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Olivier Geoffroy Parameterization of precipitation in boundary layer clouds at the cloud system scale Pier Siebesma, Roel Neggers RK science lunch, 05/10/2010.

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Presentation on theme: "Olivier Geoffroy Parameterization of precipitation in boundary layer clouds at the cloud system scale Pier Siebesma, Roel Neggers RK science lunch, 05/10/2010."— Presentation transcript:

1 Olivier Geoffroy Parameterization of precipitation in boundary layer clouds at the cloud system scale Pier Siebesma, Roel Neggers RK science lunch, 05/10/2010

2 Microphysical processes w CCN : D ~ 0.01-10 µm D 40 µm n(D) Cloud droplets : ~ 1 µm < D < ~ 40 µm CCN Activation

3 Microphysical processes Condensation w CCN : D ~ 0.01-10 µm D 40 µm D n(D) Cloud droplets : ~ 1 µm < D < ~ 40 µm CCN Activation

4 Microphysical processes Condensation w CCN : D ~ 0.01-10 µm D 40 µm D n(D) Cloud droplets : ~ 1 µm < D < ~ 40 µm CCN Activation Mixing D 40 µm n(D)

5 Microphysical processes Condensation w CCN : D ~ 0.01-10 µm D 40 µm D n(D) Cloud droplets : ~ 1 µm < D < ~ 40 µm CCN Activation Cloud droplet sedimentation Mixing D 40 µm n(D)

6 Microphysical processes Cloud droplets : ~ 1 µm < D < ~ 40 µm Condensation w precipitation embryo D ~ 40 µm Cloud droplet sedimentation CCN : D ~ 0.01-10 µm D 40 µm D n(D) Collection D 40 µm n(D) ECS CCN Activation Collection : Efficient for D > 40 µm (Bartlett, 1970) Mixing D 40 µm n(D)

7 Microphysical processes Cloud droplets : ~ 1 µm < D < ~ 40 µm Condensation precipitation embryo D ~ 40 µm Cloud droplet sedimentation CCN : D ~ 0.01-10 µm D 40 µm D n(D) Collection D 40 µm n(D) ECS CCN Activation Collection : Efficient for D > 40 µm (Bartlett, 1970) Mixing D 40 µm n(D) Polluted cloud w  precipitation efficiency (?)  LWP ( ? (feedbacks) ) (2 nd aerosol indirect effect)

8 Microphysical processes Condensation w CCN : D ~ 0.01-10 µm D 40 µm D n(D) Cloud droplets : ~ 1 µm < D < ~ 40 µm CCN Activation Cloud droplet sedimentation Mixing D 40 µm n(D) Marine cloud

9 Microphysical processes Cloud droplets : ~ 1 µm < D < ~ 40 µm Condensation w precipitation embryo D ~ 40 µm Cloud droplet sedimentation CCN : D ~ 0.01-10 µm D 40 µm D n(D) Collection D 40 µm n(D) ECS CCN Activation Collection : Efficient for D > 40 µm (Bartlett, 1970) Mixing D 40 µm n(D)

10 Microphysical processes Condensation w Cloud droplet sedimentation CCN : D ~ 0.01-10 µm D 40 µm D n(D) Collection D 40 µm n(D) ECS Rain drops ~ 40 µm <D < 100-500 µm Cloud droplets : ~ 1 µm < D < ~ 40 µm precipitation embryo D ~ 40 µm CCN Activation Mixing D 40 µm n(D) Growth depends on the available amount of water i.e. H or LWP

11 Microphysical processes Condensation w Rain drops ~ 40 µm <D < 100-500 µm Cloud droplet sedimentation CCN : D ~ 0.01-10 µm D 40 µm D n(D) Mixing D 40 µm n(D) Collection D 40 µm n(D) ECS Cloud droplets : ~ 1 µm < D < ~ 40 µm precipitation embryo D ~ 40 µm CCN Activation Rain sedimentation

12 Microphysical processes Condensation Rain drops ~ 40 µm <D < 100-500 µm Cloud droplet sedimentation CCN : D ~ 0.01-10 µm D 40 µm D n(D) Mixing D 40 µm n(D) Collection D 40 µm n(D) ECS Cloud droplets : ~ 1 µm < D < ~ 40 µm precipitation embryo D ~ 40 µm CCN Activation Rain sedimentation  size sorting Rain evaporation

13 Microphysical processes Condensation Rain drops ~ 40 µm <D < 100-500 µm Cloud droplet sedimentation CCN : D ~ 0.01-10 µm D 40 µm D n(D) Mixing D 40 µm n(D) Collection D 40 µm n(D) ECS Cloud droplets : ~ 1 µm < D < ~ 40 µm precipitation embryo D ~ 40 µm CCN Activation Rain sedimentation  size sorting Rain evaporation

14 Microphysical processes Condensation Rain drops ~ 40 µm <D < 100-500 µm Cloud droplet sedimentation CCN : D ~ 0.01-10 µm D 40 µm D n(D) Mixing D 40 µm n(D) Rain sedimentation  size sorting Collection D 40 µm n(D) ECS Cloud droplets : ~ 1 µm < D < ~ 40 µm precipitation embryo D ~ 40 µm CCN Activation Rain evaporation

15 Objective - Development of a precipitation scheme for boundary layer clouds at the GCM scale Precipitation in a key process in BLC evolution.  Low cloud regimes and transitions between regimes Earth radiation budget, general circulation, hydrological cycle.  Quantification of the aerosol indirect effect.

16 explicit or bin D n(D) Bulk Cloud rain D D0D0 n(D) Autoconversion Accretion Self-collection 2 bins  4 collection processes Collection processes : Stochastic Collection Equation (SCE) LES collection schemes Cloud rain Cloud : q c (g kg -1 ) N c (cm -3 ) Rain : q r (g kg -1 ) N r (cm -3 ) Measured spectra D 0 ~ 40 - 100 µm D0D0 Cloud rain D (μm)

17 Autoconversion Cloud : q c (g kg -1 ) N c (cm -3 ) Rain : q r (g kg -1 ) N r (cm -3 ) Precipitation formation, autoconversion rate Khairoutdinov and Kogan (2000) 2.47-1.79 Beheng (1994) 4.7-3.3 Seifert and Beheng (2001) 4-2 Tripoli and Cotton (2000) 2.33-0.33 α β Kessler (1969) 1 Treshold H(q c -q treshold ) Sundqvist (1978) 1 Liu and Daum (2006) 2.33-0.33 H(r 6 -r treshold ) H(r v -r vtreshold ) N aerosol Highly non linear 0 0 1 1 1 Auto rate qcqc Aerosol indirect effect  dependance in N c necessary NcNc NcNc Accretion Depends on local values

18 Autoconversion / accretion rates mean profiles (12H) in cumulus Only in cloud core - Formation of precipitation in cloud core -Accretion = ~ 10 x autoconversion -Simulations show larger accretion rate for w up -v qr > 0 (drops go upward) Only in cloud core autoaccr w up -v qr > 0 w up -v qr < 0 v qr w up accr

19 Autoconversion: Frac=cste 0 overlap, Sundqvist (1978) scheme w=w up (k-1) q c =l up (k) =cste?

20 New scheme Autoconversion: Frac=cste w=w up (k-1) q c =l up (k)

21 New scheme, accretion regime Accretion: Frac=cste (From RICO in situ measurements)

22 New scheme, overlap Frac=cste k+1 k zkzk hoho z top ?

23 Autoconversion formulation (kg kg -1 s -1 ) LES simulations (12H) - RICO, moister RICO - N c = 40, 50, 70, 100, 200 cm -3 - Seifert and Beheng (2006) scheme: Identification of individual clouds and average clouds of same height power law hypothesis: & regression auto LES = f(auto param ) 1/1 line Horizontal mean values of:

24 SCM results

25 LWP, rain flux at surface, N c =50, 70, 100, 200 cm-3 50 cm -3 70 cm -3 200 cm -3 No rain 100 cm -3 LWP: precipitation at surface: 60 g m -2 = 25 Wm -2 ~ 0.4 mm h -1 ~ 10 mm j -1 50 cm -3 70 cm -3 100 cm -3 200 cm -3

26 rain flux profiles N c =50, 200 cm-3 N c = 50 cm -3 N c = 200 cm -3

27 Autoconversion time scale w=5ms -1 w=1ms -1 w=w up w=5ms -1 w=1ms -1 w=w up

28 Sensitivity to the overlap h 0 =1000 h 0 =600 h 0 =300 LWP N c = 50 cm -3 h 0 =300 h 0 =600 h 0 =1000

29 - Developpment and implementation of a precipitation scheme in ECMWF SCM model coupled with the DualM scheme. - Possibility to take in account the shear effect - Possible to take in account interaction between precipitation flux and the stratiform component of the cloud (for Sc). - Dependency in N CCN  Test of the scheme using the KPT and half a year of precipitation flux and CCN concentration measurements: Conclusion and perpective North Sea origins Dust episode CCN concentration at Cabauw during IMPACT (May 2008) Regional background Regionalbackground

30 Sundqvist no evapSB, no evap, N c 70 lwp R surf

31 Sundqvist no evapSB, no evap, N c 50 lwp R surf

32 SB, evap2, N c 70 lwp R surf SB, evap2, N c 200 lwp R surf

33 h 0 =300, 500, 800, 1500, SB, Nc 50, evap2 lwp h 0 300 mh 0 500 m h 0 800 m h 0 1500 m

34 SB, Nc 50, original evap lwp auto2, Nc 50, original evap auto2, Nc 50, evap2

35 SB, evap2, N c 50 lwp R surf

36 Nc 50 cm-3 Nc 70 cm-3 Nc 200 cm-3 lwp auto 2 (a=2.74, b=-1.35)

37 Param accr up + auto w 0 =5 ms -1 10e-6 a qr =1.85 b Nc =1.17

38 Param accr up + auto w 0 =5 ms -1 2.5e-6

39 LWP, rain flux at surface, N c =50, 70, 100, 200 cm-3 50 cm -3 70 cm -3 200 cm -3 No rain 100 cm -3 LWP: precipitation at surface: 60 g m -2 = 25 Wm -2 ~ 0.4 mm h -1 ~ 10 mm j -1 50 cm -3 70 cm -3 100 cm -3 200 cm -3 5 Wm -2

40

41

42 Steady state:

43 w up -v qr < 0 w up -v qr > 0


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