[PRA0003] EESA01H3 LAB #2 Weather and Climate Data

Lab 2 - Weather and Climate Data University of Toronto Assignment: Lab - Weather and Climate Data TA: Gloria Hui-Yu Gao Start Date: October 19th, 2023 Due Date: October 26th, 2023 1

Question 1 . Using the weather data from the UTSC weather station, A) calculate average monthly values for June and July separately, for all weather variables where the average is appropriate. Then B) calculate total monthly values for June and July separately, for any weather variables where a summed value is appropriate. Use the appropriate Excel functions. (9 marks) Average & Total Values for the weather in June Average Temp. ( ℃ ) Average RH (%) Average BP (kPa) Total Rain (mm) Average Wind Speed (kph) Average Wind Direction (°) Average Solar Irradiance (W/m^2) Total Solar Irradiance (kJm^2) June 18.095 77.336 101.222 2.052 6.118 139.671 245.265 26489.09 Average & Total Values for the weather in July Average Temp. ( ℃ ) Average RH (%) Average BP (kPa) Total Rain (mm) Average Wind Speed (kph) Average Wind Direction (°) Average Solar Irradiance (W/m^2) Total Solar Irradiance (kJm^2) July 23.2996 81.557 101.365 1.771 5.122 164.058 247.614 27633.71 Question 2 . Use Equation 1 above to calculate the dew point for every day in both June and July. Use this information to calculate the mean dew point for each month. Next, use Equation 2 above to calculate the vapor pressure for every day in both June and July. From there, use Equation 3 above to calculate the humidex for every day in both June and July. Finally, calculate the mean humidex for each month. (10 marks Tdew = Tair [100-77.336]/5 =4.5328 Tdew= Tair [100-81.557]/5 =3.6886 e=6.11x10 (7.5xTdew)/237.3 +Tdew) 2

Daily Average Wind Direction for June Daily Average Direction for July 4

Question 4. Make a scatterplot that shows the relationship between daily temperature and daily solar irradiance. Be mindful of which variables should be on the independent and dependent axes. Add a linear trendline to the data and include both an equation and r2 value for the trendline. Comment on the observed relationship in terms of its strength, and why you would or would not expect a strong statistical relationship (10 marks). The connection between June's daily temperatures and solar irradiance can be seen in the scatterplot above. Equation y= 12.815x + 13.37 and coefficient of determination R2=0.2338 represent the linear regression line. The average temperature (x-axis) is the independent variable, while the average solar irradiance (y-axis) is the dependent variable. With a weak linear relationship, the data points form a positive linear trendline. It is possible to define the link between temperature and solar irradiation as weak because the coefficient of determination is close to 0. The points also deviate significantly from the linear trendline. It suggests that there is a weak strength in the relationship. Question 5. In less than 10 lines, explain how a vane anemometer works. You will have to do some research and reference your sources using APA style. What two meteorological variables does this instrument measure (6 marks) A “Vane anemometer” is a device that uses 3 cups on a pole, to measure the wind speed. Most typically, Vane anemometers are placed on roofs, or sheds of buildings, or peoples homes. It works by taking air/wind in, as this happens, the top of the anemometer turns, creating a measurement of wind speed. The 2 variables that can be measured by a vane anemometer, is the wind's velocity, and volumetric flow. 5