1. Outline for Today Brief Lecture on weather forecasting A comment on the upcoming Exam 4 and a bunch of other stuff

2. Theoretical Models and Accuracy As we discussed previously, one of the most useful ways of evaluating a theoretical model is to compare the predictions of the model against empirical data. Unfortunately, many industries do not provide you with information on the accuracy of their predictions. –how many people improve after taking a drug –how many people actually lose weight by eating Subway sandwiches –how many horoscopes accurately predict the future As a consequence, it is almost impossible for you, as a consumer, to evaluate the quality of the product.

3. In general, weather forecasters make their predictions based on either mathematical models/simulations of weather systems, past weather conditions, intuitive judgments based on the movement of current weather systems, or “all of the above”

4. Unfortunately, weather forecasters do not tell us—the consumers—how accurate their forecasts are. We don’t know what the “track record” is for any weather/news team. (Moreover, they don’t keep records of past forecasts on their websites, thereby preventing consumers from investigating the matter themselves.)

5. A scientific analysis of the accuracy of weather forecasting Students recorded the 7-day forecasts (on Sunday nights) for 1 week for a variety of sources –Weather.com –Fox News We compared the actual, end-of-the-day weather from an unrelated source: Weather Underground. This allows us to compare the predictions made by the different teams with the actual weather.

6. Actual temperatures observed, as recorded by Weather Underground, Champaign Nov 20 – Nov 26 Days Actual low temperature 1234567 20 40 60 80 Days Actual high temperature 1234567 20 40 60 80

7. DatePredicted HighObserved HighDiscrepancy (P-O) 11/20 554510 11/21 6263 11/22 6870-2 11/23 524111 11/24 524012 11/25 3241-9 11/26 33321 Average absolute discrepancy: 6.6 degrees ~ not too bad ~ Predictions made by weather.com

8. WGNTV Chicago | Mean Discrepancy = 4.3 WGN | Mean Discrepancy = 4.8 ABC 15 | Mean Discrepancy = 1.3 Predictied High Actual High 20304050607080 20 30 40 50 60 70 80 Predictied High Actual High 20304050607080 20 30 40 50 60 70 80 Predictied High Actual High 20304050607080 20 30 40 50 60 70 80

9. DateObservedPredicted 11/20 45 11/21 6345 11/22 7063 11/23 4170 11/24 4041 11/25 4140 11/26 3241 32 As an additional comparison, we can generate predictions in another way: based on “day before” temperature In this case, we’re assuming that the best bet for tomorrow’s temperature is today’s temperature. Average discrepancy: 10.8

10. What about broader weather conditions? Broader weather conditions –Sunny –Partly cloudy –Cloudy –Rain –Snow Accuracy in broad prediction (vs. day before method) –Weather.com42% (16%) –WGN-Chicago75% (57%) –WGN-Chicago57% (0%) –ABC15-Phoenix57% (17%)

11. Summary It appears that the various weather teams do a pretty good job in predicting the temperature –They were only off by approximately 4 – 7 degrees, on average. –Their ability to make accurate forecasts was lower for extended forecasts. In predicting weather conditions (e.g., rain, shine), the various stations were right 40% – 80% of the time. This was better than the accuracy obtained by predicting today’s weather from yesterday’s. Nonetheless, you wouldn’t know how good they are without doing the research yourself.