Introduction: (Initial Observation)
Wind and tornadoes are movements of the air caused by changes in the air temperature between two areas. Most winds start in sea shores where the temperature difference between the dry land and the water cause convection currents.
Hurricanes are very high speed destructive winds that destroy buildings, trees, farms and many other structures in their path.
Why some wind currents get such a destructive force? Does a larger temperature difference between two areas cause more powerful winds?
Project Plan:
In this project you will construct a model to create convection currents caused by the differences in the air temperature. You will experiment to see if a larger variation of temperature cause a higher wind speed.
Information Gathering:
Find out about wind, tornado, hurricane and their causes and effects. Read books, magazines or ask professionals who might know in order to learn about the effect of temperature difference on wind speed between two areas. Keep track of where you got your information from.
Following are samples of information you may find:
Hurricane is one of the term used to describe tropical cyclones with maximum sustained winds exceeding 33 meters per second (63 knots, 73 mph, or 117 km/h). This weather phenomena is known with different names in different regions of the world:
- hurricane in the North Atlantic Ocean, North Pacific Ocean east of the dateline, and unofficially in the South Atlantic Ocean
- typhoon in the Northwest Pacific Ocean west of the dateline
- severe tropical cyclone in the Southwest Pacific Ocean west of 160°E or Southeast Indian Ocean east of 90°E
- severe cyclonic storm in the North Indian Ocean
- tropical cyclone in the Southwest Indian Ocean and South Pacific Ocean east of 160°E.
Whilst these terms all refer to the same phenomenon, the term cyclone indicates the storm occurs in the southern hemisphere whereas hurricane refers to the northern hemisphere. This derives from the fact that in the southern hemisphere, these depressions rotate in a clockwise direction (“cyclonic”) and in the northern hemisphere rotate in an anti-clockwise direction (“anti-cyclonic”).
Identify Variables:
When you think you know what variables may be involved, think about ways to change one at a time. If you change more than one at a time, you will not know what variable is causing your observation. Sometimes variables are linked and work together to cause something. At first, try to choose variables that you think act independently of each other.
Hypothesis:
Based on your gathered information, make an educated guess about what types of things affect the system you are working with. Identifying variables is necessary before you can make a hypothesis.
Experiment Design:
Design an experiment to test each hypothesis. Make a step-by-step list of what you will do to answer each question. This list is called an experimental procedure. For an experiment to give answers you can trust, it must have a “control.” A control is an additional experimental trial or run. It is a separate experiment, done exactly like the others. The only difference is that no experimental variables are changed. A control is a neutral “reference point” for comparison that allows you to see what changing a variable does by comparing it to not changing anything. Dependable controls are sometimes very hard to develop. They can be the hardest part of a project. Without a control you cannot be sure that changing the variable causes your observations. A series of experiments that includes a control is called a “controlled experiment.”
In this project you will construct a model to create convection currents caused by the differences in the air temperature. You will experiment to see if a larger variation of temperature cause a higher wind speed.
Experiment:
Materials and Equipment:
Description
Results of Experiment (Observation):
Experiments are often done in series. A series of experiments can be done by changing one variable a different amount each time. A series of experiments is made up of separate experimental “runs.” During each run you make a measurement of how much the variable affected the system under study. For each run, a different amount of change in the variable is used. This produces a different amount of response in the system. You measure this response, or record data, in a table for this purpose. This is considered “raw data” since it has not been processed or interpreted yet. When raw data gets processed mathematically, for example, it becomes results.
Calculations:
Description
Summery of Results:
Summarize what happened. This can be in the form of a table of processed numerical data, or graphs. It could also be a written statement of what occurred during experiments.
It is from calculations using recorded data that tables and graphs are made. Studying tables and graphs, we can see trends that tell us how different variables cause our observations. Based on these trends, we can draw conclusions about the system under study. These conclusions help us confirm or deny our original hypothesis. Often, mathematical equations can be made from graphs. These equations allow us to predict how a change will affect the system without the need to do additional experiments. Advanced levels of experimental science rely heavily on graphical and mathematical analysis of data. At this level, science becomes even more interesting and powerful.
Conclusion:
Using the trends in your experimental data and your experimental observations, try to answer your original questions. Is your hypothesis correct? Now is the time to pull together what happened, and assess the experiments you did.
Related Questions & Answers:
What you have learned may allow you to answer other questions. Many questions are related. Several new questions may have occurred to you while doing experiments. You may now be able to understand or verify things that you discovered when gathering information for the project. Questions lead to more questions, which lead to additional hypothesis that need to be tested.
Possible Errors:
If you did not observe anything different than what happened with your control, the variable you changed may not affect the system you are investigating. If you did not observe a consistent, reproducible trend in your series of experimental runs there may be experimental errors affecting your results. The first thing to check is how you are making your measurements. Is the measurement method questionable or unreliable? Maybe you are reading a scale incorrectly, or maybe the measuring instrument is working erratically.
If you determine that experimental errors are influencing your results, carefully rethink the design of your experiments. Review each step of the procedure to find sources of potential errors. If possible, have a scientist review the procedure with you. Sometimes the designer of an experiment can miss the obvious.
