Recently the United Kingdom baked in a significant heatwave. With climate change being a real thing, an extreme heat event in the summer is not terribly surprising. Also not surprisingly, the BBC posted an article about the impact of climate change.
The article itself was not about the heatwave, but rather the increasing rate of sea level rise in response to climate change. But about halfway down the article the author included this graphic.
As graphics go, it is not particularly fancy—a dot plot with ten points labelled. But what this piece does well is using a dot plot instead of the more common bar chart. I most typically see two types of charts when plotting “hottest days” or something similar. The first is usually a simple timeline with a dot or tick indicating when the event occurred. Second, I will sometimes see a bar chart with the hottest days presented all as bars, usually not in the proper time sequence, i.e. clustered bar next to bar next to bar.
My issue with the the latter is always where is the designer placing the bottom of the bar? When we look at the best temperature graphics, we usually refer to box plots wherein the bar is aligned to the day and then top of the bar is the daily high and the bottom of the bar the daily low. It does not make sense to plot temperatures starting at, say 0º.
In this particular case, however, the dates would appear to overlap too closely to allow a proper box plot. Though I suspect—and would be curious to see—if the daily minimum temperatures on each of those ten hottest days have also increased in temperature.
As to the timeline option, this does a better job of showing not just the increasing frequency of the hottest days, but also the rising maximum value. In the early 20th century the hottest day was 36.7ºC, and you can see a definite trend towards the hottest days nearing and finally surpassing 40ºC.
I do wonder if a benchmark line could have been added to the chart, e.g. the summertime average daily high or something similar. Or perhaps a line showing each day’s temperature faintly in the background.
Finally, I want to point out the labelling. Here the designers do a nice job of adding a white stroke or outline to the outside of the text labels. This allows the text to sit atop the y-axis lines and not have the lines interfere with the text’s legibility. That’s always a nice feature to see.
Credit for the piece goes to the BBC graphics department.
For my readers in the northern hemisphere, which is the vast majority of you, we are in the middle of meteorological summer, the dog days. And whilst my UK and Europe readers continue to bake under temperatures greater than 40ºC (104ºF), the northeast United States and Philadelphia in particular is looking at a heatwave starting today that’s forecast to peak at a temperature of 38ºC (100ºF) this weekend and a heat index reaching 41ºC (106ºF) tomorrow.
Yesterday we examined a completely different topic, property tax increases in Philadelphia, but we contrasted that work with a heat index map from the New York Times. With the heatwave beginning this afternoon, however, it seemed apropos to revisit that contrasting article.
It begins with the map that we looked at yesterday. Of course yesterday was Tuesday. Today is Wednesday, and so you can already compare these two maps to see how and where the heat has shifted. Spoiler: the Southeast and Midwest.
It does so with a nice simple three-colour unidirectional spectrum from a light yellow to a burnt orange. And you can see the orange spreading up from the Gulf Coast and along the southeastern Atlantic Seaboard.
For those not familiar, the heat index is basically what the air “feels like” taking into consideration the actual temperature and the relative humidity in the air. Humans cool themselves via perspiration and when the air is excessively humid our ability to perspire decreases and thus the body begins to run hotter. Warmer temperatures allow the atmosphere to increase the amount of moisture it can contain and you can see all that Gulf and subtropical moisture carrying itself into the hot air moving up from the south.
Very not cool.
The piece also offers a look at the forecast for the heat index, showing the next six days. These small multiples allow the reader to see the geographic progression of the heat. Whereas today will be particularly for parts of the Midwest in southern Illinois and Indiana, tomorrow will see the worst for the Eastern Seaboard. Luckily the heat index retreats a bit, though as I noted above, the temperatures will continue to rise until Sunday, meaning higher temperatures, but lower relative humidity. For Philadelphia in particular we talking about 50% relative humidity tomorrow and only 35% on Sunday. That makes a big difference.
Overall this is a great piece despite the content.
Personally, I just can’t wait until summer.
Credit for the piece goes to Matthew Bloch, Lazaro Gamio, Zach Levitt, Eleanor Lutz, and John-Michael Murphy.
First, as we all should know, climate change is real. Now that does not mean that the temperature will always be warmer, it just means more extreme. So in winter we could have more severe cold temperatures and in hurricane season more powerful storms. But it does mean that in the summer we could have more frequent and hotter heat waves.
Enter the United States, or more specifically the North American continent. In this article from the BBC we see photographs of the way the current heatwave is playing out across the continent. But it opens up with a nice map. Well, nice as in nicely done, not as in this is actually nice weather.
The only complaint most of my American readers might have is that the numbers make no sense. That’s because it’s all in Celsius. Unfortunately for Americans most of the rest of the world uses Celsius and not Fahrenheit. Suffice it to say you don’t want to be in the dark reds. 44C equals 111F. 10C, the greenish-yellow side of the spectrum, is a quite pleasant 50F.
And that can relate to a small housekeeping note. I’m back after a long weekend up in the Berkshires. I took a short holiday to go visit the area near that north–south band of yellow over the eastern portion of the United States. It was very cool and windy and overall a welcome respite from the heat that will be building back in here across the eastern United States later this week.
At least yesterday was the summer solstice. The days start getting shorter. And in about five weeks or so we will reach the daily average peak temperature here in Philadelphia. At that point the temperatures begin cooling towards their eventual mid-January nadir.
I can’t wait.
Credit for the piece goes to the BBC graphics department.
On Friday, I mentioned in brief that the East Coast was preparing for a storm. One of the cities the storm impacted was Boston and naturally the Boston Globecovered the story. One aspect the paper covered? The snowfall amounts. They did so like this:
This graphic fails to communicate the breadth and literal depth of the snow. We have two big reasons for that and they are both tied to perspective.
First we have a simple one: bars hiding other bars. I live in Greater Centre City, Philadelphia. That means lots of tall buildings. But if I look out my window, the tall buildings nearer me block my view of the buildings behind. That same approach holds true in this graphic. The tall red columns in southeastern Massachusetts block those of eastern and northeastern parts of the state and parts of New Hampshire as well. Even if we can still see the tops of the columns, we cannot see the bases and thus any real meaningful comparison is lost.
Second: distance. Pretty simple here as well, later today go outside. Look at things on your horizon. Note that those things, while perhaps tall such as a tree or a skyscraper, look relatively small compared to those things immediately around you. Same applies here. Bars of the same data, when at opposite ends of the map, will appear sized differently. Below I took the above screenshot and highlighted two observations that differed in only 0.5 inches of snow. But the box I had to draw—a rough proxy for the columns’ actual heights—is 44% larger.
This map probably looks cool to some people with its three-dimensional perspective and bright colours on a dark grey map. But it fails where it matters most: clearly presenting the regional differences in accumulation of snowfall amounts.
Compare the above to this graphic from the Boston office of the National Weather Service (NWS).
No, it does not have the same cool factor. And some of the labelling design could use a bit of work. But the use of a flat, two-dimensional map allows us to more clearly compare the ranges of snowfall and get a truer sense of the geographic patterns in this weekend’s storm. And in doing so, we can see some of the subtleties, for example the red pockets of greater snowfall amounts amid the wider orange band.
Credit for the Globe piece goes to John Hancock.
Credit for the NWS piece goes to the graphics department of NWS Boston.
Winter is coming? Winter is here. At least meteorologically speaking, because winter in that definition lasts from December through February. But winters in Philadelphia can be a bit scattershot in terms of their weather. Yesterday the temperature hit 19ºC before a cold front passed through and knocked the overnight low down to 2ºC. A warm autumn or spring day to just above freezing in the span of a few hours.
But when we look more broadly, we can see that winters range just that much as well. And look the Philadelphia Inquirerdid. Their article this morning looked at historical temperatures and snowfall and whilst I won’t share all the graphics, it used a number of dot plots to highlight the temperature ranges both in winter and yearly.
The screenshot above focuses attention on the range in January and July and you can see how the range between the minimum and maximum is greater in the winter than in the summer. Philadelphia may have days with summer temperatures in the winter, but we don’t have winter temperatures in summer. And I say that’s unfair. But c’est la vie.
Design wise there are a couple of things going on here that we should mention. The most obvious is the blue background. I don’t love it. Presently the blue dots that represent colder temperatures begin to recede into and blend into the background, especially around that 50ºF mark. If the background were white or even a light grey, we would be able to clearly see the full range of the temperatures without the optical illusion of a separation that occurs in those January temperature observations.
Less visible here is the snowfall. If you look just above the red dots representing the range of July temperatures, you can see a little white dot near the top of the screenshot. The article has a snowfall effect with little white dots “falling” down the page. I understand how the snowfall fits with the story about winter in Philadelphia. Whilst the snowfall is light enough to not be too distracting, I personally feel it’s a bit too cute for a piece that is data-driven.
The snowfall is also an odd choice because, as the article points out, Philadelphia winters do feature snowfall, but that on days when precipitation falls, snow accounts for less than 1/3 of those days with rain and wintry mixes accounting for the vast majority.
Overall, I really like the piece as it dives into the meteorological data and tries to accurately paint a portrait of winters in Philadelphia.
And of course the article points out that the trend is pointing to even warmer winters due to climate change.
Credit for the piece goes to Aseem Shukla and Sam Morris.
When the remnants of Hurricane Ida rolled through the Northeast two weeks ago, here in the Philadelphia region we saw catastrophic flooding from deluges west of the city and to the east we had a tornado outbreak in South Jersey. At a simplistic level we can attribute the differences in outcomes to the path of the storm. As Ida was no longer a hurricane she developed what we call warm and cold sectors along the frontal boundary. Long story short, we can see different types of weather in these setups with heavy rain in the cold and severe weather in the warm. And that’s what we saw with Ida: heavy, flood-causing rains in the cold sector north and west of Philadelphia and then severe weather, tornadoes, in the warm sector south and east of the city.
But I want to talk about the tornadoes, and one in particular: an EF3 tornado that struck the South Jersey town of Mullica Hill. EF3 refers to the enhanced Fujita scale that describes the severity of tornadoes. EF1s are minor and EF5s are the worst. The Philadelphia region has in the past rarely seen tornadoes, but even moderate strength ones such as an EF3 are almost unheard of in the area.
This tornado caused significant damage to the area, but was also remarkable because it persisted for 12 miles. Most tornadoes dissipate in a fraction of that length. The Mount Holly office of the National Weather Service (NWS) produced a few graphics detailing tornadoes Ida spawned. You can see from the timeline graphic that the Mullica Hill tornado was particularly long lasting in time as well as distance travelled, surviving for twenty minutes.
To briefly touch on the design of this graphic, I think it generally works well. I’m not certain if the drop shadow adds anything to the graphic and I might have used a lighter colour text label for the times as they fight with the graphical components for visual primacy. Secondly, I’m not certain that each tornado needs to be in a different colour. The horizontal rules keep each storm visually separate. Colour could have instead been used to indicate perhaps peak severity for each tornado or perhaps at specific moments in the tornadoes’ lives. But overall, I like this graphic.
NWS Mt Holly also produced a graphic specifically about the tornado detailing its path.
Here we have a graphic incorporating what looks like Google Earth or Google Maps imagery of the area and an orange line denoting the path. At various points faint text labels indicate the strength of the tornado along its path. A table to the left provides the key points.
From a graphical standpoint, I think this could use a bit more work. The orange line looks too similar to the yellow roads on the map and at a quick glance may be too indistinguishable. Compare this approach to that of the Philadelphia Inquirer in its writeup.
Here we have a map with desaturated colours with a bright red line that clearly sets itself apart from the map. I think a similar approach would have benefitted the NWS graphic. Although the NWS graphic does have a stroke weight that varies depending upon the path of the tornado.
I also have a graphic made by a guy I know who lives in the area. He took that maximum tornado width of 400 yards and used screenshots of Google Maps in combination with his own direct evidence and photos and videos from his neighbours and their social media posts to try and plot the tornado’s path more granularly. Each red mark represents storm damage and a width of 400 yards.
I’m not going to critique this graphic because he made it more for himself to try and understand how close he was to the storm. In other words, it wasn’t meant to be published. But I’m thankful he allowed me to share it with you. But even here you can see he chose a colour that contrasted strongly with the background satellite views.
All of this just goes to show you the path and devastation one tornado caused. And that one tornado was just a fraction of the devastation Ida wrought upon the Northeast let alone the rest of the United States.
For the last two days Philadelphia and much of the East Coast suffered from a heavy haze of smoke that blanketed the region. This wasn’t just any smoke, however, but smoke from the wildfires on the West Coast. This post isn’t about the wildfires, but rather something that exacerbated them. We are talking about the heat domes that formed earlier this summer. The ones that melted trolley cables in Portland.
This was a nice print graphic in the Guardian Weekly, a magazine to such I subscribe that had several articles about the domes.
It does a nice job of showing the main components of the story and sufficiently simplifying them to make them digestible. One quibble, however, is how in the second map how oddly specific the heat dome is depicted.
The first graphic in particular is more of an abstraction and simplified illustration. But here we have contours and shapes that seem to speak with precision about the location of this heat dome. It also contains shades of red that presumably indicate the severity of the heat.
There’s nothing wrong with that, but it stuck me as odd juxtaposed against the top illustration.
Credit for the piece goes to the Guardian Weekly graphics department.
The middle third of the United States sits under some pretty cold Arctic air, helping to bring frozen precipitation, i.e. snow, to places unfamiliar with it, most notably Texas. I say unfamiliar, but Texas is also negligently unprepared. There are photos circulating the internet of Texarkana, a city straddling the Texas–Arkansas border, of the Arkansas side plowed and safe for travel whilst the Texas side…is not. You also have a deregulated and privatised energy grid, which has seen wholesale prices spike to $9,000 per megawatt hour. (Some companies in the Texan market charge wholesale rates to their customers, so I wouldn’t be surprised to see stories coming out in the next few weeks of excessively large electric bills.)
What’s driving this Texas-scale cold? Why is Arctic air over Dallas? In years past you’ve probably heard the term “polar vortex”. The super simple version is that really cold air spins in a tight upper-atmosphere vortex over the pole, hence the name. But when the vortex weakens, say due to warmer air, it becomes a bit more unstable. When it becomes unstable, a chunk of it might break off and descend south. It doesn’t always descend over continental North America, but when it does… well, since the mid 2010s we’ve been calling it the polar vortex. Keep in mind, that it’s not, it’s a part of an upper-level low whose cold air eventually falls to the surface, but despite my protestations, the name has stuck.
Anyway, it means we presently are witnessing some frigid temperatures across the US and this graphic from the National Weather Service (NWS) highlights just how extreme those temperatures are.
The distance is no surprise here, because in winter one would expect Minneapolis and Miami to exhibit extreme temperature differences. But it’s the scale of this difference that is so dramatic.
I could probably do a whole piece—or several—about the design of NWS graphics, but I’ll just point out that I’d probably lighten the black lines working as state/provincial borders. And while their colours are standardised, I wonder if making a clearer distinction between freezing and above freezing (32ºF in this map) would make some more sense.
In a first, the Gulf of Mexico basin has two active hurricanes simultaneously. Unfortunately, they are both likely to strikes somewhere along the Louisiana coastline within approximately 36 hours of each other. Fortunately, neither is strong as a storm named Katrina that caused a mess of things several years ago now.
Over the last few weeks I have been trying to start the week with my Covid datagraphics, but I figured we could skip those today and instead run with this piece from the Washington Post. It tracks the forecast path and forecast impact of tropical storm force winds for both storms.
The forecast path above is straight forward. The dotted line represents the forecast path. The coloured area represents the probability of that area receiving tropical storm force winds. Unsurprisingly the present locations of both storms have the greatest possibilities.
Now compare that to the standard National Weather Service graphic, below. They produce one per storm and I cannot find one of the combined threat. So I chose Laura, the one likely to strike mid-week and not the one likely to strike later today.
The first and most notable difference here is the use of colour. The ocean here is represented in blue compared to the colourless water of the Post version. The colour draws attention to the bodies of water, when the attention should be more focused on the forecast path of the storm. But, since there needs to be a clear delineation between land and water, the Post uses a light grey to ground the user in the map (pun intended).
The biggest difference is what the coloured forecast areas mean. In the Post’s versions, it is the probability of tropical force winds. But, in the National Weather Service version, the white area actually is the “cone”, or the envelope or range of potential forecast paths. The Post shows one forecast path, but the NWS shows the full range and so for Laura that means really anywhere from central Louisiana to eastern Texas. A storm that impacts eastern Texas, for example, could have tropical storm force winds far from the centre and into the Galveston area.
Of course every year the discussion is about how people misinterpret the NWS version as the cone of impact, when that is so clearly not the case. But then we see the Post version and it might reinforce that misconception. Though, it’s also not the Post’s responsibility to make the NWS graphic clearer. The Post clearly prioritised displaying a single forecast track instead of a range along with the areas of probabilities for tropical storm force winds.
I would personally prefer a hybrid sort of approach.
But I also wanted to touch briefly on a separate graphic in the Post version, the forecast arrival times.
This projects when tropical storm force winds will begin to impact particular areas. Notably, the areas of probability of tropical storm force winds does not change. Instead the dotted line projections for the paths of the storms are replaced by lines relatively perpendicular to those paths. These lines show when the tropical storm winds are forecast to begin. It’s also another updated design of the National Weather Service offering below.
Again, we only see one storm per graphic here and this is only for Laura, not Marco. But this also probably most analogous to what we see in the Post version. Here, the black outline represents the light pink area on the Post map, the area with at least a 5% forecast to receive tropical storm force winds. The NWS version, however, does not provide any further forecast probabilities.
The Post’s version is also design improved, as the blue, while not as dark the heavy black lines, still draws unnecessary attention to itself. Would even a very pale blue be an improvement? Almost certainly.
In one sense, I prefer the Post’s version. It’s more direct, and the information presented is more clearly presented. But, I find it severely lack in one key detail: the forecast cone. Even yesterday, the forecast cone had Laura moving in a range both north and south of the island of Cuba from its position west of Puerto Rico. 24 hours later, we now know it’s on the southern track and that has massive impact on future forecast tracks.
Being east of west of landfall can mean dramatically different impacts in terms of winds, storm surge, and rainfall. And the Post’s version, while clear about one forecast track, obscures the very real possibilities the range of impacts can shift dramatically in just the course of one day.
I think the Post does a better job of the tropical storm force wind forecast probabilities. In an ideal world, they would take that approach to the forecast paths. Maybe not showing the full spaghetti-like approach of all the storm models, but a percentage likelihood of the storm taking one particular track over another.
Credit for the Post pieces goes to the Washington Post graphics department.
Credit for the National Weather Service graphics goes to the National Weather Service.
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.
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.