Tampa Bay 2010

Polarimetric radar measurements of
precipitation to interpret, retrieve, and
validate X-band Synthetic Aperture Radar
observations
Misure radar polarimetriche della precipitazione per interpretare,
ricostruire e validare le osservazioni da radar ad apertura
sintetica in banda X
Luca Baldini, Eugenio Gorgucci, Nicoletta Roberto
CNR - Istituto di Scienze dell’Atmosfera e del Clima, Roma
Dino Giuli, Luca Facheris, Fabrizio Cuccoli (CNIT)
Università di Firenze, Lab. Radar e Radiocomunicazioni
Roberto Deidda, M.G. Badas, G. Mascaro
Gruppo di Idrologia – Dip. Ingegneria del Territorio, Università di Cagliari
Chandrasekar V. Chandra, Jason Fritz
Colorado State University, Radar & Communications Group, Ft Collins, USA
Achieved results in response to the first COSMO‐SkyMed Announcement Of Opportunity
Rome, March 27th, 28th and 29th
1
Project rationale and objective
„ Several studies have analyzed and modeled the effect of
precipitation on SAR at different frequencies (Ferrazzoli and
Schiavon (1987) Danklmeyer et al (2009), Atlas and Moore,
(1987), Marzano, Weinmann (2008, 2010).
„ Interest has revived with SAR missions at X-band. At X-band
precipitation attenuation is more pronounced than at longer
wavelengths and can affect many applications of SAR
measurements.
„ The mechanism determining SAR NRCS in precipitation is not
straightforward, combining scattering/attenuation from the
volume distribution of hydrometeors and surface scattering
which, in turn, is modified by precipitation.
„ Interpretation of SAR data in precipitation can take advantage
from ground instrumentations (Melsheimer at al. 2001), such as
(Polarimetric) Doppler Weather Radar providing
„ microphysical
properties of precipitation along the SAR beam
„ measurements to predict the attenuation/scattering properties along
the SAR beam
Effects of precipitation on SAR images
„ Influence on surface backscattering
„
„
„
Modification of surface NRCS
Backscattering due to precipitation
Attenuation due to precipitation
„ Effects on polarimetric measurements due anisotropy of
hydrometeors
„
„
„
difference between HH-VV intensity of returns
phase difference HH-VV
Differential attenuation
„ Azimuth resolution
„
Precipitation has an inherent Doppler spectrum that degrades
azimuth resolution (Atlas and Moore 1987).
ra = 2σ v R / U ≈ 250 × σ v
U: sat speed; R: slant range
σV = precip Doppler spectrum width
„ Shift along azimuth direction (Moore et. al 1997)
Δr = ur R U
For CSK and a ur of 20 m/s, shift
is more than 4 km.
Effects of precipitation on SAR images
to
Surface
backscattering
z
R
A
S
ΔR
Near
beam
edge
υf
υj
υn
Q
σ 0 (Q ) = σ 0s
Far beam
edge
x
Effects of precipitation on SAR images
to
Surface
backscattering
z
R
A
S
Precipitation
backscattering
Precipitation path
attenuation
ΔR
Near
beam
edge
r(x)
σ att
surf
υn
υf
υn
υj
x
x’
Q
p( x )
σ0 (Q ) = σ0s ⋅ l [r ( x )] + sin υ ∫ η p ( x' ) ⋅ l [r ( x' )] dx'
0
Far beam
edge
att
σ vol
Effects of precipitation on SAR images
to
Surface
backscattering
z
R
A
S
Precipitation
backscattering
Precipitation path
attenuation
ΔR
Near
beam
edge
υn
υf
υn
υj
p( x )
σ0 (Q ) = σ0s ⋅ l [r ( x )] + sin υ ∫ η p ( x' ) ⋅ l [r ( x' )] dx'
0
Far beam
edge
x
Effects of precipitation on SAR images
to
Surface
backscattering
z
R
A
S
Precipitation
backscattering
Precipitation path
attenuation
ΔR
Near
beam
edge
(1)
r(x)
σ eff (Q )HH
σdr (Q ) =
=
σeff (Q )VV
υn
(σ )
υf
υn
x
p( x )
0
surf HH HH
(σ )
υj
Far beam
edge
l
[r (x )] + sin υ ∫ ηHH (x' )lHH [r (x' )]dx'
0
p( x )
0
surf VV VV
l
[r (x )] + sin υ ∫ ηVV (x' )lVV [r (x' )]dx'
0
Weather radar data to estimate SAR
observation
to
Surface
backscattering
z
R
A
S
Precipitation
backscattering
Precipitation path
attenuation
ΔR
Zh
Z dr
Near
beam
edge
K dp
υf
υj
υn
αh
p( x )
αh
σ0 (Q ) = σ0s ⋅ l [r ( x )] + sin υ ∫ η p ( x' ) ⋅ l [r ( x' )] dx'
0
Far beam
edge
x
Weather radar data to estimate SAR
observation
Geometric mapping
1. Define a grid on a cross track plane
2. Map the grid onto GR coordinate
y
ζ
(j⋅-i)ΔR
Oa
Hmax
Ψ0
ΟΡ
Near
beam
edge
i⋅ΔR
υ
ν
Oa
υ
X
Surface backscattering
Precipitation
backscattering
Precipitation attenuation
paths
Q( y,s)
x
P
Ψ
Y’
Pi,j
Z
y′
CSK
ground
track
Far
beam
edge
υφ
ξ
ϕ
ΔR/tanυn+ …+ ΔR/tanυϕ
OS
s
θ
X0
X’
X
η
x′
Weather radar data to estimate SAR
observation
Reflectivity and
Specific attenuation
estimation
SAR image
SAR metadata
Z (CSKfreq, θ)=f1(GRmeas θ= 0°)
Ground
Radar
(S, C band)
2
η = Zπ5 K p λ− 4 × 10 −18
Zh
⎛ Zdr ⎞
⎜
⎟
⎜K ⎟
⎝ dp ⎠
α (CSKfreq, θ)=f2(GRmeas θ= 0°)
l (r ) = 10
Estimation
Microphysical
model
−0.2 ∫ α ( s )ds
r
algorithms
Non linear
regression
T-matrix
simulation
ηHH ,VV
l HH ,VV
Weather radar data to estimate SAR
observation
0° elevation
42° elevation
S-band
Single
polarization
radar
Gamma DSD
variability
3 ≤ log10 N w ≤ 5
0.5 < D0 < 3.5
−1 < μ ≤ 5
Zh<55 dBZ; R<300 mm h-1
Canting angle:mean = 0°, width= 7.5°
Temperature = 20°
Shape-size model: Beard and Chuang 1987
Baldini et al. IGARSS 2012
Fritz and Chandrasekar, JTECH submitted
0° elevation
42° elevation
Weather radar data to estimate SAR
observation
„ Datasets of simultaneous
NEXRAD WRS 88D
observation of precipitation
„
„
CSK in its different
modes
Weather radars at
ground
Bric della Croce (TO)
Owner: Regione Piemonte
Site: Lat. 45°1’53’’, Lon.
7°43’59’’ Altitude: 720 m
Manufacturer: ALENIA
Doppler: YES - Band: C
Dual polarization: NO
Beamwidth: 1° - Radome:
YES
• Operational GR
• ARPA Piemonte dual
pol C-band radar
• NEXRAD S-band
single pol
• Research GR
• dual pol C-band
ISAC-CNR Polar 55C
research radar, Rome
RU
ISAC-CNR Polar 55C, Roma
Weather radar data to estimate SAR
observation
Typical operational weather
radar volume scanning
T0
T0+ TR
Weather radar data to estimate SAR
observation
Sampling effect
φ=10 km
Ideal rain cell: a
cylinder with constant
reflectivity.
Z=40dBZ
2 cases:
1) The cell is
stationary (vc=0)
H=6 km
2) The cell is moving
(vc=6m/s)
Weather radar data to estimate SAR
observation
Sampling effect
Optimized scanning
SAR‐WR
coincident sampling
NEXRAD
Volume Coverage Pattern
VCP12
6 m/s
Baldini et al. AMS Int Conf. on Radar Meteorology, 2011
sector including SAR footprint, Vertical resolution better than 1km within SAR footprint
Case studies
Case
CSK Mode
Weather
radar
Collection
Tampa Bay
2010
Intense
precipitation
over land
Ping Pong
S-band single pol
NEXRAD,
operational
Request
Piemonte
2010
Observation
over non
constant
background
Ping Pong
C-band dual pol
ARPA Piemonte,
operational
Request
IVREA
2011
Intense
precipitation
over
mountains
Stripmap
C-band dual pol
ARPA Piemonte,
operational
Archive
Lousiana
2010
Intense
precipitation
over sea
Scansar Huge
S-band single pol
NEXRAD,
operational
Archive
Scansar Wide
C-band dual pol
ISAC-CNR,
research
Archive
Roma 2012 Snow and
mixed phase
precipitation
17
Tampa Bay 2010
NEXRAD
Tampa Bay (KTBW) – Melbourne (KMLB)
S – band Doppler radar
CSK Ping Pong HH-VV
CSKS2 2010-06-18
CSKS3 2010-06-19
CSKS1 2010-06-26
CSKS2 2010-07-04
CSKS1 2010-07-12
CSKS2 2010-07-20
Tampa Bay 2010
18
CSK3 2010-06-19
KTBW VMI:
CSKS1 2010-06-26
CSKS2 2010-07-04
CSKS2 2010-07-20
Blue:40dBZ
Red:45dBZ
Green:50dBZ
19
Tampa Bay 2010
Reconstruction of a
SAR image
from KTBW
measurements:
cross track
CSK Reflectivity
CSK Specific attenuation
l [r ( x )]
σ0 (no precip)
σ0 (no precip)
p( x )
Reconstructed
σ0 profile
sin υ
∫ η (x' )⋅ l[r (x' )] dx'
p
0
Tampa Bay 2010
CSKS2 2010-07-04
CSKS1 2010-06-26
l HH (dB )
ηatt
HH (dB )
l D (dB )
Tampa Bay 2010
CSKS1 2010-06-26
σ 0HH CSK
σ 0HH CSK no rain
+ KTWB
CSKS2 2010-07-04
Tampa Bay 2010
Scalloping effect
σ 0HH (precip)
(CSKS1 2010-06-26)
σ 0D (precip)
2.1
km
Δσ 0HH
Δσ 0D
precip − no precip
precip − no precip
23
Tampa Bay 2010
-5
-10
-15
Δσ0hh
(dB)
0
5
04 July 2010 (precip) and 20 July 2010 (coregistered, no precip)
25
30
35
40
45
Cumulative slant range S-band Z
50
[10
55
60
log10(mm6m-3
65
km)]
Tampa Bay 2010
04 July 2010 (precip)
Reconstruction from weather
radar data
[10 log10(mm6m-3 km)]
Baldini et al. Atmospheric Research, 2012 submitted
SAR measured
Piemonte 2010
PING PONG HH-VV CSK images
CSKS3 2010-05-13
ARPA Piemonte
Bric della Croce
C- band
dual polarization radar
CSKS1 2010-05-20
CSKS2 2010-05-28
CSKS1 2010-06-21
CSKS2 2010-06-29
CSKS1 2010-07-07
25
Piemonte 2010
red = |βHH|0.6 green = |βVV|0.6,
blue = (2-1/2)|βHH - βVV|0.6
CSKS3 2010 May 13 05:09:06 UTC
CSKS1 2010 May 20 05:09:01 UTC
CSKS1 2010 Jun 21 05:08:37 UTC
CSKS2 2010 Jun 29 05:08:32 UTC
26
Piemonte 2010
Dual polarization C-band weather radar data to estimate X-band SAR observation
0° elevation
65° elevation
C-band
dual
polarization
radar
Gamma DSD
variability
3 ≤ log10 N w ≤ 5
0.5 < D0 < 3.5
−1 < μ ≤ 5
Zh<55 dBZ; R<300 mm h-1
Canting angle:mean = 0°, width= 7.5°
Temperature = 20°
Shape-size model: Beard and Chuang 1987
0° elevation
65° elevation
Piemonte 2010
Contours of Bric della Croce
reflectivity (blue=29 dBZ;
red=36 dBZ; green=43 dBZ)
superimposed on CSK2 29
June image.
Baldini et al. ERAD 2010
Reflectivity and specific
attenuation reconstructed
from Bric della Croce radar
28
Ivrea 2011
ARPA Piemonte
Bric della Croce
C- band
dual polarization radar
STRIPMAP HH CSK images
CSK2 27 06 2011 (no rain 1)
CSK2 13 07 2011 (rain)
CSK2 29 07 2011 (no rain 2)
29
Ivrea 2011
Latitude
Bric della Croce
VMI:
Blue:45dBZ
Red:50dBZ
Green:55dBZ
Longitude
Ivrea 2011
(NoRain1 –NoRain2)
(Rain –NoRain1)
(Rain –NoRain2)
σ0(hh) (radar no class)
σ0(hh) (precip)
σ0(hh) (no precip)
Ivrea 2011
σ0(hh) (simu class)
σ0(hh) (precip)
σ0(hh) (no precip)
Ivrea 2011
Lousiana 2010
„ COSMO SkyMed monitoring of
Deepwater Horizon oil spill
NEXRAD
KLIX (New Orleans)
S – band Doppler radar
scanning mode: 20 PPI in 5 min
(20 elevation: 0.5-20deg;
azimuth resolution 0.5 or 1deg;
range resolution 250m, max.
range = 250 km).
CSK Huge Region image
July 6th , 2010, 12:02 UTC
Ascending, right
Lousiana 2010
CSK2 7 July 2010 12:03
Louisiana (US)
Precip
Backscattering
Attenuation
Roberto et al. EGU 2012
Oil
Spill
KLIX reflectivity
superimposed contour:
Blue=35 dBZ, Red=40 dBZ
Green=45 dBZ
Lousiana 2010
„
„
backscattering and attenuation of radiation by hydrometeors in the rain cells;
Backscattering of sea induced by the impact of raindrops and wind.
to
Surface
backscattering
z
R
A
S
Precipitation
backscattering
Precipitation path
attenuation
ΔR
Near
beam
edge
r(x)
υn
υf
υn
υj
x
x’
p( x)
σ 0 (Q ) = σ s0 ⋅ l [r ( x )] + sin υ ∫ η p (x') ⋅ l [r (x')] dx'
0
Far beam
edge
Lousiana 2010
Sea surface NRCS behavior
1. Rain intensity variation
Relationship h2(rms) and rainfall by
experimental results1
Roughness
of
water
surface
is
modeled
through
a
Gaussian
height distribution, with
variance h2(rms).
Bliven L F Sobieski PW,Elfouhaily T, 1995, “Ring Wave Frequency Spectra: Measurementes and Model”,
Proc IGARSS ’95, p.830.
Lousiana 2010
Sea surface NRCS behavior
2. Rain intensity variation
~15 dB
Wind speed 4.3
m/s
CSK incidence angles
Bahar e and Fitzwater M A, 1984 “Scattering cross sections for composite rough surfaces using the unified full
wave approach” IEEE Trans Ant. Propag.32, N7, pp730-734
Capolino F. Facheris L. Giuli D. Sottili F. , 1997, “ The determination of the sea surface NRCS when corrugated
by blowing wind and raingall: an application to rainfall rate measurements over sea” Int. Conf. On Antennas
and Propagation, 1997, N 436.
Lousiana 2010
Radar rain rate
PIA
attenuation
ηvv
σ0
backscattering
σ0
Vw=4.3 m/s
Lousiana 2010
PIA
ηvv
Radar rain rate
σ0
Vw=4.3 m/s
Roma 2012
CSKS2 2012-02-02
CSK Scansar Wide
Orbit: descending right
Incident angles: 23.75- 36.78 °
CSKS3 2012-02-03
Polar 55C VMI:
Blue:15dBZ, Red:20dBZ,
Green:25dBZ
Roma 2012
CSKS2 2012-02-02
CSKS3 2012-02-03
120 km
Roma 2012
CSKS2 2012-02-02
120 km
Roma 2012 ……
Future acquisition of
simultaneous observations using
CSK stripmap and Polar 55C
with scanning composed of:
•PPI sectors
•RHI on a SAR cross-track
plane)
Observation area
44
45
Conclusions
„ COSMO SkyMed images collected using different modes in the presence of
precipitation events have been analyzed using simultaneous observations of the
same precipitation event collected by ground based radars
„ Use of ground based weather radar to identify and quantify precipitation effects
have been developed. Models were developed for
„
„
S-band operational single polarization radar
C-band operational dual polarization radar
Better results are obtained with dual polarization radar that allow to achieve a
classification of hydrometeors
„ Concerning the Ping Pong HH mode, the relationship between attenuation and
linear attenuation in CSK polarimetric images fairly agrees with that obtained
from a simple propagation model. However, especially in cases of low S/N, the
scalloping effect can alter significantly the ratio of copolar returns between
adjacent strips. Better results are expected with the use of the quad pol
scheme. (COSMO II)
„ Interesting results have been obtained for precipitation over the sea surface
where NRCS changes as result of wind and impinging raindrops
„ Before August 2012, collection of CSK stripmaps and ISAC-CNR Polar 55C
(using specifically designed scanning strategies) observations of precipitation
will be pursued.