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GEO-MTR: A 2-Dimensional Multi Target Retrieval
System for MIPAS/ENVISAT observations
Bianca Maria Dinelli
ISAC – CNR
Bologna
COST 723 – Opening Workshop - ESTEC 11-14 March 2004
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LIMITS of Conventional INVERSION METHODS
atmospheric domain
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The sampled atmosphere is assumed as perfectly stratified
(Horizontal Homogeneity Assumption)
In the case of a steady platform (balloon or airplane) this
assumption applies to a length of several hundreds of
kilometres
In the case of satellite measurements, because of the
movement of the platform, this assumption extends to a
larger scale (For “along track” observations it can be 2000
km)
When pronounced horizontal gradients are present, this
assumption introduces systematic errors difficult to assess
COST 723 – Opening Workshop - ESTEC 11-14 March 2004
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LIMITS of Conventional INVERSION METHODS
target domain
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Atmospheric spectra recorded by a spectrometer like MIPAS contain
features due to several gases and often these spectral features
overlap.
The retrievals are usually operated on a single target and all the target
quantities are sequentially retrieved for each limb-scanning sequence
In the sequence of the retrievals the uncertainty of the retrieved
quantities acts as a systematic error source on the subsequent
retrievals.
To minimize these errors we can
Act on the sequence of the retrievals
Act on the selection of the analysed spectral intervals
However, in many cases these errors are not negligible
COST 723 – Opening Workshop - ESTEC 11-14 March 2004
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GEO-FIT rationale
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The information content about a given location of the atmosphere can be
gathered from all the lines of sight that cross that location
the loop of cross-talk between nearby sequences closes when the starting
sequence is reached again at the end of the orbit
So all the information is exploited by merging in a simultaneous fit the
observations of a complete orbit
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GEO-FIT advantages
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The retrieval grid is independent from the measurement
grid, so the real horizontal resolution of satellite
measurements can be studied.
Enables to exploit at its best the information content of
along-track satellite limb scanning measurements
Enables to model the horizontal variability of the
atmosphere (allowing for a comprehensive assessment of
the impact of the horizontal homogeneity assumption)
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Multi Target Retrieval - rationale
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In the sequence of the retrievals the uncertainty of the
retrieved quantities acts as a systematic error source on
the subsequent retrievals.
In MIPAS PDS the target quantities are sequentially
retrieved
If we retrieve all the target quantities that are correlated
simultaneously this error propagation may be eliminated
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MTR – advantages
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the uncertainty on the initial guess of the quantities that
are going to be simultaneously retrieved does not act as a
source of systematic errors
the error due to the cross-talk between different target
quantities is properly represented by the variancecovariance matrix of the retrieved parameters.
The selection of the spectral intervals to be used in the
analysis is no longer dominated by the need to reduce the
interferences among target species
the information on pressure and temperature can be
gathered from the spectral features of all target species
COST 723 – Opening Workshop - ESTEC 11-14 March 2004
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GEO-MTR
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A new analysis system has been developed for the analysis
of MIPAS nominal and special observation modes
The system is named GEO-MTR and is based on the Geofit
and the Multi Target Retrieval (MTR) functionalities.
The system is developed by University of Bologna, ISACCNR, AOPP, LPPM, IFAC-CNR, ASPER Under ESRIN
contract No. 16700/02/I-LG
The system will be delivered to ESA as open source code
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GEO-MTR functionalities
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The functionalities of the new analysis system are:
Geofit analysis of a full orbit
orbit-segments analysis (in 2D),
single-sequence analysis
Multi Target Retrieval (MTR) of:
 p,T + n VMRs (with n=1,2,…..)
 p,T
 n VMRs
Any combination of MTR with 1, 2, or 3 can be selected
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GEO-MTR functionalities
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With the use of auxiliary files sequential retrievals can be
obtained running the analysis system in sequence through a
unix script
Any combination of MTR and sequential retrievals can be
performed
GEO-MTR can analyze all the backward looking Sn (n=1…6)
special observation modes
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GEO-MTR analysis of orbit 2081
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Orbit 2081 has been analysed performing GEO-MTR analysis for P,T,
H2O and O3
Dedicated MWs have been produced for GEO-MTR
To speed up the retrieval the pointing information and the initial guess
were the results of the L2 analysis performed by MIPAS PDS
Convergence has been reached after 2 iterations
4.95
1.78
1.70
The retrieval has also been started using IG2 profiles and L1B pointing
information
Convergence has been reached after 3 iterations
80.18
3.41
1.87
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1.83
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GEO-MTR Results
Temperature
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GEO-MTR Results
Pressure
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GEO-MTR Results
Ozone
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GEO-MTR Results
Water
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GEO-MTR vs PDS
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GEO-MTR vs PDS
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GEO-MTR vs PDS
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COMPUTING REQUIREMENTS
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The computing resources needed to run GEO-MTR are
examined for the showed retrieval (72 Sequences)
The time needed to perform the retrieval on the full orbit
is:
 54 min 55 s on a single CPU Intel Pentium IV (2.8 GHz)
 8 min 20 s on a cluster of 8 CPU Pentium IV (2.8 GHz)
The memory required by this test case is 1.05 Gbyte (can
be reduced at the expenses of code readability)
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Conclusions
A new retrieval system for MIPAS observations has been
developed
The new system is capable to perform 2D analyses in Multi
Target mode
It has been successfully tested on real MIPAS
observations
Memory and time requirements very reasonable
The MTR functionality enables to retrieve p,T H2O and O3
with lower errors than the PDS analysis system
Can perform real time processing of MIPAS observations
The code will be distributed by ESA as open source (no
profit!)
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