Integration of models and observations of aerosol-cloud interactions Robert Wood University of Washington Robert Wood University of Washington.

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Presentation transcript:

Integration of models and observations of aerosol-cloud interactions Robert Wood University of Washington Robert Wood University of Washington

Radiative “forcing” components Cloud effects Direct Twomey Mixed ph. Semi-dir 2 nd AIE  cld  N d 1/3 LWP 5/6 (First AIE/Twomey) N d   Precip.  (Second AIE/Albrecht) Isaksen et al. (Atmos. Env. 2009)

State of play Isaksen et al. (Atmos. Env., 2009) IPCC 2007

Model estimates of the two major aerosol indirect effects (AIEs) Pincus and Baker (1994) – 1 st and 2 nd AIEs comparable GCMs (Lohmann and Feichter 2005) 1 st AIE: -0.5 to -1.9 W m -2 2 nd AIE: -0.3 to -1.4 W m -2 Aerosol particles induce changes in cloud macrophysical properties. The Twomey effect is insufficient

Shiptrack surprises! Liquid water content in shiptracks is typically reduced compared with surrounding cloud Clear refutation of Albrecht’s hypothesis courtesy Jim Coakley, see Coakley and Walsh (2002) 3.7  m

LES results Cloud droplet concentration [cm-3] LWP [g m-2] P 0 [mm d-1] w e [cm s-1] Impact of aerosols simulated by varying N d Increased N d  Reduced precipitation  increased TKE  increased entrainment w e Changes in w e can sometimes result in cloud thinning (reduced LWP) Also noted by Jiang et al. (2002) Ackerman et al. (2004)

Transient response of an equilibrated mixed layer PBL model to N d increases Ratio of Albrecht to Twomey effect R IE (right) is a strong function of cloud base height More elevated cloud base heights z cb lead to Albrecht effects which partly cancel those due to Twomey effect Elevated z cb associated with dry FT and less surface drizzle, consistent with LES results, but with a far less sophisticated model  hope for the representation in climate models Wood (J. Atmos. Sci., 2007)

Sedimentation of cloud droplets Bretherton, Blossey and Uchida, GRL, 2007 Cloud droplet sedimentation removes water from the (  10 m thick) entrainment interface, lowers LWC there, reduces evaporative cooling, and suppresses entrainment, resulting in thicker clouds Since increased N d reduces sedimentation  pollution can lead to thinner clouds

Effects of drizzle vs effects of sedimentation of cloud droplets GCSS DYCOMS-2 RF02 drizzling Sc case study Ackerman et al. (MWR, 2009) With drizzle, without sedimentation With drizzle and sedimentation Effect of drizzle Effect of sedimentation.....in this case, sedimentation dominates over drizzle impact on cloud LWP

Microphysically-driven supersaturation differences, can drive LWC differences Kogan and Martin, Kogan et al. (JAS, 1994, 1995) Height [km] Steady-state supersaturation inversely proportional to N and mean radius More polluted clouds have more active turbulence and (in this case) more cloud water Also microphysically-limited evaporation rate (Feingold inter alia.)

Necessary conditions for AIEs in warm clouds Aerosols must result in increases in cloud droplet concentration Present day geographical variability of cloud droplet concentration should be simulated by GCMs

January MODIS CAM-5 Use method of Boers and Mitchell (1996), applied by Bennartz (2007) Screen to remove heterogeneous clouds by insisting on CF liq >0.6 in daily L3 Cloud top droplet concentration in warm clouds from CAM-5

MODIS CAM-5 July CAM-5 broadly captures land-ocean contrasts in N d Opposite sign of seasonal cycle over NH land (MODIS>CAM in winter; MODIS<CAM in summer) Clear evidence of S. African and S. American biomass burning in MODIS and CAM

Determine weak-link parameterizations Chuang et al. (2011) Effect of varying autoconversion schemes (in CAM 5) on second AIE Second AIE varies by a factor of 5 or more

Autoconversion in the real world z*z* z*z* cloud top cloud base Accretion, not autoconversion is the dominant precipitation production mechanism.....even in weakly- precipitating clouds Composite of aircraft data in stratocumulus from Wood (JAS, 2005)

Precipitation susceptibility Construct from Feingold and Siebert (2009) can be used to examine aerosol influences on precipitation in both models and observations S = -(dlnR CB /dlnN a ) LWP,h Data from stratocumulus over the SE Pacific, Terai and Wood (Geophys. Res. Lett., 2011) S decreases strongly with cloud thickness Consistent with increasing importance of accretion in thicker clouds Consistent with results from A-Train (Kubar et al. 2009, Wood et al. 2009)

What controls N d ? Simple budget model for CCN/N d in the MBL: Assume aerosol sources constant (here represented by FT concentration “buffer”) Model pattern almost entirely driven by precipitation sinks Can reproduce significant amount of variance in N d over oceans  implications for significance of AOD vs r e relation ships Wood (2011)

Conclusions Most ways (and these are numerous) in which aerosols impact warm clouds are mediated via cloud droplet concentration – Singling out Twomey effect is introducing a biased effect, and is pointless Cloud droplet concentration can be estimated from space but need to establish credibility of estimates, especially away from Sc regions CloudSat and A-Train providing ways of establishing sensitivity of warm rain to aerosols...and vice versa

A proposal A limited area perturbation experiment to critically test hypotheses related to aerosol indirect effects Cost  $30M

Stevens and Feingold (Nature, 2009)