page 1 envisat symposium – salzburg - austria 6-10 september 2004 geo-mtr: a 2-dimensional multi...

ENVISAT Symposium – Salzburg - Austria 6-10 September 2004

GEO-MTR: A 2-Dimensional Multi Target Retrieval System for MIPAS/ENVISAT

Observations

M. Carlotti, E. Papandrea, M. Prevedelli, M. RidolfiDCFI, Bologna University, Bologna, Italy

B.M. Dinelli, L. MagnaniISAC-CNR, Bologna, Italy

A. DudhiaAOPP, Oxford University, Oxford, UK


A new retrieval system for MIPAS measurements has been developed in the frame of ESA contract No. 16700/02/I-LG by:

The new system (named GEO-MTR) will be distributed by ESA as an open source code.

DCFI AOPP LPPM

Science

[&]

Technology

The system is designed for “nominal” and “special” observation modes


Features of the ESA Level-2 processor

Retrieval from narrow-band spectral intervals (MicroWindows);

Global-fit of one limb-scan at a time;

Atmosphere assumed horizontally homogeneous;

Sequential retrieval of the target species: pT (pointing), H2O, O3, HNO3, CH4, N2O, and NO2.


Assumptions of the ESA Level 2 processor (atmospheric model)

The sampled atmosphere is assumed as perfectly stratified (Horizontal Homogeneity Assumption).

In the case of “along track” measurements, because of the movement of the platform, this assumption extends to a scale of the order of 2000 km.

When pronounced horizontal gradients are present, this assumption introduces systematic errors that are difficult to assess.


For along track observations, 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 (North Pole);

The information is fully exploited by merging in a simultaneous fit the observations of an entire orbit.

GEO-FIT rationale


A 2-Dimensional discretization of the atmosphere must be operated


GEO-FIT advantages

Enables to model the horizontal variability of the atmosphere

The retrieval grid is independent from the measurement grid: the horizontal resolution of the retrieved atmospheric fields can be optimized;

Enables to exploit at best the information content of along-track measurements;


Assumptions of the ESA Level 2 processor (retrieval strategy)

The analysed MicroWindows usually contain transitions of several gases that generate composite spectral features.

Individual targets are sequentially retrieved.

The uncertainty on the VMR of non-retrieved (interfering) species acts as a systematic error source of the retrieval.

To minimize these errors, the following items were optimised:1. the sequence of the retrievals; 2. the selection of the analysed MWs.

Nevertheless, in most cases, these errors are not negligible.


Multi Target Retrieval (MTR)rationale

The simultaneous retrieval of target quantities that are correlated eliminates the systematic error propagation due to “interfering” species.

The uncertainty on the initial guess of the quantities that are simultaneously retrieved does not act as a source of systematic error;


MTR – advantages

No systematic error propagation due to “interfering” species;

The error due to the cross-talk between different target quantities is properly represented in the covariance matrix of the retrieved parameters;

The selection of MicroWindows 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 (not only from CO2 lines, as in the ESA's Level 2 processor).


GEO-MTR functionalities (1/2)

Main functionalities of the new retrieval system are:

1. Geofit analysis (2-Dimensional) of a full orbit;2. Orbit-segments analysis (2-Dimensional);3. Single-sequence analysis.

4. MTR analysis 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.


GEO-MTR functionalities (2/2)

Sequential retrievals can be obtained by running the analysis system in sequence through a UNIX script;

Any combination of MTR and sequential retrievals can be used;

Operates 2-D analyses on all the backward looking observation- modes;

Cross-track observations can be analyzed with the Single-scan option.

Not suitable for daytime Upper Atmosphere observations (NLTE is not modeled)


P, T, H2O, O3 retrieval with GEO-MTR

Performance test on orbit 2081+2082 Data acquired on 24 July 2002 (1/6)


Dedicated MWs have been produced for GEO-MTR.

Test using pointing information and initial guess profiles obtained from ESA's Level 2 processor:

Convergence is reached after 2 Gauss - Newton iterations:

2-test 4.95 1.78 1.70

Test using Level-1b pointing information and climatological profiles for the initial guess:

Convergence is reached after 3 Gauss - Newton iterations:

2-test 80.18 3.41 1.87 1.83

Performance test on orbit 2081+2082 (2/6)



Temperature

North Pole North PoleSouth PoleEquator Equator



Pressure



Water vapour



Ozone


GEO-MTR vs ESA Level 2 (1/3)

Temperature ESD

GEO - MTR ESA Level 2



Water vapour ESD




Ozone ESD



NOMINAL

#6673 (10 Jun 2003)

75 Scans

17 Sweeps / scan

(68-6 km)

S2

#6687 (11 Jun 2003)

89 Scans

14 Sweeps /scan

(40-5 km)

Test on special mode S2 vs NOMINAL mode (1/5)



#6673 Nominal Mode #6687 Special Mode (S2)

Temperature




Temperature


Test on special mode S2 vs NOMINAL mode (5/5)Temperature

ESD



Computing Performance on composite orbit 2081+2082

MTR retrieval of P, T, H2O, O3 followed by sequential retrieval of HNO3, CH4, N2O, NO2

Time required for the retrieval on the full orbit: 105 min on a single CPU Pentium IV (2.8 GHz) 17 min on a cluster of 8 CPU Pentium IV (2.8 GHz)

Memory (RAM) required: 1.05 Gb with static allocation 600 Mb with dynamic allocation (FORTRAN 90)


Conclusions

A new retrieval system has been developed for MIPAS observations

The system operates 2D analyses in Multi Target mode

The accuracy on nominal mode is better than that of the ESA Level 2

A validation-tests program is in progress

Computing requirements are reasonable;

Can perform real time processing of MIPAS observations;

The code will be distributed by ESA as open source (no profit!).

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