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and its influence on rainfall distribution. Blocking in areas of complex topography. Mimi Hughes Alex Hall Rob Fovell UCLA. Rain in Southern California.

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rain in southern california
Rain in Southern California

Orographic enhancement and blocking: heavy precipitation during Northern California New Year’s floods of 1997 was almost entirely due to the interaction of the flow with topography (see Galewsky and Sobel, 2005)

slide4

As air moves over topography it is forced to rise, causing moisture to condense and fall out:

P: Precipitation

qU: Moisture flux

h(x,y): Terrain

See Smith (1979), Roe (2005), etc.

Wind

Flow over?

(mechanical lifting…)

Precipitation (grayscale) and topography (contours) for an idealized numerical study. From Jiang (2003)

slide5

As air moves over topography it is forced to rise, causing moisture to condense and fall out:

P: Precipitation

qU: Moisture flux

h(x,y): Terrain

See Smith (1979), Roe (2005), etc.

Wind

Flow over?

(mechanical lifting…)

Is this too simple?

Precipitation (grayscale) and topography (contours) for an idealized numerical study. From Jiang (2003)

slide6

Wind

Or Flow around?

(aka blocked flow)

If the air approaching a barrier does not have enough kinetic energy to surmount it, the flow will be blocked (Smolarkiewicz and Rotunno, 1990; Pierrehumbert and Wyman, 1985). This can enhance precipitation upwind of the barrier.

Precipitation (grayscale) and topography (contours) for an idealized numerical study. From Jiang (2003)

case studies blocking influencing precipitation
Case studies: Blocking influencing precipitation
  • Medina and Houze (2003) compared two synoptic events during the mesoscale alpine program and found a substantial difference in precipitation and wind between them.
    • Less stable, higher wind speed case => winds uniform with height and precipitation greatly enhanced on the windward slope
    • More stable, lower wind speed case => wind shear in the lowest layers and precipitation more evenly distributed
  • Neiman et. al. (2004) found that orographic blocking affected the propagation of the fronts during a storm from the 1997/98 season, substantially impacting the distribution of precipitation
slide8

Motivation:

To investigate what processes are essential to predicting the distribution of precipitation in complex topography

Approach:

Systematic study using a hierarchy of models

slide10

Topography

Shuttle Radar Topography Mission elevation shown as shaded relief

slide11

Precipitation observations

Cooperative Observation Precipitation measurements: average of daily rainfall from May 1995 to April 2006. Black contours show topography.

slide12

Winds during rain

Vectors show wind speed and direction; colored contours show wind speed in m/s.

slide13

Coastal zone

Cooperative Observation Precipitation measurements: average of daily rainfall from May 1995 to April 2006. Black contours show topography.

slide14

Upslope Model?

Solid line shows linear regression. Large pale blue bullet is GPCP open-ocean average (119.5W-121.5W, 31.5N-32.5N)

questions i ll address
Questions I’ll address…
  • Does orographic blocking occur during raining hours in Southern California?
  • Does blocking significantly impact the climatological distribution of precipitation?
  • Is there a simple way to get a quantitative estimate of the impact of blocking on precipitation?
slide17

MM5 Configuration

  • release 3.6.0
  • boundary conditions: Eta model analysis
  • resolution:
    • domain 1: 54 km, domain 2: 18 km, domain 3: 6 km
    • 23 vertical levels.
  • time period: May 1995 to April 2006 (re-initialized every 3 days)
  • Parameterizations:
    • MRF boundary layer
    • Simple ice microphysics
    • Clear-air and cloud radiation
    • Kain-Fritsch 2 cumulus parameterization in coarse domains, only explicitly resolved convection in 6 km domain
slide18

MM5 Configuration

  • release 3.6.0
  • boundary conditions: Eta model analysis
  • resolution:
    • domain 1: 54 km, domain 2: 18 km, domain 3: 6 km
    • 23 vertical levels.
  • time period: May 1995 to April 2006 (re-initialized every 3 days)
  • Parameterizations:
    • MRF boundary layer
    • Simple ice microphysics
    • Clear-air and cloud radiation
    • Kain-Fritsch 2 cumulus parameterization in coarse domains, only explicitly resolved convection in 6 km domain

One can think of this as a reconstruction of weather conditions over this time period consistent with three constraints: (1) our best guess of the large-scale conditions, (2) the physics of the MM5 model, and (3) the prescribed topography, consistent with model resolution.

slide19

Model

Validation:

Precipitation

slide20

Model Validation: Precipitation

Spatial Correlation: 0.87

Regression:

slope = 1.13

intercept = 0.39 cm/month

slide21

Model Validation: Winds

Correlation of simulated and observed daily mean wind anomalies at 18 stations. From Conil and Hall (2006)

slide23

Average open ocean wind speed

Barrier height: 1 km

Brunt-Väisälä frequency:

Depends on the moisture content of the atmosphere. When not saturated:

When close to saturation (Durran and Klemp, 1982):

Computing a bulk Froude number

slide24

Separation by Fr2:

Precipitation

Composite maps of normalized precipitation rate for rainy hours binned by Fr2.

slide25

Separation

by Fr2:

Precipitation

slide27

High Fr2

Small N2

High U2

Adapted from Roe (2005)

slide28

Low Fr2

Large N2

Low U2

Adapted from Jiang (2003)

slide29

Separation by Fr2:

Surface winds

Vectors show wind speed and direction, normalized by open-ocean speed.

slide30

Separation by Fr2:

Surface winds

Vectors show normalized wind speed and direction; colored contours show normalized wind speed.

slide31

Separation by Fr2:

Percentage of precipitation

slide33

Linear model of orographic precipitation

Relates the precipitation to the gradient of the terrain, with the additional complexity of three shifting terms to account for upstream tilted vertically propagating gravity waves, and advection of water droplets during condensation and fallout.

(Smith 2003, Smith and Barstad 2004)

slide35

Linear model of orographic precipitation

Relates the precipitation to the gradient of the terrain, with the additional complexity of three shifting terms to account for upstream tilted vertically propagating gravity waves, and advection of water droplets during condensation and fallout.

(Smith 2003, Smith and Barstad 2004)

slide36

In Fourier space:

Where is the Fourier transform of the terrain. The inverse transform of gives the spatial distribution of precipitation once negative values are truncated and background rate is added.

Linear model of orographic precipitation

linear model applied
Linear model: applied

Precipitation distribution predicted by the Linear Model (LM) and the MM5 composite for the conditionally unstable hours.

linear model applied1
Linear model: applied

Spatial Correlation = 0.83

Precipitation distribution predicted by the Linear Model (LM) and the MM5 composite for the conditionally unstable hours.

slide39

Linear model: limitation

Precipitation distribution predicted by the LM and the MM5 composite for the hours with lowest Fr2.

slide40

Extent to which blocking affects

precipitation distribution

Spatial correlation of the LM with MM5 precipitation for different ranges of Fr2

slide41

Extent to which blocking affects

precipitation distribution

Regression lines of MM5 precipitation/

slope relationship for different ranges of Fr2.

summary
Summary

We use a hierarchy of models to identify the processes essential for predicting precipitation distribution in complex topography.

  • Upstream blocking significantly modifies precipitation distribution in Southern California, contributing a substantial percentage of total precipitation, particularly at low elevation coastal locations.
  • Defining a bulk Froude number based on the ambient atmospheric conditions provides a useful measure of the extent to which blocking is affecting precipitation distribution.

Exclusion of blocking effects is the main shortcoming of the linear model (LM), and including a term based on bulk Fr2 might make the LM accurate for all cases.

applications
Applications
  • The large-scale Fr2 can constrain the relationship between slope and rainfall for use in:
    • Statistical downscaling techniques
    • Statistical interpolation schemes (e.g., PRISM)
  • Expect these findings to apply for other regions, particularly those which have complex topography next to a large region of moist but stable air (e.g., most of the coast of North America and the central coast of South America).
future concurrent work
Future/Concurrent work

Investigation of the large scale conditions associated with and local scale response to the Santa Ana Winds…