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Showing posts with the label weather

Annual snow fall moderates the relationship between daily snow fall and the likelihood of canceling school

Moderation isn't one of those things that we typically teach in Intro Stats. But it is a statistical tool your advanced undergraduates will likely encounter in an upper-level course. I'm not going to teach you how to teach your students how to do one. I am, however, going to share a  example of what mediation is doing, inspired by living in the city in the US that has received the most snow this season (Erie, PA, with 93.9 inches for the season as of 1.30.25).  About a year ago, CNN shared data on how much snow it takes to cancel school in various parts of the country. I assure you, Erie and the rest of Northwest PA (see red outline) gets hella snow but no snow days. https://www.cnn.com/2024/02/12/us/how-much-snow-kids-school-snow-day-across-us-dg/index.html However, our lack of snow days isn't due to lack of snow. The annual amount of snow moderates the likelihood to cancel school, such that if you are used to a lot of snow (and have the infrastructure to handle it) you d...

How the USAF collects hurricane data with big, big airplanes.

I am an Air Force Brat. Growing up, my dad used to talk about all of the services the USAF provides to our country and the world. It employs many  musicians , advances  airplane safety  for civilians, and conducts and sponsors plenty of research . This post will focus on the USAF's unique position to advance weather and climate science via data collection in big, honkin' airplanes that can fly through hurricanes.  Weather forecasting requires data. As reported by Debbie Elliot for NPR , the Air Force collects data that, specifically, will help us better predict severe weather and save lives.  Aside: This whole mission started on a bet: HOW TO USE IN CLASS: -I tell my students repeatedly that I'm not trying to turn them into the world's best statisticians. I'm trying to help them learn how to be themselves, with their interests and abilities, but fluent in statistical literacy. This lesson goes better when I can have examples of data jobs that aren't traditi...

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....

Hurricane Confidence Intervals

UPDATE 10/5/22: No paywall article that conveys the same information:  https://www.msn.com/en-us/weather/topstories/cone-of-confusion-why-some-say-iconic-hurricane-map-misled-floridians/ar-AA12Bqyp Did you know that hurricane prediction maps are confidence intervals? This is one of my examples that serves more as a metaphor than a concrete explanation for a statistic, so bear with me. The New York Times created a beautiful, interactive website (it looked exceptionally sharp on my phone). The website attempts to explain what hurricane prediction maps tell us, versus how people interpret hurricane prediction maps. The website is at NYT, so you probably will hit a paywall if you have already viewed three stories on the NYT website in the last month. As such, I've included screenshots here. Here is a map with the projected hurricane path. People think that the white line indicates where the hurricane will go, and the red indicates bad weather. They also think that the broader path...

Day's Edge Production's "The Snow Guardian"

A pretty video featuring Billy Barr, a gentleman that has been recording weather day in his corner of Gothic, Colorado for the last 40 years.  Billy Barr This brief video highlights his work. And his data provides evidence of climate change. I like this video because it shows how ANYONE can be a statistician, as long as... They use consistent data collection tools... They are fastidious in their data entry techniques... They are passionate about their research. Who wouldn't be passionate about Colorado?

Why range is a lousy measure of variability

Mersereau's "Wunderground Uses Fox News Graphing Technique to Boast Forecast Skills"

Mersereau, writing for Gawker website The Vane, provides  another example of How Not To Graph. Or How To Graph As To Not Lie About Data But Make Your Data Look More Impressive Than Is Ethical. Weather Underground (AKA Wunderground, weather forecasting service/website) was bragging about it's accuracy compared to the competition. At first glance (see below), this graph seems to reinforce the argument...until you take a look at the scale being used. The beginning point on the X axis is 70, while the high point is 80. So, really, the differences listed probably don't even approach statistical significance. This story, somewhat randomly, also includes some shady graphs created by Fox News. I don't understand the need for the extra Fox News graphs, but they also illustrate how one can create graphs that have accurate numbers but still manage to twist the truth.

Harry Enten's "Has the snow finally stopped?"

This article and figure from Harry Enten (reporting for fivethrityegiht) provides informative and horrifying data on the median last day of measurable snow in different cities in America. (Personally, I find it horrifying because my median last day of measurable snow isn't until early April). This article provides easy-to-understand examples of percentiles, interquartile range, use of archival data, and median. Portland and Dallas can go suck an egg.

Anecdote is not the plural of data: Using humor and climate change to make a statistical point

Variations upon a theme...good for spicing up a powerpoint...inspired by living in the #1 snowiest city (population > 100K, 2014) in the United States. property of xkcd.com https://thenib.com/can-t-stand-the-heat-4d5650fd671b

io9's "New statistics on lightning deaths in the U.S. reveal weird patterns"

According to this data from the National Weather Service , lightning is a big, man-hating jerk!   From NWS/NOAA   And Might Thor lives to be your weekend's buzz kill! Or not. Play "Spot the Third Variable" with your students.