Lecture 8: Soundings + Air Pollution

Part of this lecture is about soundings and the structure of the atmosphere.  I have an activity (further down below) where students plot data from a weather balloon to “discover” the troposphere and stratosphere.  I have several data sets to choose from – all from the same weather balloon but at different resolutions (different amounts of data to plot).  When I do this activity with my students, we have not talked about the structure of the atmosphere at all yet.  After they plot it, then we annotate it and talk about the atmospheric layers.  If you watch the lecture, this data is the same set that I am using on screen.  So in a way the lecture kind of gives away the answer.

I also have some activities that are centered around interpretation of different soundings.  In this lecture I do not emphasize the soundings too much, but in previous classes I did.  So you may or may not be able to answer all of the questions.  This activity forces you to really understand dew point and relative humidity to make sense of what is going on:sounding_examples_II

Key to above assignment:sounding_examples_II_KEY

 

This assignment is shorter, but combines soundings, air pressure maps (from Lecture 7), and air pollution:sounding examples for pollution

Key to above assignment:sounding examples for pollution_KEY

Weather balloon graphing project – Part I (beginners)

Overview:  This project is a cross-cutting activity that asks students to first create scatter plots / line plots of data from a weather balloon and then interpret the physical meaning of their graph.  They discover how temperature changes with altitude and how the lower atmosphere is structured.  The students then fill in their graph with features of the atmosphere.  More advanced students can continue on to Part II of this project.

Video above will walk you through this project.

 

Weather balloon data:  Your students will need one of the files below.  Each has the same data from the weather balloon, but they differ in that I have highlighted (shaded) different alternate rows for the students to plot.  I only have my students plot the highlighted rows, not the entire set.  It would be ridiculous to have them plot all of the data by hand and the overall pattern of their graph will more ore less be the same no matter which subset of points you have them plot.  You can decide how many data points you want your students to plot….I have indicated how many total points that will need to be graphed for each file.  If you don’t know which one to use, start with the easy one first (11 points).

July-4th-afternoon-skipping-3-33-points  [PDF] every 4th row shaded – 33 points total to plot

july-4th-afternoon-skipping-4-27-points  [PDF] every 5th row shaded – 27 points total to plot

July-4th-afternoon-skipping-6-19-points  [PDF] every 7th row shaded – 19 points total to plot

July-4th-afternoon-skipping-9-14-points  [PDF] every 10th row shaded – 14 points total to plot

July-4th-afternoon-skipping-12-11-points  [PDF] every 13th row shaded – 11 points total to plot

July-4th-soundings-no-shading  [PDF] no shading – use this if you want to do your own thing

 

Answer keys:  An excel-generated plot for each of the above datasets.  Please realize that the aspect of your students’ graphs will depend on the scale you use.  Pick the answer key that matches the dataset you are using.

July-4th-afternoon-skipping-3-graph-only [PDF] for the dataset above with 33 points

july-4th-afternoon-skipping-4-graph-only [PDF] for the dataset above with 27 points

July-4th-afternoon-skipping-6-graph-only [PDF] for the dataset above with 19 points

July-4th-afternoon-skipping-9-graph-only [PDF] for the dataset above with 14 points

July-4th-afternoon-skipping-12-graph-only  [PDF] for the dataset above with 11 points

July-4th-soundings-all-points-graph [PDF]  for all data that the weather balloon generated.  After the students have made their plots, I show them this graph to illustrate what their graph would have looked like if they had plotted ALL of the data.  The general shape is the same is theirs, but there is more detail – more variations in temperature.

 

Annotated graph:  annotated-graph