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Using data visualization for effective science (communication)

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Using data visualization for effective science (communication)

  1. 1. USING DATA VISUALIZATION FOR EFFECTIVE SCIENCE (COMMUNICATION) ZACHARY LABE | 5 MAY 2021 | ATS 655 | LECTURE 43 | COLORADO STATE UNIVERSITY
  2. 2. Polar Amplification: acceleration of warming in high latitudes relative to the rest of the globe
  3. 3. Warmer Colder NOW Start of satellite-era
  4. 4. Polar Amplification: acceleration of warming in high latitudes relative to the rest of the globe
  5. 5. Q: What are your favorite visualizations of climate change data?
  6. 6. DON’T BE SUCH A SCIENTIST WE ARE DATA SCIENTISTS ART BY JILL PELTO
  7. 7. DATA VISUALIZATION IS STORY-TELLING.
  8. 8. 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 “ ”
  9. 9. 1. https://betterfigures.org/ 2. https://www.climate-lab-book.ac.uk/ 3. http://colorbrewer2.org/ RESOURCES
  10. 10. Q: What are your worst figures?
  11. 11. LABE ET AL. 2017, CLIMATE DYNAMICS
  12. 12. My first map subplot?
  13. 13. My first-year practicum presentation!
  14. 14. BEGINNING WITH OUR DATA.
  15. 15. LINE GRAPHS
  16. 16. :)
  17. 17. MAP PLOTS
  18. 18. YIKES!
  19. 19. YIKES – FONT IS BLEH!
  20. 20. YIKES – COLOR!
  21. 21. MAP PROJECTION!
  22. 22. :)
  23. 23. HAVE FUN!
  24. 24. SURPRISINGLY EFFECTIVE.
  25. 25. Senator Sheldon Whitehouse (D-CT) - Time to Wake Up: Climate Progress Speech (3/21/2018)
  26. 26. DANISH METEOROLOGICAL INSTITUTE
  27. 27. SCIENCE OF DESIGN.
  28. 28. #endrainbow Check out: https://betterfigures.org/2018/06/04/playing-hunt-the-discontinuity/
  29. 29. EGU 2018 Conference https://betterfigures.org/
  30. 30. SCHNEIDER AND NOCKE, 2017
  31. 31. SCHNEIDER AND NOCKE, 2017
  32. 32. SCHNEIDER AND NOCKE, 2017
  33. 33. SCHNEIDER AND NOCKE, 2017
  34. 34. SCHNEIDER AND NOCKE, 2017
  35. 35. 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
  36. 36. 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
  37. 37. BY FABIO CRAMERI
  38. 38. BY FABIO CRAMERI
  39. 39. OTHER OPTIONS THYNG ET AL. 2016; OCEANOGRAPHY
  40. 40. CMOCEAN
  41. 41. CMASHER “Scientific colormaps for making accessible, informative and cmashing plots”
  42. 42. Adjusting axes (spines)
  43. 43. Changing font styles
  44. 44. https://github.com/zmlabe
  45. 45. 1. Seaborn. 2. Plotly. 3. ggplot. 4. Matplotlib v3. ALTERNATIVES
  46. 46. LABE ET AL. 2019, GRL Bring drama to your data story
  47. 47. LABE ET AL. 2019, GRL
  48. 48. LABE ET AL. 2019, GRL STRONGER POLAR VORTEX Zonal wind at 10 hPa Geopotential at 30 hPa
  49. 49. WEAKER POLAR VORTEX Zonal wind at 10 hPa Geopotential at 30 hPa LABE ET AL. 2019, GRL
  50. 50. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI
  51. 51. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI
  52. 52. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI
  53. 53. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI
  54. 54. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI
  55. 55. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI
  56. 56. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS ET AL. 2021, JCLI
  57. 57. ACCESSIBILITY
  58. 58. ACCESSIBILITY
  59. 59. ACCESSIBILITY
  60. 60. 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
  61. 61. Q: What are the most recognizable graphs of climate change data?
  62. 62. VISUALIZING GLOBAL TEMPERATURE CHANGE
  63. 63. PLOT BY ED HAWKINS
  64. 64. 2016 RIO OLYMPICS OPENING CEREMONY
  65. 65. PLOT BY ED HAWKINS
  66. 66. PLOT BY ED HAWKINS DON’T BE SUCH A SCIENTIST WE ARE DATA SCIENTISTS
  67. 67. https://showyourstripes.info/ PLOT BY ED HAWKINS
  68. 68. Q: Do you reference your coding & data?
  69. 69. OPEN SCIENCE
  70. 70. GROWING DATA
  71. 71. GROWING TOOLS
  72. 72. Today’s weather or climate scientist is far more likely to be debugging code written in Python… than to be poring over satellite images or releasing radiosondes. “ D. Irving| Bulletin of the American Meteorological Society| 2016
  73. 73. D. Irving| Bulletin of the American Meteorological Society| 2016
  74. 74. Behind every library
  75. 75. So what can we do?
  76. 76. WHY Transparency Reproducibility Code-sharing Innovation Open-science Climate science needs this! Growing software communities Share our cool science and inspire! The future of big data Is there a crisis in science?
  77. 77. CHECK: Simple. Bold. Stories. @ZLabe Questions! ZACHARY LABE | 5 MAY 2021 | ATS 655 | LECTURE 43 | COLORADO STATE UNIVERSITY

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