Large Eddy Simulation: Estimation, Attribution, Exploration

Transcription

1 bjorn.stevens ucla atmos & ocean sci IMAGe-3 Nov Large Eddy Simulation: Estimation, Attribution, Exploration 1

2 what is large eddy simulation? A religion? Three-dimensional flows whose smallest cut-off/ filter scale is within a well developed inertial range of three dimensional turbulence. A flow realized in a manner which converges to Navier-Stokes (DNS) as the grid spacing of the solver that produces it goes to zero (auxillary condition) Compare to Eddy-Permitting simulations. 2

3 caveats? Notwithstanding the phenomenological theories, closures that properly mediate the cascade have proven elusive. Most flows of interest are bounded, and interact with their boundaries in interesting, and important ways... and calculations are always under-resolved at boundaries. Stratification. Tests on flows of interest are almost always impossible. 3

4 what is it good for? (i) parameter estimation z y x U 1, 1 U 2, 2 splitter plate Turbulent Mixing Layer x Pseudoempiricism... The spreading angle of the mixing layer. Partitioning of energy among velocity components. Similarity profile of downstream velocity. 4

5 my pet problem* q t l q l 5 *(not nearly so important as deep convection... )

6 Recall from last time, the bulk equation may be written as Defining, h D φ Dt + φ [ ] Dh Dt + Dh = w φ F φ (1) V w φ 0 0 φ, M w φ + + φ and E Dh Dt + Dh + M (2) yields Dh Dt Dŝ Dt D q Dt = E Dh M (3) = E(q + q) V ( q q 0 ) F s h = E(q + q) V ( q q 0 ) F q h (4) (5) Given the large-scale flow (D, s +, q + ), surface properties, s 0, q 0 and F s, F q, as a function of the state, closure requires a specification of M, V, E. 6

7 the stratocumulus question If and what is α? M = 0 and V = C d v E = α F s s + ŝ what is alpha? 7

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9 woops... Table 4. The averaged growth rate of the cloud-top height during the second hour of simulation Group!! E KNMI!! 1.68 UOK!!! 1.32 UMIST!! 0.94 NCAR!! 0.91 UKMO!! 0.86 CSU!!! 0.67 UW!!! 0.51 MPI!!! 0.44 WVU!!! 0.28 ARAP!! LWP [gm -2 ] Time [hours] Moeng et al., Bull. Amer. Meteorol. Soc. (1996) 9

10 E [mm/s] DH 3DN 3DM 2D 1D Bretherton et al., Quart. J. Roy. Meteorol. Soc. (1998) 10

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12 GOES, AVHRR, TRMM, QuickScat DYCOMS-II (July 2001): observing platforms SABL DMS Inlet Gust Probe Lyman s CO,O 3,CO 2 Cloud Radar 20.2m Sondes 260X, 2D-C King Probe 6.2m CIN, UFT-F King Probe SPP100, SPP 300, TDL, MCR, Cloud Water Collector Rosemounts SABL, SPP 100, Fast FSSP, PVM aerosol inlets (CVI, LTI, SDI) adapted from Stevens et al., (2003) 12

13 DYCOMS-II (July 2001): flight strategy 800m 30km 13

14 Method Estimate [cm s ] budget budget cloud-top flux O cloud-top flux DMS cloud-top flux Weighted Average Base Case Test Cases Model AL CM DL NT NT LL

15 LES evaluation using DYCOMS-II data 15 (stevens et al., 2005, MWR)

16 remarks efforts to reduce mixing made most models perform better in almost every respect. groups whose simulations better represented the cloud layer tried to take credit... data does seem to bound entrainment, which usefully guides parameterization (tuesday s talk). 16

17 what is it good for? (ii) attribution 17

18 Pockets of Open Cells during DYCOMS 18

19 ... and EPIC 19 Comstock,Yuter, Wood, Bretherton

20 (LES) Pseudo Albedo at 5400 and 17100s 20 thanks to v. savic-jovcic

21 what is it good for? (ii) exploration 21

22 what determines growth rate of layer? cloud fraction? mass flux at cloud base? velocity scales? 22

23 Visualizations (from three vantage points) of large-eddy simulations of non-precipitating shallow convection: nz=131, nx=ny=128, dz~dx=dy=37.5m Side view 45 deg view (soon) top view (eventually) orange: 1m/s isosurface purple: -1m/s isosurface white: cloud water isosurface 23

24 Temporal evolution of distinguished layers: 24

25 remarks layer grows as t... growth is mostly through injection, as opposed to mechanical mixing. mass flux scaling determined by subcloud layer scale velocity scales. more on shallow convection* in Zhiming s talk 25 *(not nearly so important as deep convection... )

26 concluding remarks large-eddy simulation is a popular and effective way to generate information about turbulent flows. because most flows of interest depend critically on the interaction of a flow with either the surface or the bounding fluid there is no guarantee that the information will be useful. these statements apply equally to other flow solving strategies (CRM). our persistent use of the methodology is also a statement about the alternatives. 26