Climate Change: An Inter-disciplinary Approach to Problem Solving (AOSS 480 // NRE 480)

1. Climate Change: An Inter-disciplinary Approach to Problem Solving(AOSS 480 // NRE 480) Richard B. Rood Cell: 301-526-8572 2525 Space Research Building (North Campus) rbrood@umich.edu http://aoss.engin.umich.edu/people/rbrood Winter 2015 February 3, 2015

2. Class Information and News • Ctools site: AOSS_SNRE_480_001_W15 • Record of course • Rood’s Class MediaWiki Site • http://climateknowledge.org/classes/index.php/Climate_Change:_The_Move_to_Action • A tumbler site to help me remember • http://openclimate.tumblr.com/

3. Resources and Recommended Reading • Paul Edwards: A Vast Machine • Rood’s Series on Bumps and Wiggles

4. Outline: Class 8, Winter 2015 • Thought problems • How to measure Earth has warmed? • “Ice-age” figure and observations • Observations: The observing system • Some examples • Characteristics of observing systems • “Internal” Variability

5. Question for Rumination • Madden and Ramanathan Predicted in 1980 that warming would be discernable in 2000. • What would you do to evaluate the theory and predictions of global warming? • Surface of planet will warm • Sea level will rise • Weather will change • Think about • Measurements • Feedbacks • Correlative behavior • Impacts

6. Return to the “Ice-Age” picture • From an observational perspective, what are the characteristics, challenges of this figure?

7. Times of low temperature have glaciers, ice ages (CO2 <~ 200 ppm) • Times of high temperature associated with CO2 of < 300 ppm Bubbles of gas trapped in layers of ice give a measure of temperature and carbon dioxide 350,000 years of Surface Temperature and Carbon Dioxide (CO2) at Vostok, Antarctica ice cores • During this period, temperature and CO2 are closely related to each other

8. Observations: What do we measure? • Foundation of scientific method • What is etymology of phenomenon? • What do we measure? • Temperature • Precipitation • Carbon dioxide • That which allows us to calculate budgets • To diagnose, analyze, understand • To predict

9. “How” do we measure climate? • Strategy • “Technology” • Difference between “weather” and “climate” observations?

10. Proxy measures • Glaciers • Tree rings • Pollen • Ice cores • contain tiny bubbles of ancient air — not really a proxy, but a direct measure • Corals • Many others

11. Observations: The Observing System

12. Surface Air Temperature • Why do we use this as a measure of climate?

13. United States Temperature

14. U.S. Surface Observations 1828 http://www.ncdc.noaa.gov/oa/ncdc.html

15. U.S. Surface Observations 1848 http://www.ncdc.noaa.gov/oa/ncdc.html

16. U.S. Surface Observations 1888 http://www.ncdc.noaa.gov/oa/ncdc.html

17. Global Surface Temperature Observations http://www.ncdc.noaa.gov/oa/ncdc.html

18. Surface observations • What is most disturbing about the surface observations in the previous figure?

19. Looking up and down

20. Down in the ocean

21. ERROR IN DATA IPCC Ocean Heat Content

22. Error in Ocean Data Set Ocean Cooling Correction • Outgoing Energy • Sea level rise • Direct comparisons with other observations

23. Up in the air

24. Temperature Above the Ground A Balloon Borne Radiosonde

25. Balloon Radiosonde Average vertical temperature profile Very high vertical resolution. Most accurate measurement in the atmosphere. (This is representative of the tropics)

26. Balloon (radiosonde) network (2001)

27. “Climate” Radiosondes Selected because of length and quality of the record. Revisit this data and look for errors and correct them. Commitment to standards in the future. … See: http://www.ncdc.noaa.gov/oa/cab/igra/index.php http://www.ncdc.noaa.gov/oa/cab/ratpac/index.php

28. What about satellites?

29. Satellites • Satellites can measure the absorption or emission of radiative energy. • This energy can be related to temperature. • This is not easy. • Satellite is going fast. • Launching shakes things up. • Space is a harsh environment. • Once you have a radiance measurement, how do you make it temperature? • Absolute calibration from one satellite to the next

30. Why satellite data? Coverage, coverage, coverage. Only calibrate one instrument.

31. The Elements of the Data System • Applications: Prediction and Hindcast • Objective evaluation of change • Alternative scenarios for climate forcings • How to use observations in prediction • Predictions for multi-member ensembles Research Satellite • Applications: Process Definition • - Definition of physical mechanisms • Use of observations to • define feedback mechanisms • - Reanalysis data sets Operational Satellite • Observation mission support • - Quality Control/Instrument Monitoring • Validation (linking different scales) • Definition of future observing system • Retrieval of geophysical parameters Conventional

32. Characteristics of data systems

33. Characteristics of data systems (1) • Coverage varies with time • Coverage is high in some areas, low in others • Where people live • Data, for the most part, not taken for climate • Weather • Agriculture • Transportation • Research • …

34. Characteristics of data systems (2) • Quality control of calibration • How does instrument hold up over time? • New types of instrument • New manufacturers of instrument • Different countries have different instruments • … • The measurement site changes • The tree grows up and it’s in the shade • A parking lot is built • They move the airport • …

35. Characteristics of data systems (3) • The measure site isn’t “representative” • Next to the harbor • Top / Bottom of the hill • In the middle of the city • Next to the exhaust vent • Measurement standards vary • 12 inches off the ground • 5 feet off the ground • Shielded from sun and wind • Time of day it is recorded • The data is recorded incorrectly • …..

36. Changes in instrumentation (Karl et al. 1993)(Thank you Paul Edwards)

37. Note: There is consistency from many models, many scenarios, that there will be warming. (1.5 – 5.5 C) Also, it’s still going up in 2100! Basic physics of temperature increase is very simple, non-controversial. This represents the uncertainties in the observations

38. Some prominent data controversies • Surface temperature observations • Satellite versus surface trends • Ocean heat content • Warming “hiatus”

39. Back to that thought problem

40. Question for Rumination • Madden and Ramanathan Predicted in 1980 that warming would be discernable in 2000. • What would you do to evaluate the theory and predictions of global warming? • Surface of planet will warm • Sea level will rise • Weather will change • Think about • Measurements • Feedbacks • Correlative behavior • Impacts

41. Internal variability

42. Temperature and CO2: The last 1000 years Surface temperature and CO2 data from the past 1000 years. Temperature is a northern hemisphere average. Temperature from several types of measurements are consistent in temporal behavior.

43. Schematic of a model experiment. Model prediction without forcing Model prediction with forcing Model prediction with forcing and source of internal variability Observations or “truth” T Start model prediction T Eat+Dt=Eat + Dt((Pa – LaEa)+(Traoil+Ma ))

44. Sources of internal variability • There is “natural” variability. • Solar variability • Volcanic activity • Internal “dynamics” • Atmosphere - Weather • Ocean • Atmosphere-ocean interactions • Atmosphere-ocean-land-ice interactions • “Natural” does not mean that these modes of variability remain constant as the climate changes. Separation of “natural” and “human-caused.”

45. Energy doesn’t just come and go • The atmosphere and ocean are fluids. The horizontal distribution of energy, causes these fluids to move. That is “weather” and ocean currents and the “general circulation.” • “General circulation” is the accumulated effect of individual events.

46. Transport of heat poleward by atmosphere and oceans • This is an important part of the climate system • One could stand back far enough in space, average over time, and perhaps average this away. • This is, however, weather ... and weather is how we feel the climate day to day • It is likely to change because we are changing the distribution of average heating

47. Some Aspects of Climate Variability • One of the ways to think about climate variability is to think about persistent patterns of weather • Rainy periods • Floods • Dry periods • Droughts • During these times the weather for a region does not appear random – it perhaps appears relentless

48. An example of variability: Seasons Warm Cold Cold Temperature Messy Messy Winter Summer Winter Rain comes in thunderstorms Rain comes in fronts Forced variability responding to solar heating

49. Wave Motion and Climate

50. Internal Variability? • Weather – single “events” – waves, vortices • There are modes of internal variability in the climate system which cause global changes. • El Niño – La Niña • What is El Niño • North Atlantic Oscillation • Climate Prediction Center: North Atlantic Oscillation • Annular Mode • Inter-decadal Tropical Atlantic • Pacific Decadal Oscillation