Global Warming Activity and Worksheet (1)
pdf
keyboard_arrow_up
School
California State University, Fullerton *
*We aren’t endorsed by this school
Course
MISC
Subject
Geography
Date
Feb 20, 2024
Type
Pages
5
Uploaded by Vanessamunoz21
WEEK 14: GLOBAL WARMING ACTIVITY and WORKSHEET BACKGROUND Most of the solar radiation that reaches Earth is reflected by Earth’s surface. Greenhouse gases in the atmosphere capture much of this reradiated energy, preventing it from escaping back into space. This phenomenon, known as the greenhouse effect, is incredibly important—it keeps Earth warm enough to support living organisms. Without greenhouse gases and the greenhouse effect, Earth would not retain sufficient solar radiation, temperatures would be extremely cold, and the planet would be devoid of life. A major greenhouse gas in the atmosphere is carbon dioxide (others are methane, ozone, and water vapor). Fossil fuels (coal, oil, and natural gas), as well as living organisms, contain organic carbon. When fossil fuels and the wood of trees are burned for energy, the organic carbon is converted to CO
2
, which is released into the atmosphere. The excessive burning of fossil fuels and wood by humans during the past century has led to a significant increase in the amount of CO
2
present in the atmosphere. At the same time, deforestation by humans has removed huge expanses of trees that would otherwise absorb much of this excess CO
2
for use during photosynthesis. Higher quantities of CO
2
in the atmosphere means more reradiated energy is trapped by the atmosphere, causing Earth’s temperature to rise beyond normal. This phenomenon is known as global warming. The potential implications of global warming are severe. Greater temperatures will lead to melting polar ice. Melting polar ice will result in rising ocean levels. Rising ocean levels will submerge coastal areas. Elevated temperatures coupled with a decreased area in the interior of continents will alter global climate patterns, shifting the distribution of biomes as a result. For example, temperate grasslands, which are vital for agriculture, may be encroached upon or eliminated altogether as other biomes take over their space. During this lab you will analyze real data to determine whether or not temperatures have actually increased over the past century. These results can then be used to support or refute the occurrence of global warming and climate change. At your computer, open 1) a blank Microsoft Excel spreadsheet and 2) the website https://wrcc.dri.edu/cgi-bin/cliMAIN.pl?ca5115
. This website contains climate data from Downtown Los Angeles that have been consistently recorded over the past 100+ years. EXERCISE 1 – AVERAGE ANNUAL TEMPERATURES **If you aren’t familiar with Microsoft Excel, please view the tutorial video** Within the left column of the Downtown Los Angeles webpage, click on the link for average monthly temperatures. This can be found under the section headed “Period of Record.” From there, it is located under the “Temperature” category and “Monthly Temperature Listings.” Although the data go back to 1877, you will work with the period from 1916 to 2015 (exactly 100 years). Highlight all of the data (years, monthly averages, and annual averages) from 1916 to 2015. Copy and paste these data into Sheet 1 of your blank Excel file. You will now work with just the average annual temperatures (the last column of data). The data will be divided into four 25-year time periods (1916 to 1940, 1941 to 1965, 1966 to 1990, and 1991 to 2015). Highlight the average annual temperatures (the last column of data in Sheet 1) from 1916 to
1940. Copy and paste these data into the first column (column A) of Sheet 2 in your Excel file. Highlight the average annual temperatures for the remaining three time periods (1941 to 1965, 1966 to 1990, 1991 to 2015) and copy and paste the data into columns B, C, and D, respectively, of Sheet 2 in your Excel file. You should now have four columns of data, each with 25 values representing the average annual temperatures for the different time periods of the past century. As there are four samples, ANOVA is the appropriate statistical test to use to determine any potential differences in the data. Select Tools → Data Analysis → Anova: Single Factor
. When you are asked to input the range, highlight your data. Click OK. The output table (Sheet 3 of your Excel file) contains the means (and sample sizes—be sure each sample size equals 25) of the four 25-year time periods. The p-value comparing the time periods is also provided. 1. What are the means for each of the four time periods? 1916 – 1940 average: 63.8896 1941 – 1965 average: 64.2624 1966 – 1990 average: 66.2816 1991 – 2015 average: 66.1528 2. What is the p-value? -
The P-value is 2.94E-11 3. What does the p-value tell you? In other words, is there a significant difference in average annual temperature among the four time periods? Keep the null and alternative hypotheses in mind when answering these questions. The data shows a significant difference in average temperatures 4. If there is a significant difference, what is the difference? Use the means to answer this question. -There is a difference in average temps because it starts at 63.8896 (1916) and goes to 66.1528 (2015). the difference between an increase of 2.2632. EXERCISE 2 – MAXIMUM ANNUAL TEMPERATURES Repeat the procedures of Exercise 1 using the maximum annual temperatures from the Downtown Los Angeles web page rather than the average annual temperatures. These can be found under the section headed “Period of Record.” From there, they are located under the “Temperature” category and “Monthly Temperature Listings.” (Remember, though monthly data are provided, you will be working with the annual data.) Use the “Average Maximum” data rather than the “Extreme Maximum” data. Before beginning any highlighting, copying, or pasting, clear all of the average annual data from Sheets 1, 2, and 3 of your Excel file. 1. What are the means for each of the four time periods? 1916 – 1940 Average: 72.7968 1941 – 1965 Average: 73.6924 1966 – 1990 Average: 75.3652 1991 – 2015 Average: 75.31 2. What is the p-value? -The P-Value is 6.70362E-11 3. What does the p-value tell you? In other words, is there a significant difference in maximum annual temperature among the four time periods? -
There is a significant difference in maximum annual temperature among the four time periods
. 4. If there is a significant difference, what is the difference? Use the means to answer this question.
-there is a significant difference because it went from 72.7968 (1916) to 75.31 (2015) which is an increase by 2.5132 EXERCISE 3 – MINIMUM ANNUAL TEMPERATURES Repeat the procedures of Exercises 1 and 2 using the minimum annual temperatures from the Downtown Los Angeles webpage, rather than the average or maximum annual temperatures. These can be found under the section headed “Period of Record.” From there, they are located under the “Temperature” category and “Monthly Temperature Listings.” Use the “Average Minimum” data rather than the “Extreme Minimum” data. Before beginning any highlighting, copying, or pasting, clear all of the maximum annual data from Sheets 1, 2, and 3 of your Excel file. 1. What are the means for each of the four time periods? 1916 – 1940 Average: 54.9808 1941 – 1965 Average: 54.8308 1966 – 1990 Average: 57.198 1991 – 2015 Average: 56.9952 2. What is the p-value? -
The P-Value is 8.52E-11 3. What does the p-value tell you? In other words, is there a significant difference in minimum annual temperature among the four time periods? -There is a significant difference in minimum annual temperature among the four time periods. 4. If there is a significant difference, what is the difference? Use the means to answer this question. -There is a significant because it went from 54.9808 (1916) to 56.9952 which is an increase by 2.0144 EXERCISE 4: ANNUAL PRECIPITATION Repeat the procedures of Exercises 1, 2, and 3 using the annual precipitation totals from the Downtown Los Angeles webpage. These data can be found under the section headed “Period of Record.” From there, they are located under the “Precipitation” category and “Monthly Precipitation Listings.” Use the “Monthly Totals” rather than the “Daily Extremes.” (Remember, though monthly data are provided, you will be working with the annual data.) Before beginning any highlighting, copying, or pasting, clear all of the minimum annual temperature data from Sheets 1, 2, and 3 of your Excel file. 1. What are the means for each of the four time periods? 1916 – 1940 Average: 14.7304 1941 – 1965 Average: 13.4492 1966 – 1990 Average: 14.9804 1991 – 2015 Average: 14.4984 2. What is the p-value? -The P-Value is 0.870473821 3. What does the p-value tell you? In other words, is there a significant difference in annual precipitation among the four time periods? -
There is no significant difference in the annual precipitation among the four time periods. 4. If there is a significant difference, what is the difference? Use the means to answer this question. -
There is no significant difference, According to the means temp remains around 14 most of the time it only drops to around 13.4492 once.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
Data Tables ANOVA Avg Temp ANOVA Max Temp Groups Count
Sum
Average Variance Column 1
25
1819.92
72.7968
1.530272667 Column 2
25
1842.31
73.6924
1.630827333 Column 3
25
1884.13
75.3652
1.991834333 Column 4
25
1882.75
75.31
2.11715 SUMMARY Groups Count Sum Average Variance Column 1 25 1597.24 63.8896 1.56151 Column 2 25 1606.56 64.2624 1.52414 Column 3 25 1657.04 66.2816 1.81404 Column 4 25 1653.82 66.1528 1.89316 ANOVA Source of Variation SS df MS F P-value F crit Between Groups 116.5631 3 38.85435 22.87897 2.94E-11 2.699393 Within Groups 163.0326 96 1.698256 Total 279.5956 99 Source of Variation SS df MS F P-value F crit Between Groups 119.5806 3 39.86018 21.93107 6.7E-11 2.699393 Within Groups 174.482 96 1.817521 Total 294.0626 99
ANOVA min Temp
Groups Count
Sum
Average
Variance Column 1
25
1374.52
54.9808
1.705632667 Column 2
25
1370.77
54.8308
1.735249333 Column 3
25
1429.95
57.198
2.139675 Column 4
25
1424.88
56.9952
1.855026 ANOVA ANNUAL PRECIPITATION Groups Count
Sum Average
Variance Column 1
25
368.26 14.7304
30.01772067 Column 2
25
336.23 13.4492
49.94675767 Column 3
25
374.51 14.9804
61.56926233 Column 4
25
362.46 14.4984
49.71199733 Source of Variation SS df MS F P-value F crit Between Groups 120.7855 3 40.26182 21.659 8.52E-11 2.699393 Within Groups 178.454 96 1.858896 Total 299.2395 99 Source of Variation SS df MS F P-value F crit Between Groups 33.97197 3 11.32399 0.236847 0.870474 2.699393 Within Groups 4589.898 96 47.81143 Total 4623.87 99