Geo Lab 1 Energy and Climate Change Winter 2023.docx (1)

GEOS 102 Our Changing Environment: Climate and Ecosystems Lab 1 Lab 1 - Energy and Climate Change Objectives: ● Understand all components in the surface radiation budget ● Identify environmental variables that affect components in the radiation budget ● Calculate net radiation and albedo ● Explain annual patterns and trends in atmospheric CO 2 concentrations ● Explain the concept of a carbon footprint and the factors that contribute to it Total marks: 26 Introduction Read the lab carefully. Some of the material we haven't covered in class yet - but we will soon. The purpose of this first week is to "get your feet wet" and get used to working with calculations and help you learn to use Excel. Your textbook (chapters are listed under the Course Schedule on Canvas) and lectures will provide the required background. The Lab assignment will be a file uploaded to Canvas. You can cut and paste your answers into a separate document from this sheet. Provide answers to TWO decimal places where appropriate (While you may use any spreadsheet program (Microsoft Excel, Open Office, Google Sheets ), we recommend Excel, free to all UBC students via the student software site. PART 1: Daily Radiation Budget [12 marks] We will be using the SURFRAD network website to access radiation data from 2 monitoring sites in the United States. The network provides long-term, continuous measurements of the surface radiation budget for multiple sites, and available data includes incoming and reflected shortwave radiation, incoming and outgoing longwave radiation and net radiation. This data can be downloaded and used to inform climate research. Also available on the website are photographs of the sites, which can be used to gain insight on radiation budgets. Firstly, follow the instructions in the document: Accessing the SURFRAD network . This document, will show you how to obtain the data and graphs needed to complete the following questions. Note: For date selection in step 3, choose the date following date which applies to you (based on the last 2 digits of your student number): 0-25 : June 01 2019 26-50 : July 05 2018 51-75 : May 28 2018 76-99 : August 05 2019 1

GEOS 102 Our Changing Environment: Climate and Ecosystems Lab 1 Fort Peck, MT Q1. ( upload a screenshot of the graph, acquired by following the above instructions (Accessing the SURFRAD dataset), to canvas ) Answer the following questions for the graph of Fort Peck, MT: Q2. Name 2 variables that could affect the value of SW ↓ and SW ↑. [2] - Cloud cover. The density of clouds as well as their presence in the atmosphere will impact the amount of incoming solar radiation which reaches the earths surface & reflected back into space. - Albedo of the surface. Albedo is the reflectivity of a surface, hence various surfaces will reflect a varying proportion of incoming solar radiation. For example a white surface such as fresh snow will reflect a larger proportion and thus have a higher SW ↑ Q3. Why do SW ↓ and SW ↑ have similar (if not the same) values between 3 and 11 UTC? [1] - Between 3 and 11UTC the time is 20:00 to 04:00 which is a time period where temperatures tend to be constant and low as theres less energy as it’s night. Q4. Why is LW ↑ greater than LW ↓? [1] 2

GEOS 102 Our Changing Environment: Climate and Ecosystems Lab 1 Q7. State 2 differences between the two sites and suggest some reasons for these differences in terms of climate and environment. [2] - The first difference is that both radiation values ( downwelling infrared, upwelling infrared, downwelling solar and upwelling solar) are greater in Desert Rock, Nevada compared to Fort peck. This is likely due to various physical/environmental features present in these areas, influencing the climate. Desert areas have less water vapor in the air, hence resulting in less cloud coverage. Furthermore the increased air temperature affects dew points which is the reason for the lack of water vapor condensing, ultimately causing Desert Rock to have higher rates of radiation. - Secondly the other difference evident when comparing graphs is that the total net radiation is higher at Fort Peck, compared to Desert Rock. This is resultant due to insolation and outgoing radiation values both being high at Desert Rock, Nevada, thus leading to a lower total net radiation value. At Fort Peck it is evidently clear that the infrared radiation is higher then at Desert Rock, likely due to higher vegetation coverage and cloud coverage, ultimately leading to a greater total net radiation. Calculating albedo and net radiation (see more in the endnotes) 1. Download the Fort Peck radiation data spreadsheet containing radiation data for a day in July in Fort Peck. Fill in the columns for albedo and net radiation using the following equations: Net radiation (1) (𝑄 *) = (?↓ + ?↓) – (?↑ + ?↑) = (?↓ − ?↑) + (?↓ − ?↑) The albedo or reflectivity (α) of a surface refers to the proportion of incident short-wave radiation which is reflected by the surface: Albedo ( α) = (2 ) ?↑ ?↓ Q8. At what time of day does the maximum Q* occur? [1] - The max value for the Net Radiation is 670.3 at 1:01:59 PM Q9. What is the value of albedo at 0900 and 1700 hours? Express answers in percentages (e.g. 10% not 0.1). Explain how albedo changes between these hours. [3] - At 09:00 the albedo is 19.72% - At 17:00 the albedo is 18.81% - The spreadsheet displays how the albedo at Fort Peck falls slightly by 0.91% between 9AM and 5PM. This decrease in albedo can be justified by the decrease in incoming solar radiation as a result of an increasing zenith angle, which therefore increases the area of diffusion. This moreover correlates to the decrease in downwelling and upwelling radiation, regardless of the possibility of other variables such as cloud coverage influencing these values. 4

GEOS 102 Our Changing Environment: Climate and Ecosystems Lab 1 PART 2: CO 2 , Temperature, and Climate Change [12 marks] There is a growing body of evidence and data on the issue of climate change. Some of this is outlined in Chapter 7 of your textbook. You will need to refer to the endnotes at the end of this document for help with some of the questions. Examine the updated version at the end of this document (in endnotes; Fig. 2), downloaded from the NOAA web-site: https://www.esrl.noaa.gov/gmd/ccgg/trends/ . This famous graph is often referred to as the “Keeling Curve” after the name of first author who originally published the data. It represents atmospheric CO 2 concentration atop Mauna Loa, Hawaii (in parts per million, ppm). Q10. List 4 processes/activities that are responsible for the peaks and troughs observed in the keeling curve (2 for each). [1] - Throughs are resultant of a increase in CO2 concentrations in the atmosphere leading to peaks. Activities which could lead to troughs would be increased calcification, photosynthesis and an increase in the amount of carbon settling in carbon sinks such as the ocean. Peaks on the other hand are resultant from deforestation, burning fossil fuels and rapid industrial and farming expansion. Click on the “data” tab in the NOAA web-site listed above to get the files with the annual mean data (“Mauna Loa CO 2 annual mean data” in ppm or parts per million) and the annual growth rate data (“Mauna Loa CO 2 annual mean growth rates”; represents change in CO 2 from one year to the next, reported as ppm/year). Click on ‘CSV’ next to the file name to download. Familiarize yourself with these two tables. Q11. Find the most recent annual mean atmospheric CO 2 concentration at Mauna Loa (i.e., for 2019). By what percent has the atmospheric CO 2 concentration increased from the pre-industrial value of 280 ppm? [1] - For the most recent annual mean atmospheric CO2 concentration recorded would be for 2022, which presents a value of 418.53ppm. - Finding the difference between the most recent mean (2022) and the value of 280ppm we get a result of an increase by 138.53ppm or by 49.475% Q12. Watch the film at: https://www.esrl.noaa.gov/gmd/ccgg/trends/history.html . Focusing on the data shown on the left figure (snapshot, below) from about 0-2 minutes of the film, explain what is being portrayed. Also: Can you explain why there is so much more variation in values at latitudes 30°N and higher than those south of the equator? See clock to the right of the graph for year and month – you may need to play the film a couple of times to become familiar with the trends) [2] - What is being portrayed? The video portrays CO2 concentrations in various latitudes and at different times. The graphical data allows single point data to be compared with other data at the same place over a chosen time period. By watching the video is comprehensible that the CO2 concentration is fluctuating over time however the mean value is positively increasing over time. - Theres more variation in values at latitudes 30°N and higher than those south of the equator due to the photosynthetic activity of plants and therefore areas with more plants will experience higher fluctuations. At latitudes of 30°N and higher there is a larger concentration 5

GEOS 102 Our Changing Environment: Climate and Ecosystems Lab 1 Q13. Examination of data used to compute the climate change index: Download the dataset in the climate change index spreadsheet . This table presents the following data for the time period 2006-2019: 1) Global average temperature, 2) Atmospheric CO 2 concentration, 3) Global Mean Sea Level (mm height with reference to a fixed datum), 4) Average Arctic Sea Ice Extent. These variables are critical indicators of human impact on climate and affected systems. The variables are used to compute the Climate Change Index, a single number calculated annually that can be used to show accumulated change over time. Here, we will ignore the index and examine the data it derives from. Open the Excel spreadsheet. Create time-series (line) graphs to illustrate the variables. Because the variables are measured on different numerical scales, I suggest you either construct: i) four separate line graphs, one for each variable, or ii) three graphs, the first with CO 2 ; the second with Global Mean Sea Level, and the third with Global Avg. Temp. and Average. Arctic Sea Ice Extent. Your TA will help you with the “line graph” feature in Excel. For general graphing instructions, refer to the handout on Constructing Line Graphs (posted in Canvas) or consult your TA in lab. Note that: if you choose option ii), you will have a secondary y-axis on the last graph: one, on the left for the first variable (e.g., Global avg. temp.), the second on the right, for the other variable, e.g., Average. Arctic sea ice extent (e.g., see Fig. 1 below). Remember, time is always your x-axis variable in a time-series graph. The following Excel help tutorial will help with adding secondary y-axes: https://www.youtube.com/watch?v=P-mB4I16GC8 1 st Y-axis 2 nd Y-axis Fig 1: Example of graph with secondary y-axis. Accessed from: https://www.youtube.com/watch?v=viD-WVEK_s0 Present your graphs together (e.g., side by side; one on top of the other) so you can easily compare trends among the variables. Be sure to include a title, axis labels indicating units of measurement and, if you have more than one series per graph, a legend to indicate which is which. Place the graphs (copy and paste each) into a Word document and convert to pdf. If you are unable to convert to pdf, you may submit your Word doc. Follow the prompts (click ‘browse computer’, select your file, etc.) to attach to the electronic submission in Canvas. [3] 7

GEOS 102 Our Changing Environment: Climate and Ecosystems Lab 1 8

GEOS 102 Our Changing Environment: Climate and Ecosystems Lab 1 To do this, access one of the leading carbon calculators such as the Cool Climate Network’s: https://coolclimate.berkeley.edu/calculator , (see Appendix “Using the Calculator”) or Conservation International’s: https://www.conservation.org/act/carboncalculator/calculate-your-carbon-footprint.aspx#/ Note: Both of these tools are American. You may need to mentally convert your travel into US units (miles from kilometres) or other units. You may simply estimate – you want rough but representative numbers. Also: Please visit the site as soon as you can – it may become overloaded as students access it, and you may need to return to it at a later time. Q17. Carbon footprint: [1] - 10.65 metric tonnes of CO 2 Q18. Justify your answer by providing details of, e.g., indicate those elements of your lifestyle that are particularly carbon-hungry; those that are relatively conservative of energy/carbon, etc. You will not be judged for this. Some of us have taken more than our share of international flights; or drive SUV’s! [1] - The reason for this higher result is likely due to my diet, and travels. As I live in downtown vancouver I take the bus 15 km each way everyday. I likewise work as a chef at a steakhouse, hence influencing my dietary intake where I consume more meat. Furthermore, as I am a international student who has family in canada I used to travel from the netherlands to canada every summer, flying over 500 km. These are the main reasons why my carbon footprint is higher then the global average. Through travel, CO2 emissions are obvious as they physically emmit carbon into the atmosphere however having a meat based diet indirectly causes higher CO2 emissions through embedded emissions. REFERENCES Arbogast et al. 2018 (course text) Or: either of the following references in lieu: Christopherson, et al. 2015. Geosystems, (any Canadian Edition), Pearson. Strahler and Archibold 2011 Physical Geography: Science and Systems of the Human Environment (any edition) . Hoboken, NJ: John Wiley & Sons Inc. 10

GEOS 102 Our Changing Environment: Climate and Ecosystems Lab 1 Endnotes Part 1: The surplus or deficit of radiant energy that may exist at a given place or time can be obtained by calculating the net radiation budget – the difference between total incoming and total outgoing radiation. The terms short-wave and long-wave radiation refers to radiation from the sun (short-wave) and radiation from the Earth and atmosphere (long-waves). The net radiation, Q*, may be positive, negative, or zero. When the surface is gaining more radiant energy than it is losing, Q* is positive, indicating the potential for warming. A negative Q* implies the surface is losing energy, indicating the potential for cooling. Q* may be determined from the radiation balance equation: Q* = (K↓ + L↓) – (L↑ + K↑) = (K↓ - K↑) + (L↓ - L↑), where K↓ = incoming short-wave radiation from the Sun K↑ = short-wave radiation reflected by the surface L↓ = incoming long-wave radiation emitted by the atmosphere L↑ = out-going long-wave radiation emitted by the surface The albedo or reflectivity (α) of a surface refers to the proportion of incident short-wave radiation which is reflected by the surface: α = K↑/ K↓ Part 2: Keeling curve: https://www.esrl.noaa.gov/gmd/ccgg/trends/ , accessed August 07, 2020. Fig 2. Keeling curve. Accessed August 2020 11

GEOS 102 Our Changing Environment: Climate and Ecosystems Lab 1 Part 3: Ecological footprint concept: This was derived in the 1980’s by UBC professor Dr. William Rees to characterize the impact on environment that a single person or entity makes. The World Wildlife Fund define it as simply “the amount of the environment necessary to produce the goods and services necessary to support a particular lifestyle” ( http://wwf.panda.org/ ). Using the calculator ● Change Miles to KM in settings ○ Click on settings (this can be found on the right hand of the site) ○ Click “Switch to metric units” underneath the Assumption Values box ● Hold on to your results! ○ The browser will save your data, however there’s potential for your results to get lost. We recommend taking a screen shot or documenting them manually ○ Your initial results will be important to compare with yur final results and be used for our final discussion ● Necessary details for the calculation: ○ Heating oil and other fuels…$0.13 per kWh ○ Natural gas…………………$0.10 per kWh 13