AMSU-B Channels (Details: John and Buehler, GRL, 31, L21108, doi:10.1029/2004GL021214) Water vapor...
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Transcript of AMSU-B Channels (Details: John and Buehler, GRL, 31, L21108, doi:10.1029/2004GL021214) Water vapor...
AMSU-B Channels
(Details:John and Buehler,GRL, 31, L21108, doi:10.1029/2004GL021214)
Water vapor
Oxygen
AMSU-B Channels Water vapor
Oxygen(Figure by Viju O. John)
AMSU-B Jacobians
ARTS Simulation,
Atmosphere: Midlatitude-Summer
20 19 18 19 20
(Figure by Viju O. John)
Jacobians depend on Atmospheric State
(Figures by Viju O. John)
• Measurement not in TTL, but below
• Altitude where OLR is very sensitive to H2O changes
1D-Var RETRIEVALS AND THE COST FUNCTION
It can be shown that maximum likelihood approach to solving the inverse problem (which is a particular case of the generalized analysis problem covered in previous lectures replacing T(z) with a vector x and L with y) requires the minimization of a cost function J which is a combination of 2 distinct terms.
])H[(])H[()()()( 11 xyxyxxxxxJ Tb
Tb RB
Fit of the solution to the background estimate of the atmospheric state weighted inversely by the background error covariance B
Fit of the solution to the measured radiances (y) weighted inversely by the measurement error covariance R (observation error + error in observation operator H)
The solution obtained is optimal in that it fits the prior (or background)
information and and measured radiances respecting the uncertainty in both.
1D state or profile Radiance vector RT equation
Observations
“True” state of the atmosphere
Model vari
able
s, e
.g.
tem
pera
ture
00 UTC 5 May
Analysis
Background Analysis
12 UTC 5 May
00 UTC 6 May
12 UTC 6 May
12-h
our fo
reca
st
Data Assimilation
Improving vertical resolution with hyper-spectral instruments (AIRS / IASI)
Many thousands of channels improves things, but the vertical resolution is still limited by the physics
CLOUD
AIRS channel 226 at 13.5micron(peak about 600hPa)
AIRS channel 787 at 11.0 micron(surface sensing window channel)
temperature jacobian (K)
pre
ssu
re (
hP
a)
unaffected channels
assimilated
contaminated channels rejected
RETAINING USEFUL INFORMATION ABOVE CLOUDS(Cloud detection scheme for AIRS / IASI)
A non-linear pattern recognition algorithm is applied to departures of the observed radiance spectra from a computed clear-sky background spectra.
This identifies the characteristic signal of cloud in the data and allows contaminated channels to be rejected
obs-
calc
(K
)
Vertically ranked channel index
CONTENUTI INTEGRATI COLONNARI DI GAS: Principi generali: l'assorbimento differenziale
• VAPOR D'ACQUA.
• O2 come misura della pressione superficiale
• OZONO
MIPAS Near Real Time productsTarget species
0
10
20
30
40
50
60
70
80
90
100
110
120
Alt
itu
de
[k
m]
O3 H2 O N O CH4 HNO3 p,T
Mesosphere
Thermosphere
Troposphere
Stratosphere O3 layer
N O22 NO
MIPAS possible products
MIPAS can simultaneously observe most molecular constituents of the Earth’s atmosphere
Complementary ENVISAT measurements
Species GOMOS MIPAS SCIA
AerosolAir densityCloudsPressureTemperatureBrOCCl4CFC11
CFC12
CFC22
CF4
CH4
ClOCLONO2
COCO2
C2H2
Clear colours: operational Shaded colours: further scientific targets
Species GOMOS MIPAS SCIA
C2H6
HCHOHNO3
HNO4
HOClH2OH2O2
NONO2
NO3
N2ON2O5
O2,O2*,(O2)2
O3
OCSOClOSO2
GOMOS: Stratosph. MIPAS: upper Troposph. - lower Mesosphere SCIA:Troposph. - lower Mesosph.
San Diego, CA
SUPERFICIETEMPERATURAVAPOR D’ACQUAOZONOCH4CO
Limb measurements resolve the vertical structure of the atmosphere and emission measurements provides continuous (global) geographical coverage.
Limb emission measurements
Aerosols• UV based (only absorbing aerosols: dependence from the vertical distribution)• VIS based• IR (only some type of aerosols (volcanic)• Lidar• Limb profiling (upper atmosphere)• Attempt of retrieving aerosol profile from measurements in the O2 A-Band (760 nm)
In general aerosols in the atmosphere are represented with 2 parameters optical thickness at a given wavelength (amount) and aerosol model (type).
Ls=Lp+Lr+Lw Lp=F(aerosols,p)Lr=F(observation geometry, wind (foam, roughness, glint))
Aerosols=F(Ls670,Ls870)
Reflectances depends from aerosols amount and typeThe ratio of reflectances (an estimation of color of the aerosols) is independent from the amount and used to selecte the aerosol typeOnce the type is selected optical properties (ω,P) from LUT are used to compute τ
Ob
serv
atio
n
geo
met
ry
Aer
oso
ls
amo
un
t
Aer
oso
ls
typ
e
Aerosols type dependent variables
lidar
Comment: only 1 wavelength
• Aerosols• CONTENUTO COLONNARE/SPESSORE OTTICO
• TIPO • PROFILO VERTICALE
• PROFILI VERTICALI DI TEMPERATURA E DI CONCENTRAZIONE DI GAS.
• profilo di temperatura • Profilo verticale di vapor d'acqua • PARAMETRI D'INSTABILITA'
Atmospheric Profile Retrieval from MODIS Radiances
ps
I = sfc B(T(ps)) (ps) - B(T(p)) [ d(p) / dp ] dp .
o
I1, I2, I3, .... , In are measured with MODISP(sfc) and T(sfc) come from ground based conventional observations(p) are calculated with physics models
Regression relationship is inferred from (1) global set of in situ radiosonde reports, (2) calculation of expected radiances, and (3) statistical regression of observed raob profiles and calculated MODIS radiances
Need RT model, estimate of sfc, and MODIS radiances
MODIS bands 20-29 MODIS bands 30-36
• Parametri dinamici • VENTO ORIZZONTALE IN QUOTA: • VENTO ORIZZONTALE ALLA SUPERFICIE DEL MARE:• VELOCITA' VERTICALE: • CORRENTI MARINE SUPERFICIALI: • • Oceanografia• SST• Ocean Colour Clorofilla+correzione aerosols• topografia
• Bilancio Radiativo• COMPONENTI DEL BILANCIO RADIATIVO
• Boundary layer fluxes• Latent heat flux• sensible heat flux
• The trace gas analyses reported in this study started from calibrated radiance measurements from GOME channel 2 (311-405 nm), where the spectral sampling is 0.12 nm at a resolution of 0.18 nm (FWHM). Slant column amounts of SO2, OClO, and BrO have been calculated from the measured radiances using the technique of differential optical absorption spectroscopy (DOAS). Given a background spectrum IB( ) and the earth radiance I( ), both measured by GOME, and absorption cross sections i( ) of the relevant species, their slant column densities Li are fitted together with polynomial coefficients cj according to the Lambert-Beer law for the optical density
• D = ln [IB( ) / I( )] = Li i( ) + cj j • For each trace gas, the table below summarizes the selected wavelength
window and the references included in the fit. • Window [nm]References• 314-327SO2,O3 • 357-381OClO, NO2, O4, Ring• 345-359BrO, O3, NO2, Ring
GOME fit results (blue) for SO2, OClO, and
BrO, compared to reference absorption cross sections measured in the laboratory (violet red). The difference between each fit result and the corresponding reference spectrum is the overall fit residual. Each spectrum represents a single selected groundpixel.
http://earth.esa.int/workshops/ers97/papers/eisinger/#intro