GCM climate projections

The IPCC 2001 report distinguishes between climate prediction and climate projection. A climate projection describes the response of the climate system to emission or concentration scenarios of greenhouse gases and aerosols, or radiative-forcing scenarios, based upon simulations by climate models. Climate projections depend upon the forcing scenarios used, which are based on assumptions, concerning, e.g. future socio-economic and technological developments, that may or may not be realized, and are therefore subject to substantial uncertainty.

In Chapter 1 we discussed the IPCC Special Report on Emission Scenarios (SRES), scenarios that were used as a basis for climate projections in the IPCC 2001 report. Four scenario families, each with a similar demographic, societal, economic and technical-change storyline, comprise the baseline set. Probably the most important are A2 (medium-high emissions), which describes a world of self-reliance and preservation of local economic and technological identities, and B2, in which the emphasis is on local solutions to economic, social and environmental sustainability. Both feature a continuously increasing global population, B2 at a rate lower than A2.

11.5.1 SRES emission scenarios

Apart from co2, for which deforestation and land-use values are given, the SreS scenarios define only the changes in direct anthropogenic emissions of gases and do not specify the current magnitude of the natural emissions nor the concurrent changes in natural emissions due either to direct human activities such as land-use change or to the indirect impacts of climate change.

11.5.1.1 Emissions Table 11.9 gives the total anthropogenic emissions for the SreS A2 scenario. The co2 emission sources are fossil fuel, industrial, deforestation and land use. The projection by the end of the twenty-first century is for almost a trebling in co2, cH4, co and No, emissions, a doubling of N2o emissions and an initial rise in So2 emissions followed by a decline to below present levels. The SreS emission scenarios show a lot of variation in projected emissions over the next century. The B2 scenario gives, as a general rule, a slower rise, reflecting the many uncertainties in industrial, technological and environmental developments to come.

Table 11.9 Anthropogenic emissions for the SRES A2 scenario. CO2 emission (PgC/year) sources are fossil fuel, industrial, deforestation and land use. Units of emission; CH4 (Tg/year), N2 O (TgN/year), NOX (TgN/year), CO (Tg/year), SO2 (TgS/year), and black carbon BC (Tg/year). (Source: IPCC 2001)

Year

co2

ch4

n2o

no,

co

so2

bc

2000

7.97

323

7.0

32.0

877

69.0

12.4

2010

9.58

370

8.1

39.2

977

74.7

13.6

2020

12.25

424

9.6

50.3

1075

99.5

14.8

2030

14.72

486

10.7

60.7

1259

112.5

17.0

2040

16.07

542

11.3

65.9

1344

109.0

18.0

2050

17.43

598

12.0

71.1

1428

105.4

19.0

2060

19.16

654

12.9

75.5

1545

89.6

20.4

2070

20.89

711

13.9

79.8

1662

73.7

21.8

2080

23.22

770

14.8

87.5

1842

64.7

24.0

2090

26.15

829

15.7

98.3

2084

62.5

26.8

2100

29.09

889

16.5

109.2

2326

60.3

29.7

11.5.1.2 Evolution of mixing ratios The evolution of the mixing ratios of co2, cH4 and N2o over this century are given in Table 11.10, based on the SreS A2

Table 11.10 Evolution greenhouse gas mixing ratios (ppmv) for the SRES A2 emission scenarios. The CO2 mixing ratio is based on the Bern-CC (carbon cycle) model (high), while the CH4 and N2O mixing ratios are based on 3D chemistry-transport models. (Source: IPCC 2001)

Year

co2

ch4

n2o

2000

367

1.760

0.316

2010

393

1.861

0.325

2020

431

1.997

0.335

2030

477

2.163

0.347

2040

533

2.357

0.360

2050

597

2.562

0.373

2060

670

2.779

0.387

2070

753

3.011

0.401

2080

848

3.252

0.416

2090

957

3.493

0.432

2100

1080

3.731

0.447

emission scenario.

While the trebling in the anthropogenic emission rate in co2 produced a trebling in the mixing ratio, based on a carbon-cycle model, the rise in the cH4 anthropogenic emission rate to 2.75 times its present rate by the end of the century was translated by a 3D chemistry-transport model to a 2.1 times increase in the methane abundance, a translation ratio of 0.77. We note that the rc climate-photochemical model given in §11.3.5, gave similar results for methane; a doubling of an adopted total global emission rate (anthropogenic plus natural) equivalent to 6.69 times the present (A2 year 2000, Table 11.9) anthropogenic rate was translated to 4.74 times the present (Table 11.4) methane abundance, a translation ratio of 0.71. cH4 and N2o have large, but uncertain, sources of natural emissions, and the anthropogenic emissions of these gases are primarily associated with agricultural sources that are also difficult to quantify accurately.

11.5.1.3 Radiative forcings and temperature change The Ipcc defines the radiative forcing of the surface-troposphere system due, for example to a change in greenhouse-gas concentrations, as the change in net downward (all-wave down minus all-wave up) irradiance at the tropopause, after allowing for stratospheric temperatures to readjust to radiative equilibrium, but with surface and tro-pospheric temperatures and state held fixed at the unperturbed values. The increase relative to the pre-industrial period in the mixing ratios of the greenhouse gases co2, cH4 and N2o, as well as the rise in black-carbon aerosols was translated via simple expressions to radiative forcing in the Iccp 2001 report.

The radiative forcing due to the increases in the well-mixed greenhouse gases from 1750 to 1998 was estimated to be 2.43 W m~2 (warming), comprising

CO2 (1.46 W m-2), CH4 (0.48 W m-2), N2O (0.15 W m-2) and halocarbons (halogen-containing compounds) (0.34 W m-2), with an uncertainty of 10%. For aerosols, models were used to estimate the direct radiative forcing for five distinct species of anthropogenic origin. The global, annual mean radiative forcing is estimated as -0.4 W m-2 (-0.2 to -0.8 W m-2, cooling) for sulphate aerosols; -0.2 W m-2 (-0.07 to -0.6 W m-2) for biomass-burning aerosols; -0.10 W m-2 (-0.03 to -0.30 W m-2) for fossil fuel organic-carbon aerosols; 0.2 W m-2 (0.1 to 0.4 W m-2) for fossil-fuel black-carbon aerosols; and in the range -0.6 to 0.4 W m-2 for mineral-dust aerosols.

11.5.1.4 Climate sensitivity parameter This parameter is defined as the global mean surface temperature response, ATg, to the radiative forcing, AF, (Dickinson 1982; WMO 1986; Cess et al. 1993) and is given by

The concept of radiative forcing thus gives a quick estimate of the global mean annual surface temperature, Tg, response to a radiative forcing. In 1D RC models, where the concept was initiated, A varied slowly with climatic parameters, with a value typically about 0.5 K W m-2 (Ramanathan et al. 1985), for a variety of radiative forcings. In eqn (11.5) we used the notion of radiation balance at the top of the atmosphere to derive a quick estimate of the Earth's effective temperature. We can also derive a similar expression for Tg via the radiative flux balance equation (erg cm-2 s-1)

The planetary albedo is a, while e represents the planetary emissivity that gives a measure of the effect of the surface-atmosphere (greenhouse gases, clouds, surface emissivity and temperature) on the outgoing radiation. Thus, we can translate the radiative forcing arising from changes in the outgoing longwave radiation, AFLW, to temperature changes via

aflw 1

and those due to changes in the solar constant, ASq, from

We can also show that the climate sensitivity parameter corresponding to changes in the reflected solar shortwave to space is Arsw = — ALW/4. For the present

Table 11.11 Radiative forcings (W m-2) for year 2000 relative to the pre-industrial period 1970, for the SRES A2 scenario, for the greenhouse gases CO2, CH4 and N2O, and total radiative forcing together with its corresponding estimated translation to global annual mean surface temperature change based on eqn (11.24). (Radiative forcings from, IPCC 2001)

Table 11.11 Radiative forcings (W m-2) for year 2000 relative to the pre-industrial period 1970, for the SRES A2 scenario, for the greenhouse gases CO2, CH4 and N2O, and total radiative forcing together with its corresponding estimated translation to global annual mean surface temperature change based on eqn (11.24). (Radiative forcings from, IPCC 2001)

Year

co2

CH4

n2o

Total

A Ts

2000

1.49

0.49

0.15

2.13

0.64

2010

1.85

0.53

0.18

2.56

0.77

2020

2.35

0.58

0.21

3.14

0.94

2030

2.89

0.63

0.25

3.77

1.13

2040

3.48

0.70

0.29

4.47

1.34

2050

4.09

0.76

0.33

5.18

1.55

2060

4.71

0.83

0.37

5.91

1.77

2070

5.33

0.89

0.41

6.63

1.99

2080

5.97

0.96

0.45

7.38

2.21

2090

6.61

1.02

0.49

8.12

2.44

2100

7.26

1.09

0.53

8.88

2.66

earth we can set e « 0.61, and Tg = 288 K, with Sq = 1367 W m 2 and using a = 5.669 x 10-8 W m-2K-4, we obtain for the climate sensitivity parameters

Thus, a radiative forcing AFLw = 2.4 Wm-2 translates to a warming of ATg = 0.72 K, a 1% change in the solar constant or ASq = 13.67 W m-2 translates to a corresponding change ATg = 0.68 K, and a 1% change in the outgoing shortwave radiation, typically 1 W m-2, translates to a 0.075 K change.

In Table 11.11 are given the radiation forcings based on the reference year 1750 for the SreS A2 emission scenario. We see that the trebling in co2 mixing ratio over the twenty-first century is translated to almost 5 times in radiative forcing. The estimated change in global annual mean surface temperature to bring the planet back into radiative equilibrium, neglecting solar radiation and planetary albedo changes, is also given.

11.5.2 Global change in temperature

Most model experiments show broadly the same pattern for the change in annual mean surface air temperature. There is a maximum warming in the high latitudes of the Northern Hemisphere and a minimum in the Southern ocean, due to ocean heat uptake (see the example in Fig. 11.6). ocean heat uptake also contributes to a minimum of warming in the North Atlantic, while land

120W

120E

120W

120E

flG. 11.6. The multimodel ensemble annual mean change of the temperature (shading), its range (thin isolines) (Unit: C) and the multimodel mean change divided by the multi-model standard deviation (solid isolines, absolute values) for the SRES A2 scenario. It shows the period 2071-2100 relative to the period 1961-1990. (Source: IPCC 2001)

warms more rapidly than ocean almost everywhere. The large warming in high latitudes of the Northern Hemisphere is connected with a reduction in the snow and sea-ice cover. There is also consistent midtropospheric tropical warming and stratospheric cooling. The range tends to increase with altitude, partly due to the variation in the level of the tropopause among the models.

For the SRES A2 scenario the mean change is 1.1 C with a range from 0.5 to 1.4 °C; while for B2, the mean is 1.2 °C with a range from 0.5 to 1.7 °C. By the end of the twenty-first century (2071 to 2100), the global average surface temperature change is 3.0 °C with a range 1.3 to 4.5 °C, while for B2 the mean SAT change is 2.2 °C with a range is 0.9 to 3.4 °C. The evolution of the temperature change for some of the models involved in these experiments appears in Fig. 11.7.

11.5.3 Global change in precipitation

Figure 11.8 shows the global distribution of the relative change in the mean precipitation for the SRES A2 emission scenario for the period 2071-2100 relative to the period 1961-1990. There is a general increase in the tropics, particularly the tropical oceans and parts of northern Africa and south Asia, and the mid-and high latitudes, while the rainfall generally decreases in the subtropical belts.

1990

2010

2030 2050

Year

2070

2090

1990

1990

2010

2030 2050

Year

2070

2090

1990

2010

2030

2050 Year

2070

2090

2010

2030

2050 Year

2070

2090

flG. 11.7. The time evolution of the globally averaged temperature change relative to the baseline period 1961-1990 of the SRES simulations A2 (top) and B2 (bottom) (Unit: C), produced by various AOGCMs. (Source: IPCC 2001)

Over the central and eastern tropical Pacific, an El Nino-like surface temperature warming is associated with an eastward shift of precipitation. The A2 scenario experiment exhibits a relatively large percentage increase in precipitation over the Sahara and Arabia, although in absolute values the precipitation amount gained by these very dry regions is very small. Figure 11.9 shows the time evolution of the globally averaged precipitation change for the SRES A2 and B2 scenarios. For the 30-year average for the period 2071-2100 the increase that the A2 scenario gives is 3.9% with a range of 1.3 to 6.8%, while the B2 scenario gives an increase of 3.3% with a range of 1.2 to 6.1%. The lower precipitation increase values for the B2 scenario are consistent with less globally averaged warming for that scenario at the end of the twenty-first century compared to A2.

180 120W 60W 0 60E 120E 180

180 120W 60W 0 60E 120E 180

flg. 11.8. The multimodel ensemble annual mean change of the precipitation (shading), its range (thin isolines) (Unit: %) and the multimodel mean change divided by the multimodel standard deviation (solid isolines, absolute values) for the SRES A2 scenario. Shown is the period 2071-2100 relative to the period 1961-1990. (Source: IPCC 2001)

11.5.4 Global change in sea level

The main processes that are expected to result in increased sea levels are thermal expansion, snow and ice sublimation, and melting and break-up of ice sheets, particularly that of Greenland. Snow and ice accumulation over Antarctica, due to lower temperatures there, are expected to contribute to a drop in sea level.

11.5.4.1 Thermal expansion In a warmer world, the volume of the ocean will increase and its density will decrease, at a rate that (for both atmosphere and ocean) depends strongly on the rate at which heat is stored in the deeper oceanic layers. The large heat-storage capacity of the oceans means that the oceans will not be in equilibrium on timescales of centuries, so that the global average sea level will initially be slow to rise but will continue to increase well after atmospheric greenhouse-gas concentrations have stabilized. The rise is not the same everywhere, since local sea levels are influenced by atmospheric pressure, air-sea exchange of mass, momentum and energy fluxes, and gains via land runoff and ice inputs. Salinity changes, in particular, affect the local sea-water density and thus local sea level. The geographical distribution of sea-level change due to density and circulation changes can be obtained from AOGCM results. The IPCC summary suggests that over the last hundred years the average rate of

1990 2010 2030 2050 2070 2090

Year

1990 2010 2030 2050 2070 2090

Year

1990 2010 2030 2050 2070 2090

Year

1990 2010 2030 2050 2070 2090

Year flg. 11.9. The time evolution of the globally averaged precipitation change relative to the baseline period 1961-1990 of the SRES simulations A2 (top) and B2 (bottom) (Unit: %), produced by various AOGCMs. (Source: IPCC-2001)

sea-level rise due to thermal expansion was in the range 0.3-0.7 mm/year, rising to 0.6-1.1 mm/year in recent decades.

11.5.4.2 Glaciers and ice sheets The present Greenland and Antarctic ice sheets contain enough water to raise the sea level by almost 70 m, so that only a small fractional change in their volume would have a significant effect. The average annual snowfall onto the ice sheets is equivalent to 6.5 mm of sea level, this input being approximately balanced currently by the loss from melting and icebergs. Antarctic temperatures are very low, so melting is unimportant and water is lost mainly as floating ice shelves, which eventually break up to form

Table 11.12 The average total sea-level change (mm) for the SRES A2 scenario, based on the results of various AOGCMs. Also shown are important components of sea-level change; thermal expansion (TE), glaciers and ice caps (GIC), Greenland (G), and Antarctica (A). Note that the sum of the various components of sea-level change do not add up to the average owing to the addition of other terms. (Source: IPCC 2001)

Table 11.12 The average total sea-level change (mm) for the SRES A2 scenario, based on the results of various AOGCMs. Also shown are important components of sea-level change; thermal expansion (TE), glaciers and ice caps (GIC), Greenland (G), and Antarctica (A). Note that the sum of the various components of sea-level change do not add up to the average owing to the addition of other terms. (Source: IPCC 2001)

Year

Total

TE

GIC

G

A

2000

17

10

4

0

-2

2010

38

23

10

1

-5

2020

61

39

16

2

-8

2030

88

57

23

4

-12

2040

120

81

31

5

-17

2050

157

109

41

7

-23

2060

201

142

52

10

-31

2070

250

180

65

13

-40

2080

304

224

79

16

-50

2090

362

272

93

20

-62

2100

424

325

108

25

-76

icebergs. In contrast, Greenland summer temperatures are high enough to cause widespread melting, which accounts for about half of the ice loss, the remainder being discharged as icebergs and small ice shelves.

For Greenland, estimates of the response to a 1 °C local warming over the ice sheet range from about 0.1 to 0.4 mm/year increase in global sea level (Table 11.12). This range mainly reflects differences in the predicted precipitation changes and the yearly distribution of temperature increase, predicted to be larger in winter than in summer. Some palaeoclimatic data from central Greenland ice cores indicate that variations in precipitation during the Holocene were related to changes in atmospheric circulation rather than directly to local temperature.

For Antarctica, the predicted response to a 1 °C warming is a sea-level decrease of about 0.4 mm/year. The role of melting is insignificant, even for summer temperature increases of a few degrees, so that only accumulation of snow/ice is important resulting in a reduction in sea level. In a warmer climate, changes in atmospheric circulation and increased moisture advection might become equally important, in particular close to the ice-sheet margin.

Antarctica is predicted to play a larger role than Greenland in a realistic scenario, so that the net effect of both polar ice sheets could be to contribute a net decrease to the sea level budget, which still increases overall (Table 11.12). The average total sea-level change evolution based on AOGCMs with climate sensitivities in the range 1.7 to 4.2 °C is shown in Table 11.13. For the complete range of AOGCMs and SRES scenarios, and including uncertainties in land-ice changes,

Table 11.13 Final rise (m) in sea level due to thermal expansion in 2xCO2 and 4x CO2 experiments, produced by various climate models, after stabilization of CO2 levels. (Source: IPCC2001)

Model

2xC02

4xCO:

CLIMBER

0.78

1.44

ECHAM3/LSG

1.53

2.56

GFDL-R15-a

1.96

3.46

BERN2D GM

1.93

3.73

BERN2D HOR

1.28

4.30

UVic GM

0.53

1.24

UVic H

1.19

2.62

UVic HBL

0.65

1.78

flG. 11.10. Model results of projected global mean temperature changes when the concentration of CO2 is stabilized. The broken lines after 2100 indicate increased uncertainty in the simple climate model results. The black dots indicate the time of CO2 stabilization. (Source: IPCC 2001)

permafrost changes and sediment deposition, global average sea level is projected to rise by 0.09 to 0.88 m over the period 1990 to 2100, with a central value of 0.48 m. The central value gives an average rate of 2.2 to 4.4 times the rate that was recorded over the twentieth century.

Predictions beyond 2100 are very uncertain, not least because it is virtually impossible to guess what will be the levels of anthropogenic emissions. However, it is possible to estimate what will happen in the very long term if emissions are stabilized at the levels that might be reached by the end of the present century. As already noted, thermal expansion and ice sheet changes are likely to continue, since the processes involved have very long characteristic times of change. According to the modellers, the sea level would continue to rise for many centuries, perhaps reaching increases of 3 m or more over present levels (Table 11.13), even after greenhouse gas concentrations have stabilized (Fig. 11.10).

11.6 Bibliography

11.6.1 Notes

For an early review on radiative-convective (RC) modelling see Ramanathan and Coakley, and references therein.

For the convective adjustment approach to RC modelling see early work of Man-abe and Strickler, Manabe and Wetherald. For parameterizations for solar and terrestrial radiation transfer see Ramanathan; and Vardavas and Carver.

GCM model descriptions can be found in Pope et al., Roeckner et al. and Collins et al.

11.6.2 References and further reading

Aspray, W. (1990). John von Neumann and the origins of modern computing. MIT Press, Cambridge, MA.

Cess, R. D. and coauthors (1993). Uncertainties in CO2 radiative forcing in atmospheric general circulation models. Science, 262, 1252-1255.

Charney, J. G., Fjortoft, R. and von Neumann, J. (1950). Numerical integration of the barotropic vorticity equation. Tellus, 2, 237-254.

Collins, W. D. and coauthors (2004). Description of the NCAR Community Atmosphere Model (CAM 3.0). NCAR/TN464, NCAR, Boulder, Colorado.

Dickinson, R. E. (1982). Modeling climate changes due to carbon dioxide increase. In: Carbon dioxide review 1982. Clark, W. C. (ed.). Oxford University Press, Oxford.

Goody, R. M. and Yung, Y. L. (1996). Atmospheric radiation: Theoretical basis. Oxford University Press, Oxford.

Houghton, J. T. (1997). Global warming: The complete briefing. 2nd edn., Cambridge University Press, Cambridge.

IPCC, 2001: Climate change 2001: The scientific basis. Contribution of working group I to the Third Assessment Report of the Intergovernmental Panel on

Climate Change. Houghton, J. T., Ding, Y., Griggs, D. J., Noguer, M., van der Linden, P. J., Dai, X., Maskell, K. and Johnson, C. A. (ed.), Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Iribarne, J. V. and Godson, W. L. (1981). Atmospheric thermodynamics. D. Reidel, Dordrecht.

Kiehl, J. T. and Ramanathan, V. (2006). Frontiers in climate modeling. ed., Cambridge University Press, Cambridge.

Lavvas, P. P., Coustenis, A. and Vardavas, I. M. (2007). Coupling photochemistry with haze formation in Titan's atmosphere. Part I: Model description. Planet. Space Sci., in press.

Lopez-Puertas, M. and Taylor, F. W. (2001). Non-LTE radiation transfer in the atmosphere. World Scientific, Singapore.

Manabe, S. and Bryan, K. (1969). Climate calculations with a combined ocean-atmosphere model. J. Atmos. Sci., 26, 786-789.

Manabe, S. and Stouffer, R. J. (1994). Multiple-century response of a coupled ocean-atmosphere model to an increase of atmospheric carbon dioxide. J. Clim., 7, 5-23.

Manabe, S., Smagorinsky, J. and Strickler, R. F. (1965). Simulated climatology of general circulation with a hydrologic cycle. Mon. Weath. Rev., 93, 769-798.

Manabe, S. and Wetherald, R. (1967). Thermal equilibrium of the atmosphere with a given distribution of relative humidity. J. Atmos. Sci., 24, 241-259.

Pope, V. D., Gallani, M. L., Rowntree, P. R. and Stratton, R. A. (2000). The impact of new physical parameterizations in the Hadley Centre climate model -HadAM3. Climate Dynamics, 16, 123-146.

Ramanathan, V. (1976). Radiative transfer within the Earth's troposphere and stratosphere: A simplified radiative-convective model. J. Atmos. Sci., 33, 13301346.

Ramanathan, V. and Coakley, J. A. (1978). Climate modeling through radiative-convective models. Rev. Geophys. Space. Phys., 16, 465-490.

Ramanathan, V., Cicerone, R., Singh, H. and Kiehl, J. (1985). Trace gas trends and their potential role in climate change. J. Geophys. Res., 90, 5547-5566.

Richardson, L. F. (1922). Weather prediction by numerical process. Cambridge University Press, Cambridge.

Roeckner, E. and coauthors. (2003). The atmospheric general circulation model ECHAM5. Max Planck Institute for Meteorology, RN. 239, Hamburg.

Smagorinsky, J., Manabe, S. and Holloway, J. L. (1965). Numerical results from a nine-level general circulation model of the atmosphere. Mon. Weath. Rev., 93, 727-768.

Taylor, F. W. (1991). The greenhouse effect and climatic change. Rep. Prog. Phys., 54, 6, 881-918.

Taylor, F. W. (2002). The greenhouse effect revisited. Reports on progress in physics, 65, 1-25.

Vardavas, I. M. and Carver, J. H. (1984a). Solar and terrestrial parameterizations for radiative-convective models. Planet. Space Sci., 32, 1307-1325.

Vardavas, I. M. and Carver, J.H. (1984b). Comments on the Newton-Raphson method for obtaining temperature profiles from radiative-convective models. Planet. Space Sci., 32, 803-807.

WMO (1986). Atmospheric ozone: 1985, Global ozone research and monitoring project. World Meteorological Organization, Report No. 16, Chapter 15, Geneva, Switzerland.

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