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Modeling Stratocumulus Clouds: From Cloud Droplet to the Meso-scales Stephan de Roode Clouds, Climate & Air Quality Multi-Scale Physics (MSP), Faculty.

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Presentation on theme: "Modeling Stratocumulus Clouds: From Cloud Droplet to the Meso-scales Stephan de Roode Clouds, Climate & Air Quality Multi-Scale Physics (MSP), Faculty."— Presentation transcript:

1 Modeling Stratocumulus Clouds: From Cloud Droplet to the Meso-scales Stephan de Roode Clouds, Climate & Air Quality Multi-Scale Physics (MSP), Faculty of Applied Sciences, TU Delft

2 Clouds, Climate and Air Quality atmospheric boundary layer in the laboratory N2ON2OCH 4 new methods for measuring emission rates cloud-climate feedback detailed numerical simulation

3 Landsat satellite ~65 km Large Eddy Simulation ~10 km ~mm viscous dissipation ~1 km shallow cumulus ~1  m-100  m Cloud droplets Earth ~13000 km slide by Harm Jonker

4 Contents (1) Eddy diffusivity profiles in stratocumulus Does its shape matter? When is a turbulent flux countergradient? (2) Grid resolution in weather forecast models Are parameterizations independent of the grid size? (3) Stratocumulus equilibrium states How will global warming affect cloud amount? (4) “Cloud droplets” on the ground: dew formation Can we measure it? (5) Summary and outlook Stratocumulus equilibrium states, an interesting study case for WRF?

5 GEWEX Cloud Systems Study (GCSS) Stratocumulus Intercomparison Cases Stratocumulus case based on observations (FIRE I) Use observations to prescribe - initial state - large-scale horizontal advection - large-scale subsidence rate Simulation of diurnal cycle - 1D versions of General Circulation Models - Large-Eddy Simulation Models (LES)

6 GEWEX Cloud Systems Study (GCSS) Stratocumulus Intercomparison Cases Stratocumulus case based on observations (FIRE I) Use observations to prescribe - initial state - large-scale horizontal advection - large-scale subsidence rate Simulation of diurnal cycle - 1D versions of General Circulation Models - Large-Eddy Simulation Models (LES) initial jumps for three GCSS stratocumulus cases

7 3D results from Large-Eddy Simulation results - The cloud liquid water path

8 1D results from General Circulation Models - The cloud liquid water path (LWP) Single Column Model liquid water path results very sensitive to entrainment rate drizzle parameterization convection scheme (erroneous triggering of cumulus clouds) Duynkerke, P. G., S. R. de Roode, M. C. van Zanten, J. Calvo, J. Cuxart, S. Cheinet, A. Chlond, H. Grenier, P. J. Jonker, M. Koehler, G. Lenderink, D. Lewellen, C.-L. Lappen, A. P. Lock, C.-H. Moeng, F. Mller, D. Olmeda, J.-M. Piriou, E. Sanchez, I. Sednev, 2004: Observations and numerical simulations of the diurnal cycle of the EUROCS stratocumulus case. Quart. J. R. Met. Soc., 130,

9 Entrainment - mixing of relatively warm and dry air from above the inversion into the cloud layer - important for cloud evolution

10 Entrainment parameterizations - Implementation in K-diffusion schemes Turbulent flux at the top of the boundary layer due to entrainment with rate w e : ("flux-jump" relation) Top-flux with K-diffusion:

11 Diagnose eddy- diffusivity coefficients from LES results

12

13 K-coefficients from FIRE I LES

14 Importance of eddy-diffusivity coefficients on internal boundary- layer structure Vary magnitude K profile Compute solutions  l and q t for given surface and entrainment fluxes

15 Total water content profiles for different K-profiles but identical vertical fluxes For weakly unstable conditions above sea : small values for the eddy diffusivity if it depends on the convective velocity scale w *

16 Liquid water content profiles for different K-profiles Magnitude K-coefficient in interior BL important for liquid water content! K factorLWP [g/m 2 ]  109 De Roode, S. R., 2007: The role of eddy diffusivity profiles on stratocumulus liquid water path biases. Monthly Weather Rev., 135,

17 Contents (1) Eddy diffusivity profiles in stratocumulus Does its shape matter? When is a turbulent flux countergradient? (2) Grid resolution in weather forecast models Are parameterizations independent of the grid size? (3) Stratocumulus equilibrium states How will global warming affect cloud amount? (4) “Cloud droplets” on the ground: dew formation Can we measure it? (5) Summary and outlook Stratocumulus equilibrium states, an interesting study case for WRF?

18 Countergradient fluxes: Clear Convective Boundary Layer (CBL)

19 Flux profiles in the Clear Convective Boundary Layer virtual potential temperature (buoyancy) potential temperature (temperature) moisture

20 Countergradient fluxes in the CBL temperature buoyancy moisture No countergradient flux if vertical flux does not change sign in the mixed layer De Roode, S. R., et al., 2004: Countergradient fluxes of conserved variables in the clear convective and stratocumulus-topped boundary layer. The role of the entrainment flux., Bound.-Lay. Meteor, 112,

21 Contents (1) Eddy diffusivity profiles in stratocumulus Does its shape matter? When is a turbulent flux countergradient? (2) Grid resolution in weather forecast models Are parameterizations independent of the grid size? (3) Stratocumulus equilibrium states How will global warming affect cloud amount? (4) “Cloud droplets” on the ground: dew formation Can we measure it? (5) Summary and outlook Stratocumulus equilibrium states, an interesting study case for WRF?

22 Cloud dynamics 10 m100 m1 km10 km100 km1000 km10000 km turbulence  Cumulus clouds Cumulonimbus clouds Mesoscale Convective systems Extratropical Cyclones Planetary waves Large Eddy Simulation (LES) Model Cloud System Resolving Model (CSRM) Numerical Weather Prediction (NWP) Model Global Climate Model The Zoo of Atmospheric Models DNS mm Cloud microphysics

23 Countergradient fluxes in the CBL Dx = 25.6 km Dy = 25.6 km t=8h

24 Countergradient fluxes: destruction of variance prohibiting growth of length scales temperature buoyancy moisture De Roode, S. R., P. G. Duynkerke and H. J. J. Jonker, 2004: Large Eddy Simulation: How large is large enough? J. Atmos. Sci., 61,

25 Stratocumulus cloud albedo: example cloud layer depth = 400 m effective cloud droplet radius= 10  m optical depth  = 25 homogeneous stratocumulus cloud layer

26 Real clouds are inhomogeneous Stratocumulus albedo from satellite

27 Albedo for an inhomgeneous cloud layer 27 Redistribute liquid water: optical depths  = 5 and 45 inhomogeneous stratocumulus cloud layer mean albedo = 0.65 < 0.79

28 Cloud albedo in a weather forecast or climate model Decrease optical thickness: Cahalan et al (1994):  = 0.7 (FIRE I observations)  effective  mean inhomogeneous albedo homogeneous albedo

29 Analytical results for the inhomogeneity factor  Assumption: Gaussian optical depth distribution

30 Value of correction factor depends on grid size De Roode, S. R., and A. Los, 2008: The effect of temperature and humidity fluctuations on the liquid water path of non-precipitating closed cell stratocumulus clouds. Quart. J. Roy. Meteor. Soc., 134,

31 Contents (1) Eddy diffusivity profiles in stratocumulus Does its shape matter? When is a turbulent flux countergradient? (2) Grid resolution in weather forecast models Are parameterizations independent of the grid size? (3) Stratocumulus equilibrium states How will global warming affect cloud amount? (4) “Cloud droplets” on the ground: dew formation Can we measure it? (5) Summary and outlook Stratocumulus equilibrium states, an interesting study case for WRF?

32 Feedback effects in a changing climate Dufresne & Bony, Journal of Climate 2008 Radiative effects only Water vapor feedback Surface albedo feedback Cloud feedback

33 The playground for cloud physicists: Hadley circulation deep convectionshallow cumulusstratocumulus

34 EU Cloud Intercomparison, Process Study and Evaluation Project (EUCLIPSE) Future Sea water temperature: T+  T  enhanced surface evaporation Present Sea water temperature: T Positive Feedback? Entrainment drying dominates moisture tendency Negative Feedback?

35 CGILS: CFMIP-GCSS Intercomparison of Large-Eddy and Single-Column Models

36 CGILS – Simulation details Simulation time 10 days adaptive time step, dtmax = 10 secs radiation time step = 60 secs Domain size 4.8 x 4.8 x 4 km 3, 96 x 96 x 128 grid points (  z = 25 m in lower part) Total CPU hours on 32 processors 2700 hours

37 CGILS Hourly-averaged vertical mean profiles during the last 5 hours

38 CGILS Cloud liquid water path (LWP)

39 Top Of Atmosphere Net Radiative Fluxes

40 Contents (1) Eddy diffusivity profiles in stratocumulus Does its shape matter? When is a turbulent flux countergradient? (2) Grid resolution in weather forecast models Are parameterizations independent of the grid size? (3) Stratocumulus equilibrium states How will global warming affect cloud amount? (4) “Cloud droplets” on the ground: dew formation Can we measure it? (5) Summary and outlook Stratocumulus equilibrium states, an interesting study case for WRF?

41 Dew formation at Cabauw

42 Mean surface energy balance at Cabauw during the night De Roode, S. R., F. C. Bosveld and P. S. Kroon, 2010: Dew formation, eddy-correlation latent heat fluxes, and the surface energy imbalance at Cabauw during stable conditions. In press, Bound.-Layer Meteorology.

43 Summary and outlook Equilibrium states  Good approach to investigate model representation of stratocumulus NWP future  Scale dependency of paramaterizations (variances, mass flux approach) Stable boundary layers and dew formation  Dew formation can occus for very stable conditions (Ri B >1)  Difficult to measure References CGILS case Papers can be downloaded from -> publicationswww.srderoode.nl/


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