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Parametrization (climate modeling) Parameterization in a weather or climate model is a method of replacing processes that are too small-scale or complex to be physically represented in the model by a simplified process. This can be contrasted with other processes—e.g., large-scale flow of the atmosphere—that are explicitly resolved within ...
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.
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.
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 process of entering observation data into the model to generate initial conditions is called initialization.
Atmospheric reanalysis. An atmospheric reanalysis (also: meteorological reanalysis and climate reanalysis) is a meteorological and climate data assimilation project which aims to assimilate historical atmospheric observational data spanning an extended period, using a single consistent assimilation (or "analysis") scheme throughout.
Atmospheric model. A 96-hour forecast of 850 mbar geopotential height and temperature from the Global Forecast System. In atmospheric science, an atmospheric model is a mathematical model constructed around the full set of primitive, dynamical equations which govern atmospheric motions. It can supplement these equations with parameterizations ...
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.
The history of numerical weather prediction considers how current weather conditions as input into mathematical models of the atmosphere and oceans to predict the weather and future sea state (the process of numerical weather prediction) has changed over the years. Though first attempted manually in the 1920s, it was not until the advent of the ...