Physical Geography Laboratory Manual Temperature Change Appear Linear And Constant Which Frequently It Is Not Best Fit 1 (71.89 KiB) Viewed 37 times
Physical Geography Laboratory Manual Temperature Change Appear Linear And Constant Which Frequently It Is Not Best Fit 2 (71.89 KiB) Viewed 37 times
Physical Geography Laboratory Manual Temperature Change Appear Linear And Constant Which Frequently It Is Not Best Fit 3 (54.82 KiB) Viewed 37 times
Physical Geography Laboratory Manual temperature change appear linear and constant, which frequently it is not. Best-fit lines are often superimposed over the annual-and 5-year running averages, creating a useful composite "snapshot" with several levels of data generalization on the same chart (such as has been done in Figure 24-6). Similar techniques can be used when looking at long-term precipitation patterns, such as is shown for Bozeman and Tucson in Figure 24-7. The precipitation variability of a location describes the expected departure from average ("normal") precipitation in any given year. Precipi- tation variability is generally greater in dry climates than in humid ones. Average Annual Temperature (degrees F) 75 70 2 33 3 60 55 50 45 40 35 30 25 20 9061 Tucson Bozeman AMA 1910 1915 1920 1925 1930 1935 1940 1945 Nome 0561 S561 Tucson 1960 5961 1970 5/6L بیا سه با 1980 1985 1990 9661 2000 2005 2010 SLOZ 2019 Figure 24-6: Average annual temperature in Tucson, Arizona; Bozeman, Montana; and Nome, Alaska, from 1905 to 2019. Five-year moving average shown with thick trend line; "best fit shown with thin straight line. (Data sources: National Climate Data Center and Alaska Climate Research Center, University of Alaska, Fairbanks) Bozeman Figure 24-7: Annual precipitation in Tucson, Arizona, and Bozeman, Montana, from 1905 to 2019. Five-year moving average shown with thick trend line; "best-fit" line with thin straight line. (Data source: National Climate Data Center)
Physical Geography Laboratory Manual 7. 9. 10. 11. 12. (a) 13. (b) (a) (b) The following questions are based on Figure 24-8, charts showing annual precipitation in Tucson, Arizona, and Bozeman, Montana, from 1905 to 2019. Look at the temperatures from 1990 to 1992. Describe any possible effect of the 1991 eruption of Mount Pinatubo on the temperature record of these cities. (a) (b) ISORS Based on your observations in question 7a, how important were volcanic erup- tions in the overall temperature patterns of these cities over the last century? erup Tucson's population grew from about 7500 in the year 1900 to about 554,00 by 2020 (with about 1,000,000 in the surrounding county), and so a portion of the observed tempera- ture increase here may be due to the urban heat island effect. Using your answer in ques- tion 2 as a starting point, use the EPA's upper-end estimate of the UHI effect (5.4°F) to calculate the approximate amount of temperature increase that probably cannot be explained by urbanization. (Note: This answer is based on simplistic assumptions.) What cyclical factor helps explain the cool period in Nome between about 1945 and 1975? (a) What cyclical factor helps explain the warm period between about 1975 and 2005? (b) Using the best-fit line for reference, what generally happened to annual precipitation in these cities over the last century? Tucson: Bozeman: Using the 5-year moving average lines for reference, did all of the major wet and dry periods of the last century occur at the same time in Bozeman and Tucson? Which city exhibits the greatest precipitation variability? Why? "F Which city shows a greater increase in precipitation during the 1982-83 El Niño event? Why might this be the case? 174
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