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    24-Jul-2014
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MIPAS Data Formats Products
Records
2 MDSR per MDS 1 forward sweep 1 reverse sweep
2 MDSRs per MDS 1 forward sweep 1 reverse sweep
LOS calibration GADS
Spectral Lines MDS
P T Retrieval MW ADS
VMR Retrieval Parameters GADS
P t Retrieval GADS
Framework Parameters GADS
Processing Parameters GADS
Inverse LOS VCM matrices MDS
General GADS
Occupation matrices for vmr#1 retrieval MDS
MDS2 -- 1 mdsr forward sweep 1 mdsr reverse
Occupation matrices for p T retrieval MDS
General GADS
Priority of p T retrieval occupation matices
P T occupation matrices ADS
MIP_NLE_2P SPH
Summary Quality ADS
Instrument and Processing Parameters ADS
Microwindows occupation matrices for p T and trace gas retrievals
Scan information MDS
Level 2 product SPH
MDS1 -- 1 mdsr forward sweep 1 mdsr reverse sweep
H2O Target Species MDS
P T and Height Correction Profiles MDS
Continuum Contribution and Radiance Offset MDS
Structure ADS
Summary Quality ADS
Residual Spectra mean values and standard deviation data ADS
PCD Information of Individual Scans ADS
Instrument and Processing Parameters ADS
Microwindows Occupation Matrices ADS
Scan Information MDS
1 MDSR per MDS
Scan Geolocation ADS
Mipas Level 1B SPH
Calibrated Spectra MDS
Structure ADS
Summary Quality ADS
Offset Calibration ADS
Scan Information ADS
Geolocation ADS (LADS)
Gain Calibration ADS #2
Gain Calibration ADS #1
Level 0 SPH
DSD#1 for MDS containing VMR retrieval microwindows data
DSD for MDS containing p T retrieval microwindows data
VMR #1 retrieval microwindows ADS
P T retrieval microwindows ADS
1 MDSR per MDS
VMR profiles MDS (same format as for MIP_IG2_AX)
Temperature profiles MDS (same format as for MIP_IG2_AX)
Pressure profile MDS (same format as for MIP_IG2_AX)
P T continuum profiles MDS (same format as for MIP_IG2_AX)
GADS General (same format as for MIP_IG2_AX)
Level 0 MDSR
Values of unknown parameters MDS
Computed spectra MDS
Jacobian matrices MDS
General data
Data depending on occupation matrix location ADS
Microwindow grouping data ADS
LUTs for p T retrieval microwindows MDS
GADS General
P T retrieval microwindows ADS
ILS Calibration GADS
Auxilliary Products
MIP_MW1_AX: Level 1B Microwindow dictionary
MIP_IG2_AX: Initial Guess Profile data
MIP_FM2_AX: Forward Calculation Results
MIP_CS2_AX: Cross Sections Lookup Table
MIP_CS1_AX: MIPAS ILS and Spectral calibration
MIP_CO1_AX: MIPAS offset validation
MIP_CL1_AX: Line of sight calibration
MIP_CG1_AX: MIPAS Gain calibration
MIP_SP2_AX: Spectroscopic data
MIP_PS2_AX: Level 2 Processing Parameters
MIP_PS1_AX: Level 1B Processing Parameters
MIP_PI2_AX: A Priori Pointing Information
MIP_OM2_AX: Microwindow Occupation Matrix
MIP_MW2_AX: Level 2 Microwindows data
MIP_CA1_AX: Instrument characterization data
Level 0 Products
MIP_RW__0P: MIPAS Raw Data and SPE Self Test Mode
MIP_NL__0P: MIPAS Nominal Level 0
MIP_LS__0P: MIPAS Line of Sight (LOS) Level 0
Level 1 Products
MIP_NL__1P: MIPAS Geolocated and Calibrated Spectra
Level 2 Products
MIP_NLE_2P: MIPAS Extracted Temperature , Pressure and Atmospheric Constituents Profiles
MIP_NL__2P: MIPAS Temperature , Pressure and Atmospheric Constituents Profiles
Glossary
References
Glossaries of technical terms
Level 2 processing
Pointing
Miscellaneous hardware and optical terms
Spectrometry and radiometry
Data Processing
Alphabetical index of technical terms
Frequently Asked Questions
The MIPAS Instrument
Inflight performance verification
Instrument characteristics and performances
Preflight characteristics and expected performances
Subsystem description
Payload description and position on the platform
MIPAS Products and Algorithms
Data handling cookbook
Characterisation and calibration
Calibration
Latency, throughput and data volume
Auxiliary products
Level 2
Instrument specific topics
Algorithms and products
Level 2 products and algorithms
Products
The retrieval modules
Computation of cross-sections
Level 1b products and algorithms
Products
Calculate ILS Retrieval function
Level 1a intermediary products and algorithms
Product evolution history
Definition and convention
MIPAS Products User Guide
Image gallery
Further reading
How to use MIPAS data?
Summary of applications and products
Peculiarities of MIPAS
Geophysical coverage
Principles of measurement
Scientific background
MIPAS Product Handbook
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2.4 Algorithms and products

2.4.1 Level 0 products and algorithms

Level 0 data is the data stream received directly from the instrument without any further processing. Since MIPAS performs some onboard processing, this does not mean that Level 0 data is free of processing. The interferogram recorded by the detectors undergo a series of modification before being downlinked to the ground station. The main processing steps are:

2.4.1.1 Decimation and filtering


In order to lower the size of the signals to be transmitted, measured interferograms are filtered and decimated. This operation is part of the onboard processing.
 

Neglecting the dispersion phenomenon inducing a non-null phase, an observed interferogram is basically a real and symmetrical function. The symmetry is about ZPD and, by extension about every multiple of MPD.
The Fourier transform of such an interferogram is a real and symmetrical spectrum with symmetry about every multiple of the sampling frequency. In other words, the full spectrum will show on one half the true physical spectrum and on the other half the image of this spectrum. Depending on the convention, this second half may be displayed as negative frequencies or as frequencies above the sampling frequency divide by 2, as displayed in the figure below.
 

For a given sampling rate of ss (equal to 7692 cm“1 for MIPAS, corresponding to a laser operating at 1300 nm), the Nyquist sampling theorem states that this sampling frequency defines a fixed spectral band of maximum width ss / 2. This spectral band is quite large and can be reduced. The principle of data compression is to sample at a lower rate by decimating the interferogram (taking one point out of n) already sampled by the metrology laser system. The result is a reduced number of interferogram data points that permits a smaller data throughput.
 

image
Figure 2.2 Filtering and decimation scheme

When a spectrum is band limited between s0 and s1 , the sampling frequency can be reduced up to 2s1 without any information loss as stated by the Nyquist sampling theorem. Reducing the sampling frequency further can produce spectral overlap that disturbs the interesting information (aliasing effect). However, since there is a useless spectral region from 0 to so , it is possible to sample at a lower rate than 2s1 and still keep all the information. For a real filtered signal, where both the desired physical band and its image are present, the lowest possible sampling frequency preserving the information is twice the spectral bandwidth  .
For MIPAS, complex filters have been devised in such a way that it has no image passband, by defining its imaginary part anti-symmetrical such that it produces a compensating negative image. After such a filtering, the only undersampling condition is:

   ss = s1 - so eq 2.1

Thus, the decimation factor can be two times larger after complex filtering. The integer ratio of the initial sampling frequency to the new one is called the decimation factor, noted DF. Since the folding frequencies are not restricted to be out of the band of interest, there is no additional restriction on the decimation factor. It is then possible to better optimize the decimation factor. This is where a gain can be made with respect to data reduction.
The shape of the apodisation function applied to the filtering impulse response (FIR) is critical. It must produce sufficient smoothing of the filter, but must avoid widening it to the point of reducing too much the effective bandwidth of the pass bands and the possible data compression. MIPAS FIR filters respect these criteria and are defined over 256 taps using 16-bit coefficients. The isolation of the various MIPAS filters range from 65 to 87 dB.
The processing needed for the proper recovery of the wavenumber axis for each spectrum consists of computing a Fourier transform of the decimated signal, unfolding of the spectral axis (for cases where spectral limits do not exactly correspond to an integer factor of the band width), followed by axis limit identification. Further details about this procedure can be found in the ATBD Ref. [1.6 ] .
 

2.4.1.2 Word length reduction

During the formatting of the data stream by the SPE, the word length (or bit size) of the interferogram is reduced on a fraction of the interferogram. Due to the typical shape of an interferogram (see the figure below), the full dynamic range (16 bits) is used only near the ZPD. Far from the ZPD, only a small fraction of the ADC range is used. The regions far from the ZPD, on both side of the interferogram, can thus be coded using a smaller number of bits without loosing any information. The size of the data transmitted is thus significantly reduced.
 

imagefull size
Figure 2.3 Typical analogue (left) and digitalised (right) interferograms.

2.4.1.3 Data compression

2.4.1.4 Formatting into instrument source packets


Keywords: ESA European Space Agency - Agence spatiale europeenne, observation de la terre, earth observation, satellite remote sensing, teledetection, geophysique, altimetrie, radar, chimique atmospherique, geophysics, altimetry, radar, atmospheric chemistry