Name:________________________________________________ Section:________________
part 1:
Temperature Conversions
1. Convert the following Fahrenheit temperatures to Celsius.
a. 32 °F = 0°C
b. 50 °F = 10°C
c. -22 °F = -30°C
d. 0 °F = -17.8°C
2. Convert the following Celsius temperatures to Fahrenheit.
a. 25 °C = 77°F
b. 0 °C = 32°F
c. 5 °C = 41°F
d. -10 °C = 14°F
TABLE 3.3 Monthly Temperature Data (°C)
for Three Midlatitude
|
MONTH |
|||||||||||||
|
|
J |
F |
M |
A |
M |
J |
J |
A |
S |
O |
N |
D |
|
|
|
|
||||||||||||
|
Mean
Temp. |
9.2 |
11.2 |
11.8 |
13.1 |
14.5 |
16.3 |
17.0 |
17.6 |
18.0 |
16.1 |
12.6 |
9.6 |
|
|
Max.
Temp. |
13.1 |
15.2 |
16.0 |
17.7 |
19.1 |
21.2 |
22.0 |
22.3 |
23.1 |
21.1 |
16.8 |
13.3 |
|
|
Min.
Temp. |
5.4 |
7.2 |
7.6 |
8.4 |
9.8 |
11.4 |
12.1 |
12.7 |
12.8 |
11.0 |
8.3 |
5.9 |
|
|
|
|
||||||||||||
|
Mean Temp. |
-0.9 |
0.8 |
6.9 |
13.1 |
18.3 |
23.6 |
26.7 |
26.1 |
21.3 |
14.6 |
6.8 |
0.9 |
|
|
Max. Temp. |
4.5 |
7.9 |
13.3 |
19.9 |
24.8 |
30.6 |
33.6 |
32.7 |
27.7 |
21.5 |
12.7 |
6.6 |
|
|
Min. Temp. |
-6.6 |
-4.0 |
0.6 |
7.0 |
12.6 |
18.1 |
20.8 |
19.9 |
15.1 |
8.3 |
0.9 |
-4.2 |
|
|
|
|
||||||||||||
|
Mean Temp. |
3.9 |
5.0 |
9.2 |
13.8 |
18.9 |
23.3 |
25.6 |
25.1 |
22.1 |
16.2 |
11.3 |
6.5 |
|
|
Max. Temp. |
8.5 |
9.8 |
14.3 |
19.3 |
24.0 |
28.2 |
30.2 |
29.5 |
26.4 |
20.8 |
16.2 |
11.2 |
|
|
Min. Temp. |
-0.6 |
0.1 |
4.0 |
8.3 |
13.7 |
18.4 |
21.1 |
20.7 |
17.8 |
11.6 |
6.5 |
1.8 |
|
Name:________________________________________________ Section:________________
part 2:
Continentality and Air Temperature
1. Plot the cities in Table 3.3 on the base map provided (Figure 3.2).
2. Compute the statistics listed below using the data in Table 3.3.
|
|
|
|
|
|
Average Annual Temperature* |
13.9 |
13.2 |
15.1 |
|
Maximum Range in Annual Temperature* |
17.7 |
40.2 |
30.8 |
|
Month of Highest Mean Temperature |
September
|
July
|
July
|
*See Table 3.2 for
definition
3. Plot the mean monthly temperatures for all three locations on the graph paper provided. Plot temperature on the Y-axis (vertical axis) according to the range of values in the temperature data. Plot months of the year on the X-axis (horizontal axis). Connect the points for each city as a smooth line, and label each line.

4. Based on the statistics computed in Question 2, describe the relationship between location and maximum range in temperature.
drier interior locations have
greater temperature range, whereas moister coastal sites have less temperature
range
5. Why does
San Francisco is on the windward side of a
continent (facing the Pacific Ocean); Norfolk is on the leeward side of a continent
(facing 3000 miles of land upwind)
6. Assuming that all three cities receive their highest total monthly insolation in June, how long (in months) is the seasonal lag at:
San
Francisco: 3 Wichita: 1 Norfolk: 1
7. a. Which
city has the longest seasonal lag in mean monthly temperature? San Francisco
b. Why? Because San Francisco is immediately downwind of the ocean-thus thermal inertia of moist oceanic air that is immediately upwind; i.e., oceans moderate temperature of overlying air by 1) energy diversion of heat for LE (heat used to keep air humid), and 2) thermal conduction between air and seawater
FIGURE 3.2

Name:________________________________________________ Section:________________
part 3:
Latitudinal Temperature Gradient in North AMERICA
1. Plot the cities in Table 3.4 on the base map provided (Figure 3.2).
2. Plot the January and July average temperatures listed in Table 3.4 against latitude on the graphs provided.
3. Draw a straight line through each temperature graph that best represents the trend of the plotted points. Try to minimize the vertical distance between each point and the “best fit” line.
4. Calculate the January (winter) and July (summer) temperature gradients in degrees Celsius per degree of latitude over the latitudinal range of these cities. Show your work.
a. January Gradient = -18.6-14.7/49.9-25.7 = - 1.38oC/1oLatitude
b. July Gradient = 19.6-27.7/49.9-25.7 = - 0.33oC/1o Latitude
5. Is
the temperature gradient larger or smaller during the winter? larger
6. a. Compute the difference between July average and January average temperatures for each city and enter the value in the space provided in Table 3.4.
b. Describe the relationship between the temperature range and location between 25° N and 50° N latitude.
increased temperature range at
increased latitude (+1.88oF/1oLatitude)
TABLE 3.4 Average
January and July Temperatures for Selected
Latitude Avg. Temperature (°C) Temperature
Ft. Worth TX 32.8 6.3 29.6 23.3
San
Antonio, TX 29.5 9.6 29.4 19.8
Monterrey, Mexico 25.7 14.7 27.7
13
7.
a. Predicted Average January Temperature: ((34-25.7)-1.38)+14.7 = 3.25oC
b. Predicted Average July Temperature: ((34-25.7)-0.33)+27.7 = 25.0oC
c. Predicted temperature range: 25.0 oC -3.25 oC = 21.75
d. Plot
e. How do the predicted values compare to the actual values for Hot Springs?
slightly low for January and
July temperatures; slightly low estimate for range
Actual Average January Temperature: 4°C
Actual Average July Temperature: 27.6°C
Actual temperature range: 23.6°C
8. Portland,
OR is located at approximately 45o N while Hot Springs is located at
34° N. Given your answer to question 6b, would you expect
smaller, as
9. Use the graphs you constructed to estimate the average January and July temperatures at Portland 45o N.
a. Predicted Average January Temperature: ((45-25.7)-1.38)+14.7 = -11.9oC
b. Predicted Average July Temperature: ((45-25.7)-0.33)+27.7 = 21.3oC
c. Predicted temperature range: 21.3 - -11.9 = 33.2
d. Plot
e. How do the predicted values compare to the actual values for Portland below?
Predicted 16o
too low for January; Predicted 2o too high for July;
predicted double the actual range
Actual Average January Temperature: 3.9°C
Actual Average July Temperature: 19.6°C
Actual temperature range: 15.7°C
10. a. Which city, Portland or Hot Springs, did your graph best predict the average temperatures and temperature range for?
Hot Springs
b. Why? (Hint: Consider where Portland is located and the location of the data used to construct your graphs.)
Data to determine gradient came from interior; Portland is coastal.
