METR 104:
Our Dynamic Weather
(Lecture w/Lab)
Lab Exploration #2:
Solar Radiation & Temperature
Part V: A More Complex
Computer Model
Dr. Dave Dempsey
Dept. of Geosciences
SFSU, Spring 2012

(5 points)
(Lab Section 1: Wed., March 7; Lab Section 2: Fri.., March 9)

Learning Objectives. After completing this activity, you should be able to:

Materials Needed. To complete this activity, you will need:

Prior Knowledge Required:

I. Introduction. This lab activity continues our development of a sense of how we might use (a) experience with observations and (b) basic physical principles, to understand and forecast surface temperature over the course of one to several days. In particular, it continues the development and testing of a computer model of the daily temperature cycle at the earth's surface introduced in Lab #2, Part IV.

In this lab you'll configure two more sophisticated version of the computer model, run experiments with them, and evaluate them based on your experience reading surface weather observations displayed on meteograms.

II. A Somewhat More Sophisticated Computer Model of Temperature Driven by Solar Heating

The sun certainly plays a central (though not necessarily the only) role in controlling daily temperature variations, and clouds modify (in particular, reduce) the effect that solar radiation has on temperature during the daytime. However, we discovered in Lab #2, Part IV that solar radiation alone doesn't account for some aspects of the daily temperature cycle. In particular, by accounting only for solar radiation absorption (even when modified by clouds), the temperature never goes down (at night or any other time), and the temperature rises all day to a maximum at about sunset, not to a maximum time in the afternoon between noon and sunset.

In retrospect, the fact that the temperature never went down in that model should make sense. For an object to cool, it must lose heat. The mere absence of solar heating does not by itself give the earth's surface any way to lose heat and cool off—it merely means that it's not gaining any heat and so the temperature wouldn't change, as the model predicted.

To overcome this shortcoming, we'll try adding emission of radiative energy to the model, a mechanisms by which the earth's surface can lose heat.

With this new physical processes included, the Law of Conservation of Energy applied to the earth's surface and written in a form that describes how the surface gains and loses heat and how its temperature responds as a result, can be written like this:

The rate at which
the earth's
The rate at which
the heat content
of a layer of
the earth's
= The rate
at which
the surface

The rate
at which
the surface

Using this relationship can calculate how fast the surface temperature changes, and from that we can estimate what the temperatures will be in the near future (if they are driven by absorption of solar radiation and emission of radiative energy).

We can run this somewhat more sophisticated model, compare the results to observed daily temperature cycles, and see how well the model performs. That is, we can evaluate or validate the model. If the model does well, it could be useful for helping us understand better how the atmosphere works and for making temperature forecasts. (To be sure, further experience and validation of the model would be necessary.) If the model doesn't do well, we have to question any assumptions that underlie the physical relationship as we've applied above or perhaps take into account physical processes that are important but that we neglected.

III. Instructions. Respond in writing to questions posed in section D below. Turn in your responses at the end of lab.

  1. Access "Daily Temperature Cycle II.A", a computer model of the daily temperature cycle written using STELLA modeling software.

      1. Locate a file called "DailyTempCycle.II.A.STM" on the Desktop.
      2. Double-click on the DailyTempCycle.II.A.STM file. This should start STELLA, open the file, and present you with the model interface.

    Your instructor will describe the model features and explain how to configure it, run it, and access and read the model output graphs. Note the ways in which this model differs from the version in Lab #2, Part IV.

  2. Note the default model configuration.

    1. In this version of the daily temperature cycle model, the latitude is set to 36°N (the approximate latitude of Hanford, CA). However, you can specify:

      • Either of two days of the year (May 22 or December 16)
      • Whether or not the surface emits longwave infrared radiative energy
      • "Surface Type" (land or water)

      By default, the day of the year is set to May 22; the radiative emission switch is set to "off"; and the surface type is set to "land".

      For this lab activity, start out with these default settings (that is, don't change anything yet). Don't run the model yet, either.

  3. Make your own prediction of the daily temperature pattern, given how the sun angle varies.

    1. You have been provided with a plot of sun angle (in degrees) vs. time (in hours) for 2.5 days (60 hours) starting on May 22 at the latitude of Hanford, CA. Identify nighttime vs. daytime periods and the times of sunrise, sunset, and (solar) noon.

      Based on the sun angle, sketch the pattern of temperature that you would expect to see (assuming no clouds). [The actual temperatures aren't important here, just the pattern of temperature—that is, the time(s) when the temperature is lowest and highest and what it does in between—relative to the sun angle pattern.]

    2. Run the model and view the second graph (Page 2). (To view Page 2, click on the lower left-hand corner of the graph, which looks as if the corner has been bent forward slightly.) This graph plots (1) the sun angle (in degrees, the blue line) and (2) temperature (in °F, the red line) simulated by the model. Compare your prediction to the model results.

    3. Repeat for December 16, and note any differences from May 22.

  4. Reconfigure the model to run with radiative emission turned on, predict the results, run the model, and compare your prediction to the model simulation.

    1. Turn on IR Emission and set the day of the year to May 22.

    2. You have been provided with a second plot of sun angle (in degrees) vs. time (in hours) for 2.5 days (60 hours) starting on May 22 at the latitude of Hanford, CA.

      Based on the sun angle, sketch the pattern of temperature that you would expect to see with radiative emission turned on (again assuming no clouds).

    3. Run the model and view the second graph (Page 2). As before, this graph plots (1) the sun angle (in degrees, the blue line) and (2) temperature (in °F, the red line) simulated by the model.

    4. Describe any apparent connections or associations that you can see between temperature (as calculated by the model) and sun angle.

      [For example, how does each behave at night? During daylight hours? When is temperature changing and not changing, relative to what the sun angle is or is not doing?]

      [You can refine your sense of this as follows: (a) place the cursor on the graph; (b) click and hold the click, so that a vertical line appears on the graph through the location of the cursor; and (c) drag the cursor back and forth, which drags the vertical line with it. Beneath the "Hours" label along the horizontal axis you'll see the time (in hours) corresponding to the cursor's position, and beneath the "Sun Angle deg" and "Temperature F" labels along the top of the graph you'll see the values of these quantities at that hour.]

    5. View the third graph (Page 3). It shows (1) the rate at which the surface absorbs solar energy (in Watts, the blue line), and (2) the temperature (in °F, the red line).

      In what ways does the model simulation seem reasonable and in what ways does it not? [You should consider surface temperature observations that you've seen plotted on meteograms (for example, on the meteograms accompanying this lab from Hanford, CA, which we first saw in Lab #2, Part II), and your own personal experience with the daily temperature cycle.]

    6. Does the model seem to perform better than it did previously, when it calculated the effects of only solar radiation absorption? If so, how?

    7. Are there aspects of the model prediction that don't seem to capture reality very well? If so, what? (You can rerun the model for December 16 and see if any of your observations and conclusions differ.)

    8. Print a copy of the third graph only (Page 3), for the May 22 model simulation. Put your name on it, and turn it in along with your written responses to questions posed in the rest of this section (Section D).

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