Kein Folientitel

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WP 8 Impact on Satellite Retrievals
Partners (according to Contract)
University of lAquila (DFUA 12) Vincenzo Rizi
Ecole Polytechnique (EPFL 13) Bertrand Calpini
Observatory of Neuchatel (ON 14) Valentin Mitev
Met. Institute Munich (MIM 17) Matthias Wiegner
I have to apologize for my absence I tried the
Jan Ullrich Loop but my collar-bone didnt like
it.
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Goals of the Work-Package
The goal of Workpackage No. 8 includes the
modeling of the aerosol influence on radiances
measured by satellites and the provision of
additional lidar measurements on request. What
does this mean? Measurements Lidar data are
available since May 2000. Dedicated measurements
simultaneous to satellite overpasses make sense
if pixel are small and cloud free conditions can
be guaranteed. On the other hand, the existing
data base can be used for validation of
satellite measurements and their
products. Model calculation Models for
atmospheric corrections (e.g., to retrieve
surface properties) and models to derive aerosol
properties can be supported by supplying lidar
data. Remark The development of such models
itself is beyond the scope of EARLINET. Both
classes are linked and cannot be considered
separately.
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EARLINET and Satellites
General remarks Meteorological satellites
suitable for aerosol remote sensing require
good spatial and spectral resolution. For that
reason, SeaWIFs is presently the most promising
candidate. Geostationary satellites have poor
radiometric accuracy and spectral resolution,
GOME et al. have very poor spatial resolution,
Landsat et al. have very poor temporal sampling,
and sensors with very high spatial resolution
are not yet in orbit (MERIS 250 m, Chris et
al. 25 m). Thus, we follow two options Option
1 plan dedicated experiments on the compare
same atmospheric volume-concept risk overcast
conditions and Option 2 select data sets
already available on the validate aerosol
parameters-concept
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Option 1 dedicated measurements for sensor
calibration
Goal Full characterization of surface and
atmosphere of exactly the same scene (for
calibration of satellite sensor and
algorithms) Requirements co-incidence and
co-location and very small satellite pixel
required.
Location Gilching near Munich and Rhine valley
Time PROBA/CHRIS shifted to 2002
Acquisition mode CHRIS 18 km swath, 25 m
resolution, 19 spectral bands, along track (5
angles)
In co-operation with
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Option 1 dedicated measurements for sensor
calibration
Goal Full characterization of surface and
atmosphere of exactly the same scene (for
calibration of satellite sensor and
algorithms) Requirements co-incidence and
co-location and very small satellite pixel
required.
Location Gilching near Munich and Rhine valley
Time PROBA/CHRIS shifted to 2002
Acquisition mode CHRIS 18 km swath, 25 m
resolution, 19 spectral bands, along track (5
angles)
In co-operation with
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Option 2 aerosol validation with existing data
Goal Support model validation by supplying lidar
data
Actions proposed Supply of aerosol optical
depths (derived from lidar extinction profiles)
at several stations for validation of models that
derive aeosol optical depth from SeaWIFs data
(other aerosol products are not available).
Data Select suitable co-incident, high qualitity
lidar measurements during cloud free conditions
from the existing EARLINET data base fitting to a
SeaWIFs overpass.
Possible co-operation with University of Bremen
(v. Hoyningen-Huene)
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Option 2 Aerosol Validation
Output Several calibration points for the map of
aerosol optical depth derived from (e.g.) v.
Hoyningen-Huenes SeaWIFs retrieval. Information
of special aerosol stratifications that might
help to explain possible deviations. E.g., check,
whether algorithm works in the presence of
Saharan dust layers. Provision of information of
the aerosol type (if possible, e.g., from
trajectories, lidar data themselves, auxiliary
data) to support satellite retrieval algorithm
(input for them).
Possible co-operation with University of Bremen
(v. Hoyningen-Huene)
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Option 2 Aerosol Validation
Output Several calibration points for the map of
aerosol optical depth derived from (e.g.) v.
Hoyningen-Huenes SeaWIFs retrieval. Information
of special aerosol stratifications that might
help to explain possible deviations. E.g., check,
whether algorithm works in the presence of
Saharan dust layers. Provision of information of
the aerosol type (if possible, e.g., from
trajectories, lidar data themselves, auxiliary
data) to support satellite retrieval algorithm
(input for them).
Possible co-operation with University of Bremen
(v. Hoyningen-Huene)
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Option 2 Aerosol Validation (contd.)
Background Information A SeaWIFs algorithm to
derive aerosol optical depth exists and has been
(successfully) applied. SeaWIFS has a spatial
resolution of about 1 km and a coverage of 1800
km (swath width) similar to AVHRR Algorithm
works best in the spectral range between 412 -
510 nm (surface is dark) lidar data of 532 nm
can be extrapolated. Times to be compared should
be in spring and early summer (green vegetation
no problems with water stress) MERIS will have a
better resolution but will be available not
before spring 2002. Sciamachy has a very poor
spatial resolution.
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Option 2 Aerosol Validation (contd.)
To be Discussed Data from stations not directly
involved in this work package would be required.
Is that possible? Who will calculate the
optical depth from the extinction profiles (owner
or M.W.)? Is an extra qualitity check
required/desired by the owner of the
data? Selection of episodes from the diurnal
cycle subset (best time of the day is 11-13
hours)? How many episodes should be selected
(one, two, more?) Should we include algorithms
to derive aerosol optical depth over land from
other institutes (answer from Berlin is pending)?
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Goals of the Work-Package
The goal of Workpackage No. 8 includes the
modeling of the aerosol influence on radiances
measured by satellites and the provision of
additional lidar measurements on request. What
does this mean? Measurements Lidar data are
available since May 2000. Dedicated measurements
simultaneous to satellite overpasses make sense
if pixel are small and cloud free conditions can
be guaranteed. On the other hand, the existing
data base can be used for validation of
satellite measurements and their
products. Model calculation Models for
atmospheric corrections (e.g., to retrieve
surface properties) and models to derive aerosol
properties can be supported by supplying lidar
data. Remark The development of such models
itself is beyond the scope of EARLINET. Both
classes are linked and cannot be considered
separately.
12
Support Model Development
Goal Support model development by supplying
lidar data
Actions Supply of realistic vertical profiles
of aerosol extinction to investigate the
influence (and relevance) of aerosol
stratification on top-of-the-atmosphere-radiances
(atmospheric masking)
Data Special measurements over Munich during the
presence of Saharan dust layers in summer 2001
were provided.
In co-operation with
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Support Model Development
Goal Support model development by supplying
lidar data
Actions Supply of realistic vertical profiles
of aerosol extinction to investigate the
influence (and relevance) of aerosol
stratification on top-of-the-atmosphere-radiances
(atmospheric masking)
Data Special measurements over Munich during the
presence of Saharan dust layers in summer 2001
were provided.
In co-operation with
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Timeframe of WP 8
Start May 2000 End December 2002
Deliverables
April 2002 and February 2003 Report on aerosol
impact on satellite retrievals
Other Deadlines
August 2001 Quality Assurance Report (?)
May 2002 Contribution to Annual Report