analysis of atms and amsu striping noise from their … their earth scene observations ... global...
TRANSCRIPT
Analysis of ATMS and AMSU Striping Noise
from Their Earth Scene Observations
Zhengkun Qin1, Xiaolei Zou1, Fuzhong Weng2
1. Center for data assimilation in research and applications Nanjing University of Information Science & Technology, China
2. National Environmental Satellite, Data & Information Service, National Oceanic and Atmsopheric Administration, Washington, DC, USA
March 26, 2014
Outline
• ATMS Striping Phenomena• Striping analysis based on PCA and EEMD• Striping noise of water vapor channels• Striping analysis of Maneuver data• Summary
Suomi NPP ATMS Striping
It was first identified by NWP user communitythrough the global distribution of the bias (O-B)between ATMS observations and simulations. UnlikeAMSU-A, ATMS O-B displays a distinct O-Birregularity in its along-track direction. NWP users referthis irregularity as striping brightness temperatures orradiances.
Global Distribution of ATMS Ch10 O-BFebruary 24, 2012
Obvious Stripping noise can be found in the O-B figure of Ch10
K
K
Principle Component Analysis (PCA)
1,1 1,
96
96,1 96,
N
N
N
TB TBA
TB TB
Data Matrix:
: Brightness temperature at the kth FOV and the jth scanline
k=1,2,…,96; j=1,2,…,N
TBk, j
kj
The covariance matrix: S AAT
i iie eS
Principle Component Analysis (PCA)
: the PC coefficient for the ith mode.
1 2 96
T Tu u u E A
1, 2, 96,i i i ie e e e
: the principle component (PC) for the ith mode. ,1 ,2 ,i i i i Nu u u u
96
1i i
i
e u
A
The ATMS data can be then expressed as:
Scan angle dependence of the brightness temperature
Variations same for all FOVs are tend to appear in the 1st mode
PCA modes of TB for ATMS Ch10
1 1e u
2 2e u
TB
K
K K K
3 3e u
PCA modes of TB for NOAA-18 AMSU-A Ch9TB
K
K K K
Same features as ATMS Ch10, but the first mode is more smooth.
1 1e u
2 2e u
3 3e u
Brightness Temperature at nadir
Number of Scanline
Number of Scanline
TB(1
) (K
)
TB(1
) (K
)
ATMS Ch10
NOAA-18 AMSU-A Ch9
48,1nadir
iTB e u
Obvious oscillations can
be found in ATMS, but not in
AMSU-A
Observation
Simulation
EEMD Method
Huang and Wu (2008) and Wu and Huang (2009)
Tb t Cj t j1
n
Rn t
Rn t Rn1(t)Cn1
Cn1 Intrinsic Mode Function (IMFs) Mean of the envelopes of Rn-1
R0 t Tb (t)
Raw data
Brightness temperature for the first PCA mode at nadir
Scanline
Scanline
Scanline
Scanline
e 48,
1u 1
,j (K
)
e 48,
1u 1
,j (K
)
e 48,
1u 1
,j (K
)
e 48,
1u 1
,j (K
)
TB at Nair TB-1st IMF
TB-first two IMFs TB-first three IMF
Power Spectral of the first three IMFs
Am
plitu
de (K
)
Frequency (s-1)
Scanline
C1
(K)
C2
(K)
C3
(K)
Power spectral density distributions
Frequency (s-1)
Frequency (s-1)
Pow
er S
pect
rum
Den
sity
Pow
er S
pect
rum
Den
sity
SNPP ATMS channel 10
NOAA-18 AMSU-A channel 9
Before
After
Power spectral is modified after striping noise removed for ATMS, but there are just a little differences for AMSU-A before and after EEMD smoothing.
Global distribution of Stripping noise
Before After
Before-After
Of O-B for
ATMS Ch10
K
K K
Obs and O-B of the TBObs ATMS Ch22 O-B ATMS Ch22
Obs MHS Ch3 O-B MHS Ch3 IWP
Kg/m2
LWP
Kg/m2
KK
KK
PCA modes of TB for ATMS Ch22TB
1 1e u
2 2e u
3 3e u
K KK
K
Eigenvector and TB at nadir
Scanline
TB(1
) (K
)
FOV
e 1
Scanline
FOV
TB(1
) (K
)e 1
ATMS Ch22 NOAA-18 MHS Ch3
Striping noise can be found in both ATMS Ch22 and NOAA-18 MHS Ch3
Global distribution of stripping noiseSNPP ATMS Ch 22
NOAA-18 MHS Ch3
NOAA-16 AMSU-B Ch3
Stripping noises are stronger in ATMS and MHS, but weaker in AMSU-B.
K
Striping noise of maneuver TBSc
anlin
e
Scan
line
Scan
line
Scan
line
FOV FOV FOV FOV
ATMS Ch10 ATMS Ch22
Stripping noise can be removed in maneuver data also.
KK
K K
K K
Striping Index (SI) of maneuver TB
Channel
Channel
Varia
nce
(K2 )
Strip
ing
Inde
x
alongVs
alongV
crossVs
crossV
Valong 1N
1M
Tb(k, j) 1M
Tb(k, j)k1
M
2
k1
M
j1
N
SI Valong
Vcross
along-track variance Valong
cross-track variance Vcross
Vcross 1M
1N
Tb (k, j) 1N
Tb (k, j)j1
N
2
j1
N
k1
M
Stripping Index (SI) is reduced to close to one. It shows that our method can removed stripping noise reasonably.
Summary
• For tempearture channels, ATMS’s striping noise is much stronger than AMSU-A
• For water vapor channels, both ATMS and MHS (AMSU-B) have striping noise
• Method based on PCA and EEMD can filter the striping noise obviously and flexibly
• Root-cause and more accurate filters need further investigation
Thank you !
Questions ?