Machine learning & AI

AI weather forecasting for smart farms

Researchers working on smart irrigation systems have developed a way to choose the most accurate weather forecast out of those offered in the week leading up to a given day.

Computer Sciences

A neural network improves forecasts for severe storm hazards

The National Center for Atmospheric Research (NCAR) is using artificial intelligence to run experimental forecasts for hail, tornadoes, and intense winds—storm hazards that can cause serious damage but that are notoriously ...

Internet

Microsoft adds features to its Teams groupchat product

Microsoft Corp. has announced on its blog that it has added new features to Microsoft Teams, a group chat competitor to Zoom. In its announcement, Microsoft outlined the new features and included screen grabs to demonstrate ...

Consumer & Gadgets

Hey Google, are my housemates using my smart speaker?

Surveys show that consumers are worried that smart speakers are eavesdropping on their conversations and day-to-day lives. Now University of British Columbia researchers have found that people are also concerned about something ...

Telecom

Trump 5G push could hamper forecasting of deadly storms

As atmospheric rivers dumped record volumes of rain on California this spring, emergency responders used the federal government's satellites to warn people about where the storms were likely to hit hardest.

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Weather forecasting

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.

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 the wind chill, forecasts can be used to plan activities around these events, and to plan ahead and survive them.

This text uses material from Wikipedia, licensed under CC BY-SA