Nt1310 Week 1 Case Study Of Tornados

Like Achilles, everything has a major weakness. In this case we are talking about an quasi linear convective system. Everything has a weakness, you see. An quasi linear convective system is an system thunderstorm lines. Within the quasi linear convective system, there is an supercell hidden. An supercell is an thunderstorm with an large, rotating mesocyclone. This could cause tornadoes to form, but it is not the only way a tornado could form. An mesocyclone is an large rotating updraft, detected by doppler radars. Because there is an supercell, there is a 30% chance a tornado could be formed. You may be thinking, so what? Well, actually, here's the twist: some tornados inside cannot be tracked. This is even more dangerous, because people cannot be warned. Also,

You can predict quasi linear convective systems, but you can’t track them. Another way a tornado could form that could be useful for tracking tornados are when they are formed by an Cumulonimbus Cloud. A Cumulonimbus Cloud is an dence, vertical cloud with thunderstorms in/surrounding it. A Cumulonimbus Cloud also has an powerful mesocyclone carrying it. This could form tornados in it, like an supercell. Knowing how tornadoes can form is an powerful skill when tracking tornados. It shows what type of tornado you're dealing with. It could also give hints of what rank the tornado could be based on the fujita scale. Other things that make tornados hard to track, predict, and warn is that tornado warnings are short-term. They are, because tornados in satellites prediction are beforehand. Tornados happen quickly, and that’s Why they are really hard to track. Because of this, tornado watches are a few hours ahead of time. Tornado’s path are short, so predicting any particular tornado requires a fine-grain understanding that's more difficult for scientists. Knowing this, you should have lots of knowledge about tracking tornadoes now. As said, let's move on predictions, so we can see