1. The challenges of climate change
Lecture 3 – Forcings and Feedback

2. Outline of course Do we understand the science behind climate change?
Historical climate
Basics of climate science
Modeling the climate
Understanding the uncertainty
What are the implications of climate change?
Biological/environmental implications
Economic political implications
What human actions can be taken to address climate change?
Individual action
Political action
Technology
Economic action
Sources of inertia

3. A greenhouse Energy in = Energy out Energy in = 2 Energy out E ½ E
Greenhouse gas E E
½ E
in-coming
Re-radiated E
Earth Surface

4. Radiative forcing Imbalance in incoming and outgoing radiation
Top of troposphere
(W/m2)
Pre-industrial CO2 = 280 ppm,
now = 400 ppm
x2 CO2
T=15 oC
T=15 oC
T= oC
Earth surface
Radiative forcing arises from all greenhouse gases, and can be assessed via global warming potential

5. Land Use

6. Aerosol forcing
Aerosols are particulate matter in the atmosphere – natural (e.g. volcanoes, ice, sand) and anthropogenic (carbon etc).
Can create two types of forcing (not feedback).
DIRECT
Global dimming (negative, 2 W/m2)
INDIRECT
Changes in cloud chemistry, albedo and lifetime (negative 1.5 W/m2)

7. Climate Sensitivity
Change in temperature for a given radiative forcing
G0= Change in temperature / Change in forcing = 0.27 oC/W/m2

8. Feedback Change Positive Negative Change Positive Negative
Note: Feedback can be unstable

9. Daisyworld

10. Daisyworld
Black daisies like it cool

11. Daisyworld
Black daisies like it cool
White daisies like the heat

12. Daisyworld Black daisies like it cool White daisies like the heat
At early times the star is faint (like the sun)

13. Daisyworld Black daisies like it cool White daisies like the heat
At early times the star is faint (like the sun)
Black daisies dominate, albedo is low, and temperature rises.

14. Daisyworld Black daisies like it cool White daisies like the heat
At early times the star is faint (like the sun)
Black daisies dominate, albedo is low, and temperature rises.
White daisies begin to grow, albedo rises

15. Daisyworld Black daisies like it cool White daisies like the heat
At early times the star is faint (like the sun)
Black daisies dominate, albedo is low, and temperature rises.
White daisies begin to grow, albedo rises.
As planet gets much hotter, white daisies dominate.

16. Daisyworld
No daisies
With daisies
Temperature
Time

18. Ca 6m sleq possibly vulnerable
Ca 70m sleq total
Ca 6m sleq possibly vulnerable
Flemming et al. 1998

19. Blackbody feedback Peak proportional to Temperature
Energy out proportional to T4
Note: T in Kelvin

20. Blackbody feedback Constant heat input (e.g. boiling a pan of water)
Negative feedback
Temperature
Time
Higher temperatures => Greater energy loss (T4)

21. Water Vapour Feedback Water vapour is dominant greenhouse gas
Increased water vapour increases absorption in IR
Causes additional increases in temperature
Water saturation
(mid troposphere)
<-Simulation
Observed->

22. Clouds? Complex and controversial
Clouds are white, they reflect sunlight (negative feedback)
Clouds have high humidity, so lots of water vapour (positive feedback)
Probably a negative feedback, but level of scientific understanding still poor (but improving, see IPCC AR5).

23. Figure TS.5
Radiative Forcings
IPCC AR4 2007

24. IPCC AR5 2013

25. “Real” Climate Sensitivity
No feedback
With feedback

26. Radiative forcing Imbalance in incoming and outgoing radiation
Top of troposphere
With feedback
x2 CO2
T=15 oC
T=15 oC
T= oC
T= oC
Earth surface
Pre-industrial CO2 = 280 ppm,
now = 400 ppm

27. The scary stuff – non-linear feedback
Shutting down of the North Atlantic Thermohaline circulation
North atlantic surface temperature
salinity

28. Ocean Circulations

30. The younger dryas

31. Avoiding “non-linear” events
The risk of irreversible change increases with temperature rises
Vulnerability of ice sheets increases
Larger degree of permafrost melting
Breakdown of biomass in rainforests
Smaller rises minimize this risk, 2 degrees is thought to be reasonable (450 ppm CO2) but there is still much uncertainty (week 4).

32. Conclusions
Detailed measurements enable the degree of imbalance between incoming and outgoing radiation from various physical processes to be calculated as a radiative forcing
Anthropogenic changes are amplified by feedbacks, which makes climate twice as sensitive to changes as might otherwise be expected.
Potential for major, and irreversible (on the short term) changes exist.

33. The challenges of climate change
Lecture 4 – Modeling the Climate

34. Weather is not climate
Daily Express 2013
Daily Express (yesterday)

35. Ocean Atmosphere General Circulation Models (OAGCM)
AIM: To enable projections of future climate

36. What’s in a model Basic physics Conservation laws Equations of state
Transport of energy via convection/radiation
Moist processes (evaporation/condensation etc)
Geography/resolution
Ab initio
Parameterization

37. State of art ca 1997
Major Volcanos
-> Major volcanic eruptions are a visible and predictable perturbation on the climate.

38. Climate
Weather

39. State of the art ~today

40. State of the art ~today
Models are highly advanced (e.g. GEOS-5) BUT still fail to match some detailed measurements
……These errors include: too strong surface wind stress in high latitudes; too strong cloud radiative forcing in low latitudes, and too weak cloud radiative forcing in high latitudes; errors in precipitation typical of most state-of-the-art climate models, e.g.,a strong double Inter-Tropical Convergence Zone (ITCZ). (Vikhliaev et al. GEOS-5)

41. “Greenhouse gas forcing has very likely [90%] caused most
“Warming of the climate is unequivocal”, “It is extremely likely that human influence has been the dominant cause of the observed warming”
IPCC 2013
“Greenhouse gas forcing has
very likely [90%]
caused most
of the observed global warming over the last 50 years.”
IPCC 2007
….likely [67%]..
IPCC 2001
IPC 2007
Figure TS.23. (a) Global mean surface temperature anomalies relative to the period 1901 to 1950, as observed (black line) and as obtained from simulations with both anthropogenic and natural forcings. The thick red curve shows the multi-model ensemble mean and the thin lighter red curves show the individual simulations. Vertical grey lines indicate the timing of major volcanic events. (b) As in (a), except that the simulated global mean temperature anomalies are for natural forcings only. The thick blue curve shows the multi-model ensemble mean and the thin lighter blue curves show individual simulations. Each simulation was sampled so that coverage corresponds to that of the observations. {Figure 9.5}

42. Inevitable Problems of projection
Even with a perfect model:
Anthropogenic changes in future climate depend on human activity – need different scenarios (SRES)
Some natural variations (e.g. volcanoes) are unpredicatable, so can’t be easily folded in.

43. Potentially soluble problems with projection
Garbage in = Garbage out (GIGO)
Real world is complex
Geography
Ocean cycles (El Nino etc)
Real physics is complicated and not all well understood.
Water
Radiative transfer

44. Special Report on Emissions ScenariosB2
Population peaks mid century.
A1: technology-led economy,
F fossil fuels vs ( B “balanced” ) vs T non-fossil fuelled.
B1: info & service economy; sustainability & global sol’ns.
Population continues to increase.
A2: very heterogeneous world (“business as usual”)
B2: lower growth rate; emphasis on local solutions (smart but laissez-faire)
not predictions, but a range of plausible assumptions

45. Figure TS.28
IPCC 2007: Scenario -> OAGCM -> Climate prediction

46. IPCC 2007

47. Figure TS.29. Decadal mean continental surface temperature anomalies (°C) in observations and simulations for the period 1906 to 2005 and in projections for 2001 to Anomalies are calculated from the 1901 to 1950 average. The black lines represent the observations and the pink and blue bands show simulated average temperature anomalies as in Figure TS.22 for the 20th century (i.e., pink includes anthropogenic and natural forcings and blue includes only natural forcings). The yellow shading represents the 5th to 95th percentile range of projected changes according to the SRES A1B emissions scenario. The green bar denotes the 5th to 95th percentile range of decadal mean anomalies from the 20th-century simulations with only natural forcings (i.e., a measure of the natural decadal variability). For the observed part of these graphs, the decadal averages are centred on calendar decade boundaries (i.e., the last point is at 2000 for 1996 to 2005), whereas for the future period they are centred on calendar decade mid-points (i.e., the first point is at 2005 for 2001 to 2010). To construct the ranges, all simulations from the set of models involved were considered independent realisations of the possible evolution of the climate given the forcings applied. This involved 58 simulations from 14 models for the red curve, 19 simulations from 5 models (a subset of the 14) for the blue curve and green bar and 47 simulations from 18 models for the yellow curve. {FAQ 9.2.1, Figure 1 and Box 11.1, Figure 1}

48. The last 20 years
IPCC 2013

49. Hallmarks of real warming
Carbon dioxide and other greenhouse gases can have their radiative forcing directly measured.
Stratospheric cooling, more heat is being returned to Earth than escapes.
The re-radiated IR emission has been directly observed.
Models only re-create recent past temperature trends with the addition of anthropogenic forcing
Nights are warming faster than days
The ocean is warming from the top down

50. Not only global warming
Sea level rises – loss of habitat, fish spawning grounds etc.
CO2 absorbed in the ocean causes acidification
More on implications next lecture.

51. Think about how you might now answer these critics
Doubting voices
Massive, non-anthropogenic climate change has occurred in the past, and will happen in the future.
Human activity is dwarfed by natural processes which render the impact of e.g. fossil fuel burning on global climate negligible.
Evidence for recent warming depends critically on the data and time range chosen.
There is insufficient evidence to conclude that anthropogenic global warming is occurring.
Think about how you might now answer these critics

52. Justifiable concerns?
Statistical and systematic errors on direct measurement
Baselines for temperature proxies
Attribution
Past performance is not a good guide to future return

53. Real data Measurements aren’t perfect………. Thermometers
Statistical errors affect the accuracy to which the thermometer can be read – inevitable, and act in both directions.
Systematic errors reflect additional sources of uncertainty, and often act in a single direction

54. Temperature proxies

55. Natural variability

56. Simple temperature records
Strongly dependent on quality of data, and local effects (note the units of the x-axis are standard deviations, not degrees)

57. IPCC approach
Note that improved treatment of uncertainty is a “key goal” of AR5

58. Attribution
A warming record does not attribute the cause