A Thermal Plume Model for the Boundary Layer Convection: Representation of Cumulus Clouds C. RIO, F. HOURDIN Laboratoire de Météorologie Dynamique, CNRS,

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Presentation transcript:

A Thermal Plume Model for the Boundary Layer Convection: Representation of Cumulus Clouds C. RIO, F. HOURDIN Laboratoire de Météorologie Dynamique, CNRS, IPSL, PARIS, France

(Atkinson & al., 1996) The convective boundary layer Unstable surface layer: diffusion Mixed layer: Mesoscale convective cells Inversion layer: Overshoot Free atmosphere

Parameterization of the convective boundary layer Diffusive scheme Deardorff (1972): countergradient term Mass-flux approach (Betts, Randall, Albrecht …) Combined diffusive/mass-flux scheme (Chatfield, Hourdin, Siebesma, Soares) Transilient matrix (Stull, 1984): Exchanges between all layers of the PBL

Parameterization of the convective boundary layer Diffusive scheme of Mellor & Yamada based on a pronostic equation of the turbulent kinetic energy Thermal plume model of Hourdin & al. (2002) adapted to shallow convective cases: Condensation process and lateral entrainment with F In the subcloud layer (Hourdin & al.) Inside the cloud (Tiedtke, Siebesma, Soares)

The cloud scheme (Bony & Emanuel) Distibution of the subgrid total water : Thermal plume model

Validation on a 1D configuration against LES: The EUROCS Cumulus Case LES case: development of shallow convection over land (Brown & al.) Observations made on the ARM site the 21st June 1997: development of cumuli at the top of a clear boundary layer Run: ARPEGE 1D / LMDZ physical package Vertical resolution: 40 layers (4 km) Timestep: 20s Forcings: - radiative tendencies - large-scale advective tendencies - sensible and latent surface fluxes

Time evolution of temperature and humidity near the surface MY: Mellor&Yamada diffusive scheme THdry: MY + thermal plume model for dry convection TH: MY + thermal plume model for shallow convection

Profiles at 15:30 LT

Multi-order moments - Underestimation of the variance of w - good agreement for the third order moment of w Possible link to deep convection Mass flux and vertical velocity Prescription of lateral entrainment and detrainment Inside the cloud

Clouds characteristics Too high cloud base height Too low cloud cover Results improved with ‘TH’ compared with ‘MY’ or ‘THdry’ but:

Influence on the clouds characteristics of: - Small-scale turbulence : - Detrainment and entrainment rates: To decrease the entrainment rate increases the vertical extension of clouds and cloud cover To increase the detrainment rate in clouds reduces the vertical extension of clouds and increases the cloud cover

Validation on a 3D configuration against SIRTA observations LMDZ in a stretched and nudged mode: Run: Vertical resolution: 40 layers Physical timestep: 3 min Period: 26,27,28 May 2003: Development of small cumuli after a sunny morning Soundings in TrappesLIDAR observations

Temperature and relative humidity at 17m (first layer of the model)

Clouds characteristics and radiative forcing

Conclusions Importance of accounting for mesoscale structures to represent the diurnal cycle of shallow convection Better representation of the evolution of temperature and relative humidity near the surface when considering condensation process and lateral entrainment Importance on the clouds characteristics of - the prescription of entrainment and detrainment rates - the sub-mean plume variability Satisfactory prediction of the skewness of the distribution of w: important variable for the coupling with deep convection