GEOG 140 Marine, Continentality, Latitude, and Temperatures Lab: Dr. Rodrigue

GEOG 140

Introduction to Physical Geography

Lab: Marine versus Continentality Effects
and Latitude Effects on Climate

Objectives of this lab:

to give you practice in calculating basic descriptive statistics (means, standard deviations) from tabular data
to give you practice in the construction of a type of X-Y graph called a "line chart," which is very commonly used for graphic communication of data in the sciences. Those in this lab have month on the X (or horizontal) axis. The Y (or vertical) axis is temperature in degrees Fahrenheit.
to familiarize you with the marine influence and continentality as they affect the annual march of temperature through the seasons and as they are both modified by latitude
to give you practice in analyzing tabular data, their descriptive statistics, and their graphs to classify records according to basic physical principles
to give you a chance to sharpen your writing skills as you summarize your findings

Lab A: Getting Your Data

Two pairs of weather stations are described at https://home.csulb.edu/~rodrigue/geog140/labs/tempbymonthform.pdf. Download and print this form. One pair of cities is in Northern California (San Francisco and Chico) and one pair is in Southern California (Santa Monica and Twentynine Palms). For each location, you are given the average temperature for each month, from data obtained at the Western Regional Climate Center http://www.wrcc.dri.edu. Before you have a chance to forget, autograph your form.

You will be graphing the temperatures for the four cities on the chart provided at https://home.csulb.edu/~rodrigue/geog140/labs/tempbymonthchart.pdf. So, go on ahead and download/print that, too. And autograph it!

Lab B: Some Basic Statistics

On the form, you will see the four cities' data listed in four groups of columns labelled "A," "B," "C," and "D." The average monthly temperature is provided for each in the twelve rows of the tables. You will calculate the mean and the standard deviation for each of the four.

Go on ahead and add up the temperatures for each town. Then, divide the sums by 12 to calculate the mean or average annual temperature. Enter your answers in the boxes below the tables, in the "Means" row. Piece of cake.

Calculating standard deviations is a little bit more challenging, unfortunately. First, what IS a standard deviation? It's a measure of the degree of variability or dispersion in a data set, how much the scores vary around the mean. One standard deviation typically takes in about 68% of the variation, so that only one out of three-ish will fall farther than 1 SD away from a mean (that's true of grades, too, usually, but I digress).

To calculate standard deviations, you need to subtract the mean from EACH score. Go on and do that now, putting your answers in the middle column of each table, the column labelled "° F-Mean" (for temperature in degrees Fahrenheit minus the mean).

You then square each of those differences. So, for each "° F-Mean," multiply it by itself (or, if you're doing this with a calculator, as soon as you find "° F-Mean," press "x²." Put that square in the column labelled, well, "Square."

After you've done this somewhat tedious list of subtractions and squares, add up all the squares and put that sum in the box below the table ("Sum of Squares" row).

Then, divide your answer by 11 (12 months minus 1 "degree of freedom"). Put that in the next box below, in the row labelled "Sum of Squares/11."

Now, take the square root of that answer. You will need a calculator with the √ key. Actually, if you have a fancier calculator, you can have it calculate the standard deviation by entering each score into the ∑+ key and then hitting the σn-1 key. Alternatively, it's really easy to do all of this, standard deviations and all, in a spreadsheet (e.g., Excel, Works, OpenOffice Calc). If you're proficient in one of these, you might try doing the lab in your spreadsheet. However you do this, put your standard deviations in the boxes labelled "√of Sum of Sq/11 (St Dev)."

Lab C: Analysis of Marine Influence and Continentality

Look carefully at your temperature data and identify, for each city, which month is the hottest. Enter that month in the box labelled "Hottest Month." Now, remembering that our Northern Hemisphere summer solstice is in June, how many months after the solstice does the city achieve its hottest temperatures? Put that answer in the form.

Think about how water has a higher specific heat than land does. Water requires the input of something like five times as much energy to raise its temperature by a given amount than land surfaces do. Since it takes so much longer to bump water up a degree, which of the cities do you suppose is right along the coast, just based on the delay in achieving the highest temperatures of the year?

Another way of looking at this is to consider how the presence of water affects air temperatures. If there's a lot of water lying around, it will change state from liquid to vapor and absorb heat energy that would otherwise go to heating the air. At night, as temperatures drop, water vapor in the air may be forced to condense if temperatures reach dew point, saturating the air. When water vapor condenses, it releases that latent heat of evaporation, which slows down the cooling of the air. The result is that temperatures do not vary dramatically in either direction, hot or cold.

Take a look at your four standard deviations. The more coastal locations could be expected to have smaller standard deviations than the drier inland locations. Alternatively, you could look at the range of temperatures, the difference between the hottest month and the coldest month. That difference will be much greater inland.

You can surmise which two cities have to be coastal and which two have to be inland. Go on and check which is which on the second page of your form. Then, explain your reasoning, based on all these copious hints.

Lab C: Analysis of the Influence of Latitude

So, you now know which two cities among A, B, C, or D have to be San Francisco and Santa Monica (coastal) and which two have to be Twentynine Palms and Chico (inland). But which of the two coastal locations is which? Which of the two inland locations is which?

Take a closer look at the four annual means you calculated. Consider each pair, A/B and C/D as a unit. Which pair has higher mean temperatures? Which pair is relatively cooler?

So, which pair is probably the northern pair and which the southern pair? Mark each pair on the form with an "N" or an "S." And explain your choice.

Now, identify each data table, A, B, C, and D by its city, San Francisco, Santa Monica, Twentynine Palms, and Chico.

Lab D: Graphing the Annual March of Average Monthly Temperatures

Now, the fun part: Charting your data. On a single chart, you'll make four lines (connect-the-dots), each a different color/pattern keyed to a particular city. To avoid confusion, do each city's line before moving to the next one.

For each city, place a small dot in each month's column at the height corresponding to its average temperature for that month. After you have the dots pencilled in for that city, connect each dot with a straight segment. Then, do the next one. Use the following color scheme (or one similar to it anyhow): a solid blue line for San Francisco, a broken blue line (----) for Chico, a solid red line for Twentynine Palms, and a broken red line for Santa Monica. Make sure to fill in the legend below the chart, indicating which line color/pattern is for which city.

The graph very succinctly conveys which two cities are coastal with their flatter, less variant lines and which two are inland with their steeper degree of deviation. You can readily see that the coastal towns peak later in the summer and the inland, more extreme towns peak noticeably earlier. And you can also see how the two coastal curves and the two inland curves parallel one another but with both southern towns being warmer than their coastal/inland counterparts to the north, due in large part to their latitudes and distance from the tropics.

So, now you are experts in "data visualization," the marine versus continentality effects, and how latitude noticeably affects climates within California. Not only that, you now know how to calculate, not just averages, but standard deviations (which are used all over the place: nearly all of you can count on encountering them in your career, calculating them or interpreting them!).

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