IBM-нің "Deep Thunder" жобасы: ауа райын болжаудың жаңа технологиясы

Deep Thunder is a research project by IBM that aims to improve short term local weather forecasting through the use of high performance computing. It is part of IBM's Deep Computing initiative that also produced the Deep Blue chess computer. Deep Thunder is intended to provide local, high resolution weather predictions customized to weather sensitive specific business operations. For example, it could be used to predict the wind velocity at an Olympic diving platform, destructive thunderstorms, and combined with other physical models to predict where there will be flooding, damaged power lines and algal blooms. The project is now headquartered at IBM's Thomas J. Watson Research Center in Yorktown Heights, New York.

The Deep Thunder project is headed by Lloyd Treinish, who joined IBM in 1990, after working for 12 years at NASA's Goddard Space Flight Center. The project began in 1995 as an outgrowth of a project designed to help provide accurate weather forecasts for the 1996 Atlanta Olympic Games. In collaboration with the National Oceanic and Atmospheric Administration, IBM scientists built one of the first parallel processing supercomputers to be used for weather modeling, based on the IBM RS/6000 SP. It was installed at the National Weather Service office in Peachtree City, Georgia, in 1996, where it ran for several months and produced multiple forecasts daily. After a few years of development, the team set up an implementation in New York City in 2001 to test the project. The group is currently working on establishing the Rio de Janeiro operations center. The name Deep Thunder arose after the IBM Deep Blue system played and defeated the world chess champion Garry Kasparov in May, 1997. In the following November, a journalist used the name Deep Thunder in an article, which stuck with the developers. The Watson computer system will be used to generate the Deep Thunder weather forecasts. Input data will be collected from over 200,000 Weather Underground personal weather stations, weather satellite data, smartphone barometer and data from other sources.

IBM worked with a North American utility company that has over 90,000 poles, wires, and transformers to develop a prediction service that can pinpoint where incoming storms will bring down trees and power lines. The service can be used to call in the needed number of repair crews and station them near where the damage will occur, drastically decreasing downtime.

Deep Thunder could be used to determine optimal times to plant, irrigate, and harvest crops, based on the dynamic environmental conditions of individual farm locations. Precision agriculture using Deep Thunder could lead to better price points for crops by saving water, allocating labor more effectively, and improving supply chain efficiency. Using these methods of predictive weather farming, crop losses from the weather can be cut by over 25%. The island nation of Brunei is working with Deep Thunder to develop precision weather forecast models to increase rice production.

Deep Thunder was used during the 1996 Atlanta Olympic Games to accurately predict that there would be no rain during the closing ceremony.

New York City was the first city to test a full scale implementation of Deep Thunder. IBM is experimenting with using a mobile app to distribute location specific predictions and issue alerts. Data from the app can be used by maintenance crews to determine if wind levels are too high to work, or it could be used to get a weather forecast at a certain address.