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Modeling Stratocumulus Clouds: From Cloud Droplet to the Meso-scales

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. N 2 O. CH 4. new methods for measuring emission rates. atmospheric boundary layer in the laboratory.

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Modeling Stratocumulus Clouds: From Cloud Droplet to the Meso-scales

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  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. N2O CH4 new methods for measuring emission rates atmospheric boundary layer in the laboratory Clouds, Climate and Air Quality cloud-climate feedback detailed numerical simulation

  3. Landsat satellite ~65 km Large Eddy Simulation ~10 km ~1mm-100mm Cloud droplets ~mm viscous dissipation ~1 km shallow cumulus 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. initial jumps for three GCSS stratocumulus cases 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)

  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, 3269-3296.

  9. Entrainment • 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 we: ("flux-jump" relation) • Top-flux with K-diffusion:

  11. Diagnose eddy- diffusivity coefficients from LES results

  12. Diagnose eddy- diffusivity coefficients from LES results

  13. K-coefficients from FIRE I LES

  14. Importance of eddy-diffusivity coefficients on internal boundary-layer structure • Vary magnitude K profile • Compute solutions ql and qtfor 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! De Roode, S. R., 2007: The role of eddy diffusivity profiles on stratocumulus liquid water path biases. Monthly Weather Rev., 135, 2786-2793.

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

  20. temperature buoyancy moisture Countergradient fluxes in the CBL 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, 179-196.

  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. The Zoo of Atmospheric Models Cloud dynamics mm 10 m 100 m 1 km 10 km 100 km 1000 km 10000 km Cloud microphysics  turbulence Cumulus clouds Cumulonimbus clouds Mesoscale Convective systems Extratropical Cyclones Planetary waves DNS Subgrid Large Eddy Simulation (LES) Model Cloud System Resolving Model (CSRM) Numerical Weather Prediction (NWP) Model Global Climate Model

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

  24. temperature buoyancy moisture Countergradient fluxes: destruction of variance prohibiting growth of length scales 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, 403-421.

  25. Stratocumulus cloud albedo: example homogeneous stratocumulus cloud layer cloud layer depth = 400 m effective cloud droplet radius = 10 mm optical depth t = 25

  26. Real clouds are inhomogeneous Stratocumulus albedo from satellite

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

  28. Cloud albedo in a weather forecast or climate model inhomogeneous albedo homogeneous albedo Decrease optical thickness: Cahalan et al (1994): c = 0.7 (FIRE I observations) teffective tmean

  29. Analytical results for the inhomogeneity factor cAssumption: 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, 403-416.

  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 Cloud feedback Surface albedo feedback Water vapor feedback Radiative effects only Dufresne & Bony, Journal of Climate 2008

  33. The playground for cloud physicists: Hadley circulation deep convection shallow cumulus stratocumulus

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

  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 km3, 96 x 96 x 128 grid points (Dz = 25 m in lower part) Total CPU hours on 32 processors 2700 hours

  37. CGILSHourly-averaged vertical mean profiles during the last 5 hours

  38. CGILSCloud 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 formationat 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 (RiB>1)  Difficult to measure References CGILS case http://atmgcm.msrc.sunysb.edu/cfmip_figs/Case_specification.html Papers can be downloaded from www.srderoode.nl/ -> publications

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