Yesterday Hurricane Ophelia hit Ireland and the United Kingdom. Yes, the two islands get hit with ferocious storms from time to time, but rarely do they enjoy the hurricanes like we do on the eastern seaboards of Canada, Mexico, and the United States.
Earlier this hurricane season the US had to deal with Harvey, Irma, and Maria. And in early October the Wall Street Journal published a piece that looked at the economic impact of the former two hurricanes as exhibited in economic data.
Overall the piece does a nice job explaining how hurricanes impact different sectors of the economy, well, differently. And wouldn’t you know it that leisure and hospitality is the hardest hit? But then they put together this stacked bar chart showing the impact of the hurricanes on both Florida/Georgia and Texas for Irma and Harvey, respectively.
The problem is that the stacked bar chart does not allow us to examine each hurricane as a specific data set. Because the Harvey data set is first, we have the common baseline and can compare the lengths of the magenta-ish bars. But what about the blue sets for Irma? How large is natural resources and mining compared to professional and business services? It is incredibly difficult to tell because neither bar starts at the same point. You must mentally move the bars to the same baseline and then hope your brain can accurately capture the length.
Instead, a split bar chart with each sector having two bars would have been preferable. Or, barring that, two plots under the same title. Then you could even sort the data sets and make it even easier to see which sectors were more important in the impacted areas.
Stacked bar charts work when you are trying to show total magnitude and the breakdowns are incidental to the point. But as soon as the comparison of the breakdowns becomes important, it’s time to make another chart.
Over the last several weeks we dealt with the impact of a few hurricanes from H to K, i.e. Harvey, Irma, Jose, and Katia. Now that the Atlantic basin has quieted a wee bit, it is time we get back to the lighter side of things.
So we turn to xkcd and its look at ensemble models, often used to try and predict the paths of hurricanes.
So I thought I would be done with Harvey coverage, but this morning I saw this map from the New York Times that plotted out requests for aid throughout the storm.
You can really see the storm’s movement through the impacts upon the people. It’s especially true later in the timeline as the storm moved further to the east.
Credit for the piece goes to Gregor Aisch, Sarah Almukhtar, Jeremy Ashkenas, Matthew Bloch, Audrey Carlsen, Jose A. Delreal, Ford Fessenden, K.K. Rebecca Lai, Adam Pearce, Anjali Singhvi, and Karen Yourish.
One more day of Harvey-related content. At least I hope. (Who knows? Maybe someone will design a fantastic retrospective graphic?) Today, however, we look at a piece from the Economist about the rising number of weather-related disasters, but thankfully falling numbers of deaths. The piece has all the full suite of graphics: choropleths, line charts, and bar charts (oh my!). But I want to look at the bar chart.
I cannot tell from this chart whether there has been any change in the individual elements, the meteorological, hydrological, or climatological disasters. And unfortunately stacked bar charts do not let us see that kind of detail. They only really allow us to see total magnitude and the changes in the element at the bottom of the stack, i.e. aligned with the baseline. So I took their chart and drew the shapes as lines and realigned everything to get this.
You can begin to see that meteorological might be overtaking hydrological, but it is too early to tell. And that right now, climatological causes are still far behind the other two.
Credit for the piece goes to the Economist Data Team.
Let’s consider today a follow-up to yesterday’s piece. (No, I do not believe I have ever done a follow-up piece, but why not start now all these years later.)
Yesterday we looked at the Post, Journal, and Times for their coverage of the fallen rain amounts in southeast Texas. But at the time, we only had actual totals from the Post and Journal. The Times had only produced a projection map. The Times piece yesterday was perhaps the most underwhelming of the three, though it certainly did some things correctly, namely it was small, simple, and quick to get the reader to the point that Houston was likely to be flooded by storm’s end.
What is different about this piece? Well this one is an animated .gif showing the cumulative rainfall. In other words, Texas starts dry and every hour just makes the map bluer and bluer. An additional feature that I find particularly useful is the dot map, which indicates where the heaviest rain was falling in each hour. Especially early on in the event, you can see the bands of rain sweeping in from the Gulf.
The bins also work better here, though I wonder if more segregation or a different palette would have worked a bit better. But, my biggest critique is the same I have with many animated .gifs: the looping. And unfortunately I do not have an easy solution. You certainly need to see it loop through more than once to understand the totality of the rainfall. But then I really do want to be able to examine the final map, or at least final as of 03.00 today.
Anyway, this was a really nice piece that should have been showcased alongside the others yesterday.
Credit for the piece goes to Gregor Aisch, Sarah Almukhtar, Jerey Ashkenas, Matthew Bloch, Joe Burgess, Audrey Carlsen, Ford Fessenden, Troy Griggs, K.K. Rebecca Lai, Jasmine C. Lee, Jugal K. Patel, Adam Pearce, Bedel Saget, Anjali Singhvi, Joe Ward, and Josh Williams.
Hurricane Harvey landed north of Corpus Christi, Texas late Friday night. By Monday morning, Houston has been flooded as nearly two feet of water have fallen upon the city, built on and around wetlands long ago paved over with concrete. Naturally the news has covered this story in depth all weekend. Even leading up to it, when I was still posting eclipse things, various outlets had projections and why we should care graphics. But as the storm begins to move back into the Gulf—only to move back inland tomorrow—I wanted to compare some of the graphics I have been seeing.
Of course, not all graphics are the same, let alone cover the same things. So this morning we are looking at just the rainfall total maps of a few different outlets.
From the Washington Post, we have the following graphic.
The palette chosen performs well at quickly scaling up to the record level of rainfall, i.e. the 20+ inches realm, but quickly shifting from the green–blue palette into dark purples.
Here we have a more familiar blue–red diverging spectrum. The point of divergence set to 20 inches.
Lastly, we have the New York Times graphic. Though in this case, it’s not an exact like-for-like comparison. I could not find a graphic mapping total rainfall, instead this is for projected rainfall totals. But the design is for the same type of map, i.e. how much rain falls in a location.
The Post takes the closest approach to the true continuous spectrum palette, where the shift from dry to drenched is gradual. It makes for a smoother, more blended looking map. Somewhere around that 20 inch point, however, the palette shifts from the green to blue range to purple. It emphasises the record-hitting point, but otherwise the totals are presented as more fluid. Perhaps correctly since rain does not neatly fall evenly into pixels.
By comparison, the Journal segments the rainfall totals into bins of blues. The scale is not even, the lighter blues incorporate two inches, the darkers upwards of five. And then again, like the Post, separate 20+ as a different colour, here switching to reds.
Lastly the Times keeps to a simple segmented bin palette of all blues. 20+ inches is rendered is just a dark blue.
Each map has pluses, each has minuses. The Times map, for example, is simple and quick to understand. Southeastern Texas will be wet by the middle of next week. If your goal is only to communicate that point, well this map has done its job. It is worth noting, again, that this is a map of projections. Because the other thing missing from this map is the storm’s path. So if the goal were to showcase the rainfall along the storm’s path, well this graphic does not accomplish that nearly as well as the other two.
The Post and the Journal both show the track of the storm. The Journal takes it one step further and plots its projected course through Thursday. This helps us really see if not understand the east side problem of hurricanes. That is, the eastern quadrants of hurricanes typically experience the heaviest amounts of rain. And as the darker portions of the map all fall to the north and east of those lines, it reaffirms this for us.
So what really differentiates the two? The colour palette and its application. The Post’s palette is more natural as, again, rain does not fall neatly into bins and instead makes for blurred and messy totals across a map. Separating the heaviest rains into the purples, however, makes a lot of sense as that amount of rainfall, as we are seeing this morning, makes for a mess in Houston.
But the point of a graphic is to translate nature and the observed into a digestible and pointed statement of the observed. What should I learn? Why should I care? The Journal, like the Post, does a fantastic job of splitting out the 20+ inch totals by using a divergent palette. But instead of blending into that colour, the distinction is sharp. And then below that threshold, we get rainfall totals segmented into just a few bins. These help the reader see, also more starkly because of the selection of the specific blues, just where the bands of heavy rain will fall.
I do want to point out, however, that all of these maps occur in articles with lots of other fantastic graphics that visually explore lots of details about the story. And in particular, I want to highlight that the normal bit where I state the credits includes a lot of people. Creating a whole host of graphics to support a story takes a lot of work.
Credit for the Washington Post piece goes to Darla Cameron, Samuel Granados, Chris Alcantara, and Gabriel Florit.
Credit for the Wall Street Journal piece goes to Bradley Olson, Arian Campo-Flores, Miguel Bustillo, Dan Frosch, Erin Ailworth, Christopher M. Matthews, and Russell Gold.
Credit for the New York Times piece goes to Gregor Aisch, Sarah Almukhtar, Jeremy Ashkenas, Matthew Bloch, Joe Burgess, Audrey Carlsen, Ford Fessenden, Troy Griggs, K.K. Rebecca Lai, Jasmine C. Lee, Jugal K. Patel, Adam Pearce, Bedel Saget, Anjali Singhvi, Joe Ward, and Josh Williams.