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Orographic Precipitation
John HorelDepartment of Meteorology
University of Utahjohn.horel@utah.edu
AcknowledgmentsJim Steenburgh, U/Utah
Steenburgh and Alcott 2008
Salt Lake City Snow Season
Mean: 161 days from first 1inch to last
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References• Bailey, C. et al., 2003: An objective climatology, classification scheme, and assessment of sensible weather impacts for
Appalachian cold-air damming Weather and Forecasting , 18, 641-661. • Bougeault, P., and Coauthors, 2001: The MAP Special Observing Period. Bull. Amer. Meteor. Soc., 82, 433–462. • Colle, B., Y. Lin, S. Medina, B. Smull, 2008: Orographic modification of convection and flow kinematics by the Oregon coast
range and Cascades during IMPROVE-2 . Monthly Weather Review , 136, 3894–3916.• Hanna, J., D. Schultz, and A. Irving , 2008: Cloud-Top Temperatures for Precipitating Winter Clouds . Journal of Applied
Meteorology and Climatology, 47, 351–359 • Houze, R., S. Medina, 2005: Turbulence as a Mechanism for Orographic Precipitation Enhancement . Journal of the
Atmospheric Sciences , 62, pp. 3599–3623 • James, C., R. Houze, 2005: Modification of Precipitation by Coastal Orography in Storms Crossing Northern California Monthly
Weather Review , 133, 3110–3131 • Lundquist, J., P. Neiman, B. Martner, A. White, D. Gottas, F. Ralph , 2008: Rain versus Snow in the Sierra Nevada,
California: Comparing Doppler Profiling Radar and Surface Observations of Melting Level Journal of Hydrometeorology , 9, 194–211.
• Medina, S., E. Sukovich, R. Houze, 2007: Vertical Structures of Precipitation in Cyclones Crossing the Oregon Cascades Monthly Weather Review , 135, 3565–3586.
• Olson. J et al.,2007: A comparison of two coastal barrier jet events along the southeast Alaskan coast during the SARJET field experiment. Mon. Wea. Rev., 135, 3642-3663.
• Neiman P. J., F. M. Ralph, A. B. White, D. D. Parrish, J. S. Holloway, and D. L. Bartels, 2006: A midwinter analysis of channeled flow through a prominent gap along the northern California coast during CALJET and PACJET. Mon. Wea. Rev., 134, 1815–1841.
• Schultz, D. M., and Coauthors, 2002: Understanding Utah winterstorms: The Intermountain Precipitation Experiment. Bull.Amer. Meteor. Soc., 83, 189–210.
• Smith, R. B., 1979: The influence of mountains on the atmosphere. Adv. Geophys, 21, 87-230 • Steenburgh, W. J., 2003: One hundred inches in one hundred hours: Evolution of a Wasatch Mountain winter storm cycle.
Wea. Forecasting, 18, 1018-1036. • Steenburgh, J., T. Alcott, 2008: Secrets of the “Greatest Snow on Earth” . Bulletin of the American Meteorological Society, 89,
1285–1293 • Stoelinga, M. T., and Coauthors, 2003: Improvement of microphysical parameterization through observational verification
experiment. Bull. Amer. Meteor. Soc., 84, 1807–1826. . • Woods, C., M. Stoelinga, J. Locatelli, P. Hobbs, 2005: Microphysical Processes and Synergistic Interaction between Frontal
and Orographic Forcing of Precipitation during the 13 December 2001 IMPROVE-2 Event over the Oregon Cascades Journal of the Atmospheric Sciences , 62, 3493–3519.
• Woods, C., M. Stoelinga, J. Locatelli, 2008: Size Spectra of Snow Particles Measured in Wintertime Precipitation in the Pacific Northwest Christopher P. Woods, Mark T. Stoelinga, and John D. Locatelli Journal of the Atmospheric Sciences , 65, 189–205
COMET Module Resources• Flow Interaction with Topography • Thermally-forced Circulation II: Mountain/Valley Breezes • Mountain Waves and Downslope Winds • PBL in Complex Terrain - Part 1 • PBL in Complex Terrain - Part 2 • Gap Winds • Cold Air Damming • Challenges of Forecasting in the West
• Dynamics & Microphysics of Cool-Season Orographic Storm– Jim Steenburgh U/Utah
Recent Orographic Precipitation Field and Testbed Programs
• CALJET/PACJET (Neiman et al. 2006, Kingsmill et al. 2007)
• Mesoscale Alpine Programme (MAP; Bougeault et al. 2001)
• Intermountain Precipitation Experiment (IPEX; Schultz et al. 2002)
• Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE; Stoelinga et al. 2003)
• Hydrometeorological Testbed West http://hmt.noaa.gov/
Recognizing terrain’s role in the forecast process
• Planetary scale – mean ridge and trough positions
• Synoptic scale – cyclogenesis and anticyclogenesis– fronts
• Mesoscale– Dynamically & thermally driven
circulations– Orographic precipitation processes
• Local scale– Impacts of local surface
inhomogeneities
Does Terrain Improve or Destroy Predictability?
TerrainDegradedforecasts
Observations may not be representative
Improvedforecasts
Inadequate modelresolution
Incomplete modelphysics
Nonlinearscale interactions
Does Terrain Improve or Destroy Predictability?
Terrain
Degradedforecasts
Improvedforecasts
Recurring phenomena
Recognizablespatial dependencies
Physically-basedconceptual models
Does Terrain Improve or Destroy Predictability?
Terrain
Degradedforecasts
Observations may not be representative
Improvedforecasts
Recurring phenomena
Recognizablespatial dependencies
Inadequate modelresolution
Incomplete modelphysics
Nonlinearscale interactions
Physically-basedconceptual models
Forecaster has decided advantage over models to improve forecasts when dealing with terrain issues compared to dealing with mesoscale instabilities
If the earth were greatly reduced in size while maintaining its shape, it would be smoother than a billiard ball. (Earth radius = 6371 km; Everest = 8.850 km)
However, the atmosphere is also shallow (scale height ~8.5 km) so mountains are a significant fraction of atmosphere’s depth
And: Stability gives the atmosphere a resistance to vertical
displacements The lower atmosphere can be rich in water vapor so that slight
ascent brings the air to saturation Example: flow around a 500-m mountain (<< 8.5 km) might lead
to 1) broad horizontal excursions, 2) downslope windstorm on lee side, and 3) torrential orographic rain on windward side.
Smith, R. B., 1979: The influence of mountains on the atmosphere. Adv. Geophys., 21, 87-230.
Why is Terrain So Important?
Building blocks for orographic storms• Large-scale weather (e.g., cyclones and
fronts)– Determines the airmass characteristics, including
wind speed, wind direction, stability, and humidity• Dynamics of air motion over and around the
mountains– Determines depth and intensity of the orographic
ascent• Cloud and precipitation microphysics
– Determines if condensation will lead to precipitation
See COMET module Dynamics & Microphysics of Cool-Season Orographic Storms
Summary of cold cloud precipitation processes
• Condensational growth of cloud droplet
• Some accretional growth of cloud droplets
• Development of mixed phase cloud as ice nuclei are activated and ice multiplication process occurs
• Crystal growth through Bergeron-Findeisen process– Creates pristine ice
crystals– Most effective at –10 to
–15 C
Summary of cold cloud precipitation processes
• Other possible effects– Accretion (riming) of supercooled cloud droplets onto
falling ice crystals or snowflakes• Snowflakes will be less pristine or evolve into
graupel• Favored by:
– Warm temperatures (more cloud liquid water)– Maritime clouds (bigger cloud droplets)– Strong vertical motion
– Aggregation• Entwining or sticking of ice crystals
• Fig. 1. Histograms of cloud-top brightness temperatures (°C) for (a) all snow, (b) light snow, (c) moderate snow, and (d) heavy snow.
Cloud-top temperatureHanna et al. (2008)
Steep slope in the snow distribution for cloud-tops warmer than −15°C likely due to the combined effects of:• above-freezing
cloud-top temperatures not producing snow,
• the activation of ice nuclei
• the maximum growth rate for ice crystals at temperatures near −15°C
• ice multiplication processes from −3° to −8°C.
• FIG. 7. A sample spectral trajectory from a frontal precipitation band off the coast of Washington State (not during IMPROVE), with the growth stages indicated by the shaded regions (from Lo and Passarelli 1982).
Woods et al. (2008)
Large Small
Many
Few
Orographic Enhancement
• Role of mountains on precipitation can be examined by comparing climatological or storm total precipitation in upstream valleys to that in the mountains
• Orographic Enhancement Ratio: – Mountain precipitation/Valley precipitation
• Ratio> > 100% then mountains playing significant role enhancing total precipitation
Orographic precipitation mechanisms• Stable upslope
• “Seeder-Feeder”
• Potential instability release
• Sub-cloud evaporation contrasts
• Terrain-driven convergence
• Terrain-induced thunderstorm initiation
Usually multiple mechanisms evolving during storm
University of Utah
Stable upslope
• Stable (laminar) ascent is forced by flow over a mountain
• If air forced over mountain is sufficiently moist through a deep layer, precipitation develops
• If not, shallow, non-precipitating clouds develop• Not very efficient if operating alone
www.capetownskies.com
Seeder-Feeder
• Snow or rain generated in “seeder” clouds aloft falls through low-level orographic “feeder” clouds– Feeder cloud might not otherwise produce precipitation– Precipitation enhanced by collision-coalescence and accretion
in feeder cloud• Seeder cloud can be frontal, or orographically generated/enhanced• Common over Cascades, Sierra, and coastal ranges, particularly in
pre-frontal environment
Seeder Cloud
Feeder Cloud
Jay Shafer
Sub-cloud evaporation contrasts
• Precipitation reaches ground over mountains because layer in which sub-cloud evaporation is occurring is shallower
• Common over Great Basin, particularly during periods of stable, overrunning precipitation
Jay Shafer
Sub-cloud evaporation contrasts
• Orographic ascent increases RH, resulting in less evaporation over mountains compared to over plains
• Further enhances sub-cloud evaporation contrast
RH=50% RH=75%
Jay Shafer
Upslope release of “potential instability”
• Potential instability – Special situation where orographic lift triggers convection
• Convection may be deep or shallow – both can result in substantial precipitation
enhancement• Important for postfrontal snow, or precipitation just ahead
of cold front if there’s a pre-frontal surge of cold air aloft
Terrain-driven convergence • Terrain-induced flow produces
convergence, lift, and precipitation• Examples
– Windward convergence in Wasatch, San Juans, Front Range, Park Range
• Ascent shifted upstream of initial mountain slope
• Slight reduction in crest-level precipitation
– Lee-side convergence zones • e.g., Puget Sound Convergence
Zone• Flow converges to lee of
Olympics
Mass (1981)
Terrain-forced flows• Two types of mountain winds
– Diurnal mountain winds (thermally driven circulations): produced by temperature contrasts that form within mountains or between mountains and surrounding plains
– Terrain-forced flows: produced when large-scale winds are modified or channeled by underlying complex terrain
• Terrain forcing can cause an air flow approaching a barrier to be carried over or around the barrier, to be forced through gaps in the barrier or to be blocked by the barrier. Use COMET modules for further background– See http://meted.ucar.edu/mesoprim/flowtopo/– See http://meted.ucar.edu/mesoprim/gapwinds/– See http://meted.ucar.edu/mesoprim/mtnwave/
• Three variables determine this behavior of an approaching flow– Stability of approaching air (Unstable or neutral stability air can be easily
forced over a barrier. The more stable, the more resistant to lifting)– Wind speed (Moderate to strong flows are necessary)– Topographic characteristics of barrier
Over or Around?
• Potential energy: energy required to lift parcel over obstacle in statically stable environment– PE proportional to stability (N2) * obstacle height (h2)
• Kinetic energy: energy available due to air’s motion– KE proportional to wind speed (U2)
• Froude number squared: ratio of kinetic energy to potential energy– Fr = U/(Nh)– Fr >> 1 plenty of kinetic energy to lift air over obstacle– Fr << 1 not enough kinetic energy and flow blocked
by terrain
Blocking
-Affect stable air masses and occur most frequently in winter or coastal areas in summer
-The blocked flow upwind of a barrier is usually shallower than the barrier depth. Air above the blocked flow layer may have no difficulty surmounting the barrier and may respond to the ‘effective topography’ including the blocked air mass.
-Onset and cessation of blocking may be abrupt
-Predicting onset often easier than predicting demise
Cold Air Damming:Geostrophic Adjustment
Bailey, C. et al., 2003: An Objective Climatology, Classification Scheme, and Assessment of Sensible Weather Impacts for Appalachian Cold-Air Damming Weather and Forecasting , 18, 641-661.
Case Study: The “Hundred Inch Storm”• Produced by two major storm
systems (22-27 Nov 2001)• Alta, Utah
– 100” in 100 hours– 108” storm total
• Questions:– What are the primary storm
stages?– How do precipitation
processes vary between stages?
– How does the orographic enhancement vary between stages?
– How do precipitation rates and totals vary between stages?
Steenburgh, W. J., 2003: One hundred inches in one hundred hours: Evolution of a Wasatch Mountain winter storm cycle. Wea. Forecasting, 18, 1018-1036.
Initial strike – Stable prefrontal stage
• Mainly stratiform precipitation• Subcloud
sublimation/evaporation limited valley precipitation
• Alta/SLC SWE = 217%
0 0.05 0.1 0.15 0.2
Alta
SLC
Precip rate (SWE/ h)
Alta SLC
Initial strike – Unstable prefrontal stage
• Intrusion of cold, dry air aloft produces in convection
• Convection not always tied to topography
• Smallest orographic enhancement of first storm
• Alta/SLC = 180%
0 0.05 0.1 0.15 0.2
Alta
SLC
Precip rate (SWE/ h)
Alta SLC
Initial strike – Frontal passage• Cold front with trailing
precipitation region • Alta/SLC = 218%
0 0.05 0.1 0.15 0.2
Alta
SLC
Precip rate (SWE/ h)
Alta SLC
Initial strike – Postfrontal stage I
• Precipitation became increasingly confined and heaviest to lee of GSL and over Wasatch Mountains
• Lake band development• Alta/SLC = 278%
0 0.05 0.1 0.15 0.2
Alta
SLC
Precip rate (SWE/ h)
Alta SLC
Initial strike – Midlake band
• Solitary midlake band• Orographic enhancement in
lakeband• Alta/SLC = 241%
0 0.05 0.1 0.15 0.2
Alta
SLC
Precip rate (SWE/ h)
Alta SLC
Initial strike – Postfrontal Stage II• Scattered snowshowers• Most frequent to lee of
GSL• Alta/GSL = 500%
0 0.05 0.1 0.15 0.2
Alta
SLC
Precip rate (SWE/ h)
Alta SLC
Initial strike summaryPostFront II Lakeband Postfront I Frontal UPF Stable
63% of Alta SWE was postfrontal20% due to orographically enhanced lakeband
Additional lake effect in PF1 and PF2
Alta SWE by Stage
StableUPFFrontalPF1LakebandPF2
11%
16%
10%
33%
20%
10%
UpperCold Front
Cold Front
Physical Mechanisms modulating orographic precipitation
• Gravity waves in statically stable environments• Transient turbulent updrafts observed under statically stable conditions in
the presence of strong low-level shear• Upstream enhancement in statically stable and blocked-flow conditions• Windward enhancement in potentially unstable cases, which can organize
convection into narrow convective bands
(adapted from Colle et al. 2008)
Conceptual model of the dynamical and microphysical mechanisms responsible for the orographic enhancement of precipitation during storms with stable stratification. Houze and Medina (2005)
Convective Organization
• Observational and modeling studies show that orographic precipitation is enhanced in convective events compared to stratiform events– increased area-averaged precipitation– quasi-stationary banded structures that concentrate most of their
rainfall over specific locations. • Common ingredients for band formation
– potential instability– High relative humidity– moderate wind speeds in the upstream flow– presence of small-scale topographic obstacles on the terrain
upstream of the ridge crest
Adapted from Kirshbaum et al. (2007)
Convective banding
• FIG. 14. Three-dimensional simulation of band formation. The underlying terrain is green, and the qc = 0.05 g kg−1 contour is light blue. Parcel trajectories at y = 10 km and y = 15 km overlaid on these fields are red (blue) when the parcel’s buoyancy is positive (negative) relative to the nodal line at y = 12.5 km.
Strategies for Forecasting Orographic Precipitation
• Take advantage of local observational resources– Station and radar climatologies
• Identify kinematic features on meso and local scales
Strategies for Forecasting Orographic Precipitation
• Take advantage of lessons learned and conceptual models relevant to your region developed from field programs and modeling studies
Woods et al. 2005
Schematic representation of potential frontal structures and cloud liquid water production above a mountain barrier in response to low-level flow patterns. Darkly shaded regions indicate clouds with the highest cloud liquid water. (a) For a tipped-backward front and prefrontal easterly flow. (b) As in (a), but for a tipped-forward front. (c) For a tipped-backward front and prefrontal westerly flow. (d) As in (c), but for a tipped-
forward front. Woods et al. (2005)
Strategies for Forecasting Orographic Precipitation
• Use high resolution forecast models carefully• Model vertical motions induced by terrain may be quite
different from those observed given characteristics of model terrain
• Local model biases• Model realism is not necessarily an indicator of accuracy• There are signficant practical limitations to high
resolution modeling- be particularly cognizant of tendency for high false alarm rate for high impact weather events
• “All models are wrong, but some are useful” J. Steenburgh