The Washington Post's "The coronavirus pandemic and loss of aircraft data are taking a toll on weather forecasting"

The Washington Post, and numerous other media outlets, recent wrote about an unintended consequence of COVID-19 and the sudden drop off in commercial flights: Fewer data points for weather forecasts (PDF).

Due to the coronavirus, commercial flights are down:

How does this affect weather forecasts? Data is constantly being collected from commercial flights, and that data is used to predict future weather:

Ways to use in class:

A conceptual example of multivariate modeling: Windspeed...temperature...humidity...lots of different data points, from lots of different elevations, come into play when making our best guess at the weather. This is a non-math, abstract way to discuss such multivariate models.

A conceptual example of effect sizes/real-world effects: In the article, they clearly spell out the magnitude of the data loss. That is pretty easy to track since we can count the number of flights that have been canceled. More complex is determining the effect size of this data loss. 

Data in everyday life: Per my introduction, we use weather forecasts for many different reasons. 

Control groups and alternate means of data collection: The article also contains excerpts of an interview data scientists who are trying to understand the magnitude of the issue AND solve it. Specifically, they stated that it is difficult to gauge the overall impact of the lack of data because they don't have a true control group (a nice example for RM) AND that they have come up with an alternative way of collecting high-altitude data: Good old weather balloons. This a good example of how a bit of expertise and creative thinking can be used to solve problems.