首页
登录
职称英语
"Weather and Chaotic Systems" Scientists today have a ve
"Weather and Chaotic Systems" Scientists today have a ve
游客
2024-01-04
70
管理
问题
"Weather and Chaotic Systems"
Scientists today have a very good understanding of the physical laws and mathematical equations that govern the behavior and motion of atoms in the air, oceans, and land. Why, then, do we have so much trouble predicting the weather? For a long time, most scientists
assumed
that the difficulty of weather prediction would go away once we had enough weather stations to collect data from around the world and sufficiently powerful computers to deal with all the data. However, we now know that weather is
fundamentally
unpredictable on time scales longer than a few weeks. To understand why, we must look at the nature of scientific prediction.
→ Suppose you want to predict the location of a car on a road 1 minute from now. You need two basic pieces of information: where the car is now, and how fast it is moving. If the car is now passing Smith Road and heading north at 1 mile per minute, it will be 1 mile north of Smith Road in 1 minute.
Now, suppose you want to predict the weather. Again, you need two basic types of information: (1) the current weather and (2) how weather changes from one moment to the next. You could attempt to predict the weather by creating a "model world." For example, you could overlay a globe of the Earth with graph paper and then specify the current temperature, pressure, cloud cover, and wind within each square. These are your starting points, or initial conditions. Next, you could input all the initial conditions into a computer, along with a set of equations (physical laws) that describe the processes that can change weather from one moment to the next.
→ Suppose the initial conditions represent the weather around the Earth at this very moment and you run your computer model to predict the weather for the next month in New York City. The model might tell you that tomorrow will be warm and sunny, with cooling during the next week and a major storm passing through a month from now. Now suppose you run the model again but make one minor change in the initial conditions—say, a small change in the wind speed somewhere over Brazil.A For tomorrow’s weather, this slightly different initial condition will not change the weather prediction for New York City.B But for next month’s weather, the two predictions may not agree at all! C
The disagreement between the two predictions arises because the laws governing weather can cause very tiny changes in initial conditions to be greatly magnified over time.D This extreme sensitivity to initial conditions is sometimes called the butterfly effect: If initial conditions change by as much as the flap of a butterfly’s wings, the resulting prediction may be very different.
→ The butterfly effect is a hallmark of chaotic systems. Simple systems are described by linear equations
in which
, for example, increasing a cause produces a proportional increase in an effect. In contrast, chaotic systems are described by nonlinear equations, which allow for subtler and more intricate interactions. For example, the economy is nonlinear because a rise in interest rates does not automatically produce a corresponding change in consumer spending. Weather is nonlinear because a change in the wind speed in one location does not automatically produce a corresponding change in another location. Many (but not all) nonlinear systems exhibit chaotic behavior.
→ Despite their name, chaotic systems are not completely random. In fact, many chaotic systems have a kind of underlying order that explains the general
features
of their behavior even while details at any particular moment remain unpredictable. In a sense, many chaotic systems are "predictably unpredictable." Our understanding of chaotic systems is increasing at a tremendous rate, but much remains to be learned about them. [br] According to the passage, it will be difficult to predict weather
选项
A、unless we learn more about chaotic systems
B、because we don’t have enough weather stations
C、without more powerful computers
D、until we understand the physical laws of atoms
答案
A
解析
"Our understanding of chaotic systems is increasing at a tremendous rate, but much remains to be learned about them." Choice B is not correct because it was an incorrect assumption. Choice C is not correct because it was also an incorrect assumption. Choice D is not correct because today we have a very good understanding of the physical laws of atoms.
转载请注明原文地址:https://tihaiku.com/zcyy/3333620.html
相关试题推荐
Lookatthefollowingstatements(Questions19-23)andthelistofscientistsbe
Lookatthefollowingstatements(Questions19-23)andthelistofscientistsbe
Lookatthefollowingstatements(Questions19-23)andthelistofscientistsbe
AccidentalScientistsAAparadoxliesclosetotheheartofscientificdiscover
AccidentalScientistsAAparadoxliesclosetotheheartofscientificdiscover
Usingdataisacomplexbusiness.Wellbeforeachampionship,sportsscientists
Usingdataisacomplexbusiness.Wellbeforeachampionship,sportsscientists
Inthelastdecadearevolutionhasoccurredinthewaythatscientiststhinkab
FIELDTRIPPLAN;WEATHER:everyoneneedswarmclothinganda【L6】________ACTIVI
FIELDTRIPPLAN;WEATHER:everyoneneedswarmclothinganda【L6】________ACTIVI
随机试题
【B1】[br]【B2】A、wereB、couldC、wouldB后面fly用的是原形,再从行文的时态一致性考虑,选B最佳。
A------trackandfieldJ------roadraceB------cheerleaderK------platformdiv
PreparingforTestsI.Preparingfortests—Tounder
十九届三中全会强调,面对新时代新任务,党和国家机构设置和职能配置有两个“还不完全
李某有一处住过两年的房屋要转让,委托A房地产经纪公司的小张办理房屋的买卖事宜
A.[P]=38.2kN B.[P]=10Kn C.[P]=3.75kN
葡萄糖或氨基酸逆浓度梯度跨细胞膜转运的方式是A.原发性主动转运 B.继发性主动
某企业经营第一年亏损10万元,第二年实现税前利润30万元(弥补期限超过5年),所
(2021年真题)下列选项中,不会影响回函的可靠性的是()A.回函的及时性
将工程项目总费用根据工程分解结构分配到各工作单元上去的工作是指编制项目的 ()
最新回复
(
0
)