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Multiscale aspects of cloud-resolving simulations over complex terrain

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Presentation on theme: "Multiscale aspects of cloud-resolving simulations over complex terrain"— Presentation transcript:

1 Multiscale aspects of cloud-resolving simulations over complex terrain
Wolfgang Langhans, Jürg Schmidli, Christoph Schär Institute for Atmospheric and Climate Science, ETH Zurich NWP Seminar MeteoSwiss January 25, 2012 Wolfgang Langhans, NWP Seminar MeteoSwiss

2 What is cloud-resolving?
Also know as: cloud-permitting / convection-permitting cloud system-resolving typically x ~ 1 km nonhydrostatic dynamics resolves deep convection explicitly no parameterization for deep convection may not fully resolve turbulent eddies ... and requires sgs-microphysics parameterization Δ Wolfgang Langhans, NWP Seminar MeteoSwiss

3 What is cloud-resolving?
Weisman et al., MWR (1997) Moeng et al., JAS (2010) Wolfgang Langhans, NWP Seminar MeteoSwiss

4 Moist orographic convection
Fair-weather diurnal convection Weak synoptic-scale forcing Conditionally unstable profiles Triggered from heated surface Pronounced thermally driven flows Observed precipitation (Switzerland) July 2006 Wolfgang Langhans, NWP Seminar MeteoSwiss

5 Convection parameterizations
Randall et al., BAMS (2003): “The cloud parameterization problem is “deadlocked,” in the sense that our rate of progress is unacceptably slow.” SCM GCM (IFS; dx~40 km) RCM (CLM; dx~25 km) mm/h 12 24 UTC Bechtold et al., QJ (2004) Brockhaus et al., MZ (2008) Wolfgang Langhans, NWP Seminar MeteoSwiss

6 Wolfgang Langhans, NWP Seminar MeteoSwiss
Questions 1) Can simulations using parameterized deep convection be improved by increasing numerical resolution? 2) Do cloud-resolving simulations converge? Wolfgang Langhans, NWP Seminar MeteoSwiss

7 Comparison of CPM and CRMs
Long-term (18 days) simulations: CRMs (1.1 and 2.2 km) vs. CPM (6.6 km) Evaluate diurnal evolution of surface flow, its forcing, clouds, and precipitation for the Alpine region Model domain Measurement sites Wolfgang Langhans, NWP Seminar MeteoSwiss

8 Comparison of CPM and CRMs
Diurnal cycle of precipitation and Alpine-scale convergence Wolfgang Langhans, NWP Seminar MeteoSwiss

9 Comparison of CPM and CRMs
Average midday near-surface flow Cloud-resolving Convection-parameterizing Wolfgang Langhans, NWP Seminar MeteoSwiss

10 Comparison of CPM and CRMs
Observed CRM 1.1 km CRM 2.2 km CPM 6.6 km Wolfgang Langhans, NWP Seminar MeteoSwiss

11 Comparison of CPM and CRMs
Average valley wind (Switzerland) and precipitation Wolfgang Langhans, NWP Seminar MeteoSwiss

12 Comparison of CPM and CRMs
Average valley wind (Switzerland) and precipitation Wolfgang Langhans, NWP Seminar MeteoSwiss

13 Comparison of CPM and CRMs
Average valley wind (Switzerland) and precipitation Wolfgang Langhans, NWP Seminar MeteoSwiss

14 Comparison of CPM and CRMs
Average diurnal cycle of cloud cover for Alpine region Low Mid 3 h High Observation (Meteosat-8) Convection-parameterizing Cloud-resolving Wolfgang Langhans, NWP Seminar MeteoSwiss

15 Wolfgang Langhans, NWP Seminar MeteoSwiss
Short summary Increasing resolution will not improve the errorenous timing of convective activity in simulations using traditional parameterizations of deep convection The discontinuity introduced by the parameterization prevents the convergence with kilometer-scale cloud- resolving runs Differences between CRMs (1.1 and 2.2) are found to be small (except local valley winds) Do CRMs converge? Wolfgang Langhans, NWP Seminar MeteoSwiss

16 What governs convergence of CRMs?
Stability and consistency of applied numerical schemes Reynolds number (i.e., eddy viscosity) Underlying topography Predictability Response of other parameterizations (e.g., microphysics) to modified grid-scale flow Numerical convergence of CRMs? Physical convergence of CRMs? Wolfgang Langhans, NWP Seminar MeteoSwiss

17 Setup for convergence experiment
Approach analogous to method applied by Mason and Brown, JAS (1999) Turbulent length-scales Physical convergence Numerical convergence Physical convergence Langhans et al., JAS (submitted) Wolfgang Langhans, NWP Seminar MeteoSwiss

18 Setup for convergence experiment
Topography: Grid-independent A B C D Predictability: Bulk properties for a large Alpine control volume and for an ensemble of nine consecutive days Wolfgang Langhans, NWP Seminar MeteoSwiss

19 Resolved energetic scales
Numerical convergence Physical convergence Involved scales are grid-independent Involved scales are grid-dependent Wolfgang Langhans, NWP Seminar MeteoSwiss

20 Small-scale cloud structures
Numerical convergence: constant Reynolds numbers Physical convergence: increasing Reynolds numbers Wolfgang Langhans, NWP Seminar MeteoSwiss

21 Numerical bulk convergence
Net volume heating Net volume moistening Wolfgang Langhans, NWP Seminar MeteoSwiss

22 Numerical bulk convergence
RMSE for Heating RMSE for Moistening Δ x Δ x All bulk properties converge to the 0.55 km solution Bulk heating/moistening and vertical fluxes are almost resolution- independent at km-scales Wolfgang Langhans, NWP Seminar MeteoSwiss

23 Physical bulk convergence
Mean diurnal cycles for heating (“3D turbulence closure”) Weak sensitivity of net PBL heating/moistening to horizontal resolution Compensating behavior of advection and diabatic tendencies Wolfgang Langhans, NWP Seminar MeteoSwiss

24 Mean diurnal cycle of precipitation
Numerical Conv. Phys. Conv. (1D) Phys. Conv. (3D) mm/h averaged for Alpine region Wolfgang Langhans, NWP Seminar MeteoSwiss

25 Physical bulk convergence
decreasing resolution-sensitivity decreasing resolution-sensitivity 1D turbulence closure 3D turbulence closure Wolfgang Langhans, NWP Seminar MeteoSwiss

26 Summary and conclusions
Numerical convergence of bulk properties has been demonstrated Physical convergence is reflected in bulk properties for 1D closure Physical convergence is less obvious for a 3D closure, but resolution-sensitivity is generally small for net tendencies Physical convergence is also reflected in precipitation The grid spacing required to simulate the bulk PBL heating/moistening rates appears not to be controlled by eddy- resolving scales or by the subgrid-scale mixing parameterization Results enhance the credibility of kilometer-scale simulations and strengthen the physical validity of the approach Wolfgang Langhans, NWP Seminar MeteoSwiss

27 Open questions on bulk convergence
Does the large-scale topographic forcing support the convergence of bulk properties? Is the “isotropy-assumption” of the LES closure valid at km-scales? Would lv~dz, lh~dx yield an improved bulk convergence? What causes the precise compensation among turbulence and microphysics tendencies? Wolfgang Langhans, NWP Seminar MeteoSwiss

28 Explicit numerical diffusion
+ COSMO-specific technical detail (COSMO-LES and budget tool) will be presented in the next issue of the COSMO newsletter Wolfgang Langhans, NWP Seminar MeteoSwiss

29 Wolfgang Langhans, NWP Seminar MeteoSwiss
Thanks! Wolfgang Langhans, NWP Seminar MeteoSwiss

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