No, this is not our acronym for Personalized Outbound Proactive communication. It is the Probability of Precipitation. It struck me that all the weather channels use it, but does anyone really know what it means?
I used to explain it to people based upon the way I was told you could forecast the weather when I lived upstate in New York. The folklore was that cows stood up when it was going to be good weather and sat down when they thought it was going to rain. The answer was clear to me … count the number of cows sitting and divide by the total number of cows … simple enough.
But, I felt there had to be a more precise answer given all the weather forecasters now report it. So, what does “40 percent” mean? …will it rain 40 percent of the time? …will it rain over 40 percent of the area? The “Probability of Precipitation” (PoP) describes the chance of precipitation occurring at any point you select in the area.
How do forecasters arrive at this value? Mathematically, PoP is defined as follows:
PoP = C x A where “C” = the confidence that precipitation will occur somewhere in the forecast area, and where “A” = the percent of the area that will receive measurable precipitation, if it occurs at all.
So… in the case of the forecast above, if the forecaster knows precipitation is sure to occur ( confidence is 100% ), he/she is expressing how much of the area will receive measurable rain. ( PoP = “C” x “A” or “1” times “.4” which equals .4 or 40%.)
But, most of the time, the forecaster is expressing a combination of degree of confidence and areal coverage. If the forecaster is only 50% sure that precipitation will occur, and expects that, if it does occur, it will produce measurable rain over about 80 percent of the area, the PoP (chance of rain) is 40%. ( PoP = .5 x .8 which equals .4 or 40%. )
In either event, the correct way to interpret the forecast is: there is a 40 percent chance that rain will occur at any given point in the area.
So, after all that I am lead to the conclusion that you get the same answer as counting cows. What I find funny about this is that we all hear these statistics and then make decisions about things without ever asking how good this statistic is to predict what we care about.