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Over the past three decades ECMWF's wide-ranging programme of research has played a major role in developing such assimilation and modelling systems. This improves the accuracy and reliability of weather forecasting by about a day per decade, so that a seven-day forecast now (2015) is as accurate as a three-day forecast was four decades ago (1975).
It was proposed in 2005 by statistician Rob J. Hyndman and Professor of Decision Sciences Anne B. Koehler, who described it as a "generally applicable measurement of forecast accuracy without the problems seen in the other measurements."
HWRF 96-hour (4-day) forecast for Hurricane Katrina heading for New Orleans in 2005. The Hurricane Weather Research and Forecasting ( HWRF ) model is a specialized version of the weather research and forecasting model and is used to forecast the track and intensity of tropical cyclones .
Most scientific analyses of the accuracy of Farmers' Almanac forecasts have shown a 50% rate of accuracy, [7] [8] which is higher than that of groundhog prognostication, a folklore method of forecasting. [9] USA Today states that "according to numerous media analyses neither the Old Farmer's Almanac nor the Farmers' Almanac gets it right". [10]
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 ...
Microsoft's Aurora system offers global 10-day weather and 5-day air pollution (CO 2, NO, NO 2, SO 2, O 3, and particulates) forecasts with claimed accuracy similar to physics-based models, but at orders-of-magnitude lower cost. Aurora was trained on more than a million hours of data from six weather/climate models.
A "persistence" forecast can still rival even those of the most sophisticated models. An example is: "What is the weather going to be like today? Same as it was yesterday." This could be considered analogous to a "control" experiment. Another example would be a climatological forecast: "What is the weather going to be like today? The same as it ...
In this case, a perfect forecast results in a forecast skill metric of zero, and skill score value of 1.0. A forecast with equal skill to the reference forecast would have a skill score of 0.0, and a forecast which is less skillful than the reference forecast would have unbounded negative skill score values. [4] [5]