Aerosole, Wolken und Klima

Transkript

1 Aerosole, Wolken und Klima Ulrike Lohmann (IAC)

2 London smog wikipedia

3 Zürich, Photos von Amewu Mensah

4 Gliederung: Was sind Aerosole? Aerosole und Klima Wolken und Klima Klimaengineering mit Hilfe von Aerosolen und Wolken Zusammenfassung Ulrike Lohmann, ETH Zürich 4

5 Bedeutung von Aerosolpartikeln Luftverschmutzung: Reduktion der Sichtweite Winter smog durch Russ und Sulfat, z.b. London smog Wolkenbildung: ohne Aerosole keine Wolkentröpfchen Bedeutung für die Strahlung und das Klima: Aerosole streuen und absorbieren Strahlung Aerosole modifizieren Wolken: Bei konstantem Wassergehalt der Wolken, führen mehr Aerosole zu mehr aber kleineren Wolkentröpfchen und daher erhöhter Reflektion von Sonnenstrahlung Möglicher Einfluss auf die Lebenszeit, Ausdehnung und Aggregatzustand der Wolke

6 Vielfalt der Quellen von Aerosolpartikeln

7 Verschiedene Aerosoltypen Mineral dust Sea salt Pollen n e N (r) [cm-3 ] Coarse mode Giant particles Number Nucleation mode Aitken mode Sulfuric acid r [µm] Accumulation mode Ammonium sulfate Soot Lohmann et al., 2016

8 Verschiedene Aerosolquellen Lohmann et al., 2016

9 Globale Aerosolverteilung Staub: orange/rot, Meersalz: blau, kohlenstoffhaltige Partikel: grün, Sulfat: weiss Source: NASA

10 Aerosole und Klima Ulrike Lohmann, ETH Zürich 10

11 Blaz Gasparini Klimaeffekt eines Vulkanausbruchs

12 Blaz Gasparini Abkühlung nach dem Mt. Pinatubo Ausbruch

13 Strahlungseigenschaften von Aerosolpartikeln Scattering aerosols (a) (a) (b) Cooling Aerosols scatter solar radiation. Less solar radiation The atmospheric circulation and mixing processes spread Absorbing aerosols (c) (c) (d) Warming Aerosols absorb solar radiation. This heats the aerosol At the larger scale there is a net warming of the surface and IPCC, 2013, Kapitel 7

14 Keine Aerosole keine Wolken ASCOS Forschungsfahrt im Sommer 2008: Temperatur: -8 ºC, Aerosolkonzentration: < 10 cm -3 (mind. 100 x kleiner als über'm Kontinent) Tjernström et al., ACP, Movie: Zoran Ristovski,

15 Keine Aerosole keine Wolken Zoran Ristovski,

16 source: Schiffabgasfahnen

17 Schiffabgasfahnen Aerosol Droplet Droplet conc. [cm -3 ] conc. [cm -3 ] Albedo radius [µm] Durkee et al., JAS, 2000

18 60 Strahlungsantrieb durch anthropogene Aerosole 90 Forcing (W m 2) RESEARCH ARTICLE Polluted 7.0 e It is important to note that most of the natural emissions do n 90 by themselves, cause a forcing over the industrial period because t emission source strengths were defined to be the same in the PI a PD simulations (except for biomass burning); that is, a high setting the emissions in the PI simulation was paired with the same high s ting in the PD. However, natural emissions affect the uncertainty pogenic0 emissions the0 aerosol first indirect forcing0 because the backgrou they 90 affect aerosol state upon which the forcing is calculated (see below). Because our variance-based approach considers parameter inte actions, we are able to establish that the large contribution of natu aerosol emissions to forcing uncertainty is not strongly dependent 60 formation 60 Drop 10 the magnitude of the other parameters. This is important informati limited by because, for example, the large 90 sensitivity of forcing to natural sulph 90 supersaturation emissions could be overemphasized 0 m 2) Forcing (W σ (W m 2)if particle formation rates due sulphuric-acid-driven nucleation were too high in the model. Howev interactions as the 0.8difference Normalized anthropogenic emissions such parameter can be quantified betwe the sum of the main effect variances (coloured bars in Fig. 2b) and t Figure 1 The global distribution of annual mean aerosol first indirect N concentration forcing and associated a, First indirect forcing; b, standard total variance (100%uncertainty. in Fig. 2b); see the Methods. Interactions genera 90 deviation s of forcing. The maps were computed from a Monte Carlo sampling account for less than 10% of the total forcing variance, demonstrati d 60 ofthat an emulator of forcing in each grid cell of model.to uncertainties in t the ranked uncertainty results aretherobust model set-up. havethe a small on forcing uncertainty, which is related to the 30 effecteffect of some parameters on forcing uncertainty could beway unde Albedo susceptibility they perturb PI and PD CCN, as we discuss below. estimated if the parameter varied in an unknown way between the PI a lower at high drop Very high A striking aspect the not results is the large contribution to theifglobal PD eras, which weof have accounted for here. For example, DMS ) sensitivity concentrations (ref. of mean albedoforcing uncertainty from emissions of natural aerosol and preemissions were at the low end of the uncertainty range in t to emissions cursor involcanic gases. Together, emissions of volcanic DMS, biogenic 2, marine PI and at the higher end in the PD then theso resulting increase in sulpha pre-industrial time 30 volatile organic carbon (forming secondary organic aerosol), biomass aerosol over this period would constitute an additional uncertainty burning and23sea account fornatural 45% ofemissions the globalchange annualover mean the forcing. It spray is plausible that tim forcing variance (Fig. 2b). This compares with 34% of the annual mean 60 Anthropogenic emissions drop concentration implying that the uncertainty attributable to these parameters could forcing variance that is due to the eight parameters associated with Carslaw et al., Nature, Cloud albedo Forcing (W m 2) Formation of new 60 particles limited by existing aerosol

19 Strahlungsantrieb zwischen 1750 und 2011 Radiative forcing of climate between 1750 and 2011 Forcing agent Confidence Level Well Mixed Greenhouse Gases CO 2 Other WMGHG C H 4 N 2 O Halocarbons Very High Very High Natural Anthropogenic Ozone Stratospheric water vapour from CH 4 Surface Albedo Contrails Aerosol-Radiation Interac. Aerosol-Cloud Interac. Total anthropogeni c Solar irradiance Stratospheric Land Use Tropospheric Black carbon on snow Contrail induced cirrus Medium High/Low Medium Low High Medium Medium Radiative Forcing (W m -2 ) High Low IPCC, 2013, TS, Fig.6

20 Wolken und Klima Ulrike Lohmann, ETH Zürich 20

21 Wolkenklassifikation: Lohmann et al., 2016

22 Globale Verteilung von Wolken Lohmann et al., 2016

23 Globale Strahlungsbilanz in W m -2 Solar reflected 100 TOA Incoming solar 340 Imbalance 1 Thermal outgoing 239 Atmosphere Solar reflected by clouds, aerosol and gases Solar down surface 185 Solar absorbed 79 Thermal outgoing Atmospheric Greenhouse window gases Earth`s surface Imbalance 1 Absorbed solar 161 Sensible heat 20 Latent heat 84 Up surface 398 Down surface 342 Lohmann et al. (2016)

24 Strahlungseffekt von Wolken Lohmann et al. (2016)

25 Rückkopplungen bei einer CO 2 Verdopplung F: CO 2 doubling Initial/Planck feedback +1.2 K +0.9 K +0.3 K +0.7 K? Additional/temperature feedbacks Water vapor/lapse rate feedback Albedo feedback Cloud feedback 3.1 +/- 1.5K +3.1 K New equilibrium reached Lohmann et al., 2016

26 Änderung in Temperatur und Bedeckungsgrad der tiefen Wolken zum Zeitpunkt der CO 2 -Verdopplung Stephens et al., JC, 2005 change in low cloud cover [%] change in temperature [K] different global climate models change in low cloud cover [%]

27 IPCC, 2013, Fig Veränderung der Wolken bei CO 2 Verdopplung Rising High Clouds Broadening of the Hadley Cell Narrowing of Tropical Ocean Rainfall Zones Rising High Clouds Rising of the Melting Level Poleward Shift of Storms Less Low Clouds More Polar Clouds Equator 30º 60º Pole à Die Netto-Änderung der Wolken verstärkt den Treibhauseffekt wahrscheinlich

28 Klimaengineering mit Hilfe von Aerosolen und Wolken

29 Ist es notwendig, ins Klima einzugreifen? Center for Security Studies, ETH Zurich, 2017

30 Möglichkeiten das Klima zu kühlen Sources: meteo.sf.tv/sfmeteo, visibleearth.nasa.gov, wikipedia

31 Boucher et al., IPCC, 2013 Klimaengineering durch weniger Sonnenlicht à Temperatur und Niederschlag können nicht gleichzeitig stabilisiert werden

32 Netto Strahlungseffekt der Zirren Globalmittel 5 W m -2 Gasparini & Lohmann, 2016

33 Steffen Münch, ETHZ Klima Engineering mit Hilfe von Zirren

34 Zirren impfen: wie funktioniert es? Homog. cirrus Het. cirrus seeding Blaz Gasparini, ETHZ 34

35 Zirren impfen: wie effizient ist es? Net TOA CRE anomalies Storelvmo ours (r=0.5 µm) Penner2015 ours (r=50 µm) 1 W/m IN/l Blaz Gasparini, ETHZ

36 Vergleich der Klimaengineering Methoden 5 perfect GE method Effectiveness (Will it work?) cirrus worst GE method marine clouds stratospheric aerosols Affordability (How much will it cost?) Safety high low Adaptiert von Oschliess & Klepper, 2017

37 Einige Kernaussagen Aerosole stellen die grösste Unsicherheit beim anthropogenen Strahlungsantrieb dar, insbesondere durch ihre Wechselwirkungen mit Wolken Wolken stellen eine der grössten Unsicherheiten im zukünftigen Klima dar Bislang kann jede Klimaengineering Methode nur einen Teil der Erwärmung kompensieren und die negativen Nebenwirkung überwiegen die positiven Aspekte Literature: Lohmann, Lüönd, Mahrt: An introduction to clouds: From the microscale to climate. Cambridge University Press, Ulrike Lohmann, ETH Zürich 37

38 Vielen Dank für eure Aufmerksamkeit!