2.6.2 Level 2
Summary of input / output
data files
The MIPAS Level 2 processing
input / output data files are summarized in
the following table.

Table 2.11 Summary of Level 2 Processing I/O Data

Level
2 I/O Data

File No.

File Identifier

Description

Size [Bytes]

Update Period

Comments

Level
1 B Data Product (Input)


MIP_NL__1P

Level 1 B
data product

303.1 M

100.6 min


Auxiliary
Data (Input)


MIP_PS2_AX

Processing
parameters data file

10 k

1 month



MIP_MW2_AX

Microwindows
data file

1.6 M

several months



MIP_SP2_AX

Spectroscopic
data file

200 M

several months



MIP_IG2_AX

Initial
guess profile data file

3 M

several months



MIP_FM2_AX

Forward
calculation results file

95 M

several months



MIP_OM2_AX

Microwindows
occupation matrices file

25 M

several months



MIP_CS2_AX

Cross
section lookup tables file

450 M

several months



MIP_PI2_AX

A priori
pointing information file

160 k

several months


Meteorology
Data (Input)


AUX_ECF_AX

ECMWF
meteorological forecast data

TBD

6 hours



AUX_ECA_AX

ECMWF
meteorological analysis data

TBD

6 hours


Annotation
Data (referenced in
Level 2 products)


MIP_NL__1P

Level 1 B
input product





MIP_PS2_AX

Processing
parameters data file





MIP_MW2_AX

Microwindows
data file





MIP_SP2_AX

Spectroscopic
data file





MIP_IG2_AX

Initial
guess profile data file





MIP_FM2_AX

Forward
calculation results file





MIP_OM2_AX

Microwindows
occupation matrices file





MIP_CS2_AX

Cross
section lookup tables file





MIP_PI2_AX

A priori
pointing information file





deleted


AUX_ECF_AX

ECMWF
meteorological forecast data





AUX_ECA_AX

ECMWF
meteorological analysis data




Level
2 Data Products (Output)


MIP_NL__2P

Level 2 data product

9 M

100.6 min



MIP_NLE_2P

Level 2 NRT
/ Meteo product

1 M

100.6 min


Auxiliary data
The MIPAS Level 2 auxiliary
data cover the following products:

Processing parameters
data file

Microwindows data file

Spectroscopic data file

Initial guess profile
data file

Forward calculation
results file

Microwindows
occupation matrices file

Cross sections lookup
tables file

A priori pointing
information file
The data fields for these
products are presented in the following sections.
Processing parameters
data file
Product ID:
MIP_PS2_AX
This file contains a complete
list of input parameters, settings and
switches that control the execution of the
Level 2 processor.
Microwindows data file
Product ID:
MIP_MW2_AX
This file describes a set of
spectral intervals to be extracted from the
Level1B data for the subsequent retrieval
steps. For each spectral interval
(microwindow) the valid altitude range,
information on spectral range of continuum,
sensitivity and correlation parameters,
NLTE quantifiers, NESR, and contributions to
the systematic/random retrieval error is given.
Spectroscopic data file
Product ID:
MIP_ SP2_AX
This input data is used in
forward calculation for the simulation of
atmospheric spectra. Spectroscopic data are
provided for each microwindow as defined in
the microwindows data file.
Initial guess profile
data file
Product ID:
MIP_IG2_AX
This product includes initial
guess profiles of pressure, temperature, VMR
and continuum for different latitudes.
Forward calculation
results file
Product ID:
MIP_FM2_AX
This file contains initial
guess data copied from an initial guess data
file and the results of forward calculations
based on this data.
Microwindow occupation
matrices file
Product ID:
MIP_OM2_AX
This files contains
precomputed occupation matrices for p,T and
VMR retrievals for different latitude bands
and a fixed altitude grid. Also
occupation matrices to be used in cases of
missing or corrupted spectral bands are contained.
Cross sections lookup
table file
Product ID:
MIP_CS2_AX
This file contains absorption
cross section lookup tables for a set of microwindows.
A priori pointing information
Product ID:
MIP_PI2_AX
This file contains
precomputed externally provided pointing
covariance data.
ECMWF Meteo Products
The ECMWF Meteo Products
contain meteorological data (geopotential
profiles, relative humidity profiles,
temperature profiles and ozone profiles
(TBC), that is used to improve the initial
guess data in p,T and VMR retrievals. A
description of these products is given
in [RD ].
The S/W makes use of GRIB
encoded data files for geopotential height,
relative humidity profiles, temperature
profiles and ozone profiles. The I/F to the
GRIB files are provided by an ESTEC provided CFI.
Variations in Level 2
product size
The Level 2 product size
estimate corresponds to a nominal
measurement scenario, with 16sweep
measurements per elevation scan at high
spectral resolution, and a duration of ca.
71s per scan. Furthermore, it has been
assumed that ca. 10% of the available
measurement time is used for offset
calibration measurements (see also [RD ])
and that no other dedicated calibration
measurements are performed. The
corresponding measurement time available for
scene measurements will allow to complete
ca. 75 elevation scans per orbit.
It should be noted that the
number of retrieved quantities typically
varies linearly with the number of scene
measurements in an individual elevation scan
whereas the number of elevation scans per
orbit is roughly inversely proportional to
the number of height steps. As a
consequence, no significant variations are
expected in the size of the p, T and trace
gas VMR or concentration profile data
per orbit volume. However, the overall size
of the data products may vary significantly
for scenarios with different height step
numbers as the sizes of the covariance
matrices typically vary with the square of
the number of vertical grid points. In
addition, some variations in product
size will occur for different numbers of
elevation scans per orbit, each contributing
with a number of data set records in the
MDS fields and with various annotation data.
Moreover, some (minor) differences in
product size may be expected between
Level 2 NRT and Level 2 offline data sets,
depending on the specific algorithms used in
the two processing chains. These algorithms
may, for instance, use different
gridding schemes to represent the p, T and
VMR profile and covariance data.
