1. Neue Ergebnisse zum anthropogenen Klimawandel
Ein Überblick
Matthias Lüdeke, PIK, Integrated Systems Analysis

2. Themen Klimawandel? – Verursachung? – Zukunft?
Klimawirkungen auf Zivilisation und Natur
Mitigation und Adaptation – Möglichkeiten und deren Kosten

3. 1. Klimawandel Paläokimatologie Klimawandel in den letzten 150 Jahren
Potentielle natürliche und anthropogene Treiber des Klimawandels
Klimamodelle
Attributierung
Prognosen und Szenarien

4. 2. Klimawirkungen
Qualitative Wirkungen von vermehrten Extremereignissen
Wirkungen in Abhängigkeit vom Anstieg der globalen Durchschnittstemperatur
Syndrome und Klimawandel

5. 3. Mitigation/Adaptation
Wachstum und CO2-Effizienz
Technologien und Maßnahmen
Kostenabschätzungen

6. Temperatur-Proxies und atmosphärische Spurengase über die letzten 600000 Jahre
Variations of deuterium (δD; black), a proxy for local temperature, and the atmospheric concentrations of the greenhouse gases CO2 (red), CH4 (blue), and nitrous
oxide (N2O; green) derived from air trapped within ice cores from Antarctica and from recent atmospheric measurements (Petit et al., 1999; Indermühle et al., 2000; EPICA community
members, 2004; Spahni et al., 2005; Siegenthaler et al., 2005a,b). The shading indicates the last interglacial warm periods. Interglacial periods also existed prior to 450
ka, but these were apparently colder than the typical interglacials of the latest Quaternary. The length of the current interglacial is not unusual in the context of the last 650 kyr.
The stack of 57 globally distributed benthic δ18O marine records (dark grey), a proxy for global ice volume fluctuations (Lisiecki and Raymo, 2005), is displayed for comparison
with the ice core data. Downward trends in the benthic δ18O curve reflect increasing ice volumes on land. Note that the shaded vertical bars are based on the ice core age
model (EPICA community members, 2004), and that the marine record is plotted on its original time scale based on tuning to the orbital parameters (Lisiecki and Raymo, 2005).
The stars and labels indicate atmospheric concentrations at year 2000.
Im Folgenden: wenn nicht anders gekennzeichnet, aus dem
4. Assessment Report des IPCC entnommen:

7. Auslöser für den Wechsel von Glazial- und Interglazialperioden
Nächstes Glazial: Beginn frühestens in Jahren
Berger, A.L., and M.F. Loutre, 2002: An exceptionally long interglacial ahead? Science, 297, 1287–1288.

8. Multistabilität, Verstärkung des kleinen Anstoßes durch
den Milankowitsch-Zyklus
(Bsp.: Temperatur-Albedo-Rückkopplung)
MKBL, 07

9. Globale Mitteltemperatur
Annual anomalies of global land-surface air temperature (°C), 1850 to 2005, relative to the
1961 to 1990 mean for CRUTEM3 updated from Brohan et al. (2006). The smooth curves show decadal
variations (see Appendix 3.A). The black curve from CRUTEM3 is compared with those from NCDC (Smith
and Reynolds, 2005; blue), GISS (Hansen et al., 2001; red) and Lugina et al. (2005; green).

10. Trends der jährlichen Durchschnittstemeratur
Linear trend of annual temperatures for 1901 to 2005 (left; °C per century) and 1979 to 2005 (right; °C per decade). Areas in grey have insufficient data to produce
reliable trends. The minimum number of years needed to calculate a trend value is 66 years for 1901 to 2005 and 18 years for 1979 to An annual value is available
if there are 10 valid monthly temperature anomaly values. The data set used was produced by NCDC from Smith and Reynolds (2005). Trends significant at the 5% level are
indicated by white + marks.
IPCC, AR4, nach Smith and Reynolds (2005), NCDC. +: Siginfikanzlevel 5%, grau: Daten ungenügend

11. Trends im Jahresniederschlag
Trend of annual land precipitation amounts for 1901 to 2005 (top, % per century)
and 1979 to 2005 (bottom, % per decade), using the GHCN precipitation data set from NCDC. The
percentage is based on the means for the 1961 to 1990 period. Areas in grey have insufficient
data to produce reliable trends. The minimum number of years required to calculate a trend value
is 66 for 1901 to 2005 and 18 for 1979 to An annual value is complete for a given year if
all 12 monthly percentage anomaly values are present. Note the different colour bars and units in
each plot. Trends significant at the 5% level are indicated by black + marks.
IPCC, AR4, nach GHCN precipitation data set from NCDC. +: Siginfikanzlevel 5%, grau: Daten ungenügend

12. Annual averages of the global mean sea level (mm)
Annual averages of the global mean sea level (mm). The red curve shows reconstructed
sea level fields since 1870 (updated from Church and White, 2006); the blue curve shows coastal tide
gauge measurements since 1950 (from Holgate and Woodworth, 2004) and the black curve is based
on satellite altimetry (Leuliette et al., 2004). The red and blue curves are deviations from their averages
for 1961 to 1990, and the black curve is the deviation from the average of the red curve for the period
1993 to Error bars show 90% confidence intervals.

13. Estimate of the Earth’s annual and global mean energy balance
Estimate of the Earth’s annual and global mean energy balance. Over the long term, the amount of incoming solar radiation absorbed by the Earth and
atmosphere is balanced by the Earth and atmosphere releasing the same amount of outgoing longwave radiation. About half of the incoming solar radiation is absorbed by the
Earth’s surface. This energy is transferred to the atmosphere by warming the air in contact with the surface (thermals), by evapotranspiration and by longwave radiation that is
absorbed by clouds and greenhouse gases. The atmosphere in turn radiates longwave energy back to Earth as well as out to space. Source: Kiehl and Trenberth (1997).
Kiehl, J., and K. Trenberth, 1997: Earth’s annual global mean energy budget. Bull. Am. Meteorol. Soc., 78, 197–206.

14. Reconstructions of the total solar irradiance time series starting as
early as The upper envelope of the shaded regions shows irradiance variations
arising from the 11-year activity cycle. The lower envelope is the total irradiance
reconstructed by Lean (2000), in which the long-term trend was inferred from
brightness changes in Sun-like stars. In comparison, the recent reconstruction of Y.
Wang et al. (2005) is based on solar considerations alone, using a flux transport model
to simulate the long-term evolution of the closed flux that generates bright faculae.

15. Visible (wavelength 0.55 μm) optical depth estimates of stratospheric sulphate
aerosols formed in the aftermath of explosive volcanic eruptions that occurred between 1860 and
2000. Results are shown from two different data sets that have been used in recent climate model
integrations. Note that the Ammann et al. (2003) data begins in 1890.

16. Albedo-Effekt von Aerosolen

17. Recent CO2 concentrations and emissions. (a) CO2 concentrations
(monthly averages) measured by continuous analysers over the period 1970 to
2005 from Mauna Loa, Hawaii (19°N, black; Keeling and Whorf, 2005) and Baring
Head, New Zealand (41°S, blue; following techniques by Manning et al., 1997). Due
to the larger amount of terrestrial biosphere in the NH, seasonal cycles in CO2 are
larger there than in the SH. In the lower right of the panel, atmospheric oxygen (O2)
measurements from flask samples are shown from Alert, Canada (82°N, pink) and
Cape Grim, Australia (41°S, cyan) (Manning and Keeling, 2006). The O2 concentration
is measured as ‘per meg’ deviations in the O2/N2 ratio from an arbitrary reference,
analogous to the ‘per mil’ unit typically used in stable isotope work, but where
the ratio is multiplied by 106 instead of 103 because much smaller changes are
measured. (b) Annual global CO2 emissions from fossil fuel burning and cement
manufacture in GtC yr–1 (black) through 2005, using data from the CDIAC website
(Marland et al, 2006) to Emissions data for 2004 and 2005 are extrapolated
from CDIAC using data from the BP Statistical Review of World Energy (BP, 2006).
Land use emissions are not shown; these are estimated to be between 0.5 and 2.7
GtC yr–1 for the 1990s (Table 7.2). Annual averages of the 13C/12C ratio measured in
atmospheric CO2 at Mauna Loa from 1981 to 2002 (red) are also shown (Keeling et
al, 2005). The isotope data are expressed as δ13C(CO2) ‰ (per mil) deviation from a
calibration standard. Note that this scale is inverted to improve clarity.

18. The global carbon cycle for the 1990s, showing the main annual fluxes in GtC yr–1: pre-industrial ‘natural’ fluxes in black and ‘anthropogenic’ fluxes in red
(modified from Sarmiento and Gruber, 2006, with changes in pool sizes from Sabine et al., 2004a). The net terrestrial loss of –39 GtC is inferred from cumulative fossil fuel
emissions minus atmospheric increase minus ocean storage. The loss of –140 GtC from the ‘vegetation, soil and detritus’ compartment represents the cumulative emissions
from land use change (Houghton, 2003), and requires a terrestrial biosphere sink of 101 GtC (in Sabine et al., given only as ranges of –140 to –80 GtC and 61 to 141 GtC,
respectively; other uncertainties given in their Table 1). Net anthropogenic exchanges with the atmosphere are from Column 5 ‘AR4’ in Table 7.1. Gross fluxes generally have
uncertainties of more than ±20% but fractional amounts have been retained to achieve overall balance when including estimates in fractions of GtC yr–1 for riverine transport,
weathering, deep ocean burial, etc. ‘GPP’ is annual gross (terrestrial) primary production. Atmospheric carbon content and all cumulative fluxes since 1750 are as of end 1994.

20. Im AR4 benutzte AOGCMs

21. Entwicklung der Auflösung seit 1990

22. Observed climatological annual mean SST and, over land, surface
air temperature (labelled contours) and the multi-model mean error in these
temperatures, simulated minus observed (colour-shaded contours).

23. Annual mean precipitation (cm), observed (a) and simulated (b), based on the multimodel
mean. The Climate Prediction Center Merged Analysis of Precipitation (CMAP; Xie and Arkin,
1997) observation-based climatology for 1980 to 1999 is shown, and the model results are for
the same period in the 20th-century simulations in the MMD at PCMDI. In (a), observations were
not available for the grey regions. Results for individual models can be seen in Supplementary
Material, Figure S8.9.

24. Attributierung

25. SRES, IPCC

26. Solid lines are multi-model global averages of surface warming (relative to ) for the scenarios
A2, A1B and B1, shown as continuations of the 20th century simulations. Shading denotes the plus/minus one standard
deviation range of individual model annual averages. The orange line is for the experiment where concentrations were
held constant at year 2000 values. The gray bars at right indicate the best estimate (solid line within each bar) and the
likely range assessed for the six SRES marker scenarios. The assessment of the best estimate and likely ranges in the gray
bars includes the AOGCMs in the left part of the figure, as well as results from a hierarchy of independent models and
observational constraints. {Figures 10.4 and 10.29}

27. Projected surface temperature changes for the early and late 21st century relative to the period 1980–
1999. The central and right panels show the Atmosphere-Ocean General Circulation multi-Model average projections for
the B1 (top), A1B (middle) and A2 (bottom) SRES scenarios averaged over decades 2020–2029 (center) and 2090–2099
(right). The left panel shows corresponding uncertainties as the relative probabilities of estimated global average warming
from several different AOGCM and EMICs studies for the same periods. Some studies present results only for a subset of
the SRES scenarios, or for various model versions. Therefore the difference in the number of curves, shown in the lefthand
panels, is due only to differences in the availability of results. {Figures 10.8 and 10.28}

28. Niederschlag DJF unter A1B
Relative changes in precipitation (in percent) for the period 2090–2099, relative to 1980–1999. Values are multi-model
averages based on the SRES A1B scenario for December to February (left) and June to August (right). White areas are where less than
66% of the models agree in the sign of the change and stippled areas are where more than 90% of the models agree in the sign of the
change. {Figure 10.9}

29. Niederschlag JJA unter A1B
Relative changes in precipitation (in percent) for the period 2090–2099, relative to 1980–1999. Values are multi-model
averages based on the SRES A1B scenario for December to February (left) and June to August (right). White areas are where less than
66% of the models agree in the sign of the change and stippled areas are where more than 90% of the models agree in the sign of the
change. {Figure 10.9}

30. Changes in extremes based on multi-model simulations from nine global coupled climate models, adapted from Tebaldi et al. (2006). (a) Globally averaged
changes in precipitation intensity (defined as the annual total precipitation divided by the number of wet days) for a low (SRES B1), middle (SRES A1B) and high (SRES A2)
scenario. (b) Changes in spatial patterns of simulated precipitation intensity between two 20-year means (2080–2099 minus 1980–1999) for the A1B scenario.

31. Changes in extremes based on multi-model simulations from nine global coupled climate models, adapted from Tebaldi et al. (2006). (a) Globally averaged
changes in precipitation intensity (defined as the annual total precipitation divided by the number of wet days) for a low (SRES B1), middle (SRES A1B) and high (SRES A2)
scenario. (b) Changes in spatial patterns of simulated precipitation intensity between two 20-year means (2080–2099 minus 1980–1999) for the A1B scenario.

32. Time series of global mean sea level (deviation from the
mean) in the past and as projected for the future. For the period before
1870, global measurements of sea level are not available. The grey shading shows
the uncertainty in the estimated long-term rate of sea level change (Section 6.4.3).
The red line is a reconstruction of global mean sea level from tide gauges (Section
), and the red shading denotes the range of variations from a smooth curve.
The green line shows global mean sea level observed from satellite altimetry. The
blue shading represents the range of model projections for the SRES A1B scenario
for the 21st century, relative to the 1980 to 1999 mean, and has been calculated
independently from the observations. Beyond 2100, the projections are increasingly
dependent on the emissions scenario (see Chapter 10 for a discussion of sea level
rise projections for other scenarios considered in this report). Over many centuries or
millennia, sea level could rise by several metres (Section ).

35. The change with respect to 1961-1990 in the 50-year
return period extreme water level (m) in the North Sea due to changes in atmospheric
storminess, mean sea level and vertical land movements for the period
2071 to 2100 under the A2 scenario (from Lowe and Gregory, 2005).

36. Diagnosis: distribution of 7 (of 16) Syndromes in the 1990s based on about 60 indicators
Lüdeke/Petschel-Held/Schellnhuber GAIA 13 (2004) no. 1

37. Syndromes and Climate Change: Sensitivity versus Causation
Petschel-Held/Reusswig in: Goals and Economic Instruments for the Achievement
of Global Warming Mitigation in Europe, Eds. Hacker/Pelchen, Kluwer 1999

38. Sahel-Syndrome: a problem – even without climate change!
Regions, generally disposed towards the mechanism:
Lüdeke et al., Environmental Modeling and Assessment 4 (1999)

39. Sahel-Syndrome: a problem – even without climate change!
Regions, generally disposed towards the mechanism:
Lüdeke et al., Environmental Modeling and Assessment 4 (1999)

40. Sahel-Syndrome: a problem – aggravated under climate change!
Regions, where a presently low disposition may become large:
Lüdeke et al., Environmental Modeling and Assessment 4 (1999)
Moldenhauer/Lüdeke, ClimRes 21 (2002)

41. Relative global development of Gross Domestic Product measured in PPP
(GDPBpppB), Total Primary Energy Supply (TPES), COB2B emissions (from fossil fuel burning, gas
flaring and cement manufacturing) and Population (Pop). In addition, in dotted lines, the figure
shows Income per capita (GDPBpppB/Pop), Energy Intensity (TPES/GDPBpppB), Carbon Intensity of
energy supply (COB2B/TPES), and Emission Intensity of the economic production process
(COB2B/GDPBpppB) for the period

42. after:
Raskin, P., Banuri, T., Gallopín, G., Gutman, P., Hammond, A., Kates, R., Swart, R. (2002). Great Transition: The Promise and Lure of the Times Ahead. A report of the Global Scenario Group, Stockholm Environmental Institute, Boston

46. AR4:
Studies on mitigation portfolios and macro-economic costs assessed in this report are based on top-down modelling. Most models use a global least cost approach to mitigation portfolios and with universal emissions trading, assuming transparent markets, no transaction cost, and thus perfect implementation of mitigation measures throughout the 21st century. Costs are given for a specific point in time.
Global modelled costs will increase if some regions, sectors (e.g. land-use), options or gases are excluded. Global modelled costs will decrease with lower baselines, use of revenues from carbon taxes and auctioned permits, and if induced technological learning is included. These models do not consider climate benefits and generally also co-benefits of mitigation measures, or equity issues.

47. Estimated global macro-economic costs in 2030
for least-cost trajectories towards different long-term stabilization levels (AR4)

48. Das Unvermeidbare beherrschen,
Das Unbeherrschbare vermeiden

49. Das Unvermeidbare beherrschen,
Das Unbeherrschbare vermeiden
Adaptationsmassnahmen an den nicht mehr vermeidbaren Klimawandel durchführen,
Emissionen reduzieren, um den Klimawandel in einem Rahmen zu halten, der die Adaptation überhaupt noch erlaubt (2°-Ziel)