A fact from Warming stripes appeared on Wikipedia's Main Page in the Did you know column on 16 August 2019 (check views). The text of the entry was as follows:
Did you know... that a British climate scientist invented a graphic(shown) depicting historical global temperatures using coloured stripes to portray global warming to non-scientists?
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Microsoft Excel .xlsx files that automatically generate XML code for SVG graphs, including warming stripes[edit]
Click at right to show/hide preliminary comments
I've written a Microsoft Excel .xlsx spreadsheet file that semi-automates generation of SVG files of warming stripes graphics, so you don't have to buy really expensive software. You simply paste a vertical list of temperatures or other data. The spreadsheet automatically generates a column of cells containing xml code, each cell representing one "stripe" per cell. Simply copy that column and paste it into a text editor (TextEdit for Mac, presumably Notepad for Windows), and save the text file as filename.svg". Notes:
SVG filesize for a 171-point dataset is only about 9 Kbytes (file is "from scratch"; not generated by Inkscape etc.)
I've pre-programmed the colors to be the ones that warming stripes originator Ed Hawkins has used: 8 blue and 8 red colors. You can change them manually, in a conversion/translation table on the right side of the spreadsheet.
For flexibility over time, I include a cell that allows you to designate how many degrees are covered by each color (normally 0.10°C to 0.15°C per color). Enter larger numbers for datasets that span larger temperature ranges, so that colors remain in range of the sixteen colors. Data that exceed the most extreme color are truncated by the conversion/translation table to the most extreme color.
Per Ed Hawkins' early works, the boundary temperature between blue and red is 0.0 in the data column, corresponding to the average temperature over the reference period. If you want a different blue-red boundary temperature, offset your dataset up or down accordingly.
I initially (3 Feb 2021, Version 1) set the aspect ratio to be very close to 16:9, specifically 855x480 pixels, with each of the 171 stripes being 5 pixels wide (855/171=5). In Version 2 (below), you specify width and height (in pixels) and number of data points (=number of stripes).
Included instructions for Version 1 are:
Paste/Enter temperature anomaly data into "dT" column
If needed, change " ° per colour" choice above (to keep stripes within colour ranges)
Copy blue-shaded cells, paste into text file, and save as ".svg" file
You can click this v1 Dropbox link to download Version 1 of the .xlsx spreadsheet (though it's smarter to use Version 2.x, below).
I've uploaded .xlsx (Microsoft Excel) spreadsheets that automatically generate XML code for charts in SVG format.
You simply paste or enter your data into the spreadsheet, and specify image dimensions, number of grid lines, font sizes, etc. The spreadsheet instantly and automatically generates a column of XML code that you simply copy and paste into a text editor and save as an ".svg" file. The spreadsheets produce lean SVG code, avoiding the "extra stuff" that Inkscape inserts. They should save you time in creating SVG charts.
Warming stripes — Accepts a single dataset and converts to SVG code portraying Ed Hawkins'warming stripes graphics. User chooses vertical or horizontal stripes; normal or reverse data ordering; or from a variety of geometric shapes (updated 17 May 2023). . . . . Click here to see examples of warming stripes embedded in different shapes.
Warming stripes bar chart — Accepts a single dataset and creates a conventional bar chart whose individual bars/columns are coloured according to Dr. Hawkins' warming stripes colour scheme. Alternate option: choose one colour for ascending bars and another colour for descending bars. (updated 28 August 2023)
Line charts — Accepts up to six datasets. (updated 30 August 2023)
Vertical bar charts (column charts) — Accepts up to six datasets. Toggle between clustered and stacked charts; user can adjust "Yfloor"—the Y level (usually=0) from which columns rise or fall; user chooses to keep or ignore negative input values. (updated 27 August 2023)
Horizontal bar charts — Accepts up to six datasets. Toggle between clustered and stacked charts; user can adjust "Yfloor"—the value (usually=0) from which bars extend; user chooses to keep or ignore negative input values. (updated 27 August 2023)
Scatter plots — Accepts up to five datasets. (updated 28 August 2023)
Pie charts — Accepts a single dataset of up to 36 items. (updated 17 May 2023)
Variable-width bar charts — Accepts up to six datasets; is like "Vertical bar charts", above, but user can choose different widths for different bars. (updated 27 August 2023)
Examples (warming stripes):
An Excel .xlsx spreadsheet automatically+ generated the XML code for the following SVG images:
20210502 Warming stripes comparison of Global Mean Surface Temperature datasets.svg +I manually combined five automatically generated images into this one
20210507 Warming stripes - ellipses - global warming.svg
20210522 Warming stripes - longitudes - meridians on a globe - global warming.svg
20210526 Warming stripes - hearts - global warming.svg
20210507 Warming stripes - triangles - global warming.svg
20210530 Warming stripes - diamonds - global warming.svg
20210604 Warming stripes - XLSX to SVG - various Diamond etc configurations - GIF.gif
20210507 Warming stripes - rectangles - global warming.svg
20210517 Warming stripes - pentagrams - stars - global warming.svg
20210508 Warming stripes - hexagons - global warming.svg
20210507 Warming stripes - octagons - global warming.svg
The spreadsheet user can toggle a switch to reverse the order of data, so red is in the center (or left side of first graphic) and blue is at the outside (or right side of first graphic).
The spreadsheet user can choose height and width (in pixels), to compress or expand shape vertically and horizontally, for example, to change an ellipse to a circle or a rectangle to a square.
Oh, it's possible! But spreadsheets are clumsy tools for some tasks. I had to catenate text strings and calculated-numbers to create the XML elements.
Re 5-trace graphs: people who understand a little XML can separately make five unique .SVG files, and then copy the main 'path' text from four svg files into the fifth svg file (using the fifth file's plot area and grid lines etc).
To quickly generate 5-trace graphics within the spreadsheet, it would require almost about 22 columns to generate each trace. It would add a bit of complication for the user, also. Version 1.0 was meant for people who basically understand spreadsheets but don't know SVG or Inkscape etc. I plan to update the 5-trace GST graphic manually , in Inkscape, when all 2020 data is in.
@Femkemilene: Version 2.x is uploaded to Dropbox (link is above). Upgrading to five traces was more straightforward than I feared (though time-consuming!). Five actual temperature data series are included in the v2.x example. I haven't decided how to position five text legends for five traces, since different users will want them in different positions for different datasets. But this is a start.
@Femkemilene: I've updated the five-trace .svg graph (at right) with 2020 data and used the spreadsheet to generate the XML code. The only pre-processing needed in this case is to adjust some of the data sets to account for different base/reference periods. Spreadsheet Version 2.2 allows you to choose which 'quadrant' in which to put legends, to accommodate differently shaped graphs. —RCraig09 (talk)07:54, 25 February 2021 (UTC)[reply]
Warming stripes (sometimes referred to as climate stripes or climate timelines) are graphics that use a series of chronologically ordered coloured stripes to visualize trends in the temperature record of Earth. They employ a minimalist style, avoiding technical distractions by using colour alone to intuitively convey trends in global warming to non-scientists. The initial concept of visualizing historical temperature data has been extended to use animations, to visualize sea level rise and predictive climate data, and to visually juxtapose temperature trends with other data series, such as the concentration of carbon dioxide in Earth's atmosphere, global glacier retreat, precipitation, the contribution of aviation emissions to global warming, and biodiversity loss. These warming stripes were published by the British climatologist Ed Hawkins in 2018, using data from the World Meteorological Organization. The colours represent the annual mean global temperature for each year from 1850 (left) to 2018 (right) – the progression from blue (cooler) to red (warmer) stripes is indicative of global warming.
Thanks User:Uwappa, I also noticed the BBC article in the morning news. I've incorporated its summary teachings into this article, to introduce the numerous existing examples in the /* Applications and influence */ section. You may be aware, primary sources have limited acceptability on Wikipedia, and Ellie Highwood's contribution is already described in the /* Background, publication and content */ section; this is why I haven't added her blog post to the references. —RCraig09 (talk)23:14, 11 December 2023 (UTC)[reply]