What Does Percentage of Precip Actually Mean? Part 1

What does the Percentage of Precipitation actually mean on a weather forecast?  

Does it mean we'll receive rain 40% of the time, 40% of the area?  If there’s a 30% chance that it will rain, then is there a 70% chance that it won’t rain?

Or is it something else entirely?

It's one of the most commonly asked questions of meteorologists.  Everyone seems to have their own definition. Is there a standard?  

The technical definition below is taken from the NWS:  (Link here)

"the probability of precipitation is simply a statistical probability of 0.01" inch of more of precipitation at a given area in the given forecast area in the time period specified"

This is calculated by multiplying two numbers:  Forecaster confidence (Percentage) and Areal Coverage.  So if the forecaster is very confident (90%) that rain will develop but only 30% of the area in question will receive the rain, then the final precipitation probability would be: 

Percentage of Precip. = 0.90 x  0.30

Percentage of Precip =  0.27  Rounded up to 0.30 or 30%

Got it?  😮

Here's what it doesn't mean:   "If there’s a 30% chance that it will rain, then there a 70% chance that it won’t rain."

It also doesn't factor in:  How long it will rain,  How much precipitation,  Intensity of the rain/precipitation  

Summary from the NWS

This can get confusing. Plus it's hard to visualize for the lay person nor is it practical.  

The other more non-technical way is defining precipitation percentages as the amount of the region--overall coverage--that will see precipitation over a certain time frame.  This is a great benefit to an on-air meteorologist who needs to cover dozens of counties over several minutes. A generalized map can work IF the weather event is more large scale like widespread showers with no breaks.

January 2019 winter storm

The image below gives the higher likelihood (brighter green colors), time of precipitation and other useful information about duration and intensity.  All useable and relatable information for the viewer.

The problem with this generalization arises when precipitation is heavy in one location and/or spotty in another. The forecast details become highly localized. Here is an example from our first snow on November 15, 2021. The shoreline was pounded with heavy lake effect snow.  Inland hardly any precipitation with sunshine. One number doesn't work in this case.

A generalized map in this case becomes unrelatable because most viewers don't necessarily care what's happening 50 miles away unless it impacts their lives in some way.  Attempting to give a percentage for each location taking into account the numerous dry periods and pockets is just not practical for the on-air meteorologist. The conditions in this example change too fast. 

Here's another example of a line of storms moving across northern Ohio at 7:21PM on October 23, 2020. Viewers impacted by the storms in Lorain county or near Mansfield would interpret the forecast as 100% chance of rain.  Yet people in Akron or Canton would guess 0% given the lack of rain at this point. Yet another example of how ONE PERCENTAGE NUMBER doesn't even begin to tell the complete weather forecast story.

How about the extended forecast? The 5,7 or 8-day forecast that you see on television or a weather app utilizes a percentage. It's been a staple and weather forecasts for a very long time. But often times they lack context and qualifying information similar to the graphic above to make the number useful. We at WJW FOX 8 add some basic text but that too has limitations. 

 

On air meteorologists have time against them. They have a small amount of time (usually under 2 minutes) to deliver quality, usable information to the viewer. They need to do this in such a way that addresses as much of the viewing area as possible. For the Cleveland market it encompasses 25 counties and roughly 8000 square miles. 

Unfortunately, one percentage number doesn't do the forecast justice.  It lacks context. It lacks specificity.  So how do we get around this? What's the solution?

Unfortunately there is no cut and dry answer.  For me, I believe the beginning of any workable answer lies first in basic psychology and perception. That is we must always remember that most people visualize the weather through their own spatial filter.  They visualize the weather conditions or forecast through what we can see literally in our own backyard, where we work or live. Their weather universe is what we can see. If that percentage is describing something outside of their event horizon, it's irrelevant. How many times have you looked out the window, saw the weather, made an assessment and determined your daily activities only based upon that?  We all do it.  

For on-air meteorologists in my view, we need to take this viewer centered, subjective view of the weather into account.  How do we do this?  

I have my own subjective definition of what precipitation percentage defines. For me it's a combination of three elements:  I call it the "THE THREE C's".

CONFIDENCE

COVERAGE

CRITICAL

CONFIDENCE, as mentioned earlier is subjective with each forecaster. This is based upon the forecasters expert analysis of the situation. On the extended forecast I rarely put a 50% or higher further out than 5 days because the confidence is so low in most instances (see graphic below)

COVERAGE is what portion and how much of the viewing area will receive precipitation. Pretty self explanatory.  See earlier image.

CRITICAL is accessing what elements are the most important and how they impact the viewer. For me this is the meat and potatoes of the entire forecast!  

How intense is the precipitation?  How long and how hard will it rain or snow?  When is this occurring?  How will this impact the viewer? How many will be impacted?  I factor these into the overall weather setup and weight them.  Is this occurring for the first time in the season or has this been a reoccurring event? 

For example if the rain will be light and last only a brief time at midnight where it impacts only a small amount of people then I weight the precipitation event less than if it was going to downpour over an hour at rush hour.  If we anticipate a foot of heavy wet snow to fall as kids head to school in November, this will be weighted more significantly than if it was an inch of snow in February (public perception).  Some of what's Critical as defined here is quantifiable.  Some are not. 

I take into account as much information from the "THREE Cs" as possible and come up with a number in the form of a percentage that best fits the weather scenario.  It's taken me years to learn how to do this.  I've trained myself to complete this exercise each day almost subconsciously as I assess the weather forecast specifics.  

So on my graphics the percentage you see is my best interpretation of the "THREE Cs"

Example from December 19, 2022