MIPP

This is a presentation of:

python-mipp an introduction

mipp is a Meteorological Ingest-Processing Package (http://github.com/loerum/mipp).

It’s a Python library and it’s main task is to convert low level satellite data into a format understood by mpop (http://github.com/mraspaud/mpop). The primary purpose is to support Geostationary satellite data (level 1.5) but there is also support for the reading of some polar orbiting SAR data (see below).

A more sophisticated interface to satellite data objects is supported by mpop.

Currently it handles data from all current Meteosat Second Generation (MSG) satellites, Meteosat 7, GOES 11-15, MTSAT’s, and GOMS, all as retrieved via EUMETCast:

L-000-MTP___-MET7________-00_7_057E-PRO______-201002261600-__
L-000-MTP___-MET7________-00_7_057E-000001___-201002261600-C_
L-000-MTP___-MET7________-00_7_057E-000002___-201002261600-C_
L-000-MTP___-MET7________-00_7_057E-000003___-201002261600-C_
...
...
L-000-MSG2__-GOES11______-00_7_135W-PRO______-201002261600-__
L-000-MSG2__-GOES11______-00_7_135W-000001___-201002261600-C_
L-000-MSG2__-GOES11______-00_7_135W-000002___-201002261600-C_
L-000-MSG2__-GOES11______-00_7_135W-000003___-201002261600-C_
...
...

In addition mipp handles Synthetic Apperture Radar (SAR) data from Terrscan-X, Cosmo-Sky Med, and Radarsat 2.

mipp will:

  • Decompress XRIT files (if Eumetsat’s xRITDecompress is available). Software to uncompress HRIT/XRIT can be obtained from EUMETSAT (register and download the Public Wavelet Transform Decompression Library Software). Please be sure to set the environment variable XRIT_DECOMPRESS_PATH to point to the full path to the decompression software, e.g. /usr/bin/xRITDecompress. Also you can specify where the decompressed files should be stored after decompression, using the environment variable XRIT_DECOMPRESS_OUTDIR. If this variable is not set the decompressed files will be found in the same directory as the compressed ones.
  • Decode/strip-off (according to [CGMS], [MTP], [SGS]) XRIT headers and collect meta-data.
  • Catenate image data into a numpy-array.
    • if needed, convert 10 bit data to 16 bit
    • if a region is defined (by a slice or center, size), only read what is specified.

Note

  • MET7: not calibrated.
  • GOES, METSAT: calibration constants to Kelvin or Radiance (not Reflectance).

Code Layout

xrit.py

It knows about the genric HRIT/XRIT format

  • headers = read_headers(file_handle)
MTP.py

It knows about the specific format OpenMTP for MET7

  • mda = read_metadata(prologue, image_file)
SGS.py

It knows about the specific format Support Ground Segments for GOES and MTSAT

  • mda = read_metadata(prologue, image_files)
sat.py

It knows about satellites base on configurations files. It returns a slice-able object (see below).

  • image = load('met7', time_stamp, channel, mask=False, calibrated=True)
  • image = load_files(prologue, image_files, **kwarg)
slicer.py

It knows how to slice satellite images (return from load(...)). It returns meta-data and a numpy array.

  • mda, image_data = image[1300:1800,220:520]
  • mda, image_data = image(center, size)

Utilities

cfg.py

It knows how to read configuration files, describing satellites (see below).

convert.py

10 to 16 byte converter (uses a C extension)

bin_reader.py

It reads binary data (network byte order)

  • read_uint1(buf)
  • read_uint2(buf)
  • read_float4(buf)
  • ...
mda.py

A simple (anonymous) metadata reader and writer

geosnav.py

It will convert from/to pixel coordinates to/from geographical longitude, latitude coordinates.

Example definition of a satellite

# An item like:
#   name = value
# is read in python like:
#   try:
#       name = eval(value)
#   except:
#       name = str(value)
#

[satellite]
satname = 'meteosat'
number = '07'
instruments = ('mviri',)
projection = 'geos(57.0)'

[mviri-level2]
format = 'mipp'

[mviri-level1]
format = 'xrit/MTP'
dir = '/data/eumetcast/in'
filename = 'L-000-MTP___-MET7________-%(channel)s_057E-%(segment)s-%Y%m%d%H%M-__'

[mviri-1]
name = '00_7'
frequency = (0.5, 0.7, 0.9)
resolution = 2248.49
size = (5000, 5000)

[mviri-2]
name = '06_4'
frequency = (5.7, 6.4, 7.1)
resolution = 4496.98
size = (2500, 2500)

[mviri-3]
name = '11_5'
frequency = (10.5, 11.5, 12.5)
resolution = 4496.98
size = (2500, 2500)

Usage

import xrit

image = xrit.sat.load('meteosat07', datetime(2010, 2, 1, 10, 0), '00_7', mask=True)
mda, image_data = image(center=(50., 10.), size=(600, 500))
print mda
fname = './' + mda.product_name + '.dat'
print >>sys.stderr, 'Writing', fname
fp = open(fname, "wb")
image_data.tofile(fp)
fp.close()

Examples of the usage of some lower level tools

Here an example how to get the observation times (embedded in the ‘Image Segment Line Quality’ record) of each scanline in a segment:

import mipp.xrit.MSG

segfile = "/local_disk/data/MSG/HRIT/H-000-MSG3__-MSG3________-WV_062___-000002___-201311211300-__"
lineq = mipp.xrit.MSG.get_scanline_quality(segfile)
print lineq[0]

(465, datetime.datetime(2013, 11, 21, 13, 1, 48, 924000), 1, 1, 0)

A script, process_fsd

The script is intended for work on other geostationary data than the MSG (Meteosat) data, the so-called Foreign Satellite Data (FSD). That is e.g. GOES, MTSAT and COMS.

process_fsd --check-satellite <prologue-file>
    check if we handle this satellite

process_fsd --check [-l] <prologue-file>
    check if number of image segments are as planned
    -l, list corresponding image segment files

process_fsd --decompress [-o<output-dir>] <file> ... <file>
    decompress files to output-dir (default is working directory)
    -l, list decompressed files

process_fsd --metadata <prologue-file> <image-segment> ... <image-segment>
    print meta-data

process_fsd [-o<output-dir>] <prologue-file> <image-segment> ... <image-segment>
    it will binary dump image-data and ascii dump of meta-data)

[CGMS]LRIT/HRIT Global Specification; CGMS 03; Issue 2.6; 12 August 1999 “MSG Ground Segment LRIT/HRIT Mission Specific Implementation” EUM/MSG/SPE/057; Issue 6; 21 June 2006
[MTP]“The Meteosat Archive; Format Guide No. 1; Basic Imagery: OpenMTP Format”; EUM FG 1; Rev 2.1; April 2000
[SGS]“MSG Ground Segment LRIT/HRIT Mission Specific Implementation”; EUM/MSG/SPE/057; Issue 6; 21 June 2006

Calibration comments

MSG series

The calibration of the meteosat second generation satellites is done according to the Eumetsat documents [refl], [bt].

Reflectances

The visible and near infrared channels are calibrated according to the following formula:

r = R / I

where
  • r is the bidirectional reflectance factor
  • R is the measured radiance
  • I is the solar irradiance

R is derived from the xRIT data, and I is given in [refl].

In [refl] the additional following corrections are applied:
  • sun-earth distance correction
  • cosine of the solar zenith angle.
[refl](1, 2, 3) “Conversion from radiances to reflectances for SEVIRI warm channels” EUM/MET/TEN/12/0332
[bt]“The Conversion from Effective Radiances to Equivalent Brightness Temperatures” EUM/MET/TEN/11/0569

The mipp API

MIPP

exception mipp.CalibrationError
exception mipp.ConfigReaderError
exception mipp.DecodeError
exception mipp.MippError
exception mipp.NavigationError
exception mipp.NoFiles
exception mipp.ReaderError
exception mipp.UnknownSatellite
mipp.strptime()

string, format -> new datetime parsed from a string (like time.strptime()).

Metadata

class mipp.mda.Metadata
dont_eval = ('satnumber',)
ignore_attributes = ()
read(file_name)

Read until empty line, ‘EOH’ or ‘EOF’.

save(file_name)
token = ':'
mipp.mda.mslice(mda)

Configuration

mipp.cfg.read_config(satname, instrument='')

Logging

class mipp.log.NullHandler

Empty handler.

emit(record)

Record a message.

mipp.log.debug_on()

Turn debugging logging on.

mipp.log.get_logger(name)

Return logger with null handle

mipp.log.logging_off()

Turn logging off.

mipp.log.logging_on(level=None)

Turn logging on.

XRIT input layer

MSG

This module will read MSG level1.5 files, format documented in: ‘MSG Level 1.5 Image Data Format Description’, EUM/MSG/ICD/105, v5A, 22 August 2007

mipp.xrit.MSG.read_metadata(prologue, image_files, epilogue)

Selected items from the MSG prologue file.

GOMS

Read Electro L N1 HRIT files.

mipp.xrit.GOMS.read_epiheader(fp)
mipp.xrit.GOMS.read_metadata(prologue, image_files, epilogue)

Selected items from the Electro L N1 prolog file.

mipp.xrit.GOMS.read_proheader(fp)

MTP

This module will read satellit data files in OpenMTP format (eg. Meteosat-7 prolog file). Format described in: ‘The Meteosat Archive; Format Guide No. 1; Basic Imagery: OpenMTP Format’; EUM FG 1; Rev 2.1; April 2000

mipp.xrit.MTP.read_metadata(prologue, image_files)

Selected items from the Meteosat-7 prolog file.

SGS

This module will read satellit data files in SGS (Support Ground Segments) format (eg. GOES, MTSAT). Format described in: ‘MSG Ground Segment LRIT/HRIT Mission Specific Implementation’; EUM/MSG/SPE/057; Issue 6; 21 June 2006

mipp.xrit.SGS.read_metadata(prologue, image_files)

Selected items from the GOES image data files (not much information in prologue).

_xrit

This module will read LRIT/HRIT headers. Format described in: “LRIT/HRIT Global Specification”; CGMS 03; Issue 2.6; 12 August 1999 “MSG Ground Segment LRIT/HRIT Mission Specific Implementation”; EUM/MSG/SPE/057; Issue 6; 21 June 2006

mipp.xrit._xrit.read_prologue(file_name)
mipp.xrit._xrit.read_epilogue(file_name)
mipp.xrit._xrit.read_imagedata(file_name)
mipp.xrit._xrit.read_gts_message(file_name)
mipp.xrit._xrit.read_mpef(file_name)
mipp.xrit._xrit.read_mpef_clm(file_name)
mipp.xrit._xrit.decompress(infile, outdir='.')

Will decompress an XRIT data file and return the path to the decompressed file. It expect to find Eumetsat’s xRITDecompress through the environment variable XRIT_DECOMPRESS_PATH

mipp.xrit._xrit.list(file_name, dump_data=False)

bin_reader

mipp.xrit.bin_reader.read_cds_expanded_time(buf)
mipp.xrit.bin_reader.read_cds_time(buf)
mipp.xrit.bin_reader.read_cuc_time(buf, coarce, fine)
mipp.xrit.bin_reader.read_float4(buf)
mipp.xrit.bin_reader.read_float8(buf)
mipp.xrit.bin_reader.read_int2(buf)
mipp.xrit.bin_reader.read_int4(buf)
mipp.xrit.bin_reader.read_uint1(buf)
mipp.xrit.bin_reader.read_uint2(buf)
mipp.xrit.bin_reader.read_uint4(buf)
mipp.xrit.bin_reader.read_uint8(buf)

loader

class mipp.xrit.loader.ImageLoader(mda, image_files, mask=False, calibrate=False)
raw_slicing(item)

Raw slicing, no rotation of image.

convert

mipp.xrit.convert.dec10216(in_buffer)
mipp.xrit.convert.hrpt_dec10216(in_buffer)

sat

mipp.xrit.sat.load_meteosat07(time_stamp, channel, **kwarg)
mipp.xrit.sat.load_meteosat09(time_stamp, channel, **kwarg)
mipp.xrit.sat.load_goes11(time_stamp, channel, **kwarg)
mipp.xrit.sat.load_goes12(time_stamp, channel, **kwarg)
mipp.xrit.sat.load_goes13(time_stamp, channel, **kwarg)
mipp.xrit.sat.load_mtsat1r(time_stamp, channel, **kwarg)
mipp.xrit.sat.load_mtsat2(time_stamp, channel, **kwarg)
mipp.xrit.sat.load_electrol(time_stamp, channel, **kwarg)
mipp.xrit.sat.load_himawari8(time_stamp, channel, **kwarg)
mipp.xrit.sat.load(satname, time_stamp, channel, **kwarg)
mipp.xrit.sat.load_files(prologue, image_files, epilogue=None, **kwarg)

Metadata

class mipp.xrit.mda.Metadata
ignore_attributes = ('line_offset', 'first_pixel', 'coff', 'loff', 'image_data', 'boundaries')
token = ':'

XSAR input layer

Cosmo Sky-med

Radarsat-2

Terra-SAR X

sat

mipp.xsar.sat.load(satname, time_stamp, channel, **kwarg)

Metadata

class mipp.xsar.mda.Metadata
ignore_attributes = ('data', 'calibrate', 'tiepoints')
token = ':'

Indices and tables