Assignment 2:  The Orographic Effect: Comparing Climates of Two Oregon Cities

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Assignment 2:  The Orographic Effect: Comparing Climates of Two Oregon Cities

In this assignment, you will explore the effects of mountains on climate, by comparing the climates of two Oregon cities.   We’ll start by reviewing our overall framework for understand climate, and trace a model of how the orographic effect causes temperatures to change as air masses move across mountains.  We’ll then access NOAA Climate Normals data for Eugene and Bend, two Oregon cities on either side of the Cascade Mountains, and create climographs summarizing their temperature and precipitation patterns.  We’ll then interpret those graphs, testing whether they align with our model of the orographic effect.  Lastly, we’ll extend our understanding, by brainstorming about aspects of these mountain climates not included in our model.

You can think of this lab as a guided tour, or a virtual field trip.  I’ll walk you through our case studies, and along the way I’ll pose questions for you to think about.  Most of these questions are intended simply to guide you as you work—I encourage you to stop and think, and perhaps to jot down your answers, but formal responses are not required.  However, please note the italicized questions—for those, I’ll ask you to write out your answers, compile them in a word processor, and turn them in to this assignment’s Canvas dropbox.

Goals:

• Review the effects of altitude and topography on patterns of temperature and precipitation in mountain climates.
• Practice interpreting climographs, making graphs with a spreadsheet program, and exploring locations and topography using Google Earth.
• Trace the process of the orographic effect, and the effects on temperature and precipitation patterns as air moves across a mountain system.
• Compare and contrast a model of the orographic effect with real-world data for two cities in Oregon.
• Brainstorm how these climate processes would affect areas beyond our available data.

Materials:

• Climate data for Eugene and Bend, OR, downloaded from https://www.ncei.noaa.gov/products/land-based-station/us-climate-normals.  (See below for further instructions).
• Google Earth Pro, downloaded from https://www.google.com/earth/versions/ and installed on your computer.  (Make sure that you get the Pro version, for desktop or laptop computers, rather than the version that runs on a tablet or smartphone, or inside your web browser window.  You’ll need to click “Google Earth Pro on Desktop” and install it.)
• A spreadsheet program.  The instructions on this page are built around Microsoft Excel, but you can also use Google Sheets, Apple’s Numbers, LibreOffice, or any other software.  (It make take some experimenting, or a Google search or two, to figure out how to get the software to do what you want!)

What You’ll Do:

Part 1: What have we learned about climate?

One of our main themes for Module 3 was understanding both the climate patterns at a particular location, and the climate processes that produce those patterns.  We’re especially interested in the patterns of temperature and precipitation that occur in mountain locations during the course of a year.  These are often summarized with a climograph, such as this climograph for Boulder:

(As a reminder, I’ll pose a number of questions throughout this assignment.  Most are intended to guide you as you work through the material—though I’d encourage you to pause and jot down your thoughts.  However, your responses to any italicized question—like the one at the end of this section—should be submitted as part of your lab writeup.)

• Note that climographs display monthly averages for climate and precipitation.  Conventionally, temperature is shown with a line graph, and precipitation with a bar graph.
• Review the climograph for Boulder.  How would you describe the patterns of temperature and precipitation that characterize Boulder’s climate?  Do they align with your experience?
• 1) Why are we focused on temperature and precipitation as the most important dimensions of mountain climates? Are there other aspects of climate we should consider?  Suggest one, and tell me why it is important.

Next, remember that we used a framework of four “climate controls” to understand the processes driving climate, as it varies spatially and temporally.

• How are climates affected by each of the following climate controls?  (Hint: it might be helpful to think about seasonal patterns).
  • Latitude
  • Altitude
  • Continentality
  • Topography
• 2) Two of these factors—altitude and topography—are particularly relevant to mountain climates.  Summarize what we know about their effects on temperature and precipitation.

Part 2: The Orographic Effect

We are particularly interested in the Orographic Effect, which connects altitude and topography with temperature and precipitation, to create unique mountain climates.  Read over the following summary:

As an air parcel ascends, it will expand due to decreasing pressure and it will cool due to a decrease in the number of molecular collisions between air particles. As an air parcel descends, the opposite will occur–the temperature will increase due to an increase in the number of collisions between air particles. When air is dry, it will warm or cool at a relatively constant dry adiabatic rate of 10°C per 1000 meters.  That is, as it ascends, it will cool 10°C from its starting temperature for every 1000 m of elevation gain, and warm 10°C for every 1000 m it descends. Things get more complicated, however, if the air cools to the temperature where it cannot hold any more water vapor (the dew point) and water droplets begin to condense, forming dew and clouds.  At that point, additional energy (the latent heat of vaporization) will be released as the water changes from gas to liquid, causing cooling to slow.  This moist adiabatic rate is generally between 5 and 9 °C per 1000 m. However, this only occurs when air is ascending and cooling; descending air will always warm at the dry adiabatic rate. 

What does all of this mean for mountain temperature and precipitation, as air masses move from the windward side of a mountain range to the leeward side?  At the same elevation, temperatures on the leeward side are generally warmer than those on the windward side.  Additionally, the cooling and condensation that occur as air masses are uplifted leads to the formation of clouds and precipitation, concentrated on the windward side. In contrast, air becomes relatively drier as it descends and warms, causing the leeward side to receive less precipitation. The tendency for the leeward side of a mountain to be warmer and drier than the windward side is known as the “rain shadow effect.”

• Check your understanding:  can you explain the following, using your own words?
  • Why does a parcel of air expand as it ascends?
  • Why does a parcel of air cool as it ascends?
  • What will happen as a parcel of air descends the leeward side of a mountain? 
  • Why will clouds form after the air cools below the dew point?
  • How can we expect temperature and precipitation to compare between the leeward and windward side of the mountain (holding elevation constant).

Next, let’s work through a brief model of this process, as an air mass passes over a hypothetical 3500 m mountain.  Your task is to trace the temperatures at 1000 m intervals, as the air ascends from 500m to 3500 m, and descends back to 500m, and to fill them into the boxes on the sketch below.

• Assume a starting temperature of 20°C at 500 m on the windward side.
• As the air ascends, it will cool at a dry adiabatic rate of 10°C per 1000 m until it reaches the dew point of 10°C.  (This is symbolized by the cartoon clouds on the sketch).  Thereafter, it will cool at a moist adiabatic rate of 8°C per 1000m until it reaches the summit.
• As the air cools, it will warm at a consistent dry adiabatic rate of 10°C per 1000 m.
• Based on these rates, fill in the temperatures we would expect to see at each elevation, on both windward and leeward sides of the mountain.  (Yes, do the math!  You can print out the image, or draw your own sketch on a piece of scrap paper.)

• 3) What temperatures did you calculate for a 500 m elevation on the windward side of the mountain?  For a 500 m elevation on the leeward side?  Which side do you expect will have the wetter or drier climate? 
• 4) What assumptions does this model make about this mountain, in order to calculate the change in temperature?  Do those assumptions seem realistic?

Part 3: Situating Eugene and Bend

Eugene and Bend are two cities in Oregon, located on opposite sides of the Cascade Mountains.  Using Google Earth (you’ve installed it, right?), locate the two cities. (Type “Eugene, OR” and “Bend, OR” into the search field in on the left side of the Google Earth window.)

• What is Eugene’s elevation?  What is Bend’s elevation?
• How distant are the two cities from one another?  (Use the ruler tool, making sure to select a sensible unit of measurement.)
• The Cascades lie between Eugene and Bend.  What elevations do they reach?  (Hint: you can shift to a 3D view to see the Cascades in profile, and find a high summit.)
• In this part of the world, storm systems typically move across the Cascades from west to east.  Which side of the mountains is the windward side?  Which is the leeward side?
• 5) Think about our framework of climate controls.  How do Eugene and Bend differ in terms of their latitude, altitude, continentality, and topography?  Why do the cities offer a good case study of the orographic effect?  Support your answer with specific facts from your Google Earth exploration.

Part 4: Getting the Data

We’ll be looking at the US Climate Normals data for Eugene and Bend, as prepared by the US National Oceanic and Atmospheric administration.  You can download data for each city at https://www.ncei.noaa.gov/products/land-based-station/us-climate-normals

First, skim over the description of the Climate Normals data at the top of the page.  Then, scroll down: under “Data Access” (the default view on the page), click “Launch Quick Access.”  You’re interested in monthly normal for the period from 1991-2020 (which should be the default view).  Let’s start by pulling up data for Eugene: Select the state of Oregon, and “Eugene Mahlon Sweet AP”.  (This is the weather station at Eugene’s Airport.)

The website will respond with both a table of monthly averages for Eugene, and an auto-generated graph of this data.  The graph isn’t bad, but we can do better.

Select and copy the data table from your web browser.  Open your spreadsheet program, and paste the table into the upper left corner of a new blank spreadsheet.  The table data should fill into the spreadsheet cells.

We’re interested in the monthly precipitation and average temperature—so you can reduce your spreadsheet to something that looks like this:

It’s easy to delete the unnecessary columns (right-click on the heading on the top of each column, and select “Delete” to delete the column rather than clearing out each individual cell while leaving the cells intact.)

Repeat this same procedure for data from Bend—you’ll want to select the data for “Bend”, rather than any of the nearby weather stations.

As before, copy the data table into a spreadsheet (you can create a new spreadsheet file, or find an unused bit of your current spreadsheet), and delete the unnecessary columns.

• Take some time to look over these monthly averages.  Some useful comparisons:
  • Which city sees the warmest month?  The coolest month?  The wettest month?  The driest month?
  • Calculate an annual average (that is, an average of the monthly averages) for the average temperature and precipitation for each city.
  • What is the each city’s temperature range—that is, the difference between its warmest and coolest monthly temperatures?
  • Do you notice any seasonal patterns in the temperature and precipitation over the course of the year?
• Your spreadsheet program can help you calculate all of these (formulas like =AVERAGE(B2:B13) are very helpful!).  But be sure to clean things up afterward, so you can easily make a graph from your table.

Part 5: Charting and Comparing the Two Climates

If you’ve haven’t worked with a spreadsheet program before, making graphs can seem daunting.  (There are lots of fiddly little options!)  Nonetheless, it’s pretty straightforward, and might even be intuitive!

That being said, if you’re perplexed or running low on time, it’s possible (though not recommended) to forgo making your own graphs, and complete the lab on the basis of the data tables you’ve accessed, and perhaps the auto-generated graphs from the NOAA website.

But where’s the fun in that?

• To start out, select your “clean” table for Eugene, including the months and the column headings, but not any of the adjacent columns, cells, or rows.
  • In Excel, click the “Insert” ribbon at the top of the screen, and select Insert Line Chart.  (It looks like ).  From the drop-down, select the first option—a standard line chart.  If all goes well, Excel will create a line chart, with lines for your temperature and precipitation data.
  • In Google Sheets, it’s even easier: select your data, go to the Insert Menu, and insert a Chart.  (Google might even use a column chart for one of your data series, though sometimes it gets it wrong.)
• Next, you’ll want to tweak your data—remember that climographs customarily use a line graph to present temperature data, and a column graph for your precipitation averages.
  • Each program has many ways to (re)format your chart, and there’s no single right way to do this.  I’ll give you some hints; you may need to spend some time exploring.  When in doubt, take a deep breath, and remind yourself that “everything has a properties page.”
  • In Excel, click on the line representing your precipitation data to select it.  Right click to bring up a menu, and select “Change Series Chart Type”.  This brings up a properties page with lots of chart options.  The most useful to you is “Combo” at the bottom of the left-hand column.  This will let you specify a line chart for your temperature data, and a column chart for your precipitation totals.  (You can even display the precipitation totals on a secondary axis from here.)
  • In Google Sheets, right-click on the chart, select “Series”, and choose which series you want to configure.  On the “Chart Editor” sidebar, you can select a line or a column chart for that data series, as appropriate.  (There’s also an option here to display that data series on a secondary vertical axis.) 
• Some other things to do:
  • By default, your graph will show both precipitation and temperature data on the same vertical axis.  That’s fine for the temperature data, but it makes it harder to see differences in the precipitation averages.  By configuring a secondary vertical axis on the right side of the chart, you can show both more clearly.
  • Add a title to your graph, showing which city’s data you’re charting.
  • Label your axes.  Be sure to specify your units of measurement!
• Once you’re done, make another graph for Bend!
  • By default, the axes are set up to best show the range of data for each graph.  But if you’re feeling really fancy, you can tweak them, so the same range will be used for both graphs.  (This makes it especially easy to see how much wetter Eugene’s climate is!)
• 6) Copy your two charts—or the best you’ve managed them—into your writeup document.

Using information from your two charts, and the analysis you did earlier, compare and contrast the climates of Eugene and Bend:

• 7) How do the cities temperature patterns compare with each other?  What about their precipitation patterns?  What would explain why Eugene is warmer and wetter, while Bend is cooler and drier?

Part 5: Putting things into context.

By this point, you should see several clear differences between the climates of Eugene and Bend.  Based on what you’ve learned about the orographic effect, you should also have a good idea as to the processes responsible.  But the real world is often more complex than our models.  Can you answer the following questions?

• 8) Eugene and Bend are actually located at the base of the Cascades—we haven’t looked at the climates of the mountains themselves!  Nonetheless, based on your knowledge of the Orographic Effect, what temperature and precipitation patterns would you expect to see at a weather station located high in the Cascades between the two cities?
• 9) Remember that our model of the orographic effect suggested that the leeward side of a mountain would be both warmer and drier than the leeward side.  Yet our data show that Bend is frequently cooler than Eugene.  What’s going on?  What is different between our model and the real-world data we’ve just studied?
• 10)  We haven’t talked much about continentality.  Which of our two cities has the more continental climate, and which the more maritime?  What effects might this difference have for their patterns of temperature and precipitation?
• 11)  Many students learn about the orographic effect, and expect to see dramatic changes on opposite sides of an individual mountain peak—in contrast to the opposite sides of a mountain range we’ve looked at in this lab.  Would we expect to see such differences across a shorter distance?  Why or why not?  How might the geographic concepts of process and scale help us understand this contrast?

What You’ll Turn In:

• Compile your answers to the numbered and italicized questions into a document—you’ll submit this to the Canvas dropbox.
• Look over your answers—you may want to expand or revise them, based on what you found in the rest of the assignment.  Your answers to each question should be a few sentences to a paragraph in length.  It’s perfectly OK to respond to each question point-by-point, rather than fitting them into a unified structure of thesis statement, paragraphs, etc.  Bullet points may prove helpful.
• Make sure that you’ve answered all parts of each question, and that it’s clear which hazards you examined, and which additional mitigation plan you looked up.
• Be sure that you submit your assignment in .docx or .pdf format—Canvas can’t handle .pages!

Grading:

This assignment will be worth 10 points, calculated according to the following rubric.  Late assignments will not be accepted without prior instructor contact/permission.

Completion (3 Points)	Analysis (3 Points)	Writeup (4 Points)
3: Superior. All portions of activity complete.  No outstanding technical difficulties.  Student has responded to prompts and questions promoting further engagement and understanding.	3: Superior Insightfully applies course concepts to examine case studies.  Makes connections with concepts and case studies beyond the immediate assignment scope.	4: Superior Full response to questions and prompts.  High standard of writing, grammar, spelling. Demonstrates understanding of how the assignment relates to course content.
2: Competent Most portions of activity complete, possibly due to technical difficulties.  Student has worked through instructions, but not engaged in further reflection.	2: Competent Applies course concepts to directed case studies, but does not extend analysis beyond the frame of the assignment.	3: Strong Largely complete response to questions and prompts.  Writing, grammar, and spelling contain some errors but are acceptable.  Suggests links between assignment and course content, but does not delve deeply into them.
1: Weak Significant portions of the activity not completed.	1: Weak Significant errors in analysis, which call underlying understanding into question.	2: Acceptable Uneven response to questions and prompts.  Significant errors in writing, grammar, and spelling.  Shows significant gaps in understanding of course content.
0: Not Completed Activity not attempted.	0: No Analysis Minimal work to translate activity into writeup.	1: Weak Token or incomplete response to questions and prompts.
		0:  Not completed  No response to questions and prompts.