Introduction: (Initial Observation)
Cold white snowflakes that we get in winters are certainly good for playing snow ball or making a snow man; however, not everyone is happy with snow. After each snow, shovels and plows get to work to remove the snow from streets, roads, side walks and some roofs. After all it seems that snow is not the favorite type of precipitation for many people who have to remove it as soon as it covers the ground.
But what is snow? what happens when it melts? What does it contain? In some areas, piles of snow remains for a long time. Do animals live in snow banks? This project is an opportunity to learn more about the snow.
Before doing this project there are certain information that you need to gather by asking from others or studying books. Your main goal in doing this project is to find the answers to all your questions about snow. While gathering information from books or others, you will find some of the answers, so you will not need to perform any experiment about them. You may not be 100% sure about the accuracy of some of the information that you gather, in such cases you may design experiments to verify those information. You must also perform experiments to find answers to questions that there are no information about them. For example if you ask someone what happens when snow melts? The answer is that it becomes water. You may not be sure about the answer. You may be thinking that “It can’t be just water. Something else must be there that solidifies water!”. You will then perform an experiment to test this.
The main experiment proposed in this project is measuring the density of snow. Depending on your question, your project and your time you may do many other experiments as well.
One interesting experiment is observing snowflakes and see how do they look like. Collect falling snow flakes (just a few) and observe them under a magnifier glass. Repeat that at different dates and see if there is any relation between the shape of snow flakes and air temperature.
Another experiment is putting some snow in a clean pan and heat it up until snow melts and evaporates. See if anything is left in the pan. (Is there anything that solidifies water and makes it snow?). Some believe that each snowflake is formed around a dust particle. In other words snow is not pure water. Does your test show any dust left in the pan?
Engineers are measuring the density of snow at different depths. The data that they collect is used determine how much water will be produced when all that snow melts.
Another experiment that you may do is finding a snow bank and see if it contains any animal or plant life. Snow bank is a pile of snow that remains in a place for a long time. I have seen tiny black insects living on the snow, however when you search you may find other types of life as well. Just make sure that you carry your measuring tools, magnifying glass, your notebook and possibly a camera if you want to study life in a snow bank. (Be ware of polar bares)
What do you want to find out? Write a statement that describes what you want to do. Use your observations and questions to write the statement. Following are some example. You may come up with other questions.
- What is the density of snow? (Or how much water do we get from certain volume of snow? How much water do we get from one cubic foot of snow? How much water do we get from one gallon of snow?)
- Is the density of snow affected by the air temperature?
- Is the density of snow affected by the time of the year?
- Does the density of snow vary at different depths?
- Does the density of snow vary in different elevations?
You may select any of the above questions or come up with a different question for your project. In all cases you need to repeat snow density experiment at different times or elevations or conditions…
Make sure you just pick one question that you can experiment.
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.
Depending on the question that you choose, you define the related variables.
For the first question that is very general, snow is an independent variable, Snow density is a dependent variable and all other factors such as air temperature test procedures are controlled variables.
For the second question, air temperature is the independent variable, snow density is a dependent variable, snow (type, location, specification) and test procedures are controlled variables.
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. Following are some sample hypothesis:
Sample hypothesis for question number 1:
The density of snow in average is about half of the density of water. In other words from each one gallon snow we can get half gallon water.
Sample hypothesis for Question number 2:
As the temperature increased, snow will partially melt and becomes more dense.
Sample hypothesis for question number 4:
Deep snow is compressed by upper snow and must have a higher density.
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 many places, government water engineers and farmers depend on winter snow to provide an adequate water supply for cities and farms. These people watch and measure the amount of snow all winter long. It is not just the depth of the snow that is important, but the amount of precipitation or, in other words, the amount of water in the snow.
You can measure the amount of water in snow by collecting some the snow, melting it, and measuring the water. Some snow is very dense, which means it contains a large quantity of water for its relative size. An example might be that one gallon of snow, when melted, becomes one quart of water. Other snow has a very low density. In this case, a gallon of snow makes only a cup of water.
Many things affect the density of snow including: temperature, air pressure, the nature of the storm, your geographic location and altitude, etc. In truth, each snowstorm brings snow of a different density.
In this project, you are the weather watcher. You must determine how much moisture is available in the snow in your area. This experiment does not require you to track precipitation for a complete season. The best time to do it, however, is during the biggest snow weeks when there is lots of activity in the weather.
Measuring snow moisture or snow density is the main experiment of this project regardless of the main question that you choose.
DENSITY: The amount of space between molecules or particles of any substance is what determines its density. Lead is more dense than aluminum which is more dense than wood which is more dense than foam rubber which is more dense than Styrofoam. Density is equal to the mass (or weight) of a substance divided by its volume (d=m/V). The metric system was set up in such a way so that the density of water can be written as 1 gram per milliliter (1g/mL). One milliliter (mL) is also equal to one cubic centimeter.
PRECIPITATION: The word precipitation is defined as any form of water that falls from clouds and reaches the ground; the amount being expressed in inches (or centimeters) of liquid water depth. In this project, you will compare not the depth, but the volume of the snow or water. Water is “pure precipitation.” Snow, on the other hand, is mostly air. As you can see, the density of snow is related to the measure of the water in snow. The density of snow might be expressed as 1 cup of water per gallon of snow or 100 mL/L [density=V(water)/V(snow), where V=volume.]
(Determine the density of snow at different depths and different snow falls)
Before each snow, add some snow meter salt at the bottom of one bucket and leave it outside to collect falling snow. At the end of each snow or each day you may go out and check the water level on the bucket. Record the height of water in the bucket. Empty the bucket and set it up to be ready for the next snow or the next day.
After the each snow, accompanied with an adult, go into the deep snow. Get two identical buckets or similar containers. Use one to collect snow from the surface. Avoid compressing the snow as you collect it. (This can be difficult, but the activity will work regardless of the collection methods used.) In the second bucket, collect snow from deep beneath the surface.
Cover the containers and take them inside to melt.
Each day (or whatever time interval you choose) you will repeat this activity. If you are doing this project in snow season, plan ahead to guarantee that your collection activity can be repeated for at least 5 to 10 times.
Recording the results: Once the snow is melted, measure the water in each container and record the results in a data table. You may measure the water using a measuring cup, a measuring cylinder or by weighing it. If you are weighting it, you even don’t have to wait for the snow to melt.
Before starting your experiment you need to know the volume of your buckets or test containers. Volume also can be measured by weighting. For example if your test container is a cup, you can measure it’s weight. Then fill it up with water and see how much does the weight increase. In metric system it is very easy to convert weight to volume. Each gram water is one milliliter or one cubic centimeter.
This is a sample of a data table:
|Date||Density of top snow||Density of deep snow||Amount of precipitation|
|January 17,2003||0.32 g/cc||0.51 g/cc||2.5 cm (1 inch)|
Presenting The Data: Using your data table make a chart or graph to show the changes in snow precipitation during your experiment period.
Units: The first step in making a chart is to select the units of measure. Along the bottom of your chart, write in the dates that correspond to the days on which you took measurements. Put the first day next to the word “TIME” at the left. Each new date should be an increase of equal amount. The amount of change from date to date is called the unit of measure.
To determine the best units for the water (precipitation), look at the measurements on your Data Record Handout. When you write the units on your chart, you want your smallest unit to be near the bottom, just above the word “WATER.” Your largest measure should be near the top. Choose the units that would make this possible. Example: 1/8th cup steps.
Plotting Data Points: It is easiest to plot only one column from your Data Record at a time. Draw a dot above each date for the amount of “Snowfall” recorded. When you are finished, connect the dots with a colored marker. Next, draw dots for the surface density and use a different color of marker to connect the dots. Do the same for the “Snowpack.” Choose a title or headline for your graph and write it along the top.
Materials and Equipment:
Final list of material may vary based on your final experiment design and what might be available to you.
Sample Materials Needed:
- Deep snow
- Little Bear Snowshoes
- Three large buckets or liquid containers the same size with lids
- Measuring cups
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.
In addition to the data table and the chart or graph, your results can contain the answer to the following questions.
- According to your chart, how much water was in the snow pack on first day?
- Numbers from a table are represented by what on a chart?
- Give an example of something that is very dense.
- How can you find out how much precipitation is in snow?
- Why is it important to know how dense the snow is?
You may use your results and calculate the average density of snow. You may take average from snow density in different depths or different snowfalls.
Summary 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.
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.
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.