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    Do We Really Understand What The Weather Forecast Predicts?

    By Margarita Nahapetyan

    Many people have no idea what they are told on television weather forecasts. According to the scientists from the University of Washington, only about half of the population understand what a forecast means when it predicts a 20 per cent chance of rain.

    Susan Joslyn, a UW cognitive psychologist and senior lecturer, said that many people think it means that it is going to rain 20 per cent of the day, or at any given moment, it is raining over 20 per cent of the area. In fact, it means that for the forecasted atmospheric conditions, it will rain 20 per cent of the time. Or, in simpler words, if you had 10 days of these exact weather conditions, the rain would reasonably be expected on two of the days.

    If you leave the probability of precipitation aside, most weather channels report just a single value such as the high temperature will be 53 degrees, for example. This is deterministic, said Joslyn, because it makes people think that forecasters are confident that the high temperature will be 53 degrees. But forecast is based on probability and 53 degrees could be just the middle of the range of possible temperatures, say 49 to 56 degrees, she explained.

    In order to find out whether people understand the more familiar probability of precipitation, a technique used in public forecasts since the late 1960s, Joslyn and her colleagues invited more than 450 Pacific Northwest college students to take part in their three experiments. If college educated students could not understand anything, then maybe there really is a problem with how meteorologists deliver the weather, the researchers said.

    In the first experiment, the forecasts of either a low or a high percentage chance of precipitation accompanied by a number of icons, have been evaluated. The icons were visual representations of the chance of rain. In addition to using a simplified cloud icon that is frequently shown in many TV and newspaper forecasts, the researchers also used pie charts and bar graphs to show the chances of rain. Each participant only saw one forecast and one icon, and was asked then to fill out a questionnaire.

    Two of the questions asked how much of the time it would rain and approximately in what part of the region it was more likely to rain today. The correct answer for both questions was "cannot tell from this forecast," and only 43 per cent of the participants correctly answered both of the questions. Those who did not get the right answer, were more likely to say that they would wear a hooded jacket or take an umbrella, actions suggesting that they were getting a deterministic forecast for precipitation.

    For the second experiment, the scientists used the same procedure with the exception that the students were asked open-ended, rather than questions with multiple choices, about similar weather forecasts. When asked to explain how they understood the probability of precipitation, just few of the students managed to do so and the percentage of those who got the right responds was almost the same as in the first experiment.

    In the experiment number three, the students were offered one of the three different forecasts. In the first one, the conventional chance of rain forecast appeared on the screen. In the second one, the chance of rain as well as the chance of no rain was presented. And finally, in the third forecast, the pie chart icon appeared beneath the chance of rain. This time 52 per cent of the participants knew that the forecast did not predict how much of the time and in which part of the region it would rain. Also, the chances of making a mistake were significantly lower if the phrase about a chance of no rain was mentioned in the forecast.

    The experts said that the last experiment provides the first evidence that percent of time and area misconceptions can be weakened by a statement that there is a chance it will not rain. She added that if people misunderstand a probabilistic forecast to mean that the rain, snow or storm will definitely happen - in some part of the area or for some pariod of the time - they are more likely to take precautions than if they understand that the event has a less-than-certain chance of occurring. If the precaution is just to carry an umbrella, there is not much to worry about. However, if it comes to evacuation before a hurricane or a tropical storm, closing schools before a snowstorm, and so on, then the consequences of statistical illiteracy are going to be much more serious.

    The findings are published in the Bulletin of the American Meteorological Society. The research was funded by the National Science Foundation.

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