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    24-Apr-2014
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MERIS Product Handbook
MERIS Product Handbook
MERIS Product Handbook
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Glossary
Optics Glossary
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Water Vapour Glossary
Ocean Colour Glossary
Neural Network Glossary
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The MERIS instrument
MERIS Products and Algorithms
Auxiliary Files
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Auxiliary Datasets for Level 1b Processing
Summary of Auxiliary Datasets
Water Vapour Parameters Data File
Atmosphere Parameters Data File
Level 2 Control Parameters Data File
Aerosol Climatology Data File
Coastline/Land/Ocean Data File
Digital Roughness Model Data File
Radiometric Calibration Data File
MERIS Level 1b Control Parameters Data File
Digital Elevation Model
ECMWF Data Files
ENVISAT Orbit Data Files
Surface Confidence Map File
Land Vegetation Index Parameters Data File
Cloud Measurement Parameters Data File
Ocean II Parameters Data File
Ocean I Parameters Data File
Land Aerosols Parameters Data File
Ocean Aerosols Parameters Data File
MERIS Instrument Data File
MERIS-Specific Topics
Level 2 Products and Algorithms
Level 2 Products
Level 2 Geophysical Products
Annotation data set
Flags
Water Vapour products
Land products
Meris Terrestrial Chlorophyll Index
Meris Global Vegetation Index
Aerosol Angström Coefficient
Aerosol optical thickness
Reflectance
Cloud products
Cloud reflectance
Cloud Type
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Cloud albedo
Cloud optical thickness
Ocean products
The MERIS Aerosol Angström Coefficient
Aerosol optical thickness
Photosynthetically Active Radiation (PAR)
Yellow substance
Suspended matter
Algal Pigment Index II
Algal Pigment Index I
Normalized water leaving radiance / reflectance
Product description
Level 2 High-Level Organisation of Products
Full Resolution Geophysical Product
Extracted Vegetation Indices
Extracted Cloud Thickness and Water Vapour for Meteo Users
Extracted Cloud Thickness and Water Vapour
Reduced Resolution Geophysical Product
Level 2 Algorithms
Level 2 Accuracies
Level 2 Algorithm Description
MERIS Level 2 Product Formatting Algorithm
Measurement Data Sets
Annotation Data Set "Tie Points Location and corresponding Auxiliary Data"
Global Annotation Data Set - Scaling Factors
Annotation Data Set "Summary Product Quality"
Specific Product Header
Main Product Header
MERIS Land Pixels Processing
MERIS Bottom Of Atmosphere Vegetation Index (BOAVI) (step 2.8)
Atmospheric correction over land (step 2.6.23)
MERIS Top Of Atmosphere Vegetation Index (TOAVI) (step 2.2)
Water Processing
MERIS Ocean Colour Processing (step 2.9)
Clear water atmospheric corrections (step 2.6.9)
Turbid water screening and corrections (steps 2.6.8, 2.6.10)
Water Confidence Checks (step 2.6.5)
Cloud Processing
Cloud type processing (step 2.4.8)
Cloud Optical Thickness processing (step 2.4.3)
Cloud Albedo processing (step 2.4.1)
Total Water Vapour Retrieval
Water vapour polynomial (function)
Range checks (steps 2.3.0, 2.3.6)
Water vapour retrieval over clouds (step 2.3.3)
Water vapour retrieval over water surfaces (steps 2.3.2, 2.3.5)
Water vapour retrieval over land surfaces (step 2.3.1)
MERIS Pixel Identification
Land Identification (step 2.6.26) and Smile Effect Correction (step 2.1.6)
Gaseous absorption corrections (step 2.6.12)
Stratospheric Aerosol Correction (step 2.1.9)
Cloud screening (steps 2.1.2, 2.1.7, 2.1.8)
MERIS Pressure Processing
Atmospheric pressure confidence tests (steps 2.1.2)
Atmospheric pressure estimate (steps 2.1.5, 2.1.12)
MERIS Pre-processing
Pre processing step
Level 1b product check
Level 2 Physical Justification
Level 1b Products and Algorithms
Level 1b product definition
Browse Products
Level 1b Essential Product Confidence Data
Level 1b Engineering Quantities
Level 1b Accuracies
Level 1b High-Level Organisation of Products
Measurement Data Sets
Annotation Data Set "Product Quality"
Annotation Data Set "Tie Points Location and corresponding Auxiliary Data"
Global Annotation Data Set
Specific Product Header
Main Product Header
Full Resolution Geolocated and Calibration TOA Radiance
Reduced Resolution Geolocated and Calibration TOA Radiance
Level 1b Algorithms
Formatting
External Data Assimilation
Pixel Classification
Geolocation
Stray Light Correction
Radiometric Processing
Saturated Pixels
Source Data Packet Extraction
Level 0 Products
Product Evolution History
Definitions and Conventions
Notations and Conventions
Product Grid
Units
Organisation of Products
MERIS product data structure
File naming convention
Acquisition identification scheme
Product identification scheme
Latency, Throughput and Data Volume
Introduction
MERIS products overview
MERIS product types
Full and reduced resolutions
MERIS product processing levels
MERIS User Guide
Image gallery
How to Use MERIS Data
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BEAM
EnviView
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How to Choose MERIS Data
Summary of Applications vs. Products
Land
Atmosphere
Oceans
Introduction
Special Features of MERIS
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Principles of Measurement
Scientific Background
Mission Objectives
MERIS Level 3 products
Heritage
Geophysical Measurements
MERIS Product Handbook
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1.1.2 Scientific Background

1.1.2.1 Heritage

It is believed that the ocean carries between one third to one half of the heat transferred from the Earth's equator to its poles. In fact, it is the existence of this flux that keeps the mid-latitude regions of the Earth habitable. The ocean is the major sink for the constantly increasing human production of carbon dioxide and other "greenhouse gases." Analyses of cores from the ocean floor strongly suggest that during the distant past, when the Earth's climate was very different, the ocean circulation was also radically different.

Therefore, more information is urgently needed on oceanic circulation and changes and the oceanic carbon cycle. Present models of the ocean are inaccurate owing to uncertainties concerning the governing physics, chemistry, and biology, and also due to an inadequate ability to describe the instantaneous state of the system. ENVISAT offers the continuous, global observations of the oceans required to provide data sets for enhanced ocean modelling.

The first observations of ocean colour from space were carried out from 1978 to 1986 by the experimental Coastal Zone Colour Scanner (CZCS) aboard NASA's Nimbus-7 satellite. This instrument provided global and regional data sets which yielded a wealth of new information about the distribution and seasonal variability of primary productivity in oceans. During the period 1986 to 1996, the orderly development of ocean-colour science was hindered by the lack of an operational satellite sensor for the production of ocean-colour data. Although considerable energy was devoted to analysing the results of the then-defunct CZCS, there was no opportunity to conduct new studies in which observations from space could be matched with in situ data observations in near real time.

The picture began to improve in March 1996, when India launched the German sensor MOS (Modular Optoelectronic Scanner). Although this device does not provide global coverage, it was important as the first source of new ocean-colour data after a gap of ten years. In August 1996, Japan launched the Japanese sensor OCTS (Ocean Colour and Temperature Scanner) and the French sensor POLDER (POLarization and Directionality of the Earth’s Reflectance) on the ADEOS (ADvanced Earth Observation Satellite) mission. This was a very powerful combination, which operated until June 1997, until failure of the satellite's solar panel terminated the mission. In August 1997, the USA launched the SeaWiFS (Sea-viewing Wide Field-of-view Sensor), which has been in operation since September 1997. This instrument provides complete global coverage of the oceans about every two days if cloud free.

Over and above these sensors, a number of others have been launched (MISR, MODIS, OCI, OCM, OSMI, GLI, POLDER-2) other are planned for launch in the near future. Recent experience has emphasised that a certain controlled redundancy is essential if we are to enjoy an unbroken stream of ocean-colour data into the future.

IOCCG (International Ocean-Colour Coordinating Group) groups together information relative to the various missions and instruments enumerated here above (http://www.ioccg.org/sensors_ioccg.html).

Information may also be directly found at the following URLs:

MOS

http://ceos.cnes.fr:8100/cdrom-00b2/ceos1/satellit/mos/mos.htm

OCTS

http://www.eorc.nasda.go.jp/ADEOS/Project/Octs.html

POLDER

http://smsc.cnes.fr/POLDER/Fr/

ADEOS

http://kuroshio.eorc.jaxa.jp/ADEOS/index.html

SeaWiFS

http://oceancolor.gsfc.nasa.gov/SeaWiFS/

MISR

http://www-misr.jpl.nasa.gov/

MODIS

http://modis.gsfc.nasa.gov/

OCM

http://www.isro.org/programmes.htm

GLI

http://suzaku.eorc.jaxa.jp/GLI/index.html

POLDER-2

http://smsc.cnes.fr/POLDER/Fr/

1.1.2.2 MERIS Level 3 products

Level 3 demonstration products are available at http://envisat.esa.int/level3/ for each month or averaged per year (see figures below).

Figure 1.2 - Level 3 product - Chlorophyll-a case 1 – Annual average 2003.

Figure 1.3 - Level 3 product – Total column water vapour, clear sky – Annual average 2003.

Figure 1.4 - Level 3 product – Aerosol optical thickness at 865 nm – Annual average 2003.

Figure 1.5 - MERIS Level 3 Data – Year 2003

1.1.2.3 Mission Objectives

Ocean Mission

The principal contributions of MERIS data to the study of the upper layers of the ocean are:

· the estimation of photosynthetic potential by detection of phytoplankton (algae);

· the detection of yellow substance (dissolved organic material);

· the detection of suspended matter (particulates and river-borne sediments);

Apart from the above three major observable features, it should also be possible to detect plankton blooms (for example red tides) through their absorption feature near 520 nm. In addition, investigations of water quality, the monitoring of extended pollution areas, and topographic observations (such as coastal erosion), should also be possible.

Atmospheric Mission

The radiation balance of the Earth/atmosphere system is dominated by water vapour, CO2 and clouds, as well as being dependent on the presence of aerosol. However, the global monitoring of cloud properties and their processes, is not yet sufficiently accurate. MERIS is intended to help redress this balance by providing data on cloud top height and optical thickness, water vapour column content, and aerosol properties.

Land Mission

Questions related to global change include the role of terrestrial surfaces in climate dynamics and biogeochemical cycles. Spatial and temporal models of the biosphere are currently being developed to study the mechanics of such complex systems in order to predict their behaviour under changing environmental conditions. These models are based on physical and biophysical relationships, which need to be estimated on a regular basis using data from spaceborne sensors. Repetitive accurate physical measurements are necessary in order to quantify surface processes and to improve the understanding of vegetation seasonal dynamics and responses to environmental stress.

To achieve these mission goals, the different radiometric and geometric requirements imposed by the various objectives have to be satisfied. With the help of the ESA Science Advisory Group for MERIS, these requirements have been refined, taking into consideration the constraints imposed by a polar orbiting platform and the technical possibilities of an imaging spectrometer.

In advance of the launch of MERIS, the Ground Segment was designed and algorithms were developed for the interpretation of MERIS observations, and dedicated studies are ongoing to establish the means of determining the accuracy of MERIS data products. This is achieved in close cooperation with the European Expert Support Laboratories whose scientists are the main authors for all information estimation algorithms. Wherever possible, the underlying physical models are being evaluated using experience acquired before ENVISAT launch using data provided by airborne or shipborne campaigns and in situ measurements on specially equipped campaign sites.


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