Post-EPS ScatterometerPost EPS Scatterometer Performance Simulation
[email protected] Belmonte, UCAR,
Jos de Kloe, KNMI
ESA Study
IOVWST, May 2010
Wind retrieval and noise model Kp noise Geophysical noise due to ocean variabilityApproximate retrieval functionsApproximate retrieval functions
IOVWST, May 2010
Geophysical noise
Wind Vector Cell
alon
g-ec
tion
Fore FOVs
• Different kinds of FOVs are combined (views)
• Each WVC view represents
25 kmSate
llite
tr
ack
dire Aft FOVs
pa different areal mean
• The ocean surface is variable
25 kmSatellite across-track direction
• A geophysical error occurs due to ocean surface variability and WVC non-
if liuniform sampling• Mainly affects low winds
P t b ll & St ff l 2006
IOVWST, May 2010
Portabella & Stoffelen, 2006
Post EPS scatterometer (SCA) [baseline requirements and options]
• Spatial resolution (25 km) MetOp orbit Sun Sync • Dynamic range (4-25 m/s)• Radiometric resolution (~3-10% at 4 m/s)• Swath coverage (95% in 48 hours for incidences between 20 and 60)
p ywith 820 km altitude
g ( )
I - Fixed beam (ASCAT type) II - Rotating beam (RFSCAT type)
15% improvement with respect to ASCAT on MetOp
IOVWST, May 2010
Discarded: Ku-band (rain), pencil beam (skill), extended nadir coverage for ASCAT type
Specify complete SCA arrangement:p y p g1) Antenna configuration (C-band, single vs dual pol):
t t l- total power- dimensions - radiation pattern
Pseudo Level 1B fileOrbital model
2) Radar waveform(FM chirp, short vs long pulse):- PRF- chirp bandwidth
Incidence / AzimuthPolarization
NESZ # viewschirp bandwidth- noise estimation Nlooks
Nnoise
# views
IOVWST, May 2010
WVC(25 km resolution cell)
Satellitepositionat time t
Radiometric resolution (NESZ and Kp)Radiometric resolution (NESZ and Kp)
1) NESZ (Noise Equivalent Sigma Zero) for a single look:
look range azimuthA
00
2
3 4
( )B eq look
lookt TX RX
k T T BNESZSNR APG G
R L
l kx yN
3 44 propR L
2) Number of looks per node: (reduce speckle)lookslook
NA
noise s noiseN f T
2) Number of looks per node:
3) Number of noise samples:
(reduce speckle)
(noise estimation)
2 202
20
var{ } 1 1 1 11plooks noise
KN SNR N SNR
Radiometric resolution:
IOVWST, May 2010
SCA end-to-end simulator
Input wind vectorPencil beam, Kp =20%
9 m/s @ 90 deg Outer swath
GMFPseudo L1B file Geophysical noise
Backscatter vector observation Observational likelihood
Wind inversionlikelihood
Output wind vector(minimum MLE solution)
20 0 ( )
IOVWST, May 2010
Pobs(Vout|Vin)
0 0,
22 01,...,
( , )1( , ) i GMF i
i N p i
wMLE w
MLE K
Wind retrieval performanceWind retrieval performancePobs(Vout|Vin) NWP prior (5 m2/s2) Pobs(Vout|Vin)*PNWP
1) Wind Vector RMS error
2) A bi i ibiliof M
erit
v
2) Ambiguity susceptibility
3) Wind biases (skewness)Figu
re o
u
IOVWST, May 2010 1/ 22 2( ) ( | ) ( )obs true true obs true bgRMS v v v p v v p v d v
For example:
Wind retrieval performance QSCAT/ASCAT
Vector RMS error QSCAT ASCAT
S /
5 m/s
Vector RMS error at 9 m/s
5 m/ssimulated QSCATBIAS
9 m/sretrieved QSCATPDF
IOVWST, May 2010
13 m/sAMBIGUITY
Climatology FoMsClimatology FoMs
Wind retrieval performance is dependent on input wind and across track distancep p p
Use a climatology average over wind speeds (3-16 m/s)
IOVWST, May 2010
Use a climatology average over wind speeds (3 16 m/s)
SCA assessment
ASCAT RFSCAT RFSCATASCATtype
RFSCAT(1rpm)
RFSCAT(2rpm)
RFSCAT(3rpm)
IOVWST, May 2010Wind Vector RMS error across swath
ConclusionRFSCAT performs well compared to ASCAT configuration, but …
IOVWST, May 2010
To consider: geophysical noise, HH polarization, resolutionTo optimize: antenna pattern…
scat@knmi [email protected]/scatterometer
IOVWST, May 2010
Backup SlidesBackup Slides
IOVWST, May 2010
Wind retrieval and noise model Kp noise Geophysical noise due to ocean variabilityApproximate retrieval functionsApproximate retrieval functions
IOVWST, May 2010
GMF issuesGMF issues2D-histogram histogram (1st-rank Solution)
50
• Measured triplets are centered well on cone within Kp for all
40
INSIDEOUTSIDE
well on cone within Kp for all speeds
• Geophysical noise at low winds incorporated
30
Win
d S
peed
(m
/s)
• Reasonable symmetry at medium-high winds
• Around 4 m/s most triplets inside 10
20
AS
CA
T W
i
1.4•
101
1.5•
102
1.5•
103 p
the cone• At very low winds, opposite effect
-40 -20 0 20 400
10
1.4•101
1.4•101
1.5•102
1.5•102
1.5
1.5•10 4
IOVWST, May 2010
-40 -20 0 20 40MLE
1015
1010
1015
1010
1015 10001005
1010
1
ERS-2
995
1000
1005
1010
990
99510
00
10
10
1015
• Warm steady-flow air
985
990995
1000
1
985
100
1005
1010 discerned from polar
gusty air.• Wind variability
985
990
995
1005
101
985
990
990
995
10
1 Wind variability causes triplet inconsistency
985
990
995
95
1000
010 990
995
1000
1000
1005
1010 • Noise at edge of the swath; ASCAT moved outward
IOVWST, May 2010
1000
1005
1005
1010
1005
5
10101015
moved outward
Geophysical noise
Wind Vector Cell
alon
g-ec
tion
Fore FOVs
• Different kinds of FOVs are combined (views)
• Each WVC view represents
25 kmSate
llite
tr
ack
dire Aft FOVs
pa different areal mean
• The ocean surface is variable
25 kmSatellite across-track direction
• A geophysical error occurs due to ocean surface variability and WVC non-
if liuniform sampling
Portabella & Stoffelen, 2006
IOVWST, May 2010
Accuray on 50-km WVC scale• Triple collocation analysis of buoy,
scatterometer & NWPVector RMS error
[m/s]Tropical
TAO/PIRATAExtratropical
NDBC/MEDS/UKMO
Buoy 1.5 1.5
Scatterometer 1.2 1.6
ECMWF model 2.0 2.1
Scatterometer winds provide excellent forcing Remaining errors include representativeness
IOVWST, May 2010
Remaining errors include representativeness
1.0 1008
1.0 1009
u ASCATu ECMWF
v ASCAT100 km
1.0 1007
1.0 10v ASCATv ECMWFk -5/3
100 km
1.0 1006 [email protected]
04
1.0 1005
Ψ(k) • ASCAT contains small
scales down to 25 km
1.0 1003
1.0 1004
• Improved w.r.t. SeaWinds
1.0 1002
• No noise floor• k-1.9
IOVWST, May 20101.0 10-07 1.0 10-06 1.0 10-05 1.0 10-04
k (m-1)
1.0 1001
MesoscalesMesoscales
• 12 5-km box12.5 km box details appear spectrally correctspectrally correct
• It verifies well with buoysbuoys
• It corresponds ll ith l dwell with cloud
features
IOVWST, May 2010www.knmi.nl/scatterometer
High WindsHigh Winds C-band Model
F iFunctionC b d HH iti t hi h•C-band HH sensitive to high
winds
•No EUM priority due to lack•No EUM priority due to lack of high winds
log
Courtesy
IOVWST, May 2010
log Courtesy D. EstebanJPL, NASA
ASCAT L1 backscatter averagingWind Vector CellHamming filter H i filtHamming filter averaging window
Hamming filter
ASCAT Level 2 product:
100 km
ealon
g-ec
tion
• 50 km resolution
• up to 60 km off the coast
to avoid land effects
25 km
Coa
stlin
e
Sate
llite
tr
ack
dire to avoid land effects
100 km25 km
C
Satellite across-track direction
ASCAT Coastal product:
• 30-40 km resolution
IOVWST, May 2010
10 km • up to 25 km off the coast
• more noisy
ASCAT L1 backscatter averagingWind Vector CellHamming filter H i filtHamming filter averaging window
Hamming filter
ASCAT Level 2 product:
100 km
ealon
g-ec
tion
• 50 km resolution
• up to 60 km off the coast
to avoid land effectsB25 km
Coa
stlin
e
Sate
llite
tr
ack
dire to avoid land effectsBox
100 km25 km
C
Satellite across-track direction
Box
ASCAT Coastal product:
• 30-40 km resolution
IOVWST, May 2010
10 km • up to 25 km off the coast
• more noisy
Prototype at 25 km
IOVWST, May 2010
1.0 1008
1.0 1009
u ASCAT OSISAFu ASCAT Box avgv ASCAT OSISAFv ASCAT Box avg
100 km
k -5/3
1.0 1007
1.0 10v ASCAT Box avg
100 km
Box [email protected] 1006
• Box averaging maintains more tail variance
• No apparent noise floor04
1.0 1005
Ψ(k)
No apparent noise floor• Buoy verification confirms
this; see later presentation1.0 1003
1.0 1004
• Still u bump, but at lower wavelength (?)
• k -1.8 pretty close to -1 67 for1.0 1002
IOVWST, May 2010
k , pretty close to 1.67 for 3D turbulence Nastrom and Gage 1987
1.0 10-07 1.0 10-06 1.0 10-05 1.0 10-04
k (m-1)
1.0 1001
KNMI ASCAT on MetOp Phasing Study28 i t l l• 28 minutes clearly optimal
• No gain in tropics atNo gain in tropics at 50 minutes
28 minutes
IOVWST, May 2010 45 minutes
Antenna assembly
C-band, VV polarization (extension to dual HH polarization an option)
Swath FoV 3dB widthSwath FoV 3dB widthSpatial resolution 3dB length Antenna effective dimensions
Beam shaping in elevation20% better than
ASCAT M tO
30
321-way antenna gain projected into swath width
Beam shaping in elevationASCAT on MetOp(from 20 to 16 km)
Dynamic range24
26
28
1-w
ay a
nten
na g
ain
[dB
]
300 400 500 600 700 80020
22
ground range [km]
MIDSIDE
Slotted waveguide radiators:
2
3 4 04( )
TX RX
prop lookt
G GR L ASNR P
k T T B
From ASCAT on METOP
IOVWST, May 2010
to compensate for larger slant range across swath (~10 dB)
0( )B eq lookk T T B
[SNR is determined by Pt and chirp bandwidth]
Radar PRFLimited by swath extent: two different strategies
TSWATH MID SIDE
TNEAR 5.7 ms 8.4 ms
TFAR 6.0 ms 10.5 ms
Inc = 20 to 53.5 deg
RNEAR RFAR
A) Long pulse (TTX >> tSWATH)
FAR
PRF = 1/(THOR+TTx+TN) = 29.4 Hz (30%DC)
SWATH
TRx = TTx-TSWATH
Nadir TSWATH Horizon @ 22.2 ms
TTx = TFAR
TTx TN
HorizonNadir
B) Short pulse (TTX << tSWATH)
TSWATH
PRF = 1/(TFAR+TTx) = 230 Hz (7%DC)
IOVWST, May 2010
TRx
TTx = 0.3 ms TN
2) Radar waveform
LFM chirp for range resolution
0.5
1
Chirp ~ exp[i(/2)t2]1 2 3 4
-1
-0.5
( = chirp rate BTx/TTx )
Deramping ~ exp[-i(/2)t2] exp[ifDt+i(/2)(t-tr)2] = exp[i(fD+itr)t]
1
FFT
Echo bandwidth Becho (tFAR – tNEAR) + fD
Detection bandwidth Bdetection 1/TRX = Blook
Swath
detection RX look
Resolved look area:
IOVWST, May 2010 dBecho/dx 2(/c)sin(inc)
Alook= 16 km x Blook/[2(/c)sin(inc)]
Inversely proportional to chirp rate, but so is SNR!
Radiometric resolutionR i d i l b k kl i iReceived signal = backscatter + speckle + emission
2 202
20
var{ } 1 1 1 11pKN SNR N SNR
1) Accumulate independent looks to reduce speckle
0plooks noiseN SNR N SNR
N [2( /c)sin(inc)/B ] L
Naz = (PRF/vground) LWVC
Nlooks = Naz Nel
Maximum
Maximum PRF(compatible with unambiguous range)
Nel = [2(/c)sin(inc)/Blook] LWVC Maximum (compatible with SNR >-1.5dB)
WVC SNR Pt0/ sin(inc) Minimum Pt (compatible with Kp requirements)
ITER
ATE
Nnoise = NazBechoTN
2) Noise (emission) estimation and subtractionIndependent looks
IOVWST, May 2010
Where Becho = fs/2 sets the sampling frequency
Trade-offs to optimize Kp via chirp rate and total power (antenna pattern)
Min SNR check Max Kp check
20° 27 4°20 27.4
N li l d t N li l d t
53.5° 64.7°
Non-compliance leads toincrements in peak power
Non-compliance leads toincrements in chirp rate
(and/or antenna pattern accommodation?)
IOVWST, May 2010
Compliant SCA configurations enter the wind performance study
Complete SCA configurationComplete SCA configuration
1) Antenna assembly total power & pattern Orbital model- total power & pattern
2) Radar waveform- PRF chirp rate & noise
Pseudo Level 1B file
Orbital model
PRF, chirp rate & noise
WVC Node
Row/Col Satellite position and velocityLat/Lon # Views
ViewsViewcounter
0 ( )k T T B
NESZ (Noise Equivalent Sigma Zero):
IOVWST, May 2010
Azimuth Incidence # Looks 1/ NESZ Polarization
0
2
3 4
( )
4
B eq look
lookt TX RX
prop
k T T BNESZSNR APG G
R L