Yep, Still Hotter

Like I said yesterday, I wanted to compare cities, surprise, Philadelphia vs. Chicago. And so with some extra time I was able to finish this graphic that took the data from Climate Central to compare the two cities.

What you can see below is that Philadelphia has seen more significant temperature growth in both summer highs and summer lows. And, importantly, the increase in low temperatures, i.e. nighttime, has been greater than that of daytime highs. That means that we have less of an opportunity to cool down after a hot summer day, adding stress to the system.

Chicago on the other hand has seen less overall growth, though it’s still present. And there too we see the same pattern of greater increases in low, i.e. nighttime, temperatures than of daytime highs.

It’s all unbearable

It’s remarkable to think that the flat where I lived seven of my eight years in Chicago had no air conditioning unit in the bedroom, only in the living room. It was, of course, an older concrete building from the 1960s/70s when, as the chart above shows, nighttime temperatures didn’t really require air conditioning.

But like I said yesterday, I’m just glad I’ve been able to crank the air conditioning the last several days.

Credit for the piece is mine.

You’re Not Crazy, It Is Getting Hotter

First, I should say that I don’t have a lot to say about this graphic because I went back to the source because I was interested in another city and I wanted to compare the two. In other words, expect a small graphic follow up to this maybe tomorrow.

Anyways, over the last few years since returning to Philadelphia after eight years away in Chicago, I’ve had numerous conversations with different people about how “I don’t remember it always being this hot before”, which is particularly relevant as the Philadelphia region endures excessive heat. Thankfully, it’s not nearly as bad as the Pacific Northwest. Also I have air conditioning blasting next to me as I type this out, so, you know.

The common refrain in these conversations, however, tends to be less about how we have high temperatures and more about how it’s difficult to sleep at night. And there’s a reason for that as this article from the Philadelphia Inquirer explains, our average summer low temperatures are rising, and rising faster than our average summer high temperatures.

Yep, definitely getting warmer.

Of course you can probably already see where I was going with this. The Inquirer linked to their source and that’s where I’ve spent my time this morning, alas, I didn’t quite have enough to finish what I started and so this post will have to do.

Credit for the piece goes to the Philadelphia Inquirer graphics department.

It’s Warming Up

As many of my readers know, I prefer my weather cooler and summer is probably my least favourite season—weather wise at least. Appropriately, my vaccination will be kicking in just in time for a small, early season heatwave. Felt like an appropriate time to share this piece from Brian Brettschenider.

It’s just an animated map showing where in the United States and Canada the daily average high temperature is 70ºF for each day of the year. Here’s where you can expect a daily high of 70ºF for the date of 20 May. Not Philadelphia.

I’m sure going to miss those reds.

Make sure to click through to watch the video on the Twitter.

Credit for the piece goes to Brian Brettschneider.

Warmer, Wetter Winters in the UK

I remember hearing and reading stories as a child about the Thames in London freezing over and hosting winter festivals. Of course most of that happened during what we call the Little Ice Age, a period of below average temperatures during the 15th through the early 19th century.

But those days are over.

The UK’s Meteorological Office, or the Met for short, released some analysis of the impacts of climate change to winter temperatures in the United Kingdom. And if, like me, you’re more partial to winter than summer, the news is…not great.

Winter warming

Broadly speaking, winters will become warmer and wetter, i.e. less snowy and more rainy. Meanwhile summers will become hotter and drier. Farewell, frost festivals.

But let’s talk about the graphic. Broadly, it works. We see two maps with a unidirectional stepped gradient of six bins. And most importantly those bins are consistent between the maps, allowing for the user to compare regions for the same temperatures: like for like.

But there are a couple of things I would probably do a bit differently. Let’s start with colour. And for once we’re not dealing with the colour of the BBC weather map. Instead, we have shades of blue for the data, but all sitting atop an even lighter blue that represents the waters around the UK and Ireland. I don’t think that blue is really necessary. A white background would allow for the warmest shade of blue, +4ºC, to be even lighter. That would allow greater contrast throughout the spectrum.

Secondly, note the use of think black lines to delineate the sub-national regions of the UK whilst the border of the Republic of Ireland is done in a light grey. What if that were reversed? If the political border between the UK and Ireland were black and the sub-national region borders were light grey—or white—we would see a greater contrast with less visual disruption. The use of lines lighter in intensity would allow the eye to better focus on the colours of the map.

Then we reach an interesting discussion about how to display the data. If the purpose of the map is to show “coldness”, this map does it just fine. For my American audience unfamiliar with Celsius, 4ºC is about 39ºF, many of you would definitely say that’s cold. (I wouldn’t, because like many of my readers, I spent eight winters in Chicago.)

The article touches upon the loss of snowy winters. And by and large, winters require temperatures below the freezing point, 0ºC. So what if the map used a bidirectional, divergent stepped gradient? Say temperatures above freezing were represented in shades of a different colour like red whilst below freezing remained in blue, what would happen? You could easily see which regions of the UK would have their lowest temperatures fail to fall below freezing.

Or another way of considering looking at the data is through the lens of absolute vs. change. This graphic compares the lowest annual temperature. But what if we instead had only one map? What if it coloured the UK by the change in temperature? Then you could see which regions are being the most (or least) impacted.

If the data were isolated to specific and discrete geographic units, you could take it a step further and then compare temperature change to the baseline temperatures and create a simple scatterplot for the various regions. You could create a plot showing cold areas getting warmer, and those remaining stable.

That said, this is still a really nice piece. Just a couple little tweaks could really improve it.

Credit for the piece goes to the UK Met Office.

Auto Emissions Stuck in High Gear

The last two days we looked at densification in cities and how the physical size of cities grew in response to the development of transport technologies, most notably the automobile. Today we look at a New York Times article showing the growth of automobile emissions and the problem they pose for combating the greenhouse gas side of climate change.

The article is well worth a read. It shows just how problematic the auto-centric American culture is to the goal of combating climate change. The key paragraph for me occurs towards the end of the article:

Meaningfully lowering emissions from driving requires both technological and behavioral change, said Deb Niemeier, a professor of civil and environmental engineering at the University of Maryland. Fundamentally, you need to make vehicles pollute less, make people drive less, or both, she said.

Of course the key to that is probably in the range of both.

The star of the piece is the map showing the carbon dioxide emissions on the roads from passenger and freight traffic. Spoiler: not good.

From this I blame the Schuylkill, Rte 202, the Blue Route, I-95, and just all the highways
From this I blame the Schuylkill, Rte 202, the Blue Route, I-95, and just all the highways

Each MSA is outlined in black and is selectable. The designers chose well by setting the state borders in a light grey to differentiate them from when the MSA crosses state lines, as the Philadelphia one does, encompassing parts of Pennsylvania, New Jersey, Delaware, and Maryland. A slight opacity appears when the user mouses over the MSA. Additionally a little box remains up once the MSA is selected to show the region’s key datapoints: the aggregate increase and the per capita increase. Again, for Philly, not good. But it could be worse. Phoenix, which surpassed Philadelphia proper in population, has seen its total emissions grow 291%, its per capita growth at 86%. My only gripe is that I wish I could see the entire US map in one view.

The piece also includes some nice charts showing how automobile emissions compare to other sources. Yet another spoiler: not good.

I've got it: wind-powered cars with solar panels on the bonnet.
I’ve got it: wind-powered cars with solar panels on the bonnet.

Since 1990, automobile emissions have surpassed both industry emissions and more recently electrical generation emissions (think shuttered coal plants). Here what I would have really enjoyed is for the share of auto emissions to be treated like that share of total emissions. That is, the line chart does a great job showing how auto emissions have surpassed all other sources. But the stacked chart does not do as great a job. The user can sort of see how passenger vehicles have plateaued, but have yet to decline whereas lorries have increased in recent years. (I would suspect due to increased deliveries of online-ordered goods, but that is pure speculation.) But a line chart would show that a little bit more clearly.

Finally, we have a larger line chart that plots each city’s emissions. As with the map, the key thing here is the aggregate vs. per capita numbers. When one continues to scroll through, the lines all change.

Lots of people means lots of emissions.
Lots of people means lots of emissions.

There's driving in the Philadelphia area, but it's not as bad as it could be.
There’s driving in the Philadelphia area, but it’s not as bad as it could be.

Very quickly one can see how large cities like New York have large aggregate emissions because millions of people live there. But then at a per capita level, the less dense, more sprawl-y cities tend to shoot up the list as they are generally more car dependent.

Credit for the piece goes to Nadja Popovich and Denise Lu.

Urban Heat Islands

Yesterday was the first day of 32º+C (90º+F) in Philadelphia in October in 78 years. Gross. But it made me remember this piece last month from NPR that looked at the correlation between extreme urban heat islands and areas of urban poverty. In addition to the narrative—well worth the read—the piece makes use of choropleths for various US cities to explore said relationship.

My neighbourhood's not bad, but thankfully I live next to a park.
My neighbourhood’s not bad, but thankfully I live next to a park.

As graphics go, these are effective. I don’t love the pure gradient from minimum to maximum, however, my bigger point is about the use of the choropleth compared to perhaps a scatter plot. In these graphics that are trying to show a correlation between impoverished districts and extreme heat, I wonder if a more technical scatterplot showing correlation would be effective.

Another approach could be to map the actual strength of the correlation. What if the designers had created a metric or value to capture the average relationship between income and heat. In that case, each neighbourhood could be mapped as how far above or below that value they are. Because here, the user is forced to mentally transpose the one map atop the other, which is not easy.

For those of you from Chicago, that city is rated as weak or no correlation to the moderately correlated Philadelphia.

I lived near the lake for eight years, and that does a great deal for mitigating temperature extremes.
I lived near the lake for eight years, and that does a great deal for mitigating temperature extremes.

Granted, that kind of scatterplot probably requires more explanation, and the user cannot quickly find their local neighbourhood, but the graphics could show the correlation more clearly that way.

Finally, it goes almost without saying that I do not love the red/green colour palette. I would have preferred a more colour-blind friendly red/blue or green/purple. Ultimately though, a clearer top label would obviate the need for any colour differentiation at all. The same colour could be used for each metric since they never directly interact.

Overall this is a strong piece and speaks to an important topic. But the graphics could be a wee bit more effective with just a few tweaks.

Credit for the piece goes to Meg Anderson and Sean McMinn.

It’s Getting Hot in Here

The UN climate summit begins in New York today. So let’s take a look at another data visualisation piece exploring climate change data. This one comes from a Washington Post article that, while largely driven by a textual narrative, does make use of some nice maps.

Ugh.
Ugh.

There is nothing too crazy going on with the actual map itself. I like the subtle use here of a stepped gradient for the legend. This allows for a clearer differentiation between adjacent regions and just how, well, bad things have become.

But where the piece shines is about halfway through. It takes this same map and essentially filters it. It starts with those regions with temperature changes over 2ºC. Then it progressively adds slightly less hotter regions to the map.

I mean at least it could be worse?
I mean at least it could be worse?

It’s a nice use of scrolling and filtering to highlight the areas worst impacted and then move down the horrible impact scale. And because this happens in the middle of the piece, giving it the full column width (online) allows the reader to really focus on the impacts.

Credit for the piece goes to Chris Mooney and John Muyskens.

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.

The Amazon Burns

The G7 conference in France wrapped up yesterday and they announced an aid package for Brazil. Why? Because satellite data from both Brazil and the United States points to a rash of fires devastating the Amazon rainforest, the world’s largest carbon sink, or sometimes known as the lungs of the Earth. I have not had time to check this statistic, but I read that 1/5 the world’s oxygen comes from the Amazon ecosystem. I imagine it is a large percentage given the area and the number of trees, but 20% seems high.

Regardless, it is on fire. Some is certainly caused by drier conditions and lightning strikes. But most is manmade. And so after the Brazilian president  Jair Bolsonaro said his country did not have the resources to fight the fires, the G7 offered aid.

This morning, Bolsonaro refused it.

And so we have this map from InfoAmazonia that takes NASA data on observed fires for all of South America. I cropped my screencapture to Brazil.

You should also see the smoke maps
You should also see the smoke maps

A key feature to note here, in addition to that black background approach, is that you will see three distinct features: yellow hotspots fading to cold black areas, yellow dots with red outlines, and red dots. Each means something different. The yellow to red to black gradient simply means frequency of fires, the yellow dots with red outlines represent significantly hot fires from 2002 through 2014. The red dots are what concern us. Those are fires within the last month.

Sure enough, we see lots of fires breaking out across the Amazon. And Bolsonaro not only rejected the aid, but a few weeks ago he rejected similar data. He fired the head of a government agency tasked with tracking the deforestation of the Amazon after he released the agency’s monthly report detailing the deforestation. It had risen by 39%.

From a design standpoint, it is a solid piece. I do wonder, however, if some kind of toggle for the three datasets could have been added. Given the focus on the new fires breaking out, isolating those compared to the historic fires would be useful.

But before wrapping up, I also want to point out that there are a significant number of red dots appearing outside Brazil. The Amazon exists beyond borders, and there are a significant number of fires in neighbouring Bolivia and Paraguay. Let alone around the world…

Credit for the piece goes to InfoAmazonia.org.

Hotter Muggier Faster

Last week we looked at a few posts that showed the future impact of climate change at both a global and US-level scale. In the midst of last week and those articles, the Washington Post looked backwards at the past century or so to identify how quickly the US has changed. Spoiler: some places are already significantly warmer than they have been. Spoiler two: the Northeast is one such place.

The piece is a larger and more narrative article using examples and anecdotes to make its point. But it does contain several key graphics. The first is a big map that shows how temperature has changed since 1895.

The Southeast is an anomaly, but its warming has accelerated since the 1960s
The Southeast is an anomaly, but its warming has accelerated since the 1960s

The map does what it has to and is nothing particularly fancy or groundbreaking—see what I did there?—in design. But it is clear and communicates effectively the dramatic shifts in particular regions.

The more interesting part, along with what we looked at last week, is the ability to choose a particular county and see how it has trended since 1895 and compare that to the baseline, US-level average. Naturally, some counties have been warming faster, others slower. Philadelphia County, the entirety of the city, has warmed more than the US average, but thankfully less than the Northeast average as the article points out.

This ain't so good
This ain’t so good

But, not to leave out Chicago as I did last week, Cook County, Illinois is right on line with the US average.

Nor is this, but it's average
Nor is this, but it’s average

But the big cities on the West Coast look very unattractive.

Tinseltown is out of the question
Tinseltown is out of the question

The interactive piece does a nice job clearly focusing the user’s attention on the long run average through the coloured lines instead of focusing attention on the yearly deviations, which can vary significantly from year to year.

And for those Americans who are not familiar with Celsius, one degree Celsius equals approximately 1.8º Fahrenheit.

Overall this is a solid piece that continues to show just what future generations are going to have to fix.

Credit for the piece goes to Steven Mufson, Chris Mooney, Juliet Eilperin, John Muyskens, and Salwan Georges.