Blocking in areas of complex topography

1
Blocking in areas of complex topography
and its influence on rainfall distribution

• Mimi Hughes
• Alex Hall
• Rob Fovell
• UCLA

2
Rain in Southern California
Orographic enhancement and blocking heavy
precipitation during Northern California New
Years floods of 1997 was almost entirely due to
the interaction of the flow with topography (see
Galewsky and Sobel, 2005)
3
How can topography change the distribution of
precipitation?
4
Flow over? (mechanical lifting)
Precipitation (grayscale) and topography
(contours) for an idealized numerical study. From
Jiang (2003)
5
Flow over? (mechanical lifting)
Is this too simple?
Precipitation (grayscale) and topography
(contours) for an idealized numerical study. From
Jiang (2003)
6
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)
7
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 gt winds
  uniform with height and precipitation greatly
  enhanced on the windward slope
• More stable, lower wind speed case gt 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

8
Motivation
To investigate what processes are essential to
predicting the distribution of precipitation in
complex topography
Approach
Systematic study using a hierarchy of models
9
Study Region Why California?
10
Topography
Shuttle Radar Topography Mission elevation shown
as shaded relief
11
Precipitation observations
Cooperative Observation Precipitation
measurements average of daily rainfall from May
1995 to April 2006. Black contours show
topography.
12
Winds during rain
Vectors show wind speed and direction colored
contours show wind speed in m/s.
13
Coastal zone
Cooperative Observation Precipitation
measurements average of daily rainfall from May
1995 to April 2006. Black contours show
topography.
14
Upslope Model?
Solid line shows linear regression. Large pale
blue bullet is GPCP open-ocean average
(119.5W-121.5W, 31.5N-32.5N)
15
Questions Ill 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?

16
Data
17
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

18
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.
19
Model Validation Precipitation
20
Model Validation Precipitation
Spatial Correlation 0.87 Regression slope
1.13 intercept 0.39 cm/month
21
Model Validation Winds
Correlation of simulated and observed daily mean
wind anomalies at 18 stations. From Conil and
Hall (2006)
22
Diagnosing Blocking
23
Computing a bulk Froude number
24
Separation by Fr2 Precipitation
Composite maps of normalized precipitation rate
for rainy hours binned by Fr2.
25
Separation by Fr2 Precipitation
26
How are the Froude number and the distribution of
precipitation related?
27
High Fr2
Small N2
High U2
Adapted from Roe (2005)
28
Low Fr2
Large N2
Low U2
Adapted from Jiang (2003)
29
Separation by Fr2 Surface winds
Vectors show wind speed and direction, normalized
by open-ocean speed.
30
Separation by Fr2 Surface winds
Vectors show normalized wind speed and direction
colored contours show normalized wind speed.
31
Separation by Fr2 Percentage of precipitation
32
Quantifying the effect of blocking on
precipitation
33
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)
34
Linear model of orographic precipitation
In Fourier space
Fourier transform of the terrain.
Moisture coefficient
Intrinsic frequency
Depth of moist layer
Hydrometeor fallout time
Moisture conversion time
Vertical wavenumber
35
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)
36
Linear model of orographic precipitation
37
Linear model applied
Precipitation distribution predicted by the
Linear Model (LM) and the MM5 composite for the
conditionally unstable hours.
38
Linear model applied
Spatial Correlation 0.83
Precipitation distribution predicted by the
Linear Model (LM) and the MM5 composite for the
conditionally unstable hours.
39
Linear model limitation
Precipitation distribution predicted by the LM
and the MM5 composite for the hours with lowest
Fr2.
40
Extent to which blocking affects precipitation
distribution
Spatial correlation of the LM with MM5
precipitation for different ranges of Fr2
41
Extent to which blocking affects precipitation
distribution
Regression lines of MM5 precipitation/ slope
relationship for different ranges of Fr2.
42
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.
43
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).

44
Thanks!
45
Future/Concurrent work
Investigation of the large scale conditions
associated with and local scale response to the
Santa Ana Winds
46
Motivation
To investigate what processes are essential for
predicting the distribution of precipitation in
complex topography
Approach
Systematic study using a hierarchy of models
47
Findings

• 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.

Significance
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.