Weather forecasting is the application of science and technology to predict
the state of the atmosphere for a future time and a given location.
Human beings have attempted to predict the weather informally for millennia,
and formally since at least the nineteenth century. Weather forecasts are
made by collecting quantitative data about the current state of the
atmosphere and using scientific understanding of atmospheric processes to
project how the atmosphere will evolve.
Once an all human endeavor based mainly upon changes in barometric
pressure, current weather conditions, and sky condition, forecast models
are now used to determine future conditions. Human input is still required to
pick the best possible forecast model to base the forecast upon, which
involves pattern recognition skills, teleconnections, knowledge of model
performance, and knowledge of model biases.
The chaotic nature of the atmosphere, the massive computational power
required to solve the equations that describe the atmosphere, error involved
in measuring the initial conditions, and an incomplete understanding of
atmospheric processes mean that forecasts become less accurate as the
difference in current time and the time for which the forecast is being made
the range of the forecast increases.
The use of ensembles and model consensus help narrow the error and pick
the most likely outcome, thus in the future we can create better models to
determine the accuracy is 99.9%.
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