Sunday's paper featured a fascinating article about the challenges of weather forecasting in the U.S. and included extensive interviews with Cliff Mass, meteorologist and professor of atmospheric sciences at the University of Washington in Seattle. 

Using the bungled forecast of the recent Hurricane Matthew as a starting point, Mass described the underlying weakness in severe-weather prediction: Flawed forecasting models used by the National Weather Service, National Oceanic and Atmospheric Administration, and the National Centers for Environmental Prediction; insufficient computing power; inability to generate "ensemble forecasts" by tweaking variables in forecast models; and innovative-resistant unions.

The article provides an excellent behind-the-scenes look at why forecasters get it wrong time and again--why forecasting is murky, obscure, "cloudy." If you check weather forecasts to decide whether or not to carry an umbrella or slather on the sunblock before you leave your house in the morning, you can get accurate information. Accurate longer-range forecasts are critical and often a matter of life or death when it comes to severe weather--hurricanes, tornadoes, wind storms--that requires emergency evacuations and a coordinated emergency-response. 

Interestingly, the clouds were given short shrift in Sunday's article. Only once did "clouds" appear. It was in the very last paragraph--where Cliff Mass is watching for a break in an unpredicted rainstorm so he can take a hike.

The clouds are still our best predictors of future weather conditions--only if you define "future" as an hour from now. At a Seattle Town Hall lecture several years ago, I recall Cliff Mass answering a question from the audience about how far ahead can forecasters predict the weather--a week? five days? three days? Mass responded: "That depends on how much you want to be deceived."

Which is to say that if we take comfort in "knowing" what the weather is going to be like several days ahead, we can buy into the long-range forecasts despite the fact they are often wrong. 

To read the full article in the New York Times Magazine, click here.