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Tens of millions of people in Europe and the US suffered extreme temperatures this month as two simultaneous “heat” domes positioned themselves over each continent.
“Dual heat domes” were likely to “become more common as we continue to heat the planet”, said Michael Mann, professor at the Department of Earth and Environmental Science at the University of Pennsylvania.
Heat domes occur when there is a ridge of high pressure in combination with a weakened jet stream, which generally occurs during the summer months.
“The position and strength of the jet stream can lead to blocking situations, such as an omega block where high pressure ends up sandwiched between two low pressure systems, forming a shape like the Greek letter Ω,” according to the Royal Meteorological Society.
This blocking pattern means the heat dome can remain static for long periods of time.
To illustrate the heat dome over the US, the first port of call was National Oceanic and Atmospheric Administration’s global forecasting system. It has plethora of data — more than 700 atmospheric variables — forecasting up to 16 days.
The one downside to this vast array of data is that the files are huge! Each one weighs in at 520MB and downloading 210 files requires a very fast connection and plenty of space on your hard drive.
Once all the files have downloaded (it helps to have a spare computer), they are taken into R, the statistical programming software and the 2-metre air temperature band is extracted from the netCDF (the climate scientist-preferred file format) using a few lines of code.
The files are then loaded into Qgis, the FT’s geographic information system software of choice and styled with an appropriate colour ramp — shamelessly borrowed from the esteemed Joshua Steven, former lead data visualiser/cartographer at Nasa’s Earth Observatory, with minor tweaks.
Exporting the 210 layers for the animation can be tedious manually, so I used Python code in the Qgis console to save each layer in our project as a separate PNG image. Marco Hernandez, a graphics editor at the New York Times, has written a great tutorial on how to do this. These files are then pulled into Adobe after effects software to create the animation.
For the second chart, I wanted to show how many Americans had been affected by the heatwave at its peak on Wednesday. To do this, R can be used again to calculate the maximum temperature during the day from the hourly temperature files.
[Nerd note: To create the temperature bands I used the Qgis built in raster (pixel grid) calculator to output simple files based on the 2C range of each band. The resulting files are simple black and white rasters where black means the condition has been met, white where it hasn’t. These rasters are then converted into vector polygons and used as a mask layer to query a population count layer for the US downloaded from WorldPop. This is done using the ‘zonal statistics’ function in Qgis which provides you with a total count for the area.]
I inputted the values for each temperature band into a spreadsheet and brought this into Flourish software, colour coding each bar so it matches the colour ramp used on the map.
Using two different approaches with the same data helps to give a more complete picture — using a map to show where people were affected and the chart to show how many.
Research by Mann and colleagues, published in the journal Proceedings of the National Academy of Sciences, found the amplification of waves in the jet stream — the fast-moving band of air encircling the planet — led to a dramatic increase in atmospheric events, driving heatwaves, wildfires and floods.
The study found that there was roughly a tripling from approximately one event per year to about three events a year when calculated over the past 70 years.
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