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