Cloud Microphysics

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IACETH Institute for Atmospheric and Climate Science

Cloud Microphysics

Ulrike Lohmann and Daniel Cziczo

ETH Zürich Institut für Atmosphäre und Klima

Oct 24, 2006

Ulrike Lohmann (IACETH) Cloud Microphysics Oct 24, 2006 1 / 36

Outline Motivation Stratus Cumulus Cirrus Formation Microphysics Severe weather Extra

Miscellaneous

I Lecturers: Ulrike Lohmann, CHN O11, Ulrike.Lohmann@env.ethz.ch

Daniel Cziczo, CHN O16.3, Daniel.Cziczo@env.ethz.ch

I Based on “Microphysics of Clouds and Precipitation, H.R.

Pruppacher and J.D. Klett, Kluwer Acad. Publisher, 1997” and own lecture notes

I Prerequisite: Any introduction to Atmospheric Science

I Objective: Understanding the microphysics of clouds and precipitation

I Grading Scheme: 3 credit points; marked; 6 assignments: 5 take-home (15% each), 1 in-class assignment (25%)

I Notes: www.iac.ethz.ch/education/master/cloud microphysics

I Tutor: Rebekka Posselt, rebekka.posselt@env.ethz.ch, CHN O16.1, office hours: Tuesdays 14-16h

Course Outline

1. Oct 24: Introduction (UL) 2. Oct 31: Aerosol basics (DC) 3. Nov 7: Atmospheric aerosols (DC) 4. Nov 14: Hydrodynamics (DC) 5. Nov 21: Structure of water (DC)

6. Nov 28: Thermodynamics necessary for cloud formation (UL) 7. Dec 5: Surface properties of water (UL)

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Course Outline

1. Dec 12: Homogeneous freezing (UL) 2. Dec 19: Heterogeneous freezing (UL) 3. Jan 09: Microphysics of warm clouds (UL) 4. Jan 16: Microphysics of cold clouds (DC) 5. Jan 23: Weather modification (DC)

6. Jan 30: Clouds & climate change and in-class assignment (UL)

Importance of clouds

electricity aqueous chemistry clouds & precip

+ aerosols hydrological

cycle life ocean

latent heat

+ loading dynamics radiation

climate

Annual mean total cloud cover

Figure: averaged over 1983-1990 from the International Satellite Cloud Climatology Project (ISCCP)

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Hydrological cycle

Figure: The annual mean water vapor reservoirs are given in 10¹⁵kg and the fluxes in 10¹⁵kg year⁻¹(Quante, 2004)

Global energy budget

Figure: The Earth’s annual global mean energy budget (Kiehl and Trenberth, 1997)

Geographic distribution of the “cloud forcing”

(Cloud forcings from ERBE, cloud cover from ISCCP)

I shortwave cloud forcing (SCF) = FSW- FSW,cs=^S₄^o (αcs−αcld)⇒albedo effect of clouds

I longwave cloud forcing (LCF) = FLW,cs - FLW⇒greenhouse effect of clouds

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Geographic distribution of the “cloud forcing”

Figure: Cloud forcings from ERBE, cloud cover from ISCCP Global mean values:

SCF=-49 W m⁻²;LCF=32 W m⁻² ;CF=-17 W m⁻²

Clouds and climate change

Model response to 2xCO₂and change in low cloud amount [Stephens, J. Clim., 2005]

Cloud types

I Cumulus (Cu): vertical development

I Stratus (St): layered cloud

I Cirrus (Ci): ice clouds 10 cloud types in 4 families:

I Low base with vertical extent: Cu, Cb, Ns

I Low base and layered (0-2 km¹): St, Sc

I Mid level clouds (2-7 km): As, Ac

I High altitude ice clouds (7-16 km): Ci, Cs, Cc

1heights refer to mid latitudes

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Summary of different cloud types

Schematic of layer clouds

Figure:Houze’s cloud atlas: www.atmos.washington.edu/Atlas/

Stratus cloud cover

Figure: averaged over 1983-1990 from the International Satellite Cloud Climatology Project (ISCCP)

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Importance of microphysics for stratus

Figure:Durkee et al., J. Atmos. Sci., 2000

Importance of dynamics for stratus

Figure:Klein and Hartmann [J. Atmos. Sci., 1993]

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Importance of dynamics for stratus

Figure:Klein and Hartmann [J. Atmos. Sci., 1993]

Schematic of cumulus clouds

Figure: Houze’s cloud atlas

Importance of dynamics for cumulus clouds

Figure: 7.23 [Houze, 1993]

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Importance of microphysics for cumulus clouds?

Figure:Evan et al. [Geophys. Res. Lett., 2006]

Schematic of mid-level clouds

Schematic of cirrus clouds

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Schematic of cirrus clouds

Importance of dynamics for cirrus

(Fig. 5.29 Houze, 1993)

Importance of microphysics for cirrus

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Cloud formation

I Cool adiabatically until the relative humidity (RH = e/e_s) reaches 100%.

I In 98% of all cases, RH = 100% is reaches becauseT (and hence the saturation vapor pressuree_s) is decreased by expansion and lifting of an air parcel: cooling along a dry adiabat.

I In 2% of all cases, the vapor pressuree is increased by evaporation, mixing, diffusion or radiative cooling→fog

Cloud formation

I Except for Cu and Cb, all clouds need large-scale lifting (expansion and cooling). Condensation occurs at the lifting condensation level (LCL)

I Cu and Cb have prerequisite to reach the level of free convection (LFC). Above LFC they are lifted by their condensational warming→convectively available potential energy (CAPE)

I Stratus: vertical air motionw <V_ice, where V_ice represents scale of terminal velocity of an ice crystal∼1-3 m/s. w must be large enough to maintain supersaturation, it must be small enough to satisfy above criterion.

I Convective clouds: w ≥V_ice, w∼1 - 10 m/s.

Microstructure of clouds

I Stratiform versus cumuliform:

I Maritime versus continental:

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Cloud droplet size distributions

[Quante, J. Phys IV, 2004]

→bimodal distribution more often seen in precipitating clouds

Hail damage

Figure:

www.islandnet.com/see/weather/almanac/arc2002/alm02jul.htm

Drought in summer 2003 (T¨ oss)

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Formulation for the drop size distribution in clouds and fog

I Approximate observed drop size distribution by an analytical expression.

I Generally N rises sharply from low values to a maximum and decreases gently toward larger sizes→need a positively skewed distribution with a long tail toward the larger sizes.

I Gamma distribution:

n(r) =Ar^βexp(−Br^γ) (1) where r is the drop radius, n(r) dr is the number of drops cm⁻³ in the radius range (r, r+dr).

The parameters A, B,β,γmay be related to moments of the distribution.

I An example for a simplified Γ-distribution withγ=1 andβ=2 is the Khrgian and Mazin size distribution:

n(a) =Ar²exp(−Br) (2) A and B can be related to any 2 moments of the distribution.

E.g. in terms of N andr: N = 2A/B³anda=3/B

I log-normal distribution:

n(r) = N

√2π(logσ)rexp





− h

log_r^r

m

i2

2(logσ)²





 (3) σis the standard deviation of the distribution and rmis the mode radius

I multimodal distribution→approximate by superposition of single mode distributions

Cloud Microphysics