Weather forecasting | Wikipedia audio article
Channel: wikipedia tts
Date: 2019-06-23

This is an audio version of the Wikipedia Article:
https://en.wikipedia.org/wiki/Weather_forecasting


00:02:53 1 History
00:03:02 1.1 Ancient forecasting
00:05:24 1.2 Modern methods
00:09:51 1.3 Numerical prediction
00:11:58 1.4 Broadcasts
00:14:25 2 How models create forecasts
00:21:47 3 Techniques
00:21:56 3.1 Persistence
00:22:47 3.2 Use of a barometer
00:23:40 3.3 Looking at the sky
00:24:56 3.4 Nowcasting
00:25:59 3.5 Use of forecast models
00:27:31 3.6 Analog technique
00:28:45 4 Communicating forecasts to the public
00:30:45 4.1 Severe weather alerts and advisories
00:31:50 4.2 Low temperature forecast
00:32:21 5 Specialist forecasting
00:32:42 5.1 Air traffic
00:34:16 5.2 Marine
00:35:08 5.3 Agriculture
00:36:09 5.4 Forestry
00:36:51 5.5 Utility companies
00:38:19 5.6 Other commercial companies
00:39:03 5.7 Military applications
00:39:13 5.7.1 United Kingdom Armed Forces
00:39:55 5.7.2 Royal Air Force
00:40:25 5.7.3 United States Armed Forces
00:40:35 5.7.4 US Navy
00:41:30 5.7.5 US Air Force
00:42:36 6 See also



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SUMMARY
=======
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 at a given place and using meteorology to project how the atmosphere will change.
Once calculated by hand 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 massive computational power required to solve the equations that describe the atmosphere, the error involved in measuring the initial conditions, and an incomplete understanding of atmospheric processes. Hence, forecasts become less accurate as the difference between 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.
There are a variety of end uses to weather forecasts. Weather warnings are important forecasts because they are used to protect life and property. Forecasts based on temperature and precipitation are important to agriculture, and therefore to traders within commodity markets. Temperature forecasts are used by utility companies to estimate demand over coming days. On an everyday basis, people use weather forecasts to determine what to wear on a given day. Since outdoor activities are severely curtailed by heavy rain, snow and wind chill, forecasts can be used to plan activities around these events, and to plan ahead and survive them. In 2009, the US spent $5.1 billion on weather forecasting.