use of airs/amsu data for weather and climate research joel susskind university of maryland
DESCRIPTION
USE OF AIRS/AMSU DATA FOR WEATHER AND CLIMATE RESEARCH Joel Susskind University of Maryland May 12, 2005. USE OF AIRS/AMSU DATA FOR WEATHER AND CLIMATE RESEARCH. AIRS/AMSU/HSB launched on EOS Aqua May 5, 2002 AIRS is a multi-detector array grating spectrometer - PowerPoint PPT PresentationTRANSCRIPT
USE OF AIRS/AMSU DATA FOR WEATHER
AND CLIMATE RESEARCH
Joel Susskind
University of Maryland
May 12, 2005
USE OF AIRS/AMSU DATA FOR WEATHER AND CLIMATE RESEARCH
AIRS/AMSU/HSB launched on EOS Aqua May 5, 2002
AIRS is a multi-detector array grating spectrometer
2378 channels between 650 cm-1 and 2760 cm-1
Channel spacing (0.25 cm-1 - 1.1 cm-1)
Resolving power (0.5 cm-1 - 2.2 cm-1)
Footprint 13 km at nadir
3 x 3 array within AMSU A footprint - collocated with HSB
One sounding produced per AMSU A footprint
HSB failed on February 5, 2003
/2400
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OBJECTIVES OF AIRS/AMSU
Provide data to improve operational weather forecasting
Required global accuracy in up to 80% cloud cover:
1 K RMS error in 1 km layer mean tropospheric temperature
20% RMS error in tropospheric 1 km layer precipitable water
Provide long-term global coverage of surface and atmospheric parameters
Monitor climate variability and trends
Study processes affecting climate change
Extend 25 year TOVS Pathfinder data set
AIRS/AMSU PRODUCTS
Surface and Atmospheric Products - one set per FOR (45 km)
Sea/land skin temperature
Temperature profile T(p) to 1 mb
Water vapor profile q(p) to 100 mb
O3, CO, CH4 profiles
Cloud Cleared Radiances
Cloud Products - one set per FOV (13 km)Effective cloud fraction for up to two cloud layers
is geometric fractional cloud cover is cloud emissivity at 11 m
Cloud top pressure for up to two cloud layers
OLR
Computed using and retrieved parameters
Clear Sky OLRComputed using retrieved parameters with
Each product has a quality flag
Ts
Pc
, Pc ,
0
ˆ R i
M O N O C H R O M A T I C R A D I A T I V E T R A N S F E R E Q U A T I O N
C l e a r S k y
R B ( T s ) ( p s ) B T ( p )
d d np
d np H ( p s ) 1 R
( p s )
E m i t t e d b y s u r f a c e E m i t t e d b y a t m o s p h e r e R e f l e c t e d s u n l i g h t R e f l e c t e d t h e r m a l
( p ) ,
d d np
d e p e n d o n c o n s t i t u e n t p r o f i l e
p k ( p ) c ( p ) d p,0( p ) e
U n k n o w n s
s p e c t r a l s u r f a c e e m i s s i v i t y s p e c t r a l s u r f a c e b i - d i r e c t i o n a l r e f l e c t a n c e
T s s u r f a c e s k i n t e m p e r a t u r e T ( p ) t e m p e r a t u r e p r o f i l e q ( p ) O 3 ( p ) C O ( p ) C H 4 ( p ) C O 2 ( p )
P a r t i a l C l o u d C o v e r
R 1 jj
R , CLR j
j R , CLD , j j c l o u d t y p e s
MONOCHROMATIC WEIGHTING FUNCTIONS
W (p)
d d np
ddnp
dnp d 1 (ps )
If k(p), c(p) are constant and one gas is absorbing
v (p) e kcp
ddnp
kcp e kcp
x e x
Maximum value = .37 when x = 1, p 1
kc
If k increases with p, weighting function is narrower (line wing)If k decreases with p, weighting function is broader (line center)If k increases with T, and T increases with p, W(p) is narrowerIf c increases with p, W(p) is narrower – water vapor lines
R A D I A T I V E T R A N S F E R F O R C H A N N E L i
R i R f i ( ) d / f i ( ) d
if ( ) = s p e c t r a l r e s p o n s e f u n c t i o n
i = h a l f - w i d t h o f if ( ) I f
i i s n a r r o w ,
R i i B i ( T s ) i ( p s ) B i T ( p ) W i ( p ) d n p i H i i ( p s ) 1 i R i i ( p s )
w h e r e i ( p ) ( p ) f i ( ) d / f i ( ) d W i ( p ) W ( p ) f i ( ) d / f i ( ) d e t c .
PROPERTIES OF CHANNELS
= effective average temperature within weighting function
At night radiance is weighted value
(brightness temperature) is weighted average between and
As decreases, decreases because see less of warm surface and more of . Also
decreases as peak of weighting function rises, but increases in stratosphere
increases brightness temperature, primarily for
Brightness temperatures can be higher than physical temperature
Ri i Bi (Ts ) i(ps ) Bi T(pi ) 1 i(ps ) iH 1 i Ri
T(pi ) Wi(p)
i(ps ) i Bi (Ts ) 1 i Ri
, 1 i(ps ) Bi T(pi )
i Ts T(pi )
i(ps ) i Ts T(pi )
H 2000 cm 1
T(pi )
A D V A N T A G E S O F H I G H S P E C T R A L R E S O L U T I O N
H i g h s p e c t r a l r e s o l u t i o n m e a n s a b s o r p t i o n f e a t u r e s d u e t o s i n g l e l i n e s c a n b e o b s e r v e d M a n y c h a n n e l s a r e o b s e r v e d A I R S h a s 2 3 7 8 c h a n n e l s w i t h / 1 2 0 0 A l l o w s f o r s e l e c t i v i t y o f c h a n n e l s t o b e u s e d B e s t c h a n n e l s a r e p r i m a r i l y s e n s i t i v e t o a b s o r p t i o n b y a s i n g l e s p e c i e s “ F i x e d ” g a s e s – C O 2 , N 2 O – f o r t e m p e r a t u r e s o u n d i n g H 2 O , O 3 , C H 4 , C O f o r c o n s t i t u e n t p r o f i l e s W i n d o w ( r e l a t i v e l y t r a n s p a r e n t ) c h a n n e l s f o r s u r f a c e p a r a m e t e r s B e s t c h a n n e l s a r e u s u a l l y i n l i n e w i n g s o r o n l i n e c e n t e r s
C h a n n e l s w i t h r e d u n d a n t i n f o r m a t i o n c a n b e u s e d t o g e t h e r t o r e d u c e n o i s e
IR AND MICROWAVE OBSERVATIONS ARE VERY COMPLEMENTARY
IR Strengths
• Best vertical resolution (accuracy) of T(p) in mid-lower troposphere• Water vapor profile information up to the tropopause• Best information about surface skin temperature• Trace gas profile information
IR Limitations
• Most channel observations are strongly affected by clouds
MW Strengths
• MW observations are not affected by most clouds• MW observations are critical in accounting for effects of clouds on IR observations
• Microwave soundings of T(p), q(p) can be produced in overcast conditions
OVERVIEW OF AIRS/AMSU RETRIEVAL METHODOLOGY
Physically based system
Independent of GCM except for surface pressure
Uses cloud cleared radiances to produce solution represents what AIRS would have seen in the absence of clouds
Basic steps
Microwave product parameters – solution agrees with AMSU A radiancesInitial cloud clearing using microwave product: producesAIRS regression guess parameters based on cloud cleared radiances Update cloud clearing using AIRS regression guess parameters: producesSequentially determine surface parameters, T(p), q(p), O3(p), CO(p), CH4(p), using
Apply quality control
Select retrieved state - coupled AIRS/AMSU or AMSU only retrieval parametersDetermine cloud parameters consistent with retrieved state and observed radiances Compute OLR, CLR sky OLR from all parameters via radiative transfer
ˆ R i0
ˆ R i
ˆ R i
ˆ R i0
ˆ R i
ˆ R i
OVERVIEW OF CLOUD CL EARING
Use radiances in 9 fields of view Rij channel i, FOV j
Allows up to 8 cloud formations R i = average radiance over 9 FOV’s
ˆ R i, CLR R i jj1
9 Ri,j R i R j j
j1
9 R i, j
If you have estimates of R i,CLR
j R N 1 R 1 R N 1 RCLR
RCLR,i R i,CLR R i R i,CLR computed from a surface and atmospheric state N = channel noise covariance - includes uncertainty in R i,CLR
R i,CLR should be an unbiased state – agree with AMSU radiances
QUALITY FLAGS
Order of increasing difficulty to pass
1) Stratospheric Temperature Test - temperature profile good above 200 mb
90% and cloud clearing passes minimal quality control
Use coupled AIRS/AMSU retrieval state if Stratospheric Temperature Test
is passed
2) Constituent profile test
Slightly more stringent cloud clearing quality control
3) Mid-tropospheric Temperature Test - T(p) good above 3 km
Tighter quality control on cloud clearing and T(p) convergence
flagged good
4) Lower Troposphere Temperature Test - T(p) good above surface
5) SST test - for non frozen ocean only
6) Tight SST test - for non frozen ocean only
ˆ R i
USE OF AIRS OBSERVATIONS FOR DATA ASSIMILATION
Could be (used by ECMWF, NCEP) or T(p),q(p) (used by Bob Atlas)
Accuracy of T(p),q(p) degrades slowly with increasing cloud fraction
There is a trade-off between accuracy and spatial coverage
ECMWF, NCEP uses radiances “unaffected by clouds”
Passes internal threshold tests
They should try assimilating clear column radiances “unaffected by clouds”
Bob Atlas assimilated T(p) for all levels flagged as good
Treats AIRS T(p) as radiosonde reports
R̂i
R̂i
AIRS EXPERIMENTS WITH FVSSI
Global data assimilation system used:fvSSI: fvGCM - Resolution: 1x1.25 SSI (NCEP) analysis-T62
Period of assimilation: 1 January - 31 January, 2003
Experiments:
Control: All Conventional Data + ATOVS Radiance (NOAA-14, 15, 16) + CTW + SSM/I TPW+ SSM/I Wind Speed + QuikScat + SBUV Ozone
Control + AIRS Retrieved Temperature Profiles (Global, passing level quality control)
Forecasts:25 forecasts run every day beginning on January, 6 2003
AIRS LEVEL 3 PRODUCTS
Different geophysical parameters are gridded according to different tests
Stratospheric Temperature Test
T(p) 200 mb and above
Constituent Profile Test
q(p), O3(p), CO(p) at all p
Mid-Tropospheric Temperature Test
T(p) beneath 200 mb, MSU2R/MSU4, land (including ice and coasts) surface skin
temperature (and emissivity)
Sea Surface Temperature Test
Non-frozen ocean surface skin temperature (and emissivity)
Cloud parameters, OLR and clear sky OLR use all AIRS cases
Interannual Differences of T(P)
AIRS AIRS-ECMWF AIRS-TOVS Jan 2004-2003 Jan 2004-2003 Jan 2004-2003 mean STD mean STD correlation mean STD correlation
1000 mb -0.05 1.44 0.14 0.90 0.82 -0.02 1.24 0.45
850 mb -0.09 1.69 0.04 0.71 0.93 -0.04 1.28 0.69
700 mb -0.28 1.54 -0.05 0.45 0.97 -0.05 1.06 0.77
600 mb -0.15 1.55 0.07 0.42 0.98
500 mb -0.36 1.54 -0.05 0.39 0.97 -0.19 1.02 0.75
400 mb -0.45 1.50 -0.15 0.39 0.95 0.00 0.98 0.73
300 mb -0.10 1.33 0.03 0.46 0.94 0.02 0.85 0.83
200 mb -0.06 1.99 -0.13 0.53 0.99 -0.60 0.98 0.92
150 mb 0.23 2.07 0.06 0.53 0.99
100 mb -0.10 2.57 0.16 0.84 0.99 0.04 1.02 0.97
70 mb -1.01 2.35 -0.21 0.81 0.99 -0.37 1.09 0.96
50 mb -0.53 2.37 0.04 1.03 0.99 -0.29 1.12 0.95
30 mb 0.10 3.05 0.09 0.91 0.99 0.54 1.39 0.90
10 mb -0.06 2.74 0.02 0.72 0.99 0.15 1.67 0.81
1 mb -1.47 4.13 0.26 1.76 0.99
MSU2R -0.19 1.31 -0.10 0.72 0.81 -.03 0.81 0.74
MSU4 -0.42 2.00 -0.12 0.36 0.99 -.04 0.66 0.97
AIRS AIRS-Spencer-Christy AIRS-TOVS Interannual Difference of MSU2R/MSU4
DATA AVAILABILITY
Results shown are based on the AIRS Version 4.0 algorithm
We (SRT) currently have results for January 2003 and January, August, September 2004
Goddard DAAC began analyzing AIRS/AMSU data near real time April 1, 2004
DAAC is also processing backwards from March 31, 2004 at 5 days per day
Level 1B (radiances), Level 2 (spot by spot retrievals), and Level 3 (gridded) data is available
Level 3 is 1°x 1° daily, 8 day mean, and monthly mean
Ascending (1:30 pm local time) and descending (1:30 am local time) data are separate
To order data to go
http://daac.gsfc.nasa.gov/data/datapool/AIRS/index.html
Use collection 003 (Version 4.0)
Earlier DAAC products (collection 002) used AIRS Version 3.0
Do not use earlier results