Wet Bias
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Wet Bias
Wet bias is the phenomenon whereby some weather forecasters report an overestimated and exaggerated probability of precipitation to increase the usefulness and actionability of their forecast. The Weather Channel has been empirically shown, and has also admitted, to having a wet bias in the case of low probability of precipitation (for instance, a 5% probability may be reported as a 20% probability) but not at high probabilities of precipitation (so a 60% probability will be reported as a 60% probability). Some local television stations have been shown as having significantly greater wet bias, often reporting a 100% probability of precipitation in cases where it rains only 70% of the time. Discovery In 2002, Eric Floehr, a computer science graduate of the Ohio State University, started collecting historical data of weather forecasts made by the National Weather Service (NWS), The Weather Channel (TWC), and AccuWeather for the United States, and collected the data on a website calle ...
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Weather Forecasting
Weather forecasting is the application of science and technology to predict the conditions of the atmosphere for a given location and time. People have attempted to predict the weather informally for millennia and formally since the 19th century. Weather forecasts are made by collecting quantitative data about the current state of the atmosphere, land, and ocean and using meteorology to project how the atmosphere will change at a given place. Once calculated manually based mainly upon changes in barometric pressure, current weather conditions, and sky condition or cloud cover, weather forecasting now relies on computer-based models that take many atmospheric factors into account. 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 inaccuracy of forecasting is due to the chaotic nature of the atmosphere, the ...
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