What we have learned about Orographic Precipitation Mechanisms

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• What we have learned about Orographic
  Precipitation Mechanisms
• from MAP and IMPROVE-2
• MODELING
• Socorro Medina, Robert Houze, Brad Smull
• University of Washington
• Matthias Steiner
• Princeton University
• Nicole Asencio
• Meteo-France

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Windward Shear Layer Repeatable pattern in
different storms/mountain ranges
?
Medina, Smull, Houze, and Steiner (2005) JAS -
IMPROVE Special Issue
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Objective 1

• Investigate how the shear layer
• develops. Explore the role of
• Pre-existing baroclinic shear
• Surface friction
• Stable flow retarded by steep terrain

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Approach 2D Idealized simulations

• Weather Research and Forecasting (WRF) model
  version 1.3 in Eulerian mass coordinates
• Domain 800 km x 30 km (120 vertical layers)
• 2 km horizontal resolution 250 m vertical
  resolution
• Lin et al. (1983) microphysical scheme
• Land surface
• Option 1 Frictionless free-slip surface
• Option 2 Non-dimensional surface drag
  coefficient Cd 0.01
• 2D bell-shaped mountain (characterized by height
  h and half-width a) placed in the center of
  horizontal domain
• Alpine-like simulations h3.1 km a44 km
• Cascade-like simulations h1.9 km a32 km
• Results shown after 30 hours of initialization

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Initialized with vertically uniform wind speed
(10 m/s) and stability saturated atmosphere with
Ts 283 K
ALPS-like mountain
Color- Horizontal wind Contours-Wind shear
?
Nm2 0.03x10-4 s-2
Stability
Nm2 0.3x10-4 s-2
Height (km)
?
Nm2 1.0x10-4 s-2
Medina, Smull, Houze, and Steiner (2005) JAS -
IMPROVE Special Issue
Free-slip
Cd0.01
Distance (km)
Friction ?
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CASCADE-like mountain
Initialized with vertically uniform wind speed
(10 m/s) and stability saturated atmosphere with
Ts 283 K
Color- Horizontal wind Contours-Wind shear
?
Nm2 0.03x10-4 s-2
Stability
Nm2 0.3x10-4 s-2
Height (km)
?
Nm2 1.0x10-4 s-2
Medina, Smull, Houze, and Steiner (2005) JAS -
IMPROVE Special Issue
Free-slip
Cd0.01
Distance (km)
Friction ?
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Idealized Simulation of Case 13-14 Dec 2001
HORIZONTAL WIND
Height (km)
Height (km)
Shear 12.5 m s-1 km-1
WIND SHEAR
Zonal Wind (m/s)
RH ()
T (C)
Initial conditions Solid lines
Medina, Smull, Houze, and Steiner (2005) JAS -
IMPROVE Special Issue
Distance (km)
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• Conclusions 1
• Idealized simulations show that orographic
  effects alone are sufficient to produce a shear
  layer on the windward side of the terrain when
  the stability is high enough (e.g. Alpine cases)
• Simulations based on IMPROVE-2 environmental and
  terrain condition indicate that surface friction
  and/or pre-existing shear were necessary to
  produce an enhanced layer of shear

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Objective 2
Investigate if mechanisms of orographic
precipitation enhancement deduced from
observations are also present in mesoscale models
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FLOW-OVER Precipitation enhancement by
coalescence riming over first peak
Medina and Houze (2003)
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Approach

• Focus on MAP IOP2b
• Meso-NH mesoscale non-hydrostatic model used by
  French research community (Lafore et al. 1998)
• 2.5-km horizontal resolution nested in a 10-km
  horizontal resolution domain
• Initial and lateral conditions
• Given by linearly interpolating in time French
  Operational Analysis (ARPEGE) for 10-km
  resolution domain
• Given by 10-km resolution domain for 2.5 km
  resolution domain
• 2.5-km horizontal resolution domain
  Microphysical bulk parameterization including
  cloud, rain, ice, snow, and graupel (Pinty and
  Jabouille 1998)
• Validation of simulation conducted by Asencio et
  al. 2003 (QJMRS)

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Comparison of IOP2b radar observations and
simulation
20 SEP OBSERVED RAIN ACCUMULATION (mm)
20 SEP OBSERVED RADIAL VELOCITY (m/s)
(Provided by J. Vivekanandan)
20 SEP SIMULATED RAIN ACCUMULATION (mm)
20 SEP SIMULATED RADIAL VELOCITY (m/s)
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Observed and Simulated Mean Hydrometeors (over 7h)
FREQUENCY OF OCCURRENCE OF OBSERVED HEAVY RAIN
()
MIXING RATIO OF SIMULATED RAIN (kg/kg)
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Observed and Simulated Mean Hydrometeors (over 7h)
FREQUENCY OF OCCURRENCE OF OBSERVED DRY SNOW ()
MIXING RATIO OF SIMULATED SNOW (kg/kg)
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Mean Microphysical Processes CLOUD (over 7h)
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Mean Microphysical Processes GRAUPEL (over 7h)
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Mean Microphysical Processes RAIN (over 7h)
RATE OF RAIN GROWTH BY GRAUPEL AND SNOW MELT
(S-1)
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• Conclusions 2
• A Meso-NH simulated cross-barrier flow of IOP2b
  had the correct structure but the speed was
  overestimated.
• The Meso-NH simulation produced precipitation
  patterns comparable with the radar observations.
• The location and occurrence of simulated
  microphysical processes of orographic
  precipitation enhancement are consistent with the
  S-Pol polarimetric radar data.
• Graupel is created by riming of cloud and it
  grows by collection of snow and cloud.
• Rain is produced via melting of graupel ( snow)
  followed by cloud accretion.
• The model suggests that hydrometeor growth rates
  can be 4-7 times larger over the mountains than
  over the low elevations.

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FIN
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a Lr (N h) f-1 fCoriolis parameter b Ro u
(f a)-1 c Fr u (N h)-1 d Vertically averaged
over the lowest 3 km.
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Garvert et al. 2005
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IOP2b Wind profiler data
OBSERVATION
SIMULATION
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Mean Microphysical Processes GRAUPEL (over 7h)
RATE OF GRAUPEL GROWTH BY SNOW RIMING CLOUD (S-1)
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Mean Microphysical Processes RAIN (over 7h)
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Observations Simulation
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2D Simulation with 100 m resolution of stable
flow over a 2 km ridge conducted by with Bryan
and Fritsch (2002) model
Simulation conducted by D. Kirshbaum
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Precipitation
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Precipitation
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Precipitation
N_m2(g/T)(dT/dz Gamma_m)(1Lq_s/RT) Gamma_mG
amma_d(1q_w)(11Lq_s/RT)f(T,q_s,q_L)