the future.
The Weather Research and Forecasting (WRF) Model[1] (/ ˈwɔːrf /) is a numerical weather prediction (NWP) system designed to serve both atmospheric research and operational forecasting needs. NWP refers to the simulation and prediction of the atmosphere with a computer model, and WRF is a set of software for this.
The Global Environmental Multiscale Model (GEM), often known as the CMC model in North America, is an integrated forecasting and data assimilation system developed in the Recherche en Prévision Numérique (RPN), Meteorological Research Branch (MRB), and the Canadian Meteorological Centre (CMC). Along with the NWS 's Global Forecast System (GFS ...
It comprises a spectral atmospheric model with a terrain-following vertical coordinate system coupled to a 4D-Var data assimilation system.In 1997 the IFS became the first operational forecasting system to use 4D-Var. [2] Both ECMWF and Météo-France use the IFS to make operational weather forecasts, but using a different configuration and resolution (the Météo-France configuration is ...
Climate Forecast System (NCEP) The Climate Forecast System or coupled forecast system (CFS) is a medium to long range numerical weather prediction and a climate model run by the National Centers for Environmental Prediction (NCEP) to bridge weather and climate timescales. [1] Version 2 became operational as CFSv2 in 2011.
An example of 500 mbar geopotential height prediction from a numerical weather prediction model. It also shows an Omega block. In the United Kingdom the Meteorological Office first numerical weather prediction was completed by F. H. Bushby and Mavis Hinds in 1952 under the guidance of John Sawyer.
Model output statistics. In weather forecasting, model output statistics (MOS) is a multiple linear regression technique in which predictands, often near-surface quantities (such as two-meter-above-ground-level air temperature, horizontal visibility, and wind direction, speed and gusts), are related statistically to one or more predictors.
CF is intended for use with state estimation and forecasting data, in the atmosphere, ocean, and other physical domains. It was designed primarily to address gridded data types such as numerical weather prediction model outputs and climatology data in which data binning is used to impose a regular structure.