1 / 27

Chapter 12: Mountain waves & downslope wind storms

Chapter 12: Mountain waves & downslope wind storms. see also: COMET Mountain Wave Primer. trapped lee waves. Q uasi-stationary lenticular clouds result from trapped lee waves. stack of lenticular clouds.

lacey
Télécharger la présentation

Chapter 12: Mountain waves & downslope wind storms

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Chapter 12: Mountain waves & downslope wind storms see also: COMET Mountain Wave Primer

  2. trapped lee waves

  3. Quasi-stationary lenticular clouds result from trapped lee waves stack of lenticular clouds Try a real-time animation of a cross section of isentropes/winds over the Snowy Range or Sierra Madre (source: NCAR’s WRF runs) MODIS Amsterdam Island, Indian Ocean

  4. 12.1.1 linear theory: sinusoidal mountains, no shear, constant stability, 2D • vertically-propagating waves: • N2 > U2k2 or a> 2pU/N(large-scale terrain) cold u’<0 u’>0 H L warm a evanescent waves: N2 < U2k2 or a< 2pU/N (small-scale terrain) cold u’>0 H warm u’<0 L Fig. 12.3

  5. 12.1.2 linear theory: isolated mountain (k=0), no shear, constant stability, 2D • a >> U/N or U/a >> N a << U/N or U/a >> N lz lx ~0 a=1 km a=100 km witch of Agnesi mountain vertically propagating evanescent – vertically trapped Fig. 12.4 (Durran 1986)

  6. 12.1.3 linear/steady vs non-linear/unsteady both 2D linear theory – analytical solution numerical solution time-independent, i.e. steady trapped lee waves Fig. 12.5 witch of Agnesimtn, N constant, U increases linearly with height ( from Durran (2003) Fig. 12.6

  7. non-linear flow over 2D mountains • Linear wave theory assumes that • mountain height h << flow depth, and • that u’<<U (wave pert. wind << mean wind) • in other words, Fr >>1 • In reality Fr is often close to 1 • Fr <1 : blocked flow, Ep>Ek • Fr >1 : flow over mountain, Ek>Ep • Non-linear effects caused by • terrain amplitude • large u’ (wave steepening and breaking) • transience Froude number non-dimensional mountain height

  8. non-linear flow over an isolated 2D mountain: transient effects Froude # Fr • Fr ~1.3: • no mtn wave breaking, no upstream blocking • resemble linear vert. prop. mtn waves • Fr ~1: • A weakly non-linear, stationary internal jump forms at the downstream edge of the breaking wave. • strong downslope winds near the surface • Fr ~0.7: • jump propagates a bit downstream, and becomes ~stationary • upstream blocking • Fr ~0.4: • upstream flow firmly blocked • wave breaking over crest Dz=14 km 2D numerical simulations over Agnesi mountain The lines are isentropes. The ND time Ut/a = 50.4 Dx=256 km (Lin and Wang 1996)

  9. non-linear flow over an isolated 2D mountain: transient effects Froude # Fr • Fr ~1.3: • no mtn wave breaking, no upstream blocking • resemble linear vert. prop. mtn waves • Fr ~1: • A weakly non-linear, stationary internal jump forms at the downstream edge of the breaking wave. • strong downslope winds near the surface • Fr ~0.7: • jump propagates a bit downstream, and becomes ~stationary • upstream blocking • Fr ~0.4: • upstream flow firmly blocked • wave breaking over crest • linear theory • VP waves (a >> U/N) Dz=14 km 2D numerical simulations over Agnesi mountain The lines are isentropes. The ND time Ut/a = 50.4 Dx=256 km (Lin and Wang 1996)

  10. isentropes wind anomalies early late early late no wave breaking aloft no upstream blocking height (km) wave breaking aloft no upstream blocking height (km) wave breaking aloft upstream blocking wave breaking is first height (km) wave breaking aloft upstream blocking blocking is first height (km) Froude number 14 hrs 3.5 hrs time (for U=10 m/s a = 10 km) 14 hrs 3.5 hrs (Lin and Wang 1996)

  11. 12.2: flow over isolated peaks (3D): covered in chapter 13 (blocked flow) wind

  12. 12.3 downslope windstormsexample: 18 Feb 2009

  13. 12.3 downslope windstormsexample: 18 Feb 2009

  14. 12.3 downslope windstormsexample: 18 Feb 2009

  15. 12.3 downslope windstormsexample: 18 Feb 2009

  16. 12.3downslope windstorms Fig. 12. 9 & 10 q (K) less stable stable u (m/s) Fig. 12.8 Is this downslope acceleration & lee ascent dynamically the same as a hydraulic jump in water? Or is it due to wave energy reflection on a self-induced critical level & local resonance?

  17. Boulder windstorm 11 Jan 1972 Grand Junction CO 00Z 1972/01/12 tropopause 2D simulations by Ming Xue, OU mountain halfwidth = 10 km horizontal grid spacing = 1 km input stability and wind profile  animations of zonal wind u, and potential temperature q: (H=mountain height) • H= 1 km • H= 2 km • H= 3 km stable strong wind shear less stable stable This case study has been simulated by Doyle et al. (2000 in Mon. Wea. Rev.)

  18. 12.3.1 downslope windstorms: (a) hydraulic jump analogy

  19. downslope windstorms: (a) hydraulic theory: shallow water theory Fig. 12.12

  20. downslope windstorms: (a) hydraulic theory - dividing streamline (Smith 1985) dividing streamline Smith 1985 Fig. 12.13 assumptions: steady (Bernouilli) inviscid hydrostatic & Boussinesq Long’s equation Scorer parameter (l)

  21. downslope windstorms – hydraulic theory hmountain=200 m hmountain=300 m • Shallow water eqns assume a density discontinuity (free water surface). Results qualitatively similar to a hydraulic jump can be produced in a numerical model with a stability (N) discontinuity • Durran (1986) does this, using a two layer (Nlow>> Nup) constant wind U environment. Here the mountain height is varied. trapped lee waves ~ subcritical flow hmountain=500 m hmountain=800 m trapped lee waves severe downslope winds top of stable layer at 3 km in each case Fig. 12.14 (numerical simulations by Durran 1986)

  22. downslope windstorms – hydraulic theory d stable layer = 1000 m d stable layer = 2500 m • Durran (1986) also examines the effect of the depth of the low-level stable layer. severe downslope winds mountain height fixed at 500 m in each case d stable layer = 4000 m d stable layer = 3500 m ~ subcritical flow trapped lee waves Fig. 12.15 (numerical simulations by Durran 1986)

  23. plunging flow in Laramie, east of the Laramie Range plunging flow + hydraulic jump? barrier jet ?

  24. downslope windstorms: (b) resonant amplification theory Clark and Peltier (1984) Scinoccaand Peltier(1993) Resonant amplification due to wave energy reflection at the level of wave breaking. The storm is transient, with this evolution according to 2D inviscidsimulations: • wave steepening & breaking produces a well-mixed layer aloft, above the lee slope • This results in a (self-induced) critical level (U=0) • Ri<0.25  KH instability develops on top of the surface stable layer, squeezing that layer & increasing the wind speed (Bernouilli) • strong wind region expands downstream t=0 min t=20 min t=66 min t=96 min t=160 min t=166 min shading shows isentropic layers

  25. downslope windstorms:resonant amplification theory transient flow (4 different times), non-linear linear Fr=20, Ri=0.1 non-linear Fr=20, Ri=0.1 shaded regions: Ri <0.25 • Wang and Lin (1999)

  26. downslope windstorms: forecast clues • asymmetric mountain, with gentle upstream slope and steep lee slope • strong cross-mountain wind (>15 m s-1) at mtn top level • cross mountain flow is close to normal to the ridge line • stable layer near mountain top (possibly a frontal surface), less stable air above • (not always) reverse shear such that the wind aloft is weaker, possibly even in reverse direction ( pre-existing critical level) Note: The Front Range area sees less downslope winds than the Laramie valley in winter in part because of strong lee stratification, due to low-level cold air advected from the Plains states. Thus the strong winds often do not make it down to ground level.

  27. 12.4leerotors A downslope wind storm in the lee of the Sierra Nevada picks dust in the arid Owens Valley. rotor cloud wind h (s-1) blue line applies to the 26 Jan 2006 case, shown below 26 Jan Haimov et al. 2008 (IGARRS) downslope windstorm vorticity sheet (no-slip BC) reverse flow Fig. 12.17

More Related