1. Teaching Computational Thinking: Examples from Weather and Climate Modeling “Essentially, all models are wrong, but some models are useful.” - George E. P. Box (1951) Teresa Eastburn & Randy Russell National Center for Atmospheric Research University Corporation for Atmospheric Research NSTA Denver, December 12, 2013

2. Computational Thinking Solving problems, designing systems, and understanding human behavior by drawing on the concepts fundamental to computer science. ~ Jeannette Wing, Carnegie Mellon Integrating the power of human thinking with the capabilities of computers. ~CSTA Steven Gilbert NSTA Press

3. 1.What is a climate model, why are supercomputers needed, and what do they do and not do? 2.The Systems Game – Why systems thinking matters 3. What’s the difference between a weather model vs a climate model (initial value problem vs. a boundary value problem)? 4.Chaos Theory 5.Climate simulations for your you and your students to explore Here’s What We’ll Be Covering

4. Spark – science education at NCAR National Center for Atmospheric Research in Boulder

5. NCAR Mesa Lab in Boulder Public and School Group Visits spark.ucar.edu/visit

6. spark.ucar.edu/workshops

7. spark.ucar.edu/events/workshop- computational-thinking-nsta-regional-2013

8. Evolution of Climate Models Credit: Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4): Working Group 1: Chapter 1, page 99, Fig. 1.2

10. Climate Model Components Credit: UCAR (Paul Grabhorn)

11. Climate Model Components Credit: UCAR

12. Observations Theory Numerical Modeling Progress in climate models occurs as a result of: Like a sturdy 3-legged stool OBSERVATION THEORY MODELING “Science presumes that things and events in the Universe occur in consistent patterns that are comprehensible through careful, systematic study.” ~ AAAS

13. Models are today’s tech test tube for the Earth system. Image source adaption: NOAA Images adapted from K. Dickson, NOAA

14. Climate Models = Virtual Earth Now we can model various components (parts or subsystems) in the Earth system (atmosphere, ocean, sea ice, land physics…) and how they will interact and respond over time to a natural or human-made forcing agent. Atmosphere Circulation & Radiation Sea Ice Ocean Circulation Land Physics

15. Resolution: What Does It Mean?

16. Improving Resolution of Climate Models Credit: Warren Washington, NCAR Grid Cell Sizes 1990s (T42) 200 x 300 km 120 x 180 miles 2000s (T85) 100 x 150 km 60 x 90 miles

17. Improving Resolution of Climate Models Credit: Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4): Working Group 1: Chapter 1, page 113, Fig. 1.4

18. Vertical Resolution of Climate Models Vertical Layers 1990s 10 layer atmosphere 1 layer “slab” ocean 2000s 30 layer atmosphere 30 layer ocean Credit: UCAR

19. Horizontal and Vertical Grid

21. Hexagonal Grid and Sub-grids Credit: UCAR (Lisa Gardiner)

22. spark.ucar.edu/sites/default/files/SystemInMotionMaster.pdf

23. Using Models in Education “Essentially, all models are wrong, but some models are useful.” - George E. P. Box (1951)

24. Weather vs Climate Projections Physics is Physics, Right? Why do we think we can make meaningful 100 year climate projections when we can’t forecast the day-to-day weather a month from now? Initial Value Problem vs Boundary Value Problem

25. Weather Model vs Climate Model Compare and Contrast Differences (and similarities) between Weather vs. Climate Models Area Covered (scale) Resolution – distance (spatial) and time (temporal) Timespan covered by model runs Impacts on computing resources needed, time required to run models

26. Weather Model vs Climate Model Area Covered Weather Model – up to about continental size scale Climate Model – global size scale Larger area requires either more computing power/time or lower resolution (spatial and/or temporal)

27. Weather Model vs Climate Model Resolution and Precision Weather Model resolution typically about 3-10 km timesteps of hourly to 6 hours, forecast for next 3-4 days Climate Models resolutions from about 25-30 km up to 100 (or a couple hundred) km running computer models can take days or weeks, which would be impractical for weather models Precision – why Wx forecast for Christmas is suspect, but temperature next July is reliable (relationship to chaos)

28. Weather Model vs Climate Model Timeframe Weather Forecast – hours to days (up to about 10 days) Climate Projection – decades to centuries or longer (climate is usually defined as at least 30 years of observations)

29. Resolution: Spatial & Temporal (Time) Timesteps can be a few minutes to 12 hours or more Durations can be hours to centuries

30. Resolution and Computing Power Double resolution – increase number of nodes – more calculations! One Dimension Two Dimensions 2 times as many nodes 4 times as many nodes

31. Resolution and Computing Power What if we increase model to three dimensions (space) plus time?

32. Resolution and Computing Power What if we increase model to three dimensions (space) plus time? 16 times as many nodes – 16x computing power required! This is why we need supercomputers!

33. Chaos Chaos – 10-day forecast reliability limit Ensemble runs of models – tipping points – arctic ice melt – sea ice and open water albedo images Why Wx forecast for Xmas is suspect, but temperature next July is reliable (relationship to chaos)

34. Climate Forcings

35. Source: Meehl et al NCAR

36. Which of the following cannot be addressed by a physical climate model? 1.How would Earth’s average surface temperature be expected to change if carbon dioxide doubled? 2.How much carbon dioxide and methane will humans add to the atmosphere during each of the next five decades? 3.Can cosmic rays from the sun affect clouds and hence play an important role in climate variability and change? 4.Is it possible to learn about past climate variations by gathering data from holes drilled deep into the Earth’s crust? 5.All above can be addressed by physical climate science.

37. F = P x g x e x f x d F = total GHG emission rate P = population size (global and/or national) g = per capita gross world/domestic capital e = energy use per $ of gross world/national product f = GHG emissions per unit energy use d = deforestation effects How will GHG vary?

38. Ensemble Projections of Global Temperature for Various Emission Scenarios Source: UCAR/NCAR Future Projections Verses Forecasts

39. Climate Models help with… DETECTION - Is the planet’s climate changing significantly? ATTRIBUTION – If so, what is causing the change? Nature? Human Actions? Both? PROJECTION – What does the future hold for Earth’s climate?

40. Models in the Standards Next Generation Science Standards

41. Greenhouse Effect Review  CO 2 absorbs heat in the atmosphere  When heat accumulates in the Earth system, the average global temperature rises

42. Increased CO 2 & the Greenhouse Effect  When the amount of carbon dioxide in the atmosphere increases, average global temperature rises.  Longwave radiation emitted by CO 2 is absorbed by the surface, so average global temperature rises

43. Emissions -> More CO2 in Air -> Higher Temperature 15° 18°

44. Climate Sensitivity - definition Whenever the amount of carbon dioxide in the atmosphere doubles, average global temperature rises by 3 degrees Celsius. 15° 18° 15° 18°

45. Learning from the Past (ice cores) Ice age

46. CO 2 Emissions – Where are we now? In 2013, CO 2 emissions are around 10 gigatons (GtC) per year (10,000 million tons in units used on this graph)

47. CO 2 in Atmosphere – Where are we now? ice age 396 ppm in 2013  For hundreds of thousands of years, CO 2 varied between 180 and 280 parts per million, beating in time with ice ages  Since the Industrial Revolution, CO 2 has risen very rapidly to about 400 ppm today

48. Math of Climate Sensitivity When the CO2 concentration in the atmosphere doubles, temperature rises by 3°Celsius (about 5.4°F) Examples:  If CO 2 rises from 200 ppmv to 400 ppmv, temperature rises 3°C  If CO 2 rises from 400 ppmv to 800 ppmv, temperature rises 3°C  Note: as CO 2 rises from 200 to 800 ppmv (800 = 4 x 200), temperature rises 6°C ( = 2 x 3 degrees, not 4 x 3 degrees)

49. Climate Sensitivity Calculator demo spark.ucar.edu/climate-sensitivity-calculator

50. Climate Sensitivity Calculator Activity Use the calculator (previous slide) to determine the expected temperature for the various CO 2 concentrations listed in column 1 of the table above (students fill in column 2); then have them graph.

51. Advanced Climate Sensitivity Math T = T 0 + S log 2 (C / C 0 ) T : new/current temperature T 0 : reference temperature (e.g. 13.7 degrees C in 1820) S : climate Sensitivity (3 degrees C) C : new/current atmospheric CO 2 concentration C 0 : reference atmospheric CO 2 concentration (e.g. 280 ppmv in 1820) Example: What is new temperature if CO2 rises to 400 ppmv (from 280 ppmv)? T = T 0 + S log 2 (C / C 0 ) = 13.7 + 3 log 2 (400/280) = 13.7 + 3 log 2 1.43 = 13.7 + 1.54 = 15.2 degrees C

52. Dry air mass of atmosphere = 5.135 x 10 18 kg = 5,135,000 Gigatons CO 2 currently about 599 ppm by mass (395 ppmv) = 0.0599% CO 2 current mass = 0.0599% x 5,135,000 Gt = 3,076 Gt CO 2 current emissions = 9.5 GtC/year Atmospheric fraction = 45% M = M 0 + [0.45 x (3.67 x m)] = 3,076 GtCO 2 + [0.45 x (3.67 x 9.5 GtC/yr)] = 3,076 + 15.7 GtCO 2 = 3,092 GtCO 2 CO 2 concentration = 3,092/5,135,000 = 602 ppm by mass CO 2 concentration = (602/599) x 395 ppmv = 397 ppmv Math of CO 2 Emissions and Atmospheric Concentration (16 + 12 + 16) / 12 = 44/12 = 3.67 GtC vs GtCO 2

53. Poll: Rising Emissions B A C ? ? ?

54. B A C ? ? ?

55. B A C ? ? ? Poll: Emissions rise then steady

56. B A C ? ? ? Poll: Emissions rise then fall

57. Very Simple Climate Model demo spark.ucar.edu/simple-climate-model

58. Why does temperature continue to rise as emission rate declines? Atmosphere CO 2 in Atmosphere CO 2 Emissions CO 2 Removal by Oceans & Plants spark.ucar.edu/climate-bathtub-model-animations-flow-rate-rises-falls spark.ucar.edu/imagecontent/carbon-cycle-diagram-doe

59. Contact Us Teri Eastburn eastburn@ucar.edu 303.497.1000 Randy Russell rrussell@ucar.edu 303.497.1000