GEO203: Exercise 12 Nov 2020 Module 12 and chapter 9 of textbook STUDENT WORKSHEET Instructions: Complete this entire exercise worksheet FIRST. Once you are done filling out this worksheet and are satisfied with your answers, go ahead and enter your answers into Exercise Submission on D2L. Once you begin the Exercise Submission, you will have 30 minutes to enter your answers and submit them for grading – so, be sure to complete this worksheet first. This exercise is worth 10 points total. 1. Briefly describe what the data assimilation process is and why it is done. (2 points) ANSWER: 2. Understand and explain the following tools in weather forecasting (2 points) Hint: This shows up as a match question in the submission. a. analysis b. atmospheric model c. numerical weather prediction d. prognostic chart 3. Why do we have a post-processing step in the process of forecasting weather? (0.5 point) a. To make forecasts look better in the app. b. To remove biases in the forecast. c. To make maps for future climate. d. To learn from the model run about the model. ANSWER: 4. Ensemble Forecast is the product of: (0.5 point) a. a same model run with different starting conditions. b. several different model runs with the same starting conditions. c. a same model run with the same starting conditions. d. several different model runs with different starting conditions. ANSWER: 1 The data assimilation process is comparing weather forecast for theprevious model with current observations, and then tweaking it toresemble that observation. It is done to create a base for the new weather forecast.page 247page 248248248GEO203: Exercise 12 Nov 2020 Module 12 and chapter 9 of textbook STUDENT WORKSHEET 5. Ensemble Forecast explains how: (0.5 point) a. small changes in the initial conditions result in different outcomes. b. small changes in the initial conditions result in the same outcomes. c. no changes in the initial conditions result in different outcomes. d. no changes in the initial conditions result in the same outcomes. ANSWER: 5. What does the forecasting model use as input for its next run? (0.5 point) a. available observations b. data and estimates collected by meteorologists c. a previous model runs d. observations assimilated in the previous model run ANSWER: 6. What is the model grid resolution? Explain why and how it is important for weather prediction models.(2 points) ANSWER: 7. Which two of the following do Ensemble Forecasts accomplish? (0.5 point) Note: Select two of the options below. a. mitigate risk b. address uncertainty c. overlook probability d. diminish differences ANSWER: 2 Model Grid Resolution comes from how far apart grid points are located from one another, and it includes horizontal and vertical resolution. It is important for weather prediction models because it is hard to resolve fine motions in large scale simulations and parameterizationcan connect those small/fine motions with larger scale motions.GEO203: Exercise 12 Nov 2020 Module 12 and chapter 9 of textbook STUDENT WORKSHEET 8. List some of the factors that affect the accuracy of weather forecasts. (1.5 points) ANSWER: This exercise was written by Jovanka Nikolic, GEO@MSU and edited by Beth Weisenborn, onGEO@MSU, and Lifeng Luo 3 uncertainty, small changes in initial conditions of the model run, or choice of different numerical scheme in the model, can result in completely different weather pattern for some time in the