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用英语介绍蝴蝶用英语介绍它的大小、颜色、种类、故事、生长地.
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用英语介绍蝴蝶
用英语介绍它的大小、颜色、种类、故事、生长地.优质解答
One of the great modern science stories is the so-called "Butterfly Effect".It suggests that the weather is so sensitive to tiny changes,that something as microscopic as a butterfly flapping its wings in Brazil could set off a tornado in Texas.It's a great bit of Pop Science that has entered the common consciousness - but it's probably wrong.
Weather is that stuff that happens in the 5 million billion tonnes of air and water vapour that wraps around our planet in a thin layer.
Weather is big business on our planet.According to the World Meteorological Organisation,accurate weather forecasts improve the global economy by about $80 billion each year.Every time an aeroplane flight cancellation is avoided,that saves around $80,000 - and every time a flight is not diverted,that saves $300,000.
The modern science of weather predictions probably began in 1913,with the pacifist,physicist and mathematician,Lewis Fry Richardson.World War I broke out the next year,and he found a way to help without violating his personal beliefs - he enlisted as an ambulance driver with the French Army.In his spare time,he would sit down and work out tens of thousands of laborious pencil-and-paper weather calculations.A Norwegian meteorologist had already published very detailed weather data for an area in and around central Germany on May 20,1910 - some four years earlier.Richardson knew what the weather turned out to be,and he was trying to develop a mathematical model that could successfully use this data to "predict" what actually turned out.But he never could get his model to work.
Richardson thought it was because he didn't have enough data.He proposed to divide the surface of the Earth into tens of thousands of little cells,and gather all possible weather data from each cell.He wrote about this in 1922 in his book called Weather Prediction By Numerical Process.Unfortunately,it was impossible to do the calculations fast enough by pencil and paper.
But then came the Second World War and "unbustable" German war codes and the Atom Bomb - and computers were invented to solve both those problems.In 1950,John von Neumann,one of the fathers of modern computing,realised that his computers were fast enough to solve Richardson's weather problem.By 1953,the ENIAC computer at Princeton University had run Richardson's equations to make moderately successful predictions of the weather.And so the modern age of weather prediction was born.
Today we have a massive network of weather stations on land and buoys at sea,planes and balloons in the air,and satellites looking down from space.They all gather data to feed into these increasingly sophisticated mathematical models of the weather.
But in 1972,Ed Lorenz,a meteorologist at the Massachusetts Institute of Technology said it might be impossible to be truly accurate.He was the first to point out the role of Chaos in weather forecasting,and he came up with that imaginative example of the butterfly wing in Brazil.In fact,he invented the term,"butterfly effect".
Now here's a very important point.
With Chaos Theory,the error starts small and then gets bigger with time and then gets huge.But this is not,repeat NOT,what happens with the weather.
In weather forecasts,the error becomes very large very rapidly,and then begins to tail off - so most of the error in the weather forecasts is not related to Chaos Theory.
This really bothered David Orrell,a mathematician at the University College in London.He and his fellow mathematicians started thinking about what would happen if the actual mathematical models that the meteorologists use to predict the weather were wrong.They proved a mathematical theorem that predicted exactly how,if a model really was wrong,its errors would grow as time progressed.In fact,these errors should follow a "Square Root Law" - growing very rapidly at first,and then slowing down after a few days.And believe it or not,this is how the errors in the weather forecasts behave.
In other words,according to David Orrell,the main thing stopping us from getting accurate weather forecasts three days down the line is not the Butterfly Effect (which is real),but the errors in the models.
His theory can't say where the errors are,only that there are errors.And once the mathematicians and the meteorologists get together and come up with better models of the weather,they should be able to make dead accurate forecasts up to three days down the line.The Chaos effects will then begin to kick in after about a week or so.
Now David Orrell might be wrong,or he might be right.But if he is right,the meteorologists shouldn't feel too worried.After all,trying to mathematically model the 5 million billion tonnes of turbulent atmosphere and water vapour is probably one of the most difficult computing problems ever attempted in the history of the human race.
The only thing that we can be sure of is that the weather will always give us something to talk about...
用英语介绍它的大小、颜色、种类、故事、生长地.
优质解答
Weather is that stuff that happens in the 5 million billion tonnes of air and water vapour that wraps around our planet in a thin layer.
Weather is big business on our planet.According to the World Meteorological Organisation,accurate weather forecasts improve the global economy by about $80 billion each year.Every time an aeroplane flight cancellation is avoided,that saves around $80,000 - and every time a flight is not diverted,that saves $300,000.
The modern science of weather predictions probably began in 1913,with the pacifist,physicist and mathematician,Lewis Fry Richardson.World War I broke out the next year,and he found a way to help without violating his personal beliefs - he enlisted as an ambulance driver with the French Army.In his spare time,he would sit down and work out tens of thousands of laborious pencil-and-paper weather calculations.A Norwegian meteorologist had already published very detailed weather data for an area in and around central Germany on May 20,1910 - some four years earlier.Richardson knew what the weather turned out to be,and he was trying to develop a mathematical model that could successfully use this data to "predict" what actually turned out.But he never could get his model to work.
Richardson thought it was because he didn't have enough data.He proposed to divide the surface of the Earth into tens of thousands of little cells,and gather all possible weather data from each cell.He wrote about this in 1922 in his book called Weather Prediction By Numerical Process.Unfortunately,it was impossible to do the calculations fast enough by pencil and paper.
But then came the Second World War and "unbustable" German war codes and the Atom Bomb - and computers were invented to solve both those problems.In 1950,John von Neumann,one of the fathers of modern computing,realised that his computers were fast enough to solve Richardson's weather problem.By 1953,the ENIAC computer at Princeton University had run Richardson's equations to make moderately successful predictions of the weather.And so the modern age of weather prediction was born.
Today we have a massive network of weather stations on land and buoys at sea,planes and balloons in the air,and satellites looking down from space.They all gather data to feed into these increasingly sophisticated mathematical models of the weather.
But in 1972,Ed Lorenz,a meteorologist at the Massachusetts Institute of Technology said it might be impossible to be truly accurate.He was the first to point out the role of Chaos in weather forecasting,and he came up with that imaginative example of the butterfly wing in Brazil.In fact,he invented the term,"butterfly effect".
Now here's a very important point.
With Chaos Theory,the error starts small and then gets bigger with time and then gets huge.But this is not,repeat NOT,what happens with the weather.
In weather forecasts,the error becomes very large very rapidly,and then begins to tail off - so most of the error in the weather forecasts is not related to Chaos Theory.
This really bothered David Orrell,a mathematician at the University College in London.He and his fellow mathematicians started thinking about what would happen if the actual mathematical models that the meteorologists use to predict the weather were wrong.They proved a mathematical theorem that predicted exactly how,if a model really was wrong,its errors would grow as time progressed.In fact,these errors should follow a "Square Root Law" - growing very rapidly at first,and then slowing down after a few days.And believe it or not,this is how the errors in the weather forecasts behave.
In other words,according to David Orrell,the main thing stopping us from getting accurate weather forecasts three days down the line is not the Butterfly Effect (which is real),but the errors in the models.
His theory can't say where the errors are,only that there are errors.And once the mathematicians and the meteorologists get together and come up with better models of the weather,they should be able to make dead accurate forecasts up to three days down the line.The Chaos effects will then begin to kick in after about a week or so.
Now David Orrell might be wrong,or he might be right.But if he is right,the meteorologists shouldn't feel too worried.After all,trying to mathematically model the 5 million billion tonnes of turbulent atmosphere and water vapour is probably one of the most difficult computing problems ever attempted in the history of the human race.
The only thing that we can be sure of is that the weather will always give us something to talk about...
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