Transcript Atmospheric Science Faculty Retreat

STEPS
Severe Thunderstorm Electrification
and Precipitation Study
May-July 2000
Prof. Steven Rutledge
Department of Atmospheric Science
Colorado State University
Radar Network
Dual-Doppler
and Triple
Doppler
configurations
STEPS Ops Center
CSU-CHILL National Radar Facility; 10 cm polarimetric/Doppler
www.chill.colostate.edu
STEPS Fixed Instrumentation: TripleDoppler Network and LMA (VHF TOA)
At KGLD:
-NWS
-T-28
-NSSL
-Electric field
balloon
-Mobile
mesonet
-MGLASS
2130 UTC
2328 UTC
KGLD
0110 UTC
0251 UTC
Tessendorf et al., JAS, 2005
Storm swath of base reflectivities (2100-0251 UTC) with NLDN lightning data overlaid.
23 June storm
29 June Supercell
• Inverted tripole
• +CGs
3 June storm
• Inverted dipole
• No CGs
Early:
normal tripole, -CGs
Later, collapse:
inverted tripole, +CGs
Q: Why did charge structures
differ?
A: Supercooled liquid water
content.
29 June
+
3 June
+
23 June
Switching gears now, lets talk about
polarimetric radar……
NWS Polarimetric upgrade!!
A really exciting opportunity
for the science community
as well!
The STSR architecture first
developed on the CSU-CHILL
radar in 1995. Proof of
concept.
In STSR, H-V polarizations
transmitted at the same time.
Previously, alternate
transmission of H,V used.
Needed method to switch
polarizations with so called
“ferrite” switch—very
unreliable.
The polarization variables..
In addition to Z and Doppler velocity..
Zdr, differential reflectivity
Sensitive to particle shape and phase
Power based measurement
Φdp, differential phase (Kdp)
Sensitive to particle shape and phase
Phase based measurement
ρhv, correlation coefficient
Sensitive to particle shape and phase
Power based measurement
V
hail
H
rain
Zdr = 10 log10 (Zhh/Zvv)
Single particle Zdr expressed as dB
Illustrates dependence
on both shape and
phase, water
vs. ice (dielectric)
Plot from Herzegh and
Jameson (1992)
Non-precipitation echo: insects (preferred flight direction)
Zdr values reach
CHILL data
system limit (+9
dB)
Large Z and Zdr when looking
at long axis of insects, oriented
with mean wind.
see Lang et al. 2004 J. Atmos. Ocean. Tech.
Propagation Differential Phase, φdp

φdp is a phase based measurement, independent of power
V
H
 Since the H wave encounters more dielectric compared to the V wave,
the H wave moves more slowly than the V wave. H wave lags the V
wave therefore in phase.
 Φdp is then the phase difference (in degrees) between the H and V
wave as these waves propagate out and back to the radar. This
difference (degrees) will be > 0 for oblate particles (rain), zero for
isotropic media (hail), and < 0 for prolate particles (e.g., oriented ice
particles).
From A. Illingworth, Chapter 5, in Weather Radar (2003)
P. Meischner, Editor (Springer)
Illustration of H and V waves propagating through oblate raindrops. A phase lag
between H and V waves results since the H wave moves slightly more slowly than
the V wave, in oblate media. For prolate media, the V wave lags the H wave. Phi dp
(propagation differential phase) is a measure of this phase difference between H and
V waves.
PPI display presentation of differential propagation phase
-20o diff. phase at near point
+15o ~8 km farther range
35o phase change in 8 km
Basic concept:
H, V return signal phase difference
changes most rapidly in beam path
segments where net differential
forward scattering effects are large
Conversion to customary Kdp units:
(Bringi and Chandra (2001) Eq 7.17)
K dp = 1 / 2[! dp (r + ! r) ² ! dp (r)] / ! r
Kdp is only arrived at after “filtering” the range profile of φdp
Too little filtering introduces noise in rain estimates, too much
filtering removes fine scale estimates of rain rate and rain rate
local peaks.
From a physical perspective….
Kdp is product of rainwater content and deviation of mass-weighted
mean axis ratio from one. (Alternatively, particles with mean axis ratio
of one (tumbling hailstones) do not contribute to Kdp).
Kdp is phase measurement, not dependent on accurate radar reflectivity
calibration (including partial beam blockage effects), Zdr offsets / drifts,
etc.
Rain rate estimation…
Increasing rain rate
CHILL: Rainfall Accumulation
Optimization Algorithm
CHILL: Rainfall Accumulation
NEXRAD Z-R Algorithm
Ice
contamination!
Engineering Parking Lot at Colorado State University: Flash Flood of
28 July 1997
CHILL observations of the Ft. Collins
flood led to research that caused the
NWS in Denver to modify their algorithms
used to derive rainfall rates from
NWS radar measurements
An Example from the Ft. Collins Flash Flood of
28 July 1997: Cumulative Rainfall
Gauge Survey
Z = ARb
Vertical structure of microphysical classification
Hydrometeor type classification results for 5 July storm from
STEPS (data from CSU-CHILL)—Model Intercomparison
Squall line and HID using
polarimetric variables
Co-polar H,V Correlation (ρhv)
The correlation coefficient is a measure of the shape variations
or irregularities in the radar resolution volume……
The correlation coefficient decreases when diverse particles
types are present.
This diversity can be in phase of water, shape and size.
ρhv reduction to ~0.91 in a hail shaft: 7 June 1995 near
Gilcrest, CO
CSU-CHILL
data
Negative Zdr;
these values
also modeled
for larger, wet
hail. Mie effects
operate to
reduce ZH relative
to ZV, leading
to negative Zdr. For
axis ratios in range
of 0.6 to 0.8.
rhv reduced in hail area:
Mixed precip types; ρhvespecially
reduced when Zrain=Zice
Diverse shapes
REMOVING NON-MET ECHO:
FUZZY LOGIC CLASSIFICATION (FHC)
Example from
JPOLE of rain
embedded in
clutter/AP and
biological
scatterers
Clutter/AP
Rain
Insects/Birds
Ryzhkov et al. (2005)
Correlation coefficient summary:
Primarily useful to characterize variability of scatterer
characteristics within the pulse volume.
Drizzle / light rain > ~0.98
Convective (but no ice) rain > ~0.96
Hail / rain mixtures ~0.90
Bright band mixed rain and snow ~0.75
Tornado debris ~0.50 or less
Ground clutter ~0.6-0.8
Some winter storm applications…….
Bright band descending
to surface in rain/snow
transition
Vertical profile in a
snowstorm.
Dual offset antenna: 2008
Prof. Bringi leads a successful >$1M
MRI proposal to acquire a new antenna
Offset feed design, first time be used on
an S-band weather radar
Unprecedented performance has now
been demonstrated
Advances the Facility to a new level of
performance
The new antenna set the stage for
another major development…..
Dual-wavelength project
CASA
Magnetron
T/R Pkg
Main
Reflector
Dual-frequency
Feed
Horn
Feed
Horn
Sub-Reflector
12/9/2010
CSU-CHILL Update
 No other radar like
this in the world
 Will allow CHILL to
make impact on NWS
gap-filling radar
concept
 Takes advantage of
CASA second
generation radar
 Unique dualfrequency
combination enables
new science
 CSU cost share dollars
used to acquire
critical components
 Will be tested later in
the spring….
36