Yesterday's weather forecast was thunderstorms. Rain would have been good for our parched lawns and shriveling gardens, but we had a company golf tournament scheduled. Several people became insanely discouraged, but the event coordinator said not to worry. "After all," he reminded us, "When was the last time that the weather service was right?" With no proven suggestions for improving the accuracy of weather forecasting, we rely on the old standby: Have the government spend more money to send up more weather satellites. Forecasters use this recorded data with high tech ground-based analysis equipment (more accurately called "gadgetry") to predict the weather.
WORK The weather forecast is hot and sticky. Humid air at a temperature of 100F and a pressure of 14.7 psia has a dew point of 80F. The partial pressure of the air in psia is most nearly:
See answer below.
Adapted from The Fundamentals of Engineering Examination, Eugene L. Boronow, Prentice Hall Press, 1986.
I don't mean to rain on the weather forecasters' parade, but seriously, if you had $5 to $10 billion worth of high tech equipment to support your engineering work, wouldn't you hope for something better than 50% accuracy? My boss can get pretty upset even when things go right; I can only imagine his response if we started achieving accurate results only half the time. Perhaps I'll get the engineering staff together to run a test to determine his response—I give us a 98% chance of correctly predicting the outcome.
It is interesting to consider that, with this failure rate, the forecast is still reported as part of the evening news—often the lead story. Can you imagine the response if the rest of the news were reported with the same accuracy?
But of course all this is just speculation—as engineers we need to deal with "the scientific approach." A sample weather forecast will identify some problems and errors that cause many forecasts to be all wet.
The Problem: You're in Omaha and need to prepare the next day's forecast. You have the following information available to conduct your analysis:
(NOTE: The following data was collected using the $5-$10 billion in weather gizmos orbiting Earth.)
Thunderstorm (T) is over Denver with 180 mile diameter and clouds to 82,000 feet
While there are hundreds of variables and dozens of weather models, we'll eliminate those factors that are really hard to measure and predict. This leaves us with a relatively simple forecast model to solve. This is apparently where most forecasters miss the boat—by eliminating the wrong variables. One recommendation is that they should flip a coin to decide which factors are relevant for any given day. At least this way they'll be using the correct factors 50% of the time and every-other-day's forecast will be correct.
Setting the forecast F = (T * W)sin d / (Df**H) - arc tan (Js + Tw)*D + (7*Bf)/3. The Bf factor provides a variable to account for increasing humidity the day following the large quantity of water flushed from Mile High stadium. If you're like most weather forecasters I've seen lately, you'll get the following result; "Partly cloudy with a chance of rain." Your forecast will be correct, about half the time.
On the other hand, you could get the same level of accuracy by simply flipping that coin—and the best part about this technique is that it doesn't require $10 billion in high-tech satellites and electronic gizmos.
Headwork answer: D