Wicked Hot Islands

Though the temperatures might not always feel it, at least in Philadelphia, summer is ending and autumn beginning. Consequently I wanted to share this neat little work that explores urban heat islands. Specifically, this post’s author looks at Massachusetts and starts with a screenshot of the Boston area.

Wicked hot
Wicked hot

The author points out that the Boston Common and Public Garden are two areas of cool in an otherwise hot Boston. He also points out the Charles River and the divide between Boston and Brookline. I would like to add to it and point out the Fens and the Emerald Necklace.

I wonder if a scale of sorts would help, though the shift from warm yellows and reds to cooler greens and blues certainly helps differentiate between the cooler and warmer areas.

Credit for the piece goes to Krishna Karra.

The Map

I mean come on, guys, did you really expect me to not touch this one?

Well we made it to Friday, and naturally in the not so serious we have to cover the sharpie map. Because, if the data does not agree with your opinions, clearly the correct response is to just make shit up.

By now you have probably all heard the story about how President Trump tweeted an incorrect forecast about the path of Hurricane Dorian, warning how Alabama could be “hit (much) harder than anticipated”. Except that the forecast at the time was that Alabama wasn’t going to be hit. Cue this map, days later. As in days. As in this news story continued for days.

Note the sharpie weirdly extending the cone (in black, not the usual white) into Florida and onward into Alabama.
Note the sharpie weirdly extending the cone (in black, not the usual white) into Florida and onward into Alabama.

So to be fair, I went to the NOAA website and pulled down from their archive the cone maps from the date of the graphic Trump edited, and the one from the day when he tweeted about Alabama being hit by the hurricane.

Important to note that this forecast dates from 29 August. This press conference was on 4 September. He tweeted on 1 September. So in other words, two days after he used the wrong forecast, he had printed a big version of a contemporaneously two-day old forecast to show that if he drew a sharpie line on it, it would be correct.

Here is the original, from the National Hurricane Centre, for 29 August. Note, no Alabama.

No Alabama in this forecast, the OG, if you will (and if I'm using that term correctly).
No Alabama in this forecast, the OG, if you will (and if I’m using that term correctly).

And then Trump tweeted on 1 September. So let’s take the 02.00 Eastern time 1 September forecast from NOAA.

By 30 August the forecast was already tracking northward, not westward. So by 1 September the idea that the hurricane would hit Alabama was just nonsense.
By 30 August the forecast was already tracking northward, not westward. So by 1 September the idea that the hurricane would hit Alabama was just nonsense.

Definitely no Alabama in that forecast.

This could have all gone away if he had just admitted he looked at the wrong forecast and tweeted an incorrect warning. Instead, we had the White House pressuring NOAA to “fix” their tweet.

Now we can all chalk  this up as funny. But it does have some serious consequences. Instead of people in the actual path of Dorian preparing, because of the falsely wide range of impacts the president suggested, people in Alabama needlessly prepared for a nonevent.

But more widely, as someone who works with data on a daily basis, we need to agree that data is real. We cannot simply change the data because it does not fit the story we want to tell. If I could take a screenshot of every forecast and string them together in an animated clip, you would see there was never any forecast like the sharpie forecast. We cannot simply create our own realities and choose to live within them, because that means we have no common basis on which to disagree policy decisions that will have real world impacts.

Credit for the photo goes to Evan Vucci of the AP.

Credit for the National Hurricane Centre maps goes to its graphic team.

Where the Vaping Illness Is Spreading

Yesterday President Trump announced that the FDA is seeking to implement a ban on flavoured e-cigarettes. Ostensibly this is to combat teen uptake on the habit, but it comes at the same time as an outbreak of respiratory illnesses seemingly linked to vaping. Though, it should be pointed out that preliminary data points to a link to cannabis-infused vaping liquids, not necessarily cigarettes.

Regardless, the day before yesterday, I want to the CDC website to get the data on the outbreak to see if there was a geographic pattern to the outbreak. And, no, not really.

No real clear pattern here
No real clear pattern here

The closest thing that I could argue is the Eastern Seaboard south of New England. But then the deaths are all from the Midwest and westward. So no, in this graphic, there really is no story. I guess you could also say it’s more widespread than not?

Credit for this piece goes to me.

Prorogation of Parliament

If you’re among my British/European audience, you are probably well aware Boris Johnson has prorogued, or suspended, Parliament. He and cabinet ministers stated it was a normal, average-length prorogation to prepare for a Queen’s Speech. (The Queen’s Speech is the formal opening of a new session of Parliament that sets out a new legislative agenda and formally closes/kills any unpassed legislation from the old session.) Except that in documents revealed in a Scottish court case, we now know that the real reason was to shut down Parliament to prevent it from interfering in Boris’ plans for a No Deal Brexit. And just this morning the Scottish High Court did indeed rule that the prorogation is illegal. The case now moves to the UK Supreme Court.

But I want to focus on the other claim, that this is a prorogation of average length. Thankfully instead of having to do a week’s hard slog of data, the House of Lords Library posted the data for me. At least since 1900, and that works well enough for me. And so here we go.

Back to the 1930s?
Back to the 1930s?

So yeah, this is not an average prorogument. If you look at only proroguments that do not precede a general election—you need time for the campaigning and then hosting the actual election in those cases—this is the longest prorogument since 1930. (Also, a Parliament does not necessarily need to be prorogued before it is dissolved before an election. And that happened quite often in the 1960s, 70s, and 80s.)

And as I point out in the graphic, Parliament was prorogued during the depths of World War II to start new legislative sessions. But in those cases, Parliament opened the very next day, during a time of national crisis. One could certainly make the argument that Brexit is a national crisis. So wherefore the extraordinarily long prorogument? Well, quite simply, Brexit.

Credit for the piece goes to me.

The Retreat from Ilovaisk

Five years ago, I covered the Russian invasion of Ukraine a little tiny bit. Five years on and Russia has formally annexed Crimea and Russian “patriotic volunteers” continue to destabilise the Donbass. About two weeks ago, this article from the BBC caught my eye as it recounted the story of Ukraine’s deadliest day in the conflict. Initially I read it simply because I have long been fascinated by that undeclared war.

Since at least high school, but probably most definitely earlier, I have long been interested in military history. And I distinctly recall being awestruck by maps depicting the bombing of Pearl Harbour, or the Roman defeat at Cannae, or the Battle of Waterloo.

So I loved scrolling through the article and finding this graphic.

A long and bloody road
A long and bloody road

It’s a fairly simple map, showing the alignment of forces. It’s not quite a tactical map showing unit size/formations, but it does show the Ukrainian forces essentially surrounded. And how their retreat brought them through essentially a shooting gallery of Russian artillery.

Credit for the piece goes to the BBC graphics department.

Merging of the States

Dorian now speeds away from Newfoundland and into the North Atlantic. We looked at its historic intensity last week. But during that week, with all the talk of maps and Alabama, I noted to myself a map from the BBC that showed the forecast path.

Did New Jersey eat Delaware?
Did New Jersey eat Delaware?

But note the state borders. New Jersey and Delaware have merged. Is it Delawarsey? And what about Maryland, Virginia, and the District of Columbia? Compare that to this map from the Guardian.

Here the states are intact
Here the states are intact

What we have are intact states. But, and it might be difficult to see at this scale, the problem may be that it appears the BBC map is using sea borders. I wonder if the Delaware Bay, which isn’t a land border, is a reason for the lack of a boundary between the two states. Similarly, is the Potomac River and its estuary the reason for a lack of a border between Virginia, Maryland, and DC?

I appreciate that land shape boundary files are easy, but they sometimes can mislead users as to actual land borders.

Credit for these pieces go the BBC graphics department and the Guardian graphics department.

Greenland Is Melting

There is a lot going on in the world—here’s looking at you Brexit vote today—but I did not want to miss this frightening article from the BBC on the melting of Greenland’s ice. It’s happening. And it’s happening faster than thought.

There are several insightful graphics, including the standard photo slider of before and after, a line chart showing the forecast rise of sea levels within the possible range. But this one caught my eye.

Alarming rates along the coast.
Alarming rates along the coast.

The colour palette here works fairly well. The darkest reds are not matched by a dark blue, but that is because the ice gain does not match the ice loss. Usually we might see a dark blue just to pair with a dark red, but again, we don’t because the designers recognised that, as another chart shows, the ice loss is outweighing the gains, though there are some to be found most notably at the centre of the ice sheets. This is a small detail, but something that struck me as impressive.

My only nitpick is that the legend does not quantify the amounts of gain or loss. That could show the extremes and reinforce the point that the loss is dwarfing the gain.

Credit for the piece goes to the BBC graphics department.

We’re All Just Palm Trees and Patio Furniture in the Wind

For all my American readers, I hope you all enjoyed their Labour Day holiday. For the rest of you, today is just a Tuesday. Unless you live in the Bahamas, then today is just another nightmarish day as Hurricane Dorian continues his assault on the islands.

The storm will be one for the record books when all is said and done, and not just because of the damage likely to be catastrophic when people can finally emerge and examine what remains. The storm, by several metrics, is one of the most powerful in the Atlantic since we started recording data on hurricanes. If we look at pressure and sustained wind speeds, i.e. not wind gusts, Sam Lillo has plotted the path of Dorian through those metrics and found it sitting scarily in the lower-right corner of this plot.

How low can it go? Probably not much, thankfully.
How low can it go? Probably not much, thankfully.

The graphic does a couple of nice things here. I like the use of colour to indicate the total number of observations in that area. Clearly, we see a lot more of the weaker, higher pressure storms. Hence the dark blue in the upper-left. But then against that we have the star of the graphic, and my favourite part of the plot: the plot over time of Dorian’s progress and intensification as a storm. The final green dot indicates the point of the last observation when the graphic was made.

Overall this is a simple and solid piece that shows in the available historical context just how powerful Dorian is. Unfortunately that correlates with likely heavy damage to the Bahamas.

Credit for the piece I presume goes to Sam Lillo, though with the Twitter one can never be entirely certain.

Hong Kong Identity

One of the things I have been following closely the last few months has been the protests in Hong Kong. The city is one of China’s few Special Administrative Regions—basically the former British colony of Hong Kong and the former Portuguese colony of Macau, two cities bordering mainland China and separated by the Pearl River estuary.

Long story short, but since 1997 Hong Kong should enjoy 50 years of a legal system that is more aligned to that of its former status of a British colony than that of mainland China. But increasingly since Xi Jinping took power, he has been eroding those rights and the youth of Hong Kong have taken to the streets to protest, a right they enjoy but not the rest of mainland Chinese.

And so we have a survey looking at the identity by which those people living in Hong Kong choose to identify.

And it’s not Chinese.

Not a good trend for Beijing
Not a good trend for Beijing

From a news perspective, this poses problems for a Beijing-based Chinese government that is making pains to promote a greater Chinese identity throughout the world, least of all by pushing for a reunification with Taiwan by force if necessary. A generation of several million Hong Kongers and the way they raise their children, in addition to their friends and supporters abroad, weakens the authority of Beijing.

Hence the threat of a Tiananmen Square style crackdown on Hong Konger protestors.

Alas, the United States has been far more concerned with its trade dispute than it has been the democratic and human rights of several million people. At least, that is the impression given by the White House.

But, as to the design, I do not love the spaghettification of the line charts. Though I do appreciate that the Hong Kong identity has been separated by the maroon-coloured line. I wonder if labelling the lines in the small multiples is necessary given the decision to include the legend at the top of the chart.

The other tricky thing with this type of chart is that the data series is a population cohort. And yet the data is based on a time series. And so the cohorts vary over time. It might not be entirely clear to the audience that this (appears to be)/is a sample of people of an age at a particular date. How do those people change over the years? It’s hard to see that trend by separating out the data.

Overall, it’s a solid piece. And it’s important given the gravity of the protests in Hong Kong.

Credit for the piece goes to the Economist Data team.

Pub Trivia Scores

So today we have pub trivia scores.

It’s been a little while since I’ve posted from my data recording of my Wednesday night’s team trivia pub scores. For the very few of us who know what this means, here you go.

We're on a downward trend
We’re on a downward trend

Essentially, our ability to score points on music in the last round remains pretty bad. Hence the general downward trend.

Credit for this piece goes to me.