You likely often hear meteorologists use the phrases “above normal” or “below normal” when referring to forecast temperatures and precipitation. These phrases also apply to other meteorological phenomenon that you may have come across on social media, such as “heights” when referring to atmospheric pressure levels, snowfall, and even the strength of the Polar Vortex. But what does this word “normal” mean?
Sticking with temperatures and precipitation for simplicity, the word “normal” would better be stated as “average” when discussing weather data. This is because that “normal” is actually a 30-year moving average for conditions at a certain point in time, usually in the period of a day or a month. For example, an average high temperature for a day may be 60 degrees. This means that over the 30-year climatological period (we use 1980-2010 right now), 60 degrees was the average or mean high temperature on that exact day each year. Similarly, you may hear the phrase “the normal snowfall for the month of January is 14” in Random City, USA”. This means that in January, the snowfall amount in that particular city averaged out to be 14”.
However, the weather is rarely “normal” (have I used enough quotations yet?). It is expected that very few days at a specific location will feature average conditions. You’re more likely to see above or below this set value, constantly fluctuating. The climatological “normal” or average is then calculated based on these varied conditions over the 30-year period. Month-long data sets typically feature closer to average values than daily data since they cover a longer time period that accounts for these fluctuations.
Let’s look at an example below using yesterday’s high temperature data. The first map shows the “normal” or average high temperature for November 13th each year, based on climatological data from 1980-2010. The second map shows the high temperature anomaly for November 13, 2019, or difference in degrees above or below the 1980-2010 climate normal. You may see similar maps on the news in weather segments, or on social media for many other weather parameters, but all can generally be interpreted in this same way.
