Chapter 6 Atmospheric Infra-red and UV/visible Remote Sensing

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Remote Sensing I
Atmospheric Microwave Remote Sensing
Summer 2007
Björn-Martin Sinnhuber
Room NW1 - U3215
Tel. 8958
[email protected]
www.iup.uni-bremen.de/~bms
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Contents
Chapter 1
Introduction
Chapter 2
Electromagnetic Radiation
Chapter 3
Radiative Transfer through the Atmosphere
Chapter 4
Weighting Functions and Retrieval Techniques
Chapter 5
Atmospheric Microwave Remote Sensing:
A short review of spectroscopy
Chapter 6
Atmospheric IR & UV/visible Remote Sensing
Chapter 7
Radar and Sea Ice Remote Sensing
Chapter 8
Remote Sensing of Ocean Colour
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Observations in Spitsbergen (79°N)
Fourier Transform Infra-Red
Spectrometer (FTIR)
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
2
'C:\Dokumente und Einstellungen\polguest\Eigene Dateien\02052222_0\02052222_0.dat'
1.5
1
Fourier
2
transformation
Dokumente und Einstellungen\polguest\Eigene Dateien\021102
14_0\021102 14_0.dat'
0.5
0
-0.5
-1
-1.5
-2
0
100
200
300
400
500
600
Intensity
1.5
1
0.5
0
700
800
900
1000
1100
Wavenumber [cm-1]
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
1200
1300
wavelength
(mm)
Wellenlänge
(mm)
Wellenlänge
(mm)
8.73 9.0
8.725
13.0
10.0 8.720
O3
O3
O3
O3
N2O
1146.0
8.7
8.08.7
N2O
1146.5
Each trace gas has ist own ‘fingerprint‘ in the spectrum
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Chapter 6
Atmospheric Infra-red and UV/visible
Remote Sensing
•A short review of infra-red spectroscopy
•Atmospheric UV/visible remote sensing
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Molecular Vibrations

r

 
F  k r  r0 
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Molecular Vibrations
Higher energy:
Cl
Cl
H
squeezed
Cl
stretched
H
Equilibrium distance
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
H
Harmonic Oscillator
Cl
Cl
H
H
H
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Harmonic Oscillator
1 2
V  V0  kx  
2
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Harmonic Oscillator
Energy levels:
Ev  (v  ) v  0,1, 2,
1
2
12
k
  
m
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Spectrum of the Harmonic Oscillator
Energy levels:
Ev  (v  ) v  0,1, 2,
1
2
Observed transitions (spectral lines):
h v1v  Ev1  Ev
 (v 1  )  (v  )
1
2
 
(independent of v , i.e. all at the same frequency!)
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
1
2
The Molecular Potential
H2
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
The Morse Potential

V  x   hcD e 1  e

 a  r  re  2
12
 k 

a  
 2hcDe 
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Vibrational Levels and Transitions
Gv  Ev hc
E v  1  E v  
~
  G v  1  G v  

hc
hc
Ignoring anharmonic effects:
1 ~

G v    v   0
2

12
1 k
~
 
0 
2c  m 
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Rotational and Vibrational Levels
1 ~

Gv    v   0
2

F J   BJ J  1
S v, J   Gv   F J 
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Rotational and Vibrational Levels
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Rotational and Vibrational Transitions
1 ~

S v, J    v   0  BJ J  1
2

~
 J   S v  1, J   S v, J 
J   J   1
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Rotational and Vibrational Transitions
1 ~

S v, J    v   0  BJ J  1
2

v  1  v J  1 :
~P J   S v  1, J 1  S v, J   ~0  2BJ
P branch
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Rotational and Vibrational Transitions
1 ~

S v, J    v   0  BJ J  1
2

v  1  v J  1 :
~R J   S v  1, J  1  S v, J   ~0  2BJ  1
R branch
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Rotational and Vibrational Transitions
1 ~

S v, J    v   0  BJ J  1
2

v  1  v J  0 :
~
~
 Q J   S v 1, J   S v, J    0
Q branch
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Rotational and Vibrational Levels
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Observed Spectrum of CO
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Observed HCN Spectrum at 715 cm-1
Q-branch!
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Polyatomic Molecules
For a molecule with N atoms 3N degrees of freedom.
•Translation: 3 degrees of freedom
•Rotation: 3 degrees of freedom
•Vibration: 3N-6 degrees of freedom
•For a linear molecule only 2 rotational degrees of freedom,
leaving 3N-5 vibrational degrees of freedom
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Example: H2O
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
H2O: Symmetric stretch mode
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
H2O: Bending mode
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
H2O: Asymmetric stretch mode
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Example: CO2
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Electronic Transitions: Example O2
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Electronic Transitions
Example: UV absorption of O2
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Chapter 6
Atmospheric Infra-red and UV/visible
Remote Sensing
•A short review of infra-red spectroscopy
•Atmospheric UV/visible remote sensing
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Example: Ozone Measurements by Dobson Instrument
Quartz plates
Adjustable wedge
Fixed slits
Prisms
Detector: photomultiplier
Org. photographic plate
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Cross secton 
Principle of Wavelength Pairs (online - off-line)
1
I 1   I 0 1 e
2
  1 n  x dx


I 2   I 0 2 e
  2 n  x dx

  n  x dx    2 n  x dx
I 1  I 0 1   1

e
I 2  I 0 2 
Known from measurements
of solar spectrum
ln
   n  x dx
I 1  I 0 1   1 2

e
I 2  I 0 2 
I  
I 1 
 ln 0 1   1   2  nx dx
I 2 
I 0 2 


B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Absorber column amount
along effective light path
Ozone Measurements by Dobson Instrument
Used wavelength pairs
Name
WL 1 [nm]
WL 2 [nm]
A
305.5
325.4
B
308.8
329.1
C
311.45
332.4
D
317.6
339.8
C’
332.4
453.6
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Differential Optical Absorption Spectroscopy (DOAS)
•
•
•
•
•
•
remote sensing measurement of atmospheric trace gases in the atmosphere
measurement is based on absorption spectroscopy in the UV and visible wavelength
range
to avoid problems with extinction by scattering or changes in the instrument throughput,
only signals that vary rapidly with wavelength are analysed (thus the differential in
DOAS)
measurements are taken at moderate spectral resolution to identify and separate
different species
when using the sun or the moon as light
source, very long light paths can be realised
in the atmosphere which leads to very high
sensitivity
even longer light paths are obtained at twilight
when using scattered light
B.-M.ofSinnhuber,
Remote Sensing
I, University of Bremen, Summer 2007
Courtesy
Andreas Richter,
Uni Bremen
Example: Absorber Cross Sections
B.-M.ofSinnhuber,
Remote Sensing
I, University of Bremen, Summer 2007
Courtesy
Andreas Richter,
Uni Bremen
DOAS equation I
The intensity measured at the instrument is the extraterrestrial
intensity weakened by absorption, Rayleigh scattering and Mie
scattering along the light path:
scattering efficiency
integral over light path
J
I ( , )  a ( , ) I 0 ( ) exp{  (  j ( )  j ( s )   Mie( )  Mie( s )  Ray( )  Ray( s ))ds}
j 1
unattenuated
intensity
absorption by all
trace gases j
extinction by Mie
scattering
exponential from
Lambert Beer’s law
B.-M.ofSinnhuber,
Remote Sensing
I, University of Bremen, Summer 2007
Courtesy
Andreas Richter,
Uni Bremen
extinction by
Rayleigh scattering
DOAS equation II
if the absorption cross-sections do not vary along the light path, we
can simplify the equation by introducing the slant column SC, which is
the total amount of the absorber per unit area integrated along the light
path through the atmosphere:
SC j    j ( s )ds
J
I ( , )  a ( , ) I 0 ( ) exp{  (  j ( )  j ( s )   Mie( )  Mie( s )  Ray( )  Ray( s ))ds}
j 1
J
I ( , )  a ( , ) I 0 ( ) exp{  j ( ) SC j   Mie( ) SCMie  Ray( ) SCRay}
j 1
B.-M.ofSinnhuber,
Remote Sensing
I, University of Bremen, Summer 2007
Courtesy
Andreas Richter,
Uni Bremen
DOAS equation III
As Rayleigh and Mie scattering efficiency vary smoothly with
wavelength, they can be approximated by low order polynomials. Also,
the absorption cross-sections can be separated into a high
(“differential”) and a low frequency part, the later of which can also be
included in the polynomial:
 Ray  4
 Mie  
   low   '
  02
J
I ( , )  a ( , ) I 0 ( ) exp{  j ( ) SC j   Mie( ) SCMie  Ray( ) SCRay}
j 1
differential cross-section
J
I ( , )  a( , ) I 0 ( ) exp{  ' j ( ) SC j   b p  p }
j 1
slant column
B.-M.ofSinnhuber,
Remote Sensing
I, University of Bremen, Summer 2007
Courtesy
Andreas Richter,
Uni Bremen
p
polynomial
DOAS equation IV
Finally, the logarithm is taken and the scattering efficiency included in
the polynomial. The result is a linear equation between the optical
depth, a polynomial and the slant columns of the absorbers. by solving
it at many wavelengths (least squares approximation), the slant
columns of several absorbers can be determined simultaneously.
intensity with absorption (the
measurement result)
absorption cross-sections
(measured in the lab)
J
ln(I ( , ) / I 0 ( ))    ' j ( ) SC j   b*p  p
j 1
intensity without or with less
absorption (reference measurement)
slant columns
SCj are fitted
p
polynomial (bp* are fitted)
B.-M.ofSinnhuber,
Remote Sensing
I, University of Bremen, Summer 2007
Courtesy
Andreas Richter,
Uni Bremen
Example of DOAS data analysis
measurement
O3
optical depth
differential optical depth
NO2
residual
H2O
Ring
B.-M.ofSinnhuber,
Remote Sensing
I, University of Bremen, Summer 2007
Courtesy
Andreas Richter,
Uni Bremen
Example for satellite DOAS measurements
• Nitrogen dioxide (NO2) and NO
are key species in tropospheric
ozone formation
• they also contribute to acid rain
• sources are mainly
anthropogenic (combustion of
fossil fuels) but biomass burning,
soil emissions and lightning also
contribute
• GOME and SCIAMACHY are
satellite borne DOAS
instruments observing the
atmosphere in nadir
• data can be analysed for
tropospheric NO2 providing the
first global maps of NOx pollution
• after 10 years of measurements,
trends can also be observed
GOME annual changes in tropospheric NO2
1996 - 2002
A. Richter et al., Increase in tropospheric nitrogen dioxide
over China observed from space, Nature, 437 2005
B.-M.ofSinnhuber,
Remote Sensing
I, University of Bremen, Summer 2007
Courtesy
Andreas Richter,
Uni Bremen
Satellite Observing Geometries
Measured signal:
Reflected and scattered sunlight
Measured signal:
Directly transmitted solar radiation
Measured signal:
Scattered solar radiation
B.-M.ofSinnhuber,
SensingUni
I, University
Courtesy
ChristianRemote
von Savigny,
Bremen of Bremen, Summer 2007
Examples for UV/visible Nadir Sounders
Examples:
BUV (Backscatter Ultraviolet) instrument on Nimbus 4, 1970-1977
SBUV (Solar Backscatter Ultraviolet) instrument on Nimbus 7, operated from
1978 to 1990
SBUV/2 (Solar Backscatter Ultraviolet 2) instrument on the NOAA polar
orbiter satellites: NOAA-11 (1989 -1994), NOAA-14 (in orbit) can measure
ozone profiles as well as columns
TOMS (Total Ozone Mapping Spectrometer) first on Nimbus 7, operated
from 1978 to 1993. Then three subsequent versions: Meteor 3 (1991-1994),
ADEOS (1997), Earth Probe (1996-). Measures total ozone columns.
GOME (Global Ozone Monitoring Experiment) launched on ESA's ERS-2
satellite in 1995 employs a nadir-viewing BUV technique that measures
radiances from 240 to 793 nm. Measures O3 columns and profiles, as well
as columns of NO2, H2O, SO2, BrO, OClO.
SCIAMACHY (Scanning Imaging Absorption spectroMeter for Atmospheric
CHartographY) on Envisat is an improved GOME.
B.-M.ofSinnhuber,
SensingUni
I, University
Courtesy
ChristianRemote
von Savigny,
Bremen of Bremen, Summer 2007
Example: Onion
peel inversion
of occultation
observations
Retrieving
Profiles
from Occultation
Measurements
a22
a11
a32/2
a21/2
(TH1)
 y1 
(TH2)
 
(TH3)   y1 
(TH4) y   y3 
(TH5)   
Sun
•
•
•
Earth
x5 x4 x3 x2 x1
 x1 
x 
1
  
x   x3 
 
  
 x N 
N
yi   aij x j
j 1


y  Ax
 
 yM 
xi : O3 concentration at
altitude zi
yj : O3 column density at
tangent height THj
 a11
a
A   21
 

aM 1
a12
a22

aM 2
 a1N 
 a2 N 
  

 aMN 
The matrix elements aij correspond to geometrical path lengths through the layers
B.-M.ofSinnhuber,
SensingUni
I, University
Courtesy
ChristianRemote
von Savigny,
Bremen of Bremen, Summer 2007
Example: Solar Occultation Instruments
Examples:
SAGE (Stratospheric Aerosol and Gas Experiment) Series provided
constinuous observations since 1984 to date
Latest instrument is SAGE III on a Russian Meteor-3M spacecraft
HALOE (Halogen Occultation Experiment) on UARS (Upper Atmosphere
Research Satellite) operated from 1991 until end of 2005, employing IR
wavelengths
POAM (Polar Ozone and Aerosol Measurement) series use UV-visible solar
occultation to measure profiles of ozone, H2O, NO2, aerosols
GOMOS (Global Ozone Monitoring by Occultation of Stars) on Envisat will
performs UV-visible occultation using stars
SCIAMACHY (Scanning Imaging Absorption spectroMeter for Atmospheric
CHartographY) on Envisat performs solar and lunar occultation
measurements providing e.g., O3, NO2, and (nighttime) NO3 profiles.
B.-M.ofSinnhuber,
SensingUni
I, University
Courtesy
ChristianRemote
von Savigny,
Bremen of Bremen, Summer 2007
Example: UV/visible Limb Sounders
Examples:
SME (Solar Mesosphere Explorer) launched in 1981, carried the first ever limb
scatter satellite instruments. Mesospheric O3 profiles were retrieved using the
Ultraviolet Spectrometer and stratospheric NO2 profiles were retrieved using the
Visible Spectrometer
MSX satellite – launched in 1996 , carried a suite of UV/visible sensors (UVISI)
SOLSE (Shuttle Ozone Limb Sounding Experiment) flown on the Space Shuttle
flight in 1997. Provided good ozone profiles with high vertical resolution down to
the tropopause
OSIRIS (Optical Spectrograph and Infrared Imager System) launched in 2001 on
Odin satellite. Retrieval of vertical profiles of O3, NO2, OClO, BrO
SCIAMACHY (Scanning Imaging Absorption SpectroMeter for Atmospheric
CHartographY), launched on Envisat in 2002. Retrieval of vertical profiles of O3,
NO2, OClO, BrO and aerosols
B.-M.ofSinnhuber,
SensingUni
I, University
Courtesy
ChristianRemote
von Savigny,
Bremen of Bremen, Summer 2007
Satellite Observing Geometries II
Observing Geometry
Pro
Occultation
Profile retrieval
Poor geographical
possible; high accuracy coverage: only possible
due tostrong signal
for sunrise/sunset
Nadir
Near global coverage
Only column densities
Limb
Profile information with
near global coverage
Complicated radiative
transfer
B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007
Contra
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