Transcript Folie 1 - IUP Bremen: DOAS Home

Satellite observations of the atmosphere
and the ocean surface
Heraeus Summer School “Physics of the Environment”
Andreas Richter
Institute of Environmental Physics
University of Bremen
tel. ++49 421 218 4474
e-mail: [email protected]
http://www.iup.physik.uni-bremen.de/doas
1
Lecture Contents
1.
2.
3.
4.
What is Remote Sensing?
Which Quantities can be Measured?
What are the Underlying Physical Principles?
Examples:
a.
b.
c.
d.
e.
f.
g.
h.
Tropospheric Aerosols
Stratospheric Ozone
Tropospheric NO2
Stratospheric Aerosols
Temperature Profiles
Wind Speed and Direction
Sea Surface Temperature
Sea Ice
5. Summary
A. Richter, Heraeus-Summerschool, 3.9.2005
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What is Remote Sensing?
“Remote sensing is the science and art of obtaining information about an
object, area, or phenomenon through the analysis of data acquired by a
device that is not in contact with the object, area, or phenomenon under
investigation“
(Lillesand and Kiefer 1987)
“The art of dividing up the world into little multi-coloured squares and then
playing computer games with them to release unbelievable potential that's
always just out of reach.”
(Jon Huntington, Commonwealth Scientific and Industrial Research
Organisation Exploration, Geoscience, Australia)
A. Richter, Heraeus-Summerschool, 3.9.2005
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The Eye as a Remote Sensing Instrument
• eye: remote sensing instrument in the visible
wavelength region (350 - 750 nm)
• signal processing in the eye and in the brain
• colour (RGB) and relative intensity are used to
identify surface types
• large data base and neuronal network used to
derive object properties
A. Richter, Heraeus-Summerschool, 3.9.2005
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The Eye as a Remote Sensing Instrument
• eyes are scanning the environment with up to
60 frames per second
• 170° field of view, 30° focus
A. Richter, Heraeus-Summerschool, 3.9.2005
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The Eye as a Remote Sensing Instrument
• stereographic view, image processing, and a
large data base enables detection of size,
distance, and movement
!!!
A. Richter, Heraeus-Summerschool, 3.9.2005
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The Eye as a Remote Sensing Instrument
• passive remote sensing instrument, relies on
(sun) light scattered from the object
• no sensitivity to thermal emission of objects
?
8-14 microns image of a cat
A. Richter, Heraeus-Summerschool, 3.9.2005
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The Eye as a Remote Sensing Instrument
• active remote sensing by use of artificial light
sources
?
A. Richter, Heraeus-Summerschool, 3.9.2005
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Why should we use Remote Sensing?
• not all measurement locations are accessible (atmosphere, ice, ocean)
• remote sensing facilitates creation of long time series and extended
measurement areas
• for many phenomena, global measurements are needed
• remote sensing measurements usually can be automated
• often, several parameters can be measured at the same time
• on a per measurement basis, remote sensing measurements usually are
less expensive than in-situ measurements
A. Richter, Heraeus-Summerschool, 3.9.2005
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Why NOT to use Remote Sensing:
• remote sensing measurements are always indirect measurements
• the electromagnetic signal is often affected by more things than just the
quantity to be measured
• usually, additional assumptions and models are needed for the
interpretation of the measurements
• usually, the measurement area / volume is relatively large
• validation of remote sensing measurements is a major task and often not
possible in a strict sense
• estimation of the errors of a remote sensing measurement often is difficult
A. Richter, Heraeus-Summerschool, 3.9.2005
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Schematic of Remote Sensing Observation
Validation
Changed
Radiation
Radiation
Object
Sensor
Measurement
A priori
information
Data
Analysis
Final
Result
Forward
Model
A. Richter, Heraeus-Summerschool, 3.9.2005
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Classification of Remote Sensing Techniques
•
•
•
•
active / passive
platform
wavelength range
spectral resolution
 low / medium / high
• spatial resolution
 low / high
• detection technique
 absorption, emission or extinction spectroscopy
 spectral reflectance
A. Richter, Heraeus-Summerschool, 3.9.2005
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Active vs. Passive Remote Sensing
Active Remote Sensing:
Artificial source of radiation, the reflected or scattered signal is analysed:
• sound: SONAR
• radio waves: RADAR (RAdio Detection And Ranging)
• laser light: LIDAR (LIght Detection And Ranging)
• white light: long path DOAS (Differential Optical Absorption Spectroscopy)
Passive Remote Sensing:
Natural sources of radiation, the attenuated, reflected, scattered, or emitted
radiation is analysed:
• solar light
• lunar light
• stellar light
• thermal emission
A. Richter, Heraeus-Summerschool, 3.9.2005
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Remote Sensing Platforms
• ground-based measurements
 continuous, high accuracy, easy accessibility
 local measurement
• air-borne measurements (up to 15 km)
 fast moving, long distance
 expensive, sporadic
• sonde / balloon measurements (up to 30 km)
 high altitude
 logistically difficult, often expensive
• rocket measurements (up to 80 km)
 very high altitude
 expensive, sporadic
• Space Shuttle / Space Station measurements
 global coverage, limited time coverage, good accessibility
• satellite measurements
 global coverage
 poor accessibility, expensive
A. Richter, Heraeus-Summerschool, 3.9.2005
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Wavelength Ranges in Remote Sensing
UV:
some absorptions + profile information
aerosols
vis:
surface information (vegetation)
some absorptions
aerosol information
IR:
temperature information
cloud information
water / ice distinction
many absorptions / emissions
+ profile information
MW:
no problems with clouds
ice / water contrast
surfaces
some emissions + profile information
A. Richter, Heraeus-Summerschool, 3.9.2005
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Which Quantities are Measured?
•
•
•
•
•
•
absolute intensities in dedicated wavelength intervals
intensities relative to the intensity of a reference source
ratios of intensities at different wavelengths
variations of intensities
degree of polarisation
phase and delay of signal
A. Richter, Heraeus-Summerschool, 3.9.2005
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Which Quantities can be Determined?
Surface
 height
 albedo
 vegetation type
 surface (water) temperature
 fires
 surface roughness
 wind speed
 water turbidity / chlorophyll
concentrations
 ice cover
 ice type
A. Richter, Heraeus-Summerschool, 3.9.2005
Meteorology
 pressure
 temperature
 cloud cover
 cloud top height
 cloud type
 lightning frequency
Chemical constitution of the
atmosphere
 aerosol burden
 aerosol type
 trace species
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The Electromagnetic Spectrum
Wavelength λ
I
1km
I
i
100m 10m
I
I
I
1m
0.1m
10cm 1cm
Radiowaves
I
I
I
1mm
0.1mm 10μm 1μm
Microwaves
I
I
I
thermal
Infrared
I
I
0.1μm 10nm 1nm
X -ray
Visible
Ultraviolet
Interaction of electromagnetic
radiation with matter
•
•
•
•
Rotation
Vibration
Electron
Transition
nearly all energy on Earth is supplied by the sun through radiation
wavelengths from many meters (radio waves) to nm (X-ray)
small wavelength = high energy
radiation interacts with atmosphere and surface
 absorption (heating, shielding)
 excitation (energy input, chemical reactions)
 re-emission (energy balance)
A. Richter, Heraeus-Summerschool, 3.9.2005
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Radiative Transfer in the Atmosphere
Contributions:
• Direct Solar Ray
• Reflection on the Surface
• Reflection from Clouds
• Scattering in the Atmosphere
 Rayleigh Scattering
 Mie Scattering
 Raman Scattering
•
•
•
•
Absorption in the Atmosphere
Emission in the Atmosphere
Emission from the Surface
Emission from Clouds
A. Richter, Heraeus-Summerschool, 3.9.2005
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Radiative Transfer in the Atmosphere
Atmosphere
Absorption
Scattering
from a cloud
Scattering
Emission
Emission from
a cloud
Transmission
through a
cloud
Cloud
Scattering
within a cloud
Aerosol /
Molecules
Scattering /
reflection oh a
cloud
Absorption on
the ground
A. Richter, Heraeus-Summerschool, 3.9.2005
Scattering /
Reflection on the
ground
Transmission
through a
cloud
Emission from
the ground
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Scattering in the Atmosphere
Depending on the ratio of the size of the scattering particle (r) to the
wavelength () of the radiation:
Mie parameter  = 2 r / ,
different regimes of atmospheric scattering can be distinguished.
=> different wavelengths probe different parts of the atmosphere / surface
A. Richter, Heraeus-Summerschool, 3.9.2005
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What is the Optimal Instrument?
A compromise must be found to get the optimum amount of information out
of the limited number of photons available under the given boundary
conditions:
 instrument
size and price
spatial
coverage
 satellite orbit
spatial
resolution
 measurement
quantity
 data rate
 measurement
error
time
resolution
vertical
resolution
spectral
resolution
A. Richter, Heraeus-Summerschool, 3.9.2005
time
coverage
spectral
coverage
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Satellite Orbits
(Near) Polar Orbit:
• orbits cross close to the pole
• global measurements are possible
• low earth orbit LEO (several 100 km)
• ascending and descending branch
• special case: sun-synchronous orbit:
 overpass over given latitude always at the same local
time, providing similar illumination
 for sun-synchronous orbits: day and night branches
Geostationary Orbit:
• satellite has fixed position relative to the Earth
• parallel measurements in a limited area from low to
middle latitudes
• 36 000 km flight altitude, equatorial orbit
http://www2.jpl.nasa.gov/basics/bsf5-1.htm
http://www.ccrs.nrcan.gc.ca/ccrs/learn/tutorials/fundam/chapter2/chapter2_2_e.html
A. Richter, Heraeus-Summerschool, 3.9.2005
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How can Vertical Information be Derived?
In many atmospheric application, vertical profiles of quantities are needed.
Approaches:
• Vertical Scanning
sequential of parallel measurements at different altitudes
=> e.g. SCIAMACHY limb profiles
• Pressure / Temperature dependence of signal (e.g. line shape)
inversion of signal using a priori information on e.g. vertical p-profile
=> e.g. microwave sounding
• Saturation Effects at different wavelengths (frequencies)
using spectral regions with different penetration depths
=> e.g. SBUV ozone profile measurements
• Time Resolved measurements
using pulsed signals and photon flight time information
=> e.g. LIDAR
• Combination of different types of measurements, instruments or models
=> e.g. GOME tropospheric NO2 measurements
A. Richter, Heraeus-Summerschool, 3.9.2005
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How can Vertical Information be Derived?
In many atmospheric application, vertical profiles of quantities are needed.
Approaches:
• Vertical Scanning
sequential of parallel measurements at different altitudes
Nadir: observation of scattered and reflected light, total
column determination (and O3 profile), good spatial
resolution, global coverage, good SNR
Limb: observation of scattered light, stratospheric and
upper atmosphere profiles, poor spatial resolution,
near global coverage, SNR decreases with altitude
Occultation: direct observation of sun or moon at
horizon, stratospheric profiles, poor spatial
resolution, limited coverage (close to terminator),
high SNR but low UV sensitivity
Limb Nadir Matching: combination of nadir and limb
measurements to estimate the tropospheric column
of a trace gas
http://www.sciamachy.de
A. Richter, Heraeus-Summerschool, 3.9.2005
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How can Vertical Information be Derived?
In many atmospheric application, vertical profiles of quantities are needed.
Approaches:
• Pressure / Temperature dependence of signal (e.g. line shape)
pressure
broadening:
T-profile
p-profile
low p
trace gas profile
Measured Spectrum
inversion
high p
http://www.ram.uni-bremen.de/index_ram.html
A. Richter, Heraeus-Summerschool, 3.9.2005
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How can Vertical Information be Derived?
In many atmospheric application, vertical profiles of quantities are needed.
Approaches:
• Saturation Effects at different wavelengths (frequencies)
Example: ozone profiling in the UV (e.g. SBUV, GOME)
Ozone absorption is increasing by orders of magnitude over 50 nm in the UV, and
virtually no photons reach the surface below 300 nm. By measuring ozone at
different wavelengths, different sub-columns are determined => profile
331
nm
297
nm
A. Richter, Heraeus-Summerschool, 3.9.2005
306
nm
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How can the desired signal be isolated?
In most measurements, several effects on the signal interfere and need to be
corrected.
Example: retrieval of NO2 by UV/vis absorption spectroscopy of scattered sun light
• NO2 absorption
• absorption by other species (O3, O4, H2O, ...)
=> use of measurements at many wavelengths and characteristic absorption
spectrum for correction
• colour of the surface (e.g. ocean colour)
=> use of measurements at many
wavelengths and characteristic
absorption spectrum for correction
• scattering by aerosols
=> fit of broad band contribution
• elastic scattering by air molecules
=> fit of broad band contribution
• inelastic scattering by air molecules
=> explicit correction by modelling
the effect
=> in many cases, measurements at several wavelengths / frequencies help
A. Richter, Heraeus-Summerschool, 3.9.2005
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Validation of Remote Sensing Measurements
Remote Sensing measurements are indirect measurements, and need
validation!
The perfect validation measurements should
• measure the same quantity
• integrate over the same volume
• measure at the same time
• use an independent technique
• have higher accuracy and precision than the measurement to be validated
• cover a large range of geophysical conditions
• have no location bias such as measurements
 only over land,
 only during clear weather or
 mostly in the Northern Hemisphere
• not be too expensive
=> such measurements do usually not exist!
A. Richter, Heraeus-Summerschool, 3.9.2005
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Problems for Validation
Example: Stratospheric NO2 measurements from SCIAMACHY:
Amount of data: SCIAMACHY provides about 150 000 NO2 measurements per day
or more than 50 000 000 measurements per year. To validate even a small part of
these data necessitates a large number of validation measurements
Global coverage: hardly any validation measurements are truly global in coverage
but usually biased over land in NH mid-latitudes
Averaging volume: even a “small” SCIAMACHY ground pixel is 30 x 60 km2 large
and at high sun vertically integrated over the whole atmosphere. Sampling this
volume at 3 km resolution horizontally and vertically (up to 20 km) would take many
hours in an aircraft.
Inhomogeneity in time and space: many validation measurements do not coincide
exactly in time and space with the remote sensing measurement. Horizontal
variability as well as changes over time often are the largest uncertainty in
validation
Errors of validation measurements: validation measurements often have
themselves relatively large random and systematic errors, in particular if they are
remote sensing measurements (example: neglect of temperature dependence of
ozone cross-section in Brewer measurements, interference by PAN and other
compounds with in-situ NO2 measurements, pump rate problems at high altitudes
in ozone-sonde measurements, ...)
A. Richter, Heraeus-Summerschool, 3.9.2005
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Validation Example
Example:
Validation of SCIAMACHY NO2 total columns
with ground-based DOAS zenith-sky
measurements
Results:
• validation at several stations (latitudes)
• validation of complete seasonal cycle
• comparable measurement volume
• good agreement
Problems:
• ground-based measurements AM / PM twilight,
SCIAMACHY at 10:00 LT
• zenith-sky measurements not sensitive to
tropospheric pollution
• zenith-sky measurement is also remote
sensing measurement, not truly independent
technique
A. Richter, Heraeus-Summerschool, 3.9.2005
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LIDAR Measurements of tropospheric aerosols
Target Quantity: Tropospheric aerosol concentrations
Measurement Quantity: Backscatter ratio at 532 nm and time lag
Instrument type: LIDAR
Instrument: LITE on Space Shuttle, September 1994
A. Richter, Heraeus-Summerschool, 3.9.2005
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LIDAR (LIght Detection And Ranging)
Idea:
Use of an active system that emits light pulses and measures the intensity of the
backscattered light (from air molecules, aerosols, thin clouds) as a function of time
(optical Radar)
Instrument:
• a strong laser with short pulses
• possibly several wavelengths emitted
• a large telescope to collect the weak signal
Measurement quantity:
• time lag gives altitude information
• signal intensity gives information on backscattering at given altitude and extinction
along the light path
• measurements at different wavelengths provide information on absorbers and
aerosol types
• polarisation measurements provide information on phase of scatterers
=> Very good vertical resolution can be achieved!
A. Richter, Heraeus-Summerschool, 3.9.2005
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Lidar In-space Technology Experiment (LITE)
Instrument:
• flashlamp-pumped Nd:YAG laser
• 1064 nm, 532 nm, and 355 nm
• 1-meter diameter lightweight telescope
• PMT for 355 nm and 532 nm avalanche photodiode (APD) for 1064 nm
Mission Aims:
• test and demonstrate lidar measurements from space
• collect measurements on
 clouds
 aerosols (stratospheric & tropospheric)
 surface reflectance
Operation:
• on Discovery in September 1994
as part of the STS-64 mission
• 53 hours operation
http://www-lite.larc.nasa.gov/index.html
A. Richter, Heraeus-Summerschool, 3.9.2005
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LITE: Example of Aerosol Measurements
Clouds (ITCZ)
Atlas mountains
complex aerosol layer
maritime
aerosol layer
•
•
•
•
•
5 minutes of LITE data over the Sahara
low maritime aerosol layer
high complex aerosol layer over Sahara
Atlas Mountains separate two regimes
clouds close to the ITCZ
A. Richter, Heraeus-Summerschool, 3.9.2005
http://www-lite.larc.nasa.gov/index.html
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UV absorption measurements of stratospheric O3
Target Quantity: Stratospheric Ozone columns
Measurement Quantity: Differential absorption of backscattered UV
radiation
Instrument type: low resolution nadir viewing UV spectrometer
Instrument: TOMS (Total Ozone Mapping Spectrometer )
A. Richter, Heraeus-Summerschool, 3.9.2005
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Total Ozone Mapping Spectrometer TOMS
Idea:
• global measurements of ozone columns using differential measurements in
the UV
• good spatial resolution through fast measurements
• additional products (SO2, aerosols) by clever selection of wavelengths
• continuous measurements, long time series, high consistency, little
changes in instrumentation => trends
The TOMS programme:
Satellite
Nibus 7
Meteor3
Adeos
Earth Probe (EP)
Period
Oct 78 – May 93
Aug 91 – Dec 94
Aug 96 – Jun 97
Jul 96 – Dec 97
Dec 97 – today
Orbit
955 km
830 km
500 km
740 km
Wavelengths:
380.0 339.7 331.0 317.4 312.3 308.6 nm
http://jwocky.gsfc.nasa.gov/
A. Richter, Heraeus-Summerschool, 3.9.2005
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TOMS: Observation of the Ozone Hole
The Ozone Hole
• forms in the Antarctic winter /
spring
• formation of Polar Stratospheric
Clouds PSC in the extremely
cold vortex
• heterogeneous activation of
chlorine reservoirs on the cold
PSC surfaces
• rapid ozone destruction by ClO
and BrO as the sun rises
• end of ozone destruction after
warming when chlorine is
transformed back to its
reservoirs HCl and ClONO2 and
vortex air mixes with ozone rich
air
http://jwocky.gsfc.nasa.gov/
A. Richter, Heraeus-Summerschool, 3.9.2005
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UV/vis absorption measurements of tropospheric NO2
Target Quantity: Tropospheric Nitrogen Dioxide columns
Measurement Quantity: Differential absorption of backscattered radiation
Instrument type: medium resolution nadir viewing UV/vis spectrometer
Instrument: GOME (Global Ozone Monitoring Experiment) on ERS-2
A. Richter, Heraeus-Summerschool, 3.9.2005
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Global Ozone Monitoring Experiment (GOME)
Idea:
• simultaneous measurements from the UV to the near IR
• good spectral resolution (0.2 – 0.4 nm)
• use of DOAS to retrieve columns of several species (O3, NO2, OClO, BrO,
HCHO, SO2, H2O)
• use of UV wavelengths to retrieve ozone profiles
• global coverage
Launch: April 1995 on ERS-2 (sun synchronous)
GOME successor instruments:
Instrument
Satellite
SCIAMACHY ENVISAT
OMI
EOS-Aura
GOME-2
Metop-1 .. Metop-3
Launch
March 2002
Spring 2004
2006 – 2020
http://www.iup.physik.uni-bremen.de/gome/
A. Richter, Heraeus-Summerschool, 3.9.2005
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GOME: tropospheric NO2 excess
• NOx plays a key role in the
formation of photochemical
ozone smog
• sources of NOx are both
anthropogenic (combustion
of fossil fuels, biomass
burning) and natural (fires,
soil emissions, lightning)
• NOx emissions are
changing as result of
• changes in land use
Data analysis:
1. cloud screening
2. DOAS retrieval of total slant columns
3. subtraction of clean Pacific sector to derive
tropospheric slant columns
4. application of tropospheric airmass factor to
compute tropospheric vertical column
A. Richter, Heraeus-Summerschool, 3.9.2005
• improvements in
emission control
• economic development
(e.g. China)
• GOME data provided the
first global maps of
tropospheric NO2
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UV/vis Measurements of Stratospheric Aerosols
Target Quantity: stratospheric aerosol concentrations
Measurement Quantity: backscattered radiation
Instrument type: solar occultation viewing UV/vis spectrometer
Instrument: SAGE-2 (Stratospheric Aerosol and Gas Experiment)
A. Richter, Heraeus-Summerschool, 3.9.2005
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Stratospheric Aerosol and Gas Experiment (SAGE)
Measurement Geometry: solar occultation
Instrument: grating spectrometer with Si-detectors
Spectral coverage: 7 wavelengths between 385 – 1020 nm:
1020, 940, 600, 525, 453, 448 und 385 nm
Data analysis: onion peeling
Measurement targets: vertical profiles of O3, NO2, H2O and
aerosol extinction (at 385, 453, 525 and 1020 nm)
Measurement range: stratosphere, at low stratospheric aerosol loading and outside
the tropics also the upper troposphere
The SAGE programme:
SAM II
1978
SAGE I 1979-1981
SAGE II 1984 - today
SAGE III 2001 - today
280 – 1030 nm, 1-2 nm spectral resolution
CCD detector, lunar + solar occultation
http://www-sage3.larc.nasa.gov/
A. Richter, Heraeus-Summerschool, 3.9.2005
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SAGE: Stratospheric Aerosols
• Stratospheric aerosols
are dominated by
volcanic input (H2SO4).
• Large eruptions inject ash
and SO2 directly into the
stratosphere.
• Transport towards poles
within one year.
• Exponential decay over
many years
1985: Nevado del Ruiz,
Columbia
1990: Kelut, Indonesia
1991: Mt. Pinatubo
http://aerosols.larc.nasa.gov/optical_depth.html
A. Richter, Heraeus-Summerschool, 3.9.2005
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Radio Occultation Measurements of Temperature Profiles
Target Quantity: temperature profiles
Measurement Quantity: excess phase of GPS signals
Instrument type: GPS occultation
Instrument: CHAMP (CHAllenging Minisatellite Payload)
A. Richter, Heraeus-Summerschool, 3.9.2005
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CHAMP radio occultation
Principle:
• GPS receiver observes
GPS satellite during
occultation
• high accuracy time
information provides
excess phase
• this is related to the
bending angle profile α
• which depends on
refractive index n
• which is a function of p,
T and humidity
+
+
+
-
good vertical resolution
large number of measurements
good sampling
assumptions on 2 of the three
variables necessary
- problems with critical layers
http://www.copernicus.org/EGU/acp/acpd/4/7837/acpd-4-7837_p.pdf
A. Richter, Heraeus-Summerschool, 3.9.2005
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QBO Temperature Anomalies from CHAMP Radio Occultation
• downward
propagation of
temperature
anomalies in the
tropical stratosphere
• QBO (Quasi Biannual
Oscillation) signal
• maximum amplitude
of +/- 4.5 K
• impact on
stratospheric ozone
columns
http://www.copernicus.org/EGU/acp/acpd/4/7837/acpd-4-7837_p.pdf
A. Richter, Heraeus-Summerschool, 3.9.2005
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Microwave Measurements of Wind Speed and Direction
Target Quantity: wind speed and direction
Measurement Quantity: reflected microwave intensity and polarisation
Instrument type: active microwave
Instrument: Synthetic Aperture Radar (SAR).
A. Richter, Heraeus-Summerschool, 3.9.2005
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How to derive wind speed from Radar signals
Idea:
Bragg-like resonance of cm-size ocean waves with Radar signals
depends monotonically on surface wind speed
=> wind speed over oceans can be determined from scatterometer
measurements if wind direction is known from model or other
measurements
Validation:
Relationship between radar backscatter and
surface wind speed for C-band (5.3 Hz),vertical
polarization at 45° off nadir angle.
A. Richter, Heraeus-Summerschool, 3.9.2005
http://fermi.jhuapl.edu/sar/stormwatch/
user_guide/bealguide_072_V3.pdf
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Wind Speed from Radarsat SAR
Polar low imaged by 430 km
wide swath mode of
Radarsat SAR, before
application of wind algorithm,
0602 GMT 05 Feb 1998.
Polar low of 05 Feb 1998 after
application of wind algorithm,
embedded in NOGAPS model
wind field (arrows).
http://fermi.jhuapl.edu/sar/stormwatch/user_guide/bealguide_072_V3.pdf
A. Richter, Heraeus-Summerschool, 3.9.2005
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Passive Microwave Measurements of Sea Ice
Target Quantity: sea ice coverage and type
Measurement Quantity: reflected microwave intensity and polarisation
Instrument type: passive microwave radiometer
Instrument: AMSR-E (Advanced Microwave Scanning Radiometer - EOS )
 12 channels and 6
frequencies ranging
from 6.9 to 89.0 GHz
 two polarisations
A. Richter, Heraeus-Summerschool, 3.9.2005
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Sea Ice Maps from AMSR-E
Basic principle:
• strong contrast in thermal
microwave emission
between ice and open ocean
• assumption of linear
relationship between
brightness and ice cover
• parameters:
 sea ice concentration,
 surface ice temperature,
 snow depth on ice
• ice type by frequency
dependence of emission
http://www.seaice.de/
A. Richter, Heraeus-Summerschool, 3.9.2005
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IR Measurements of Sea Surface Temperature
Target Quantity: sea surface temperature
Measurement Quantity: emitted IR radiation
Instrument type: nadir broad band IR measurements
Instrument: AVHRR (Advanced Very High Resolution Radiometers)
A. Richter, Heraeus-Summerschool, 3.9.2005
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Reminder: El Niño – La Niña
•
•
•
•
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reversal of Walker circulation
change of direction of Trade Winds
change of ocean upwelling
displacement of convection areas
link to Southern Oscillation
(difference of surface pressure
between Tahiti and Darwin)
A. Richter, Heraeus-Summerschool, 3.9.2005
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Sea Surface Anomaly during El Nino Event
• Sensor: TOPEX
• Technique: radar altimeter
• Quantity: height
A. Richter, Heraeus-Summerschool, 3.9.2005
• Sensor: AVHRR
• Technique: broad band IR
measurements
• Quantity: sea surface
temperature
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Summary
• Remote Sensing of atmospheric and surface parameters from space relies
on analysis of electromagnetic radiation emitted / scattered / reflected by
the atmosphere and surface
• The target quantities interact with the radiation through absorption,
emission, scattering, reflection or by indirectly changing the optical
properties
• Remote Sensing measurements provide a large number of parameters for
atmospheric physics and chemistry on a global scale and often over long
time periods
• Remote Sensing measurements are indirect measurements and need
thorough and continuous validation
• Spatial and temporal resolution of the measurements are limited and not
always appropriate for detailed case studies
• Technological improvements and progress in data algorithms will further
improve the usefulness of satellite measurements in the future
• Remote Sensing will always be only one of many data sources needed to
understand the Earth System
A. Richter, Heraeus-Summerschool, 3.9.2005
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