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The ENIAC main control panel at the Moore School of Electrical Engineering operated by Betty Jennings and Frances Bilas. The history of numerical weather prediction began in the 1920s through the efforts of Lewis Fry Richardson, who used procedures originally developed by Vilhelm Bjerknes [1] to produce by hand a six-hour forecast for the state of the atmosphere over two points in central ...
The Weather Research and Forecasting (WRF) Model [1] (/ ˈ w ɔːr f /) is a numerical weather prediction (NWP) system designed to serve both atmospheric research and operational forecasting needs, developed in the United States. NWP refers to the simulation and prediction of the atmosphere with a computer model, and WRF is a set of software ...
The Weather Machine: A Journey Inside the Forecast. New York: HarperCollins. ISBN 978-0-062-36861-4. Ian Roulstone & John Norbury (2013). Invisible in the Storm: the role of mathematics in understanding weather. Princeton University Press. ISBN 978-0691152721.
It was based on a simplified set of atmospheric dynamical equations (the equivalent barotropic formulation) using a deep layer-mean wind. During 1972, the first model to forecast storm surge along the continental shelf of the United States was developed, known as the Special Program to List the Amplitude of Surges from Hurricanes (SPLASH). [10]
Because the output of forecast models based on atmospheric dynamics requires corrections near ground level, model output statistics (MOS) were developed in the 1970s and 1980s for individual forecast points (locations). The MOS apply statistical techniques to post-process the output of dynamical models with the most recent surface observations ...
An example meteogram showing plots of temperature, pressure, precipitation, cloud cover, wind speed and wind direction. A meteogram, also known as a meteorogram, [1] is a graphical presentation of one or more meteorological variables with respect to time, whether observed or forecast, for a particular location. [2]
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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.