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Hurricane Forecasting Technology And Dvorak Technique

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If we use hurricane forecasting technology in the world, we can avoid a lot of damage. How is Dvorak Technique? Read this article.

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How hurricane makes position in sea?

Hurricane risk due to new technology:

In India, the damage caused by cyclones was relatively small. So full credit should go to planning and innovation. A combination of computer systems can provide hurricane forecasting with the help of satellite technology, various photographs, studies and the internet and smartphones.


In India, too, it hit the east and west coasts a few days apart in two weeks and was hit by these two cyclones. A hurricane is a cyclone that moves through the atmosphere; there is also a moving column. When a hurricane is very strong, it has an eye in the middle. The air pressure is very low here. In this area the sea level is raised. Therefore, when a severe cyclone hits the coast, a large body of water spreads over the coast and inland. As the wind speed increases during that short period of the storm, it can cause landslides, uproot trees, and destroy the surrounding landscape.


There is no alternative but to stare helplessly at this kind of natural calamity. The damage from these two hurricanes is comparatively small. Full credit should go to planning and innovation. Hurricane Nargis hit in 2008, killing more than 100,000 people. The combination of computer systems with satellite technology, a wide variety of photographs, makes it easy to study various aspects of information, and with the help of the Internet and smartphones, these predictions can be made everywhere.

hurricane-forecasting-technology-and-dorak-technique

About Dvorak Technique

What is Dvorak Technique?

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"The Dvorak technique is a method using enhanced Infrared and/or visible satellite imagery to quantitatively estimate the intensity of a tropical system. Cloud patterns in satellite imagery normally show an indication of cyclogenesis before the storm reaches tropical storm intensity."

Now a question naturally comes to the mind of some, that satellite images have been used before, so what is the difference between the new technology and how it becomes more reliable? The 'Dvorak Technique', invented by Dvorak and brought to near perfection, is used all over the world. Like an earthquake, the damage caused by a cyclone depends on its intensity, ie the speed of the wind and the amount of rain that falls. Much of the effect also depends on the height, pressure and temperature of the clouds accumulating in the low pressure belt. (These storms themselves have different types like cyclones, hurricanes, typhoons).


By studying satellite images and photographs, Dvorak categorized storms according to their visual appearance. For this, infrared rays were used. From the 'face' of each storm, its intensity can be accurately described. Even so, it is still beyond the reach of the average person. That is, the intensity of the storm is not understood with the expected accuracy. After this, of course, efforts continued to make these predictions accurate. This is where technology came into existence.


Adding to the extraordinary processing capabilities of cloud computing to Artificial Intelligence, more than two million photographs in the archive can be studied in a matter of moments to get the right results. For this, convoluted neural network technology is used. There are large layers of clouds accumulate in the area before the storm. The amount of rainfall that can fall is determined by computer by studying the pattern of clouds in each layer. It uses image retrieval techniques. The technology used for this is deliberately kept open source.


The intensity of tropical storms depends on one more factor. The latent heat released into the atmosphere from the surface of the ocean. This is called Tropical Cyclone Heat Potential. This thermal power is important for storms in the Indian Ocean and the Bay of Bengal. More than 25,000 temperature records taken between 1997 and 2007 were supplied to artificial neural network type computer systems. It also studied the isotherm by drawing lines connecting points with a uniform temperature of 26 degrees Celsius on the surface of the sea.


After analyzing various methods and comparing the accuracy of the predictions made from them, ANN proved beyond any doubt that ANN is superior and reliable. Accurate weather forecasting is beneficial to farmers: in addition, early warning of heavy rains, incessant rains, storms, such as early diagnosis, can prevent property damage and move people from disaster affected areas to safer places.

© 2021 Jaya

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