METOP-AVHRR

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Main principles

The series of METOP satellites is constructed by the European Space Agency (ESA) and managed by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). METOP1 was launched in October 2006, METOP2 will follow in 2012 and the program is guaranteed to continue via METOP3 until the mid-twenties. METOP complements the European geostationary meteorological satellites (MSG, MTG), in the same way as NOAA does for GOES-East and -West. On the other hand, METOP also represents the European counterpart of the NOAA-platforms, because amongst the wide range of different sensors its payload also comprises the same AVHRR-instrument as installed on NOAA. In a joint European-US initiative, METOP assumes since 2007 the "morning orbit" (overpasses at around 08h|20h LST), while NOAA remains responsible for the "noon orbit" (14h|02h).

Contrary to NOAA, the METOP platform is well stabilized and protected against orbital drift. Moreover, it contains advanced on-board data storage capacities, so all the registered 1 km imagery of the last orbit is systematically transmitted to a single antenna in Svalbard (Norway) and further channelled to EUMETSAT (Germany). After some first but crucial adaptations, EUMETSAT distributes the "raw" data freely and in near-real time via its EUMETCAST broadcasting service. The resulting data stream is cut into segments of 3 minutes (1080 scanlines) which are distributed in near-real time via the EUMETCast broadcasting system in the form of EPS-formatted Level1B-files.

Just like NOAA, METOP-AVHRR still lacks on-board calibration standards for the shortwave bands (Red, NIR, SWIR). But EUMETSAT uses the same "vicarious" calibration methods for METOP as NASA does for NOAA. This approach guarantees an optimal agreement between the AVHRR measurements on both platforms.

EumetSatSystem.png


More information on the AVHRR sensor can be found in the section NOAA-AVHRR.


Input data for MCYFS

All the METOP EPS-files are ingested via its EUMETCast receiving antenna’s (one base, one spare) to produce near-global 10-daily composites using the same pre-processing chain as for NOAA-AVHRR. All bands of the METOP-AVHRR images are processed.


Processing of the imagery of METOP-AVHRR (since March 2007). The Level-1 products are acquired from EUMETSAT via the EUMETCAST broadcasting service.

Pre-processing

The pre-processing of the METOP-AVHRR images is done with the same processing chain as for NOAA-AVHRR. Nevertheless there are some differences, which are summarized here.

The input data for the AVHRR processing is less “raw” for METOP than those for NOAA-AVHRR, because EUMETSAT already applies a number of corrections to the data. These adaptations are: the raw observations are calibrated and transformed into top-of-atmosphere radiances (TOA), accurate “Lon/Lat-planes” are added with the geographical position of each pixel in the raw segment, and also a mask is added indicating the status of each observation (clear, cloud, snow). This simplifies the pre-processing considerably.

The following steps are briefly discussed in the sections below:

More details on the pre-processing can be found in the document (link to PDF) or on the MA10 website (see Links).

Import

All the METOP EPS-files are received through EUMETCast receiving antenna’s (one base, one spare). Then the relevant segments are selected, which are the daytime segments that include at least some land pixels. This selection implies that band3 is always SWIR. The images are in EARS-format (EUMETSAT Advanced Retransmission Service). After importing the data in the AVHRR-processing chain, the different small segments are stitched together. More information on the EUMETSAT EARS format can be found in the section Links.

Geometric corrections

Using the Lon/Lat-planes provided by EUMETSAT, the segment is remapped (nearest neighbour) to the Geographic Lon/Lat system with the same framing/resolution (1°/112) as used for SPOT-VEGETATION. The four angles of the registration (sun/view zenith/azimuth) are also computed in this stage using standard algorithms. Because of the high accuracy of the Lon/Lat-planes, chip matching is not applied.

Shortwave radiometric operations (RED, NIR, SWIR)

Radiometric calibration

The acquired images from EUMETCast are radiometrically calibrated.

Atmospheric correction

These TOA-radiances are then converted to surface reflectances by means of the SMAC algorithm for atmospheric correction (Rahman and Dedieu, 1994), using specific coefficients adapted to the METOP-bands (see Links). As to the distribution of the relevant atmospheric constituents, standard climatologies are used for ozone and aerosols, and six-hourly data from Meteo Services for water vapour.

NDVI

After this, a new image is created containing the Normalized Difference Vegetation Index NDVI.

Longwave radiometric corrections (TIR4, TIR5)

The TOA-radiances are first converted into brightness temperatures (inversion of Planck’s law) and then combined in an advanced split-window approach (Coll & Caselles) to retrieve the surface temperature of the land pixels (LST). The requested water vapour is again acquired from Meteo Services, while the emissivities are derived from NDVI. More information on the algorithms can be found on the page Land Surface Temperature (LST). The equations to derive the brightness temperatures can be found here.

Masking

The 8-bit status map indicates for each pixel the quality of the associated observation at three levels. The distinction between land and sea is made with the global land cover map GLC2000 (see Links), for some pixels no observations are available at all (“NoData” - due to errors, empty borders after the remapping, etc.), for the others the status (clear, cloud, snow) is extracted from the EUMETSAT mask.

Compositing

All layers are composited to 10-daily composites using a constrained maximum NDVI approach. The constraints used are:

  • Cloudy and snow observations are avoided
  • Viewing zenith angle
  • Solar zenith angle

As auxiliary data a Land/sea mask is needed. This is derived from GLC2000 map. Unlike for NOAA-AVHRR, the number of frost days is not computed for METOP-AVHRR.

As quality indicators, a number of additional images are created:

  • the number of good observations per compositing period
  • the time grid including segment ID
  • geolocation quality

The latter is realized by applying a chip matching procedure using fixed geolocation points for which the distortions are calculated. More information is provided on the page Quality of the geometric correction. A detailed description of the compositing method can be found in the section 10-daily composites. A new status map is created after the compositing. More information on the meaning of the bits can be found below.

StatusMapBitsCompositing.png

Post-processing

All algorithms and procedures of the post-processing are explained in detail in the concerned section. A short description of the METOP-AVHRR post-processing products is provided here.

Preliminary adaptations

Flagging

The information contained in the status mask, derived from the 10-daily compositing, is applied on all composite layers, such that the flag information is easily available for further processing. The procedure is described here.

Smoothing

Unlike for NOAA-AVHRR, the METOP-AVHRR data are not smoothed.

Preliminary adaptations

Vegetation indicators

fAPAR

The fraction of Absorbed Photosynthetically Active Radiation is derived from the 10-daily composites of RED and NIR reflectances using the method described by Weiss et al. (2010). The procedure is described in the section fAPAR.

DMP

Dry Matter Productivity (DMP) expresses the primary productivity (expressed in g DM/ha/day) in a 10-daily time step. The method uses non-smoothed fAPAR and meteo parameters (from Weather Monitoring), and is based on the Monteith equation explained in detail in the section DMP.

Time domain indicators and operations

Monthly composites

The non-smoothed vegetation indicators (NDVI, fAPAR, DMP and LST) are further aggregated into monthly composites. A different method than for the 10-daily composites is used, which is described here.

Differences to previous year

Two difference operators (absolute and relative) are used to calculate the difference between the current composite and the corresponding one from the previous year. The difference operators are discussed in the section Difference Images.

Historical year and Differences to historical year

The time series of METOP-AVHRR is not sufficiently long to calculate the Long Term Statistics. Consequently, the differences to the Historical Year cannot be calculated.

Time series analysis

No time series analysis products are produced from the data of METOP-AVHRR.

Databases with Regional Unmixed Means

The vegetation state indicators are also delivered in the form of Regional Unmixed Means (RUM) which are then added to the database of the Marsop viewer. Briefly described, RUM-values are derived by averaging (part of) the pixels of a certain administrative region which belong to a certain land cover class. In this way, the derived database can be ingested in a GIS-system. The method to derive the RUM-values is described in the section Databases with Regional Unmixed Means (RUM-values).

Products overview

The table below provides an overview of all 10-daily and monthly composite products that are generated for MCYFS from METOP-AVHRR input data.

Ten-daily and monthly composited data are generated in the form of images (I), quicklooks (Q) and databases of RUM-values (R).

OverviewMETOPAVHRRproducts.png

More information on the image format, headers and rescaling can be found in the section Images. The column V[D] refers to the filename suffix, and is explained in the section on Filename conventions.


Some examples of the output products are shown below.

OutputsMetopAvhrrPreprocessing.png

Notes on the table:

  • The data series starts in mid-March 2007 (dekad 8).
  • As a consequence, the DIFp-QLKs are only available from mid-March 2008 onwards.
  • Meaning of the D-suffixes for DIFp products: a/r = absolute/relative difference to same period in the previous year.