McLucas B Lab3 labreport.docx

GHY 1011 – Global Climate Change Clouds, Temperature, and Humidity Name: ______Brandon McLucas__________________________________ When complete, rename this file using this convention: McLucas B Lab3 labreport.docx before submitting it in the appropriate portal on the lab class ASUlearn page) Place your answers in the appropriate spaces provided. Part I: Cloud Observations Step outside and observe the daytime sky on a day that has some clouds. 1. Record the date, time, and place of your observations. (1 point) Oct 3 at 10:35 AM and I am at my home in Andrews Nc. 2. Estimate and record the percentage of the sky that is covered by clouds that are not contrails. (1 point) The number of clouds that cover the sky is 10% 3. Using Table A, record the cloud cover classification that best matches what you see (e.g., “isolated”). (1 point) Cirrostratus 4. Using the NASA GLOBE cloud chart (available at: https://www.globe.gov/documents/348614/24331082/GLOBE+Cloud+Chart or as a .pdf file on the ASUlearn page), observe and record the cloud type(s) and estimated altitude(s) (above sea level). (2 points) The Cirrostratus clouds are around 6000 m in the sky and they are close to being transparent. There is only 10% of clouds in the sky. 5. Using Table A, record which contrail classification best matches how much of the sky is covered by contrails (if contrails were present) (1 point) Theres no contrails in the sky. 6. Using hand-held Kestrel weather stations, students in a prior semester took 10 measurements over a 10-minute period of temperature, relative humidity, wet bulb temperature, and dew point temperature for a grassy surface on campus, and

recorded these observations in Table 1. Calculate the average values and include them in the Table 1. (4 points) presented in table 1. 7. Calculate the range (high minus low) for each variable (temperature, RH, wet bulb temp., and DPT) and include them in Table 1? (4 points) 8. Why do you think there was so much variability over a short time period? Provide an answer in the form of a complete sentence (2 points) Theres a lot of variability because the temperature rises from 2:58 to 3:07 rapidly and this could be the cause of cloud movement and the type of clouds that are in the sky at certain altitudes. 9. Hypothesize on the amount of radiational cooling that occurred on the evening of June 7-8, 2022, by predicting hourly values of temperature and relative humidity from 7 PM to 7 AM (thus, your hypotheses are simply your hourly predictions for temperature and relative humidity during the observational period – remember that temperature and relative humidity are inversely related!). Place your hourly numerical predictions in Table 2 (“Predicted”). 10. Summarize and discuss the logic and rationale for your predictions. (5 points) The reason why I but these predictions is because I’ve looked at the weather a lot on a normal day and the temperature shouldn’t spike too high and too low. And the humidity shouldn’t be too bad if it hasn’t rained in a bit and Boone is in the mountains so humidity shouldn’t spike too high or too low as well. 11. Test your hypotheses by filling in Table 2 with the actual hourly values of temperature and relative humidity. (12 points) done. 12. Discuss your findings. How well did your predicted values of temperature and humidity match the actual values? (4 points) My predictions of temperature were off by a lot, but my predictions on humidity was close to the actual humidity. 13. Relative to Q10, why were your predictions good (or bad) - discuss? (4 points) My predictions were bad for temperature because I thought it was during the day, but the temperatures were temperatures for the night so that one is on me, but I did good with humidity I just thought that the area we are in has low humidity, so I just stayed around the 50s and 60s.

Table 2. Predictions-night of June 7-8, 2022 Predicted Actual Time Temperate, o F Rel. Humidity, % Temperature, o F Rel. Humidity, % 7:00 PM 73 58% 73 58% 8:00 PM 74.5 60% 68 59% 9:00 PM 74.8 60% 68 60% 10:00 PM 75.2 62% 64 63% 11:00 PM 75.6 62% 65 61% 12:00 AM 77.4 65% 62 61% 1:00 AM 79.3 68% 60 60% 2:00 AM 84.5 72% 60 60% 3:00 AM 86.3 78% 60 60% 4:00 AM 83.2 73% 58 58% 5:00 AM 78.1 67% 59 59%

6:00 AM 75.2 62% 59 59% 7:00 AM 72.3 59% 61 61