1. significance of subgrid-scale parametrization for cloud resolving modelling Françoise Guichard (thanks to) F. Couvreux, J.-L. Redelsperger, J.-P. Lafore, M. Tomasini

2. cloud-resolving simulations  which « object » ? (space and time scales) mature squall line phase, one week of COARE-IFA, day-time convection...  for which purpose? phenomenology, process study, larger-scale parametrizations  numerics resolution, domain size, filters, sponge layer, advection schemes...  parametrizations (of subgrid-scale processes) subgrid-scale fluxes (turbulence), microphysics, radiation subgrid coupling between microphysics and turbulence, radiation...  boundary conditions initial conditions, boundary conditions (surface & « large-scale forcing ») different sets of choices (with intricate dependencies) these various ingredients play more or less important roles depending on the object/purpose CRMs well suited to explicitely simulate precipitating deep convection (not developed to simulate boundary layer clouds)

3. focus restricted to broad considerations: turbulence (or subgrid-scale fluxes) subgrid coupling between microphysics and turbulence (what sensitivity studies focussing on resolution tell us) no discussion about: microphysics importance of stratiform cirrus (maintenance/dissipation) significance of evaporation of precipitating hydrometeors radiation cloud-radiation interactions

4. a few words about resolution Bryan et al. (2003) for MCSs a « turbulent » point of view (structure, budget,spectra)  x = 125 m  x = 1 km  e (x,z) in simulated squall line buoyancy flux bulk features

5. Bryan et al. (2003) not strictly an LES-type simulation (turbulenty speaking;subgrid flux not negligeable, l/  ) note: among other things, no consideration of cold nor subgrid microphysics (i.e. simulation probably using fixed thresholds for microphysic processes independently of  x...) TKE (shaded) & [TKE/( resolvedKE+TKE)]  x = 1 km  x = 125 m  x = 250 m  x = 500 m 0.1 w spectrum at 5 km AGL : 6.  x (~filter order here)

6. formulation of subgrid-scale turbulence often based on Smagorinsky, prognostic TKE introduced in many schemes, but still often length scale l =  (grid), different ways to treat the impact of stability (strong numerical diffusion in some CRMs) subgrid-scale microphysics often ignored [introduction of an artificial cutoff] interactions between subgrid-scale motions and microphysics most often neglected Redelsperger and Sommeria (1986) with no subgrid precip with best subgrid param. Dx = 800 m to 2 km Dx = 800 m to 2 km sensitivity to subgrid scale param. (10 3 kg.s-1) sensitivity to horiz. resolution sensitivity to horiz. resolution convective storm surface rainrate

7. subgrid-scale vertical water flux Redelsperger and Sommeria (1986) change sign when subgrid-scale interactions between microphysics and subgrid fluxestaken into account!

8. adapted from Couvreux (2001) w(x,y) at 0.6 z i (convective boundary layer, clear sky) 30 km  x = 100 m  x = 2 km  x = 10 km max | w | < 1cm.s -1 development of spurious organizations classical organization (open cells) 1D turbulence scheme specific features associated with boundary layer treatment expected behaviour with this resolution

9. 1 2 3 8 10121416  x = 100 m  x = 2 km  x = 10 km potential temperature lst (h) height (km) Wyngaard (2004) 0.5 1.5 2.5 3.5 -0.500.51.1.5 (K..m.s-1) (km) total flux subgrid flux resolved flux buoyancy flux here resolved motions react to (compensate for) too weak subgrid transport, in their own way (cf. organisations) intricacy of interactions between resolved & subgrid processes Couvreux (2001) terra incognita

10. liquid water path (kg.m -2 ) cold air outbreak AVHRR image mesoscale modelling,  x = 2 km solid stratiform cloud deck mesoscale cellular convection  : change from 1 to 0.3 of a coeff. involved in turbu. diffusitivity Fiedler and Kong (2003) from clear sky to cloudy boundary layers...

11. 1 2 3 4 5 height (km ASL) 1 2 3 4 5 1 2 3 4 5 9612151821243 local solar time (h) without subgrid condensation with mixing length l=  in turbulence scheme  = (  x.  y.  z) 1/3 ]  x = 2 km rainwater mixing ratio (g.kg -1 ) highly sensitive, through complex interactions with simulated BL structure... to daytime precipitating convection

12. summary developement of CRMs began in the 80 ’s ; since then, they have been increasingly used (useful) and validated ; they constitute very valuable tools this occurs... even though a proper treatment of subgrid-scale fluxes in CRMs requires more than given by LES-based turbulence schemes probably because the quality of a CRM simulation does not rely on its turbulent (dry) scheme alone + subgrid-scale processes also include subgrid-scale microphysics + subgrid-scale motions and subgrid-scale microphysics interact specific issues regarding parametrisation in CRMs arise from the scales at which boundary layer and moist convection interact computing power available now allows advancing on these issues good timing as CRMs are sollicited to simulate more complex objects and to answer more delicate questions

13. simulation of trade wind cumuli –Stevens et al. (2002)  x = 80 m  x = 40 m  x = 20 m  x = 10 m cloud liquid water horizontal cross-section (g.kg -1 )