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MAKING EFFECTIVE
& ACCESSIBLE
FIGURES
Zachary Labe| 12 July 2022| REU Professional Development| Colorado State University
Zack Labe
Pioneer Coal Mine Blue Whale of Catoosa Centralia Underground Fire Roadside America Greenland Sea (81°N)
Enjoy: roadside oddities, diners, and horror movies
Hobbies: gardening, #scicomm ( @ZLabe), hiking, traveling to lighthouses
Graduate work: Arctic – midlatitude climate variability (sea-ice changes)
Recent work: using ANNs to detect patterns of climate variability/change
Now at GFDL I am thinking about: detection and attribution of extreme events
Relevance
LENS X-Single Forcing Runs
Hometown – Linglestown,
Pennsylvania
BSc – Atmospheric Science
at Cornell University
PhD – Earth System Science
at UC Irvine
Postdoc – climate variability
using AI at Colorado State U.
Postdoc – climate attribution
with T. Delworth & N. Johnson
he/him
Polar Amplification: acceleration of
warming in high latitudes relative to
the rest of the globe
NOW
Start of
satellite-era
DATA VISUALIZATION
IS STORY-TELLING.
DON’T BE
SUCH A
SCIENTIST
WE ARE
DATA
SCIENTISTS
ART BY JILL PELTO
Landscape of Change uses data
about sea level rise, glacier volume
decline, increasing global
temperatures, and the increasing use
of fossil fuels. These data lines
compose a landscape shaped by
the changing climate, a world in
which we are now living.
Jill Pelto|http://www.jillpelto.com/landscape-of-change
“
”
BEGINNING WITH
OUR DATA.
LINE GRAPHS
Temperature
Anomaly
(°C)
:)
MAP PLOTS
YIKES!
YIKES – FONT IS BLEH!
YIKES – COLOR!
MAP PROJECTION!
:)
HAVE FUN!
LEVERAGING ALL
DIMENSIONS OF
YOUR DATA.
I have a 2D-array of sea ice thickness
anomaly data [year,day]…
Each line is one day
Number of Years
Thickness
Anomaly
(m)
https://seaborn.pydata.org/examples/index.html
SURPRISINGLY EFFECTIVE.
Senator Sheldon Whitehouse (D-CT) - Time to Wake Up: Climate Progress Speech (3/21/2018)
DANISH
METEOROLOGICAL
INSTITUTE
Labe, Z.M. and E.A. Barnes (2022), Predicting slowdowns in decadal climate warming trends
with explainable neural networks. Geophysical Research Letters, DOI:10.1029/2022GL098173
TELLING A
STORY.
Labe, Z.M. and E.A. Barnes (2022), Predicting slowdowns in decadal climate warming trends
with explainable neural networks. Geophysical Research Letters, DOI:10.1029/2022GL098173
TELLING A
STORY.
Select one ensemble
member and calculate
the annual mean
global mean surface
temperature (GMST)
2-m TEMPERATURE
ANOMALY
LABE AND BARNES, 2022, GRL
Calculate 10-year
moving (linear) trends
2-m TEMPERATURE
ANOMALY
LABE AND BARNES, 2022, GRL
Plot the slope of the
linear trends
START OF 10-YEAR
TEMPERATURE TREND
2-m TEMPERATURE
ANOMALY
LABE AND BARNES, 2022, GRL
Calculate a threshold
for defining a slowdown
in decadal warming
LABE AND BARNES, 2022, GRL
Repeat this exercise for
each ensemble
member in CESM2-LE
LABE AND BARNES, 2022, GRL
Compare warming
slowdowns with
reanalysis (ERA5)
LABE AND BARNES, 2022, GRL
SCIENCE OF DESIGN.
cmap = ‘jet’
STOELZLE AND STEIN, 2021, HESS
1998!
Citations on Google Scholar…
Check out: https://betterfigures.org/2018/06/04/playing-hunt-the-discontinuity/
2004!
SCHNEIDER
AND
NOCKE,
2017
SCHNEIDER
AND
NOCKE,
2017
Adapted from Ed Hawkins at betterfigures.org
Crameri, F. (2018). Scientific colour maps.
Zenodo. http://doi.org/10.5281/zenodo.1243862
Crameri, F. (2018), Geodynamic diagnostics, scientific
visualisation and StagLab 3.0, Geosci. Model Dev., 11, 2541-
2562, doi:1 0.5194/gmd-11-2541-2018
Crameri, F., G.E. Shephard, and P.J. Heron (2020), The
misuse of colour in science communication, Nature
Communications, 11, 5444. doi:10.1038/s41467-020-19160-7
Palettable:
Color palettes for Python
Crameri, F. (2018). Scientific colour maps.
Zenodo. http://doi.org/10.5281/zenodo.1243862
Crameri, F. (2018), Geodynamic diagnostics, scientific
visualisation and StagLab 3.0, Geosci. Model Dev., 11, 2541-
2562, doi:1 0.5194/gmd-11-2541-2018
Crameri, F., G.E. Shephard, and P.J. Heron (2020), The
misuse of colour in science communication, Nature
Communications, 11, 5444. doi:10.1038/s41467-020-19160-7
CMOCEAN
THYNG ET AL. 2016; OCEANOGRAPHY
CMASHER
“Scientific colormaps for making accessible,
informative and cmashing plots”
Adjusting axes (spines)
Changing font styles
https://github.com/zmlabe
1. Seaborn.
2. Plotly.
3. ggplot.
4. Matplotlib v3.
RESOURCES
1. https://betterfigures.org/
2. https://www.climate-lab-book.ac.uk/
3. http://colorbrewer2.org/
RESOURCES
MAKING ACCESSIBLE
FIGURES.
ACCESSIBILITY
No jargon
Tell a story
Alternative text
Color contrast ratio
Label data directly
Avoid flashing GIFs
Include figure titles
Avoid data overlays
Provide data references
CHECK:
Simple.
Bold.
Stories.
@ZLabe
Questions!
ZACHARY LABE | 12 JULY 2022| REU PROFESSIONAL DEVELOPMENT | COLORADO STATE UNIVERSITY

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