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

(5 points)
(Lab Section 1: Wed., April 4; Lab Section 2: Fri., April 6)

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

• Configure and run more experiments with a simple computer model (a STELLA model) of the daily temperature cycle.
• Evaluate the model based on experience reading meteograms.
• Solidify further a description of the role that computer models play in the way that science works in atmospheric science.
Materials Needed. To complete this activity, you will need:

Prior Knowledge Required:

• Background needed for the previous lab exploration (Lab #2, Part V)
• Understanding of the Principle of Conservation of Energy, expressed in the form of a heat budget equation for an object, including the earth's surface
• some ways that the earth's surface can gain and lose heat:
• emission of longwave infrared radiation
• absorption of longwave infrared radiation emitted downward by greenhouse gases and clouds
• conduction of heat from the surface into the atmosphere (or vice versa)
• evaporation of water from the earth's surface
• Understanding of radiative absorption: when an object absorbs radiation, the energy is transformed into (an equal amount of) sensible heat in the object

I. Introduction. This lab activity continues our development and testing of a computer model of the daily temperature cycle at the earth's surface introduced in Lab #2, Part IV and Lab #2, Part V. We're doing this to try to develop 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 this lab you'll configure a more sophisticated version of the computer model, run experiments with it, and evaluate it based on your experience reading surface weather observations displayed on meteograms.

II. An Even More Sophisticated Computer Model of the Daily Temperature Cycle

In Lab #2, Part V, you experimented with a computer (STELLA) model of the daily temperature cycle that included one mechanism by which the earth's surface could gain heat (absorption of solar radiation) and one by which the surface can lose heat (emission of longwave infrared (LWIR) radiation). You could modify the model's behavior by specifying the degree of cloudiness and by changing the nature of the surface from land to water.

That model produced a daily temperature pattern that was realistic in some ways but not in others, compared to actual observations of the daily temperature cycle under similar conditions. In particular, it produced a temperature maximum in the afternoon and cooling thereafter until near (just after) sunrise, as we commonly see in observations of the real atmosphere. The daily maximum temperature, although a little too high, wasn't too bad, but the minimum temperatures were much colder than we'd expect to see, and so the daily temperature range (the difference between the minimum and maximum temperature) was too large. We conclude that, although that model did much better than its predecessor did in Lab #2, Part IV, it must not yet be complete—there is likely one or more physical mechanisms affecting surface temperature that the model doesn't account for yet. What might it (or they) be?

We know that greenhouse gases and clouds absorb longwave infrared radiation emitted by the earth's surface. We also know that greenhouse gases and clouds emit longwave infrared radiation of their own, that they emit part of that radiation downward, and that the surface absorbs it. Hence, we'll include in the model this additional source of heat for the surface.

We also know that when two objects at different temperatures are in direct contact, heat will "flow" from the warmer one to the cooler one (so the warmer one cools off and the cooler one warms up). This is the process of conduction of heat. In particular, when air in contact with the earth's surface is warmer or colder than the surface, heat will conduct from one to the other, and the surface will gain or lose heat. We'll try to represent this process in the model.

Finally, we know that when water evaporates, heat in the water transforms into latent heat in the water vapor, reducing the amount of heat in the remaining water. (We experience this directly when we overheat, produce sweat, and feel cooler when the sweat evaporates from our skin.) We'll try to represent evaporative cooling in the model (especially from the oceans, less so from land).

With these three new physical process added, 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 surface temperature changes ∝  (is proportional to) The rate at which the heat content of a layer of the earth's surface changes = The rate at which the surface absorbs solar radiation + The rate at which the surface absorbs longwave infrared radiation emitted downward by greenhouse gases and  clouds − The rate at which the surface emits longwave infrared radiation ± The rate at which heat conducts between the surface and the atmosphere − The rate at which the surface loses heat due to evaporation of water, converting heat into latent heat

Using this relationship, we can calculate how fast the surface temperature changes and estimate temperature in the near future (at least, if the model is complete and accurate).

We can run this 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 to understand better how the atmosphere works and for making temperature forecasts. (We'd need further experience and validation of the model to be sure.) If the model doesn't do well, we have to question any assumptions that underlie the physical relationship as we've applied it above, or perhaps take into account physical processes that are important but that we've neglected.

III. Instructions. Respond in writing to questions posed in sections D and E below. Turn in your responsesat the end of lab, along with the plot that you print in Section D.

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

• If you are using one of the Mac computers in TH 604 or 607:

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

• Or, if you are using a Web browser and have an internet connection:

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.

In this version of the daily temperature cycle model, you can specify:

• Where and when the model runs:
• latitude (in degrees)
• day of the year (Julian day, expressed as a number from 1 to 365)
• Whether or not each of the following ways for the surface to gain or lose heat are turned on:
• emission of longwave infrared radiative energy
• absorption of longwave infrared radiation emitted downward by greenhouse gases and clouds
• conduction of heat between the surface and the atmosphere, and evaporation of water from the surface
• Several more model parameters:
• "Surface Type" (land or water)
• "Cloud Cover" (expressed as a percentage of the sky covered by clouds)

By default, the latitude is set to 36°N (the approximate latitude of Hanford, CA); the day of the year is set at 142 (May 22); emission of longwave infrared (LWIR) radiation is turned on but the other two mechanisms listed above are not; the surface type is set to "land"; and the cloud cover is set to 0%.

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. Repeat a previous model simulation to confirm that it is the same.

You have been given a plot of sun angle (in degrees) and temperature (in °F) vs. time (in hours) for 2.5 days (60 hours) starting on May 22 at the latitude of Hanford, CA. (You generated this plot in Lab 2, Part V.) Run the latest version of the model with the default configuration described above, and verify that it reproduces this plot. (It is the second graph, on Page 2 of the five pages of graphs available in this version of the model. Click on the lower left-hand corner of the graph, which looks as if the corner has been bent forward slightly.)

Note one difference: the hours plotted along the bottom axis in this version of the model will be from 420 hours to 480 hours (17.5 do 20 days) instead of 0 to 60 hours (0 to 2.5 days). Both series of times start at midnight and end at noon, though.

Note the maximum and minimum temperatures achieved over the course of each day, and the time of day when they occur.

4. Predict what will happen with greenhouse heating turned on, then rerun the model to find out what it does.

1. Reconfigure the model to run with greenhouse (GH) heating turned on, predict how you think this will change the temperature pattern, and rerun the model without changing anything else.

2. Does the pattern of the daily temperature cycle change in any significant way? What about the actual temperatures (for example, the maximum and minimum values)—do they seem more realistic, less so, or no different? (For comparison, refer to the meteogram for Hanford, CA for the same day of the year.)

3. Repeat the previous model simulation (and address the same questions) with conduction/evaporation turned on.

4. Print a copy of the graph (on Page 2). Remember to specify that only Page 2 should be printed (not all 5 pages!).

5. Run the model to see what effect clouds have.

1. Reconfigure the model to include significant cloud cover.

2. Predict what you expect to happen to the daytime maximum temperature and the nighttime minimum temperature due to the cloud cover.

3. Run the model, and compare the model results to your prediction. How would you explain the results?

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