Dear Weather in Action Teachers,

In addition to this letter, I am sending you two other files: NET_WIA.kdn and Students.kwp. The Students.kwp file is short, in case you would like to make individual copies for your students. If you think that this letter contains too much information for your students, feel free to delete or edit any section that is not appropriate for your class before printing it.

Congratulations to the 19 classes that sent in their data files! We have data files from classes in 11 U.S. states, and British Columbia.  I've had a chance to look at all your data in various ways with NGS Works, and I hope you and your students also have been experimenting with making various graphs and maps. If you haven't yet sent your OUR_WIA.kdn table, please do so. Even if you have data only for a day or two, your research teammates will be glad to see your results.

Although I worked with data from a small group of classes, the compilation of that much data can result in a table that would be large and confusing. Scientists use computer-graphing programs and statistical analysis programs to help them make sense of the data they've collected. With NGS Works, you can help your students develop similar analysis skills for themselves. Specifically, they can take the data that they collected or received to create a variety of tables, graphs, and maps that focus on specific aspects of the data. The emphasis in this NGS Kids Network unit is on getting students to think about their data and then to think with their data. The approach involves asking a question, making predictions, looking at the data, finding answers, comparing the answers with the predictions, and then understanding the similarities and differences between answers and predictions. Anything that you can do to encourage these activities will help your students appreciate the scientific research process.

COMMENTS ON THE NET_WIA DATA TABLE

While the amount of data provided in the NET_WIA data table was somewhat limited, I feel that these data serve an important lesson, and I have enumerated several points that I feel are important. Please take some time to explain these ideas to your students.

* In order to see distinct weather patterns at any one time and draw meaningful conclusions, we need to consider a sizable amount of weather data from many locations. Preferably, we should take these observations at about the same time every day, since the temperature in the morning or at midday is less than in mid-afternoon. If you wanted to see how the weather changes over a week, you should faithfully take as many careful observations at the same time every day.
* Collecting the reading from a weather instrument tells only part of the story. Certainly, getting a reading from a thermometer is important, but we can get a better feeling for the significance of the temperature reading if additional information as to sky conditions, precipitation, and winds were included. Such additional comments--when added to the Observations entry--are often revealing, especially if the observer were experiencing rapidly changing weather such as the approach of a storm system or the passage of a front. I was impressed by the number of additional comments added to the "Observations" column of the table. For example, the comment that snow is on the ground may help explain why the morning temperature reading may have been lower than on a morning with no snow cover.

* Several teams were from neighboring schools in the same community.  Comparison of the data from these teams can provide insight into time of day, differences in location or a combination.

* How good are the data that you collected? The occurrence of two separate pairs of teams from the same schools in this data set provides an interesting test. We could inspect the data from each team to find if significant differences occur. Can we explain why differences would occur?

  Several schools had teams that made observations in the morning and in the afternoon.  To give students experience in looking for trends and making comparisons, ask students to make a map of all the temperatures using NGS Works. See where the data are plotted. Help your students determine from the data the location of the school. Likewise, have the students use just the latitude and longitude information for another team to locate that team's position. This exercise will show that if some part of scientific data does not include certain criteria--in this case, the latitude and longitude--that data would become difficult to use.

Unseasonably warm conditions were found in much of the continental United States during January 1999, even though the Midwest experienced at least one blizzard along with an arctic outbreak and the East had a major ice storm at the start of the month. These above-average January temperatures continued from a trend that saw the 1998 average temperature for the globe and the United States to be one of the highest since reliable records began more than a century ago. As we reach mid-February, the Pacific Northwest continues to be battered by storms that have been accompanied by high winds, flooding rain, and heavy mountain snow. As a result, the West Coast has remained cooler than average, while warmer than average conditions were found to the east of the Rockies.  Alaska experienced two weeks of extremely cold weather.  
 
The weather patterns are considerably different during this winter of 1998/1999 as compared with a year before. Last year, some scientists pointed to an El Niņo weather pattern as being responsible for the abnormal weather regime that was apparent across most of the U.S.  This winter, a pattern that some identify as a La Niņa pattern appears to will evolve through the upcoming winter. 

Determine from the data how many classes reported rain or snow. If it's difficult to sort through all the data, create a subset to view groups of data more easily. For example to collect the classes that reported rain, click on Create Subset from the Legend at left. In the dialog box that appears, select Precipitation as the column name and Equal as the Operator and type in Rain. Click OK. The new table contains only the sites that reported rain.

Some sections of the United States were hit by an unusual number of severe thunderstorms during the month of January 1999. The weather pattern over the Southern states was more reminiscent of spring than of winter. In fact, a new January tornado record was set as 169 tornadoes were reported across the United States.  How about having your students keep track of the number of tornadoes?   


Your students may have defined an air mass over your area on the basis of their measurements of temperature and humidity. Perhaps they saw an abrupt change in weather as a different air mass arrived along a front. The storm systems that have traversed the country during February contained fronts that show these changes. In the NET_WIA table they can look at data from another school and try to define the air mass or masses that passed through that area. You might want to assign each small group of students to study one class in the data set and report their findings. A line graph showing temperature change over a period of time is a great way to spot warming or cooling trends and dramatic changes. Use the following steps to make such a graph:

--First, extract the data from just one class by making a subset. (Click Create Subset. In the dialog box that appears, choose Teacher as the column name, Equal as the operator, and the name of one of the teachers as the value. Be sure to spell the teacher's name exactly as it appears in the table.)

--Next, sort the subset data by Date in Ascending order, from earliest to latest.

--Finally, make the Line Graph. (Click Make Graph. In the dialog box, choose Date from the left-hand list and Temperature from the right-hand list. Choose the graph type. Both the line graph and the bar graph are useful displays.)

If a line graph of temperature shows a sudden change, a look at other measurements, such as wind speed and direction, humidity, and pressure--they may help explain what was happening on that day.

TIPS ABOUT MAKING GRAPHS AND MAPS

CIRCLE (or Pie) graphs are especially useful in making comparisons, even between a very large data set and a small one or a subset. For example, you might want to compare the relative fraction of clear and cloudy days at a particular site with the corresponding proportions at another site or with the proportions of all the reporting sites. The circle graph legend gives percentages and the actual numbers from the table. You can print two circle graphs or you can compare them on the same computer screen by shrinking their windows so both can be seen at once. Clicking the little red arrow along the bottom border makes the feature bar disappear allowing more area for the circle graph and its legend. You may experiment with resizing the windows of the two graphs so that the circles are about the same size.

BAR graphs. Even with so few classes submitting data, the entire NET_WIA data table is too large for certain kinds of graphing displays, especially bar graphs. The data become too crowded to read. Therefore, making subsets is so valuable. Another reason for producing subsets is that the thinking process of defining a subset is a skill that students will need to develop for making many kinds of searches in electronic encyclopedias and other databases, including the Internet itself.

THANK YOU!

I appreciate your hard work during this session! Thanks especially for helping guide your students through the scientific process. Awakening children to the excitement of scientific inquiry is one of the most important jobs in our society today.

Sincerely,

Ed Hopkins
Lecturer
Department of Atmospheric and Ocean Sciences
University of Wisconsin-Madison
1225 West Dayton Street
Madison, WI 53706