Introduction
Anthropogenic emissions change the composition and chemistry of the
atmosphere which, in turn, have an effect on dynamics. These changes are the
primary reasons for global climate warming, air pollution and ozone loss. All
these effects have a major impact on the living conditions on the Earth.
Understanding the evolution of atmospheric composition as well as the
coupling between climate and chemistry is a challenge which requires an
efficient global monitoring system of ozone and other trace gases,
ultraviolet radiation, primary pollutants and pre-cursors, together with the
distribution and properties of aerosols. With recent volcanic eruptions
posing hazards and economic losses to the European aviation business,
detection of volcanic sulfur dioxide and aerosols from satellites has become
an integral part of the remote sensing of the atmosphere. Satellite-based
observations form an important part of this global observing system as they
can provide global, three-dimensional coverage with a regular repeat cycle.
In this context, essential climate variables have been identified by the Global
Climate Observing System and include, in the atmospheric
composition domain, water vapour, anthropogenic greenhouse gases, ozone and
its precursors as well as aerosols and its precursors. The strategy for bringing
together ground-based, aircraft and satellite observations was created under
the IGACO (Integrated Global Atmospheric Chemistry Observations) program and
is presented in the IGACO-Ozone and UV Radiation Implementation Plan
. New environmental services are emerging within the
European Union flagship programme Copernicus (http://www.copernicus.eu)
on monitoring the Earth's environment using satellite and in situ
observations. Such emerging services requiring atmospheric composition data
include the Copernicus Climate Change Service
(http://climate.copernicus.eu/) and the Copernicus Atmosphere
Monitoring Service (http://atmosphere.copernicus.eu).
The Global Ozone Monitoring Experiment-2 (GOME-2) instrument is targeted to
fulfill these expectations. It is one of the new-generation of European nadir
looking instruments carried on the Metop platforms which are part of the
EUMETSAT Polar System (EPS). The GOME-2 instruments will continue the
long-term monitoring of atmospheric constituents started by the BUV
instrument onboard the Nimbus-4 satellite in 1970 . The
nadir measurements were continued by the SBUV and TOMS instruments
onboard NOAA satellites and ESA's GOME instrument on ERS-2
. Other instruments that have been used to
study atmospheric composition are for example the SCIAMACHY
, MIPAS and GOMOS
instruments onboard ESA's Envisat platform as well as
SAGE and SAGE II on NASA's platforms. Currently operational instruments
measuring atmospheric composition include the Dutch–Finnish OMI on board
NASA's Aura satellite, NASA's OMPS instrument on the Suomi-NPP satellite and
the Canadian OSIRIS onboard the Swedish Odin satellite .
The long-term monitoring will be continued by the next generation
instruments, the Dutch Tropomi onboard ESA's Sentinel 5-Precursor satellite
(launch in 2016), followed by the Copernicus Sentinel-5/UVNS instruments
onboard EPS-SG covering the time period 2020–2035. Furthermore, atmospheric
composition, especially for air-quality purposes, will be monitored with the
Sentinel-4 instruments onboard the geostationary MTG (Meteosat Third Generation) platforms.
As an operational mission, continuity of GOME-2 observations is ensured by
three identical instruments onboard three Metop platforms: A, B and C: The
first was launched in 2006, the second in 2012 and the last one will be
launched in 2018. The GOME-2 instruments will provide unique long-term data
sets of 15 years related to atmospheric composition and surface ultra violet
(UV) radiation using stable retrieval techniques. The GOME-2 is set to make a
significant contribution towards climate and atmospheric research, whilst
providing near-real-time data for use in air quality forecasting.
The GOME-2 instrument was designed and built at the time of the strongest
ozone depletion and thus, one of its main objectives is to monitor ozone,
ozone chemistry and the development of the ozone depletion. The ozone layer
is on track to recovery, states the WMO Scientific Assessment of Ozone
Depletion: 2014 . Thus, the scientific value of the
GOME-2 instrument measurements will also continue in the future.
The provision of an operational 24/7 service is also an important response to
the expectations outlined above. The Level 2 GOME-2 product development,
processing, dissemination and user services are the responsibility of the
Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring
(O3M SAF) project, which is an integral part of the distributed EUMETSAT
Application Ground Segment. The product development includes extensive
product reviews focusing on product requirements, product algorithms as well
as validation results. Furthermore, the ground segment processing chains have
been reviewed, keeping in mind the 24/7 requirement for processing and
dissemination. The production includes continuous quality control for the
processing and products.
The current L2 data cover a wide range of products, such as ozone (total and
tropospheric columns) and trace gas columns (total and tropospheric NO2,
total BrO, HCHO, H2O, SO2), vertical ozone profiles in high and low
spatial resolution, absorbing aerosol indices from the main as well as from
the polarisation channels (AAI, AAI-PMD), surface Lambertian-equivalent
reflectivity (LER) database, clear-sky and cloud-corrected UV indices and
surface UV fields with different weightings and NO2 and O3 photolysis
rates. In future, the products will include glyoxal and BrO as well as
special climate data sets of H2O and NO2 and absorbing aerosol height.
The O3M SAF started in 2004 with a development phase, and the first
operational Continuous Development and Operations Phase started in 2007. The
second phase started in 2012 and the third one will start in 2017. Besides
GOME-2 products, the O3M SAF, together with the EUMETSAT, will also provide
some new IASI products. The first IASI product, carbon monoxide, will be
released in early 2016. The project description as well as product
information, documentation, a helpdesk, user services and the dissemination
services are available from the project web site
(http://o3msaf.fmi.fi).
The purpose of this paper is to give an overall description of the GOME-2
activities and products provided by the O3M SAF project. The paper is
organised as follows: The instrument and ground segment are described in
Sects. 2 to 4, retrieved parameters with key validation summaries are
presented in Sect. 5 and the emerging products in Sect. 6.
L0 and L1 processing
The EUMETSAT central processing facility, located in Darmstadt, is
responsible for the processing of all GOME-2 data up to Level 1b (current
version 6.1.0). This processing is carried out within the Core Ground Segment
(CGS) by the GOME-2 Product Processing Facility (PPF) which converts raw
instrument data (Level 0 data stream) into time-stamped, geolocated, and
fully spectrally and radiometrically calibrated radiances or irradiances
(Level 1b data stream). The Level 1b data are delivered to the L2 processing
centres in near-real-time via EUMETCast. The details of GOME-2 instrument
design, calibration and L1 processing is described in .
Instruments measuring in the UV and the short-wave visible regions are known
to be sensitive to effects of contamination and to degradation of their
optical elements. The magnitude and impact of degradation on the instrument
signal level and therefore the quality of the calibrated Level-1 radiance
products varies significantly with both wavelength and instrument design. The
impact on overall signal throughput and therefore on signal-to-noise levels,
through contamination or degradation of optical elements, generally
increases towards shorter wavelengths. In addition, the impact on the
product quality is very much determined by the changes in reflectance,
relevant for many Level-2 retrievals, i.e. the difference in the way the
quality of the solar radiance measurements is affected in contrast to the
change in quality of the Earth radiance measurements. This difference in
degradation between the two optical light paths is often referred to as
differential degradation and is very much dependent on instrument design,
i.e. on the number and type of optical elements used which are different for
the two light paths (e.g. solar diffusers and other optical elements in the
instrument calibration units . Differential degradation may
also vary strongly with wavelength but, in contrast to absolute signal level
degradation, may exhibit significant spectral variation of different signs
and magnitudes over the full spectrum. This type of degradation may also vary
depending on viewing geometry. The latter is especially true for instruments
using scanning mirrors, such as GOME-1, GOME-2 and SCIAMACHY. Spectrally
varying, and viewing geometry dependent differential degradation may also
have an impact on the Level-2 retrievals, which are otherwise insensitive
to absolute signal-level broad-band biases and degradation, like DOAS-type
retrievals.
The GOME-2 instrument shows quite similar degradation overall compared to the
GOME-1 instrument , especially for the shortest
wavelengths between 240 and 300 nm, since the overall design, including the
design of the solar path and the on-board calibration unit, is very similar
for the two instruments. However, higher absolute degradation levels are
observed for GOME-2 in the region between 300 and 450 nm. This is true for
both GOME-2 instruments on Metop-A and B, which degrade very similarly in the
absolute signal level. While the degradation for the shortest wavelengths is
very likely to be due to the degradation of the throughput or the
reflectivity of optical surfaces, e.g. the scanning mirror, the most likely
candidate for the additional degradation observed in the region between 300
and 450 nm is contamination of optical surfaces across the whole optical
path by the outgassing of conformal coatings of detector read-out
electronics. These electronic boards have been moved closer to the detector
housing for the GOME-2 design in order to increase read-out efficiency with
respect to GOME-1. The overall spectral signature of differential degradation
is in turn more similar to that observed for GOME-1, with the largest
spectral signature evolving in the region around 450 to 500 nm. For GOME-1
this spectral signature is assumed to originate from a contamination layer
building up over time on the scanning mirror and is strongly scan angle
dependent. It evolved at shorter wavelengths than for GOME-2 but with a
similar temporal evolution and magnitude. For more details on GOME-2 radiance
and reflectance degradation we refer to .
The impact of GOME-2 instrument degradation on Level-2 product quality is
therefore very much dependent on the spectral region and the type of
retrieval methods chosen. The impact can range from no impact, an impact on
the fit-quality but no impact on the retrieved concentrations, to an impact
on the retrieved column or profile concentrations and their spatial scatter
or long-term variations. For further details we refer to two studies on the
impact of GOME-2 on Metop-A and GOME-2 on Metop-B instrument degradation on
Level-2 retrieval quality carried out by and
.
L2 processing and archiving services
The O3M SAF GOME-2 Level 2 products are developed and processed in a
distributed EUMETSAT ground segment with four processing centres and two
archives. The leading entity, the Finnish Meteorological Institute (FMI),
processes and archives the offline UV products as well as archives the
offline absorbing aerosol index and vertical ozone profile products and LER
data set processed at Royal Netherlands Meteorological Institute (KNMI). The
Deutsches Zentrum für Luft- und Raumfahrt (DLR) processes, archives and
disseminates total and tropospheric trace gas column products. The
NRT (near-real-time) products are disseminated via EUMETCast and the WMO Global
Telecommunication System network directly by the processing centres except
the NRT UV products which are processed by the Danish Meteorological
Institute (DMI) and distributed via http and FTP. The internal O3M SAF
product, assimilated GOME-2 total ozone analysis and forecast
, is based on O3M SAF GOME-2 total ozone and processed by
KNMI and used by DMI in NRT UV production. Furthermore, the internal cloud
products needed for trace gas column retrievals are processed by DLR.
The O3M SAF GOME-2 products undergo an extensive review process during the
development before they can be declared operational. The validation
activities are an important part of this review process. The validation is
mainly performed by the specialised validation entities: Aristotle University
of Thessaloniki, Belgian Institute for Space Aeronomy, German Weather
Service, Royal Meteorological Institute and Mariolopoulos – Kanaginis
Foundation. On top of that, online quality monitoring services have been
implemented by the processing and validation institutes so that the product
users may check the latest information regarding product quality. Online
quality monitoring uses external satellite and ground-based data and plotting
of trends and special parameters. The data delay ranges from a few minutes up to
a few days depending on what kind of method is used.
The main distribution channel for the NRT data is EUMETCast, utilising the
Eurobird-9 satellite. EUMETCast is a multi-service dissemination system based
on standard Digital Video Broadcast technology that uses commercial
telecommunication geostationary satellites to multi-cast files (data and
products) to a wide user community. The channel SAF-Europe transmits nearly
all products in HDF5 format and channel SAF-Africa transmits trace gases as
HDF5 and ozone profile products in BUFR (binary universal form for the representation of universal data) format. Furthermore, trace
gas column and ozone profile products are available in BUFR format via the
WMO Global Telecommunication System. The trace gas products may also be
obtained by using the FTP services and in the case of NRT UV via a dedicated
web page, FTP and Google Earth. The timeliness requirement for the NRT
products is 3 h from sensing.
The offline products as well as long-term data records are available in HDF5
format from the data archives hosted by FMI and DLR. Both of these archives
are accessible via a registration and data ordering service that is available
on the O3M SAF main web site (http://o3msaf.fmi.fi/). Furthermore, the
offline data are also available using the EUMETSAT Earth Observation Portal
(https://eoportal.eumetsat.int/). The timeliness requirement for the
offline products is 2 weeks from sensing. The data are free of charge.
However, the registration is a mandatory step when retrieving data for the
first time.
The daily updated example images of the O3M SAF products are available from
the O3M SAF web site. Furthermore, images of several O3M SAF GOME-2 products
are also available on the TEMIS scientific data portal (www.temis.nl),
where GOME-2 data can be compared and combined with data from GOME, SCIAMACHY
and OMI. The O3M SAF L2 data can be used with The Basic Envisat Atmospheric
Toolbox (BEAT) and VISAN (BEAT visualisation package). The interfaces and
description files are implemented into the BEAT by the S&T company.
Beside broadcast dissemination and FTP/http downloads, the O3M SAF provides
web mapping services for trace gas data in three distinct timeliness
categories: latest NRT data of today updated every 15 min, NRT data of
yesterday and mission-lifetime time series of daily offline data. These
services have been established and operated by DLR and
they comply to the OGC (Open Geospatial Consortium) standards Web Map Service for
visualisation and Web Coverage Service for download.
The O3M SAF GOME-2 offline archives have 236 registered users in 41 countries
(September 2015). They downloaded about 1.4 Tb of Level 2 data in June 2015
alone. At the same time, the amount of archived data was about 10 Tb with a
monthly increase of about 260–300 Gb. Furthermore, the project has 731
(September 2015) users together in 78 countries who have registered for the
EUMETCast NRT service. The number of users that receive the data via the WMO
Global Telecommunication System is unknown. Overall, the usage of the O3M SAF
GOME-2 data is extensive, and there are users in every continent.
All retrieval options with instructions together with the product
documentation, such as Algorithm Theoretical Basis Documents, validation
reports and product user manuals as well as ordering interfaces and links to
validation and online quality monitoring sites are available from the project
web site: http://o3msaf.fmi.fi.
O3M SAF GOME-2 L2 products available to users, a summary table
showing physical properties. HR O3 profile refers to high spatial
resolutiona ozone profile product whereas LR O3 profile refers
to low spatial resolutiona ozone profile product.
Product
Unit
Target accuracy
Spatial res.a
Type
Wavelengths
Total ozone
DU
4 %/ 6 %b
80 × 40 km
Column
325.0–335.0 nm
Tropical trop. ozone
DU
25 %
1.25∘ × 2.5∘
Column
325.0–335.0 nm
Global trop. ozone
DU
20 %
80 × 40 km
265.0–330.0 nm
HR O3 profile
DU
15 %/30 %c
80 × 40 km
Profiled
265.0–330.0 nm
LR O3 profile
DU
15 %/30 %c
640 × 40 kme
Profiled
265.0–330.0 nm
Total NO2
molec cm-2
3–5 × 1014f
80 × 40 km
Column
425.0-450.0 nm
Trop. NO2
molec cm-2
30 %f
80 × 40 km
Column
425.0–450.0 nm
Total SO2
DU
50 %g
80 × 40 km
Column
315.0–326.0 nm
Total BrO
molec cm-2
30 %
80 × 40 km
Column
332.0–359.0 nm
Total HCHO
molec cm-2
50 %
80 × 40 km
Column
328.5–346.0 nm
Total H2O
kg m-2
10 %
80 × 40 km
Column
614.0–683.2 nm
AAI
unitless
0.5
80 × 40 km
Index
340, 380 nm
AAI from PMD
unitless
0.5
10 × 40 km
Index
338, 381 nm
UV index
unitless
20 %
0.5∘ × 0.5∘
Index
UV daily doseh
kJ m-2
20 %
0.5∘ × 0.5∘
Surface
UV max. doseh
mW m-2
20 %
0.5∘ × 0.5∘
Surface
NO2 photolysis
1/s
20 %
0.5∘ × 0.5∘
Surface
O3 photolysis
1/s
20 %
0.5∘ × 0.5∘
Surface
UVI clear
W m-2
20 %
0.25∘ × 0.25∘
Index
UVI cloud-corrected
W m-2
20 %
0.25∘ × 0.25∘
Index
LERi (MSC PMD)
unitless
0.04
0.5∘ × 0.5∘
Index
325–772 nm, 325–799 nm
Emerging products
Tropospheric BrO
molec cm-2
30 %
80 × 40 km
Column
Glyoxal
molec cm-2
50 %
80 × 40 km
Column
OClO
molec cm-2
50 %
80 × 40 km
Column
Monthly mean H2O
kg m-2
Column
Monthly mean NO2
molec cm-2
Column
Auxiliary products
Cloud fraction
unitless
80 × 40 km
Fraction
300–800 nm
Cloud pressure
hPa
80 × 40 km
Pressure
758–771 nm
Cloud albedo
unitless
80 × 40 km
Albedo
758–771 nm
Assimilated total O3
DU
80 × 40 km
Column
a Spatial resolution: nominal MSC (main science
channels) pixel size for GOME-2 is 80 × 40 km. The GOME-2B
instrument is operated with this resolution, whereas GOME-2A has been
providing resolution of 40 × 40 km since July 2012. For PMD
(polarisation measurement device) the corresponding resolutions are
10 × 40 and 5 × 40 km. Only the GOME-2B resolution is
indicated in this column. b 4 % for SZA (solar zenith angle) < 80∘ and
6 % for SZA > 80∘. c 15 % for stratosphere and
30 % for troposphere d ozone profiles up to 0.001 hPa,
40 layers. e 80 × 40 ground pixel resolution follows the
integration time of the 1B channel, whereas 640 × 40 integration
time follows UV wavelengths. f Accuracy of total NO2 in
unpolluted conditions and tropospheric NO2 in polluted conditions.
g SZA < 70∘. h Offline UV product has the
following weighting functions: erythemal (CIE), plant response, DNA damage,
UVA, UVB, D-vitamin. i Lambertian equivalent reflectivity.
Resolution for MSC (main science channels) product is
1∘ × 1∘ and for PMD product
0.5∘ × 0.5∘.
Operational O3M SAF GOME-2 products
The currently operational and available products are shown in Tables 1 and 2.
The following sub-chapters provide an overview of those products with
validation examples. Most of the products are available both from the GOME-2A
and GOME-2B instruments. By using both instruments together, global coverage
may be obtained in 1 day. Merged L3 products will be available during the
next phase, starting in 2017.
The original accuracy targets for Level 2 products were defined in the
EUMETSAT Polar System End-User Requirements Document. The requirements
specified in this document were established in coordination with user
representatives. Each product is subject to a requirements review before the
product can be implemented and declared operational. The objective is to
recheck the accuracy requirements together with the availability and format
requirements. Thus, the accuracy requirements for operational products
mentioned in Table 1 reflect the evolving user needs as well as improved
retrieval algorithms.
O3M SAF GOME-2 L2 products available to users, a summary table
showing additional information. HR O3 profile refers to high spatial
resolution ozone profile product, whereas LR O3 profile refers to low
spatial resolution ozone profile product.
Product
Insta
Processor vers.
Disseminationb
Main application areas
Total ozone
A, B
4.7
NRT, Ol
Ozone chemistry, NWP
Tropical trop. ozone
A, B
4.8
Ol
Air quality
Global trop. ozone
A, B
1.12
NRT, Ol
Air quality
HR O3 profile
A, B
1.12
NRT, Ol
Ozone chemistry, protocol monitoring
LR O3 profile
A, B
1.12
NRT, Ol
Ozone chemistry, protocol monitoring
Total NO2
A, B
4.7
NRT, Ol
Ozone chemistry, climate change
Trop. NO2
A, B
4.7
NRT, Ol
Air quality
Total SO2
A, B
4.7
NRT, Ol
Aviation safety, emission monitoring
Total BrO
A, B
4.7
NRT, Ol
Ozone chemistry
Total HCHO
A, B
4.7
NRT, Ol
Air quality, climate change
Total H2O
A, B
4.7
NRT, Ol
Climate change
AAI
A, B
1.28
NRT, Ol
Aviation safety, RTM
AAI from PMD
A, B
1.28
NRT, Ol
Aviation safety, RTM
UV index
B
1.20
Ol
Health research, monitoring
UV daily dosec
B
1.20
Ol
Health research, monitoring
UV max. dosec
B
1.20
Ol
Health research, monitoring
NO2 photolysis
B
1.20
Ol
Health research, air quality
O3 photolysis
B
1.20
Ol
Health research, air quality
UVI clear
B
3.3
NRT
Health warnings
UVI cloud-corrected
B
3.3
NRT
Health warnings
LER (MSC, PMD)
A
1.0
DR
RTM
Emerging products
Tropospheric BrO
A, B
Ol
Health research, air quality
Glyoxal
A, B
Ol
Health research, air quality
OClO
A, B
NRT, Ol
Health research, air quality
Monthly mean H2O
A, B
Ol
Climate studies
Monthly mean NO2
A, B
Ol
Climate studies
Auxiliary products
Cloud fraction
A, B
NRT, Ol
Total column products
Cloud pressure
A, B
NRT, Ol
Total column products
Cloud albedo
A, B
NRT, Ol
Total column products
Cloud assimilated total O3
A, B
NRT
NRT UV
a Instrument: A refers to GOME-2A and B to GOME-2B.
b NRT (near-real-time), Ol (offline), DR (data record).
c Offline UV product has the following weighting functions:
erythemal (CIE), plant response, DNA damage, UVA, UVB, D-vitamin.
Total ozone column
Total ozone columns are retrieved from GOME-2 (ir)radiance spectra using the
DOAS method in the wavelength region 325–335 nm (Huggins
absorption band). The fitting includes an effective temperature for the ozone
absorption, an NO2 absorption cross-section, and scaling factors for
interference due to the Ring effect. The retrieved ozone slant column
densities are converted to vertical columns using an iterative air mass
factor. Furthermore, a cloud correction is applied in the vertical column
retrieval for (partially) cloudy scenes. Cloud parameters are retrieved from
GOME-2 using the OCRA and ROCINN algorithms .
OCRA provides the cloud fraction using the PMD measurements and ROCINN
provides cloud height and cloud albedo using the oxygen A-band measurements.
The cloud parameters retrieved from OCRA and ROCINN have been validated and
verified by comparing with other measurements and other
cloud algorithms . To reduce the impact of the instrument
degradation, the degradation correction factors have been implemented in both
the OCRA and ROCINN algorithms . Note that the OCRA and
ROCINN cloud parameters are also used for the cloud correction of the other
minor trace gas column products (NO2, BrO, HCHO, SO2 and water vapour)
as well as for the determination of the tropical tropospheric ozone column
product.
A detailed description of the GOME-2 total ozone column algorithm can be
found in , and .
Figure shows one example of the total ozone product:
The Antarctic ozone hole for 2 October 2014 measured from GOME-2A and GOME-2B
when the minimum total ozone column reached was around 120 DU.
Total ozone map for 2 October 2014 based on data from GOME-2A and
GOME-2B instruments.
The total ozone NRT and offline products from GOME-2A and GOME-2B are
periodically validated and routinely monitored for their quality. For this
purpose, a dedicated web-portal is available at
http://lap3.physics.auth.gr/eumetsat. In this portal, online
comparisons with quality assured ground-based total ozone measurements are
available. The reference data for the offline total ozone comparisons are
archived Brewer, Dobson and M-124 total ozone data; these are deposited at
the World Ozone and UV Data Centre (http://www.woudc.org) and are
employed after being thoroughly controlled for their quality. These online
comparisons are routinely and automatically updated every month. For the
near-real-time total ozone comparisons, near-real time Brewer and Dobson
total ozone data, deposited in the World Meteorological Organisation Ozone
Mapping Center (http://lap.physics.auth.gr/ozonemaps2/), are downloaded
and compared to the GOME-2A and GOME-2B near-real-time observations on a
weekly basis.
Monthly mean differences between GOME-2A (upper) and GOME-2B (lower)
vs. ground-based total ozone columns; Brewer comparisons in the left
column and Dobson comparisons in the right.
Comparison results for the GOME-2A offline data for the period 2007–2011,
processed with GDP4.4 , have been previously presented by
, indicating that GOME-2 total ozone data agree at the
1 % level with the ground-based measurements as well as other satellite
instrument data sets, showing a small dependency on solar zenith angle for
angles less than 75∘ and almost no dependency on cloud fraction and
cloud top pressure. Results from an initial validation of the GOME-2B offline
data, processed with GDP4.7 for the year 2013, have been presented in
. These results show excellent consistency with coincident
GOME-2A total ozone measurements. In Fig. we present an
updated time series of the differences between GOME-2A and GOME-2B vs.
Dobson and Brewer total ozone data, averaged over the Northern Hemisphere for
the period 2007–2014. This confirms the consistency between the
two satellite data sets as well as their long-term stability. The use of BDM
(Brion, Daumont and Malicet) absorption cross sections
in the GDP4.7 version of the algorithm explains the overestimation of GOME-2
data, compared with the results presented earlier by .
Both satellites are consistent over the Northern Hemisphere with negligible
latitudinal dependence, while over the Southern Hemisphere there is a
systematic difference of 1 % between the two satellite instruments.
A wide community is using the GOME-2 total ozone product provided by the O3M
SAF. Since October 2013, total ozone column data have been assimilated in the
Copernicus atmosphere core service project CAMS (Monitoring Atmospheric
Composition and Climate) NRT system. The GOME-2 ozone columns are also used
in the Integrated Forecast System (IFS) of the European Centre for
Medium-Range Weather Forecasts (ECMWF). Furthermore, the GOME-2 total ozone
data were used in the WMO/UNEP Scientific Assessment of Ozone Depletion
reports of 2010 and 2014. Other users are WMO World Ozone and Ultraviolet
Radiation Data Centre, WMO Ozone Mapping Centre, DLR World Data Center for
Remote Sensing of the Atmosphere as well as ESA Tropospheric Emission Monitoring
Internet Service (TEMIS).
Vertical ozone profiles
The NRT and offline vertical ozone profile product
uses reflectance measurements from 260 to 330 nm and iteratively finds the
ozone profile best matching the original radiance measurements using optimal
estimation. The ozone profiles are given as partial ozone columns in DU in 40
logarithmically spaced layers from the surface up to 0.001 hPa. For
(partially) cloudy scenes, the retrieved cloud pressure replaces the nearest
pressure level. The cloud pressure is retrieved by the FRESCO algorithm from
the O2 A-band measurement of GOME-2 . GOME-2 has nominal
spatial resolution of 80 km × 40 km, but for the shortest UV
wavelengths the integration time is 8 times longer. The initial O3M SAF ozone
profile product was provided at a spatial resolution of
640 km × 40 km (coarse resolution, CR) but has since been improved
to the 80 km × 40 km resolution using radiance measurements from a
mix of integration times. As an example of the ozone profile product from
GOME-2B, Fig. shows a vertical cross section along
an orbit from north to south. The measurements end in a location over
Antarctica where the Southern Hemisphere spring ozone hole is present,
indicated by low ozone values in the stratosphere.
Vertical ozone profiles from GOME-2B, as a vertical cross section
along an orbit from north to south. The measurements end in a location over
the Antarctica where the Southern Hemisphere spring ozone hole is present,
indicated by low ozone values in the stratosphere.
The ozone profile products are validated with ozone sonde data as well as
with lidar and microwave measurements. The ozone sonde data are used in
particular for the tropospheric and the lower stratospheric part up to about
30 km, whereas lidar and microwave validation focus on the stratosphere from
15 to 55 km. The ozone sonde data come from the World Ozone and Ultraviolet
Radiation Data Center (WOUDC), the SHADOZ (Southern Hemisphere ADditional OZonesondes)
network, NDACC (Network for the Detection of Atmospheric Composition Change)
and the NILU's Atmospheric Database for Interactive Retrieval (NADIR) at
Norsk Institutt for Luftforskning (NILU) (http://www.nilu.no/nadir/).
The NDACC network also provides the data of four lidar and five microwave stations.
These are the only NDACC stations which deliver ozone profile data regularly
and with a comparatively small delay. A comprehensive description of
the ground-based validation methods and results for the upper stratosphere
will soon be published elsewhere.
The validation and quality monitoring is done by trending of monthly mean
values and by direct comparison of satellite and ground-based data. The
regular validation uses ground-based ozone profile measurements and considers
the dependence of the deviations between satellite and ground-based profiles
on total ozone, scan angle, solar zenith angle, cloud fraction and distance
in space and time. All comparisons are performed for the high- and coarse-resolution satellite profiles, respectively. The complete set of results is
regularly available at the O3M SAF validation internet site.
Overall target values are met in the troposphere (30 %) and the lower
stratosphere (15 %), not taking into account the UTLS zone, which shows
more elevated relative differences, which cannot be assigned to the
troposphere or to the stratosphere. However, GOME-2 shows a clear
underestimation of ozone concentrations above about 30 km
(Fig. ). The difference to ground-based data increases
with altitude, amounting up to about 25 % at 55 km for GOME-2B and up to
about 55 % for GOME-2A, depending to some degree on ground-based station
and instrument. Furthermore, a satellite to satellite comparison with the
Global Ozone Monitoring by Occultation of Stars (GOMOS), Optical Spectrograph
and Infrared Imager System (OSIRIS) and Microwave Limb Sounder (MLS) confirms
these conclusions ().
Relative differences between GOME-2A and GOME-2B ozone profiles (CR)
and corresponding ozone sonde, lidar and microwave measurements. Shown is an
average over all data from the years 2013 and 2014 for northern midlatitude
stations. Up to 30 km altitude, all available ozone sondes are used for
comparison, and above it is an average of two lidar (Hohenpeissenberg and
Haute Provence) and two microwave stations (Bern and Payerne). The black
(GOME-2A) and red (GOME-2B) curves are raw data, while the blue (GOME-2A) and
green (GOME-2B) curves show data smoothed with the GOME-2 averaging kernel
and a priori information. The red vertical lines mark the ± sigma range
of deviations.
Time series of the relative differences between GOME-2 ozone
profiles (CR) and corresponding ground-based measurements. Shown are monthly
mean values and their standard deviations. The data are averaged over all
available stations at northern midlatitudes. At the three lower altitude
layers, ozone sondes are used for comparison, and at the higher levels, two
lidar (Hohenpeissenberg and Haute Provence) and two microwave stations (Bern
and Payerne). The blue curves are for GOME-2A and the red ones for GOME-2B.
All data are smoothed, by applying the GOME-2 averaging kernel and a priori
information.
Degradation of the GOME-2A instrument is clearly visible in the ozone profile
products as a decrease in retrieved ozone concentrations at most altitudes
over the years of the mission (Fig. ). Especially for
the higher stratospheric part (above 30 km), such a decrease could be
identified. For the coarse-resolution profiles, this trend can be as large as
75 % per decade in the upper stratosphere above 30 km. GOME-2B data (red
lines in Fig. ) do not yet show this effect.
Using a comparison between measured and expected/simulated spectra, a
multiplicative bias factor can be established with which the measurement
needs to be corrected. Figure is an example of the bias
factor for 267 and 329 nm for GOME-2A. Clearly visible is that there was an
initial bias at 267 nm of roughly 8 %, increasing to 60 % in 2013 and
that while the bias at 329 nm was initially minimal it has increased to
about 10 % in 2013. The implementation of this degradation correction in
the operational retrieval will be an important part of the algorithm
development in the near future.
Degradation of the GOME-2A instrument, expressed as the ratio
between the measured and simulated spectra (multiplicative bias factor) for
267 and 329 nm. The blue lines indicate the weekly data points, the green
lines are a fitted function (fourier + polynomial), and the red line is a
long-term polynomial fit.
Total and tropospheric NO2 column
NO2 plays a key role in air quality and atmospheric chemistry. It is an
air pollutant affecting human health and ecosystems, and an important ozone
precursor. In addition, NO2 is involved in ozone depletion processes in
the stratosphere and it is important for climate change studies, because of
the indirect effect on the global climate. Total NO2 columns, including a
tropospheric and stratospheric component, are retrieved with the DOAS method
in the VIS wavelength region 425–450 nm . Tropospheric
NO2 columns are obtained from the total columns by estimating the
stratospheric content and removing it from the total amount. Several methods
exist for the stratosphere estimation: ,
and . A spatial filtering approach
is used by masking potentially polluted areas and then
applying a low-pass filter in the zonal direction . After
the stratosphere–troposphere separation, the tropospheric NO2 column is
calculated using tropospheric air mass factors based on monthly average
NO2 profiles from the MOZART-2 chemistry transport model, and a cloud
correction for partially cloudy conditions is applied (see also Sect. 5.1).
Figure shows the average tropospheric NO2 columns over
East Asia measured by GOME-2A for the period 2007–2013. The world's largest
area with high NO2 pollution is found above eastern China, which is a
result of China's spectacular economic growth during the last decade,
accompanied by a strong increase in emissions of air pollutants. Another
remarkable feature visible in Fig. is the enhanced
tropospheric NO2 along shipping lanes in the Bay of Bengal and the South
China Sea, see also .
Average tropospheric NO2 columns over East Asia measured by
GOME-2 for 2007–2013 (Logarithmic colour scale).
The near-real-time and offline total and tropospheric NO2 products are
regularly validated and monitored by comparing to (1) data sets acquired by
other satellites (GOME, SCIAMACHY, OMI) and GOME-2 retrievals performed with
other processors (such as the TEMIS system, http://www.temis.nl) and
(2) ground-based reference measurements acquired by UV-visible DOAS zenith
sky looking spectrometers performing network operation in the framework of
the Network for the Detection of Atmospheric Composition Change (NDACC,
http://ndacc.org) and zenith-sky looking spectrometers for the NO2
stratospheric column and multi-axis (MAX-DOAS) spectrometers for the NO2
tropospheric column. Detailed validation results for GOME-2A can be found in
. The results for the validation of GOME-2A and B NO2
columns can be found in and on the O3M SAF BIRA
validation pages (http://cdop.aeronomie.be/validation/valid-results).
The step by-step verification of the operational GOME-2B product against
GOME-2A, and GOME-2A and B alternative retrievals performed in
, has highlighted a global underestimation by GOME- 2B
slant columns of 1 × 1015 molec cm-2 with respect to
GOME-2A, which translates into a bias of 0.15 × 1015 and
0.4 × 1015 molec cm-2 in total and stratospheric
columns. GOME-2B tropospheric column data underestimate GOME-2A by less than
0.5 × 1015 molec cm-2 in moderately polluted conditions,
while larger differences (up to 8 × 1015 molec cm-2)
occur in polluted regions. The latter can be explained by the local time
difference between GOME-2A and GOME-2B overpasses and the associated impact
of the variability in NO2 content and cloud cover on the comparison
results. Figure presents, from pole to pole, the median
bias and spread for total NO2 between GOME-2A/B total NO2 and
correlative ground-based measurements acquired by 25 zenith-sky DOAS
instruments. Prior to the comparisons, GOME-2/NDACC co-located data are
filtered to avoid GOME-2 data contaminated by tropospheric pollution, and
corrected for photochemical diurnal effects (arising from solar local time
differences between NDACC and GOME-2 observations). Only the latest,
consolidated versions of the NDACC data are considered for
Fig. (no NRT data), and only the GOME-2 forward pixels (no
backward pixels) are considered. Figure illustrates the
good agreement between the different stratospheric NO2 data sets, usually
within 0.1–0.5 × 1014 molec cm-2, a value close to the
combined uncertainty of the comparison method and within the target
accuracies for total NO2 of 3–5 × 1014 molec cm-2 in
unpolluted conditions (Table 1). Nevertheless, the slight bias between
GOME-2A and GOME-2B data is also seen in this figure with GOME-2B,
underestimating GOME-2A by about 1–3 × 1014 molec cm-2
(bias propagated from the retrieval of slant column densities), as well as
another slight bias of 2–5 × 1014 molec cm-2 between
comparison results averaged over the Northern Hemisphere and those averaged
over the Southern Hemisphere.
Example of total (stratospheric) NO2 validation: Pole-to-pole
structure of the median absolute difference between NO2 column data
retrieved from GOME-2A/B (GDP 4.7) and from 25 ground-based zenith-sky DOAS
spectrometers archiving consolidated data to NDACC DHF, calculated over
2007–2014 for GOME-2A and 2013–2014 for GOME-2B.
Example of tropospheric NO2 validation: (a) maps of
tropospheric NO2 from GOME-2 and the location of three BIRA-IASB MAXDOAS
stations: OHP, Uccle and Xianghe. (b) The correlation plots are
given for each station for GOME-2A (OHP from June 2007 to June 2014, Uccle
from May 2011 to May 2014, Beijing from June 2008 to April 2009, Xianghe from
March 2010 to December 2013), (c) a time series of MAXDOAS, GOME-2A
and GOME-2B is given for OHP station, and a close-up of the 2012–2014 period
is given in (d).
Figure presents some examples of validation results for
tropospheric NO2 GOME-2 columns based on BIRA-IASB MAXDOAS stations. As
can be seen in Fig. a, very different conditions of
tropospheric NO2 are sampled at the four stations, from clean/remote
region (OHP, south of France), city (Uccle, Belgium) and heavily polluted
region in Beijing and Xianghe in China (just outside the city, at 60 km
south-east of Beijing). Figure b presents the scatter
plots of the monthly means at the four stations. Good correlations between
GOME-2A and the ground-based MAXDOAS data are obtained, both in terms of
correlation coefficients R (ranging from 0.65 in Uccle to 0.92 in Beijing)
and slopes of the regression analysis S, with values ∼ 0.8 at
Xianghe, slightly smaller in Uccle and OHP (∼ 0.6) and with larger
differences (S = 0.47) in Beijing. The impact of the location of the
ground-based instrument can be seen when comparing the results between
Beijing and Xianghe, that are only 60 km apart: in the first case the
MAXDOAS is situated in the centre of the Beijing megacity and then it has
been moved to the Xianghe site outside the city, in a zone more
representative of what is seen by a satellite pixel. This large differences
in Beijing compared to results in Xianghe are due to a representation error
for stations in urban locations, affected by local pollution episodes, not
seen in the averaged GOME-2 pixel. This representation error has been also
highlighted in larger scale comparisons started in for
total, stratospheric and tropospheric GOME-2 NO2 columns compared to
DirectSun, ZenithSky and MAXDOAS data sets. Figure c
presents an example of the time series of GOME-2A and B above OHP and its
comparisons to ground-based MAXDOAS tropospheric NO2 data, extending the
results presented in . The pollution episodes are captured
well by both GOME-2 instruments and the comparisons of monthly averaged
columns show consistent seasonal variations, with high NO2 in winter and
low NO2 in summer.
The GOME-2 tropospheric NO2 columns are used in the CAMS NRT system and in
support of regional (e.g. European) air quality models, for example. The
NO2 products from the O3M-SAF are also used by a number of research
institutes for various applications such as verification of emissions,
investigation of regional and global trends, and assessment of
chemistry-transport models.
Total HCHO column
Atmospheric formaldehyde (HCHO) is an intermediate product common to the
degradation of many volatile organic compounds, and therefore it is a central
component of tropospheric chemistry. While the global formaldehyde background
is due to methane oxidation, emissions of non-methane volatile organic
compounds (NMVOCs) from biogenic, biomass burning and anthropogenic
continental sources result in important and localised enhancements of the
HCHO concentration. Improving our knowledge of NMVOC emissions is essential
for a better understanding of the processes that control the production and
the evolution of tropospheric ozone, a key actor in air quality and climate
change, but also of the hydroxyl radical OH, the main cleansing agent of our
troposphere. As the lifetime of HCHO is typically a few hours, enhanced
concentrations serve as tracers for reactive NMVOC emissions
(Fig. ). Moreover, HCHO satellite observations are used in
combination with tropospheric chemistry transport models to constrain NMVOC
emission inventories in so-called top-down inversion approaches. Satellite
HCHO and NO2 observations are also combined to estimate VOC / NOx
ratios, and thereby the local chemical regime of tropospheric ozone
production. The HCHO retrieval is based on the DOAS technique and follows the
developments published in . Common settings are used for
GOME-2A and GOME-2B retrievals. The HCHO slant column inversion is performed
in the UV wavelength range 328.5–346 nm, and includes a post-treatment for
systematic biases based on a latitude dependent offset correction.
Tropospheric HCHO vertical columns are calculated using air mass factors that
depend on the solar and viewing geometries, the surface albedo, cloud
fraction and cloud top height (OCRA/ROCINN product), and the HCHO profile
shape which is derived from three-dimensional chemical-transport model
simulations obtained using the IMAGES model .
Averaged tropospheric HCHO columns for 2013 as measured by GOME-2B.
For the validation of the HCHO columns, a step-by-step verification of the
operational product against the reference scientific GOME-2 HCHO retrieval
algorithm has been performed in and
confirms the validity of the target accuracy of 50 % in polluted conditions
(Table 1). An example of this verification is given in Fig.
for two different emissions regions: northern China and Amazonia. GOME-2B
HCHO slant columns, fit residuals, and scatter are comparable to those
obtained from GOME-2A spectra at the beginning of the mission in 2007, both
for the operational and scientific products. The effect of Metop-A
degradation (increased noise caused by decreased throughput, see
) is clearly visible in Fig. , with the
DOAS fit RMS increase with time for both operational and scientific products.
Differences between operational and scientific data sets are within 40 and
28 % for GOME-2A since 2007 and within 20 and 13 % for GOME-2B since
December 2012, for Amazonia and northern China, respectively. GOME-2 A and B
GDP 4.7 HCHO retrievals are in very good agreement with the reference
scientific retrievals when using the same settings (not shown here). The
reduced HCHO slant column noise level in the scientific algorithm presented
here (v14) is obtained by pre-fitting BrO in a separate larger interval
(328.5–359 nm) which allows de-correlation of HCHO and BrO differential
absorption structures . Remaining differences between the
operational and scientific HCHO vertical columns are mainly related to the
different input parameters used for the air mass factor calculation, namely
the cloud product and the surface albedo. An improved version of the HCHO
operational product addressing both GOME-2 A and B is under preparation based
on recent scientific algorithm developments and will be released with the
next version of the GDP data product (GDP 4.8). In addition to the
verification against the scientific prototype, comparisons with other HCHO
satellite data sets, such as GOME, SCIAMACHY and OMI instruments as well as
direct comparisons with ground-based MAXDOAS and/or FTIR instruments are
planned to be performed in the near future.
Example of HCHO end-to-end validation for (a) the Guatemala
and (b) northern China regions. Monthly means comparisons of GOME-2A
and GOME-2B GDP data (black and grey) are compared to the corresponding
scientific algorithm v14 (blue and cyan) for every step of the VCD retrieval:
the normalised slant columns (delta SCD), the DOAS fit RMS (indicator of the
fit quality), the cloud-corrected (total tropospheric) air mass factor AMF
and the tropospheric vertical column VCD.
The main user of the O3M SAF NRT and reprocessed GOME-2 H2CO products is CAMS
(Copernicus Atmosphere Monitoring Service).
Total SO2 column
The main sources for SO2 in the Earth's atmosphere are anthropogenic
emissions and volcanic eruptions. During volcanic eruptions, SO2, ash and
various gases are emitted into the atmosphere. SO2 is thus a robust
indicator for volcanic activity which can serve as a proxy for the potential
emission of volcanic ash that is initially collocated with the emitted
volcanic SO2. The timely and global measurement of volcanic SO2 can
thus provide critical information for aviation hazard mitigation when it is
used by the Volcanic Ash Advisory Centers (VAACs) . Volcanic
SO2 has an impact on the local air quality affecting human health and
ecosystems and threatening aviation safety since SO2 causes sulfidation in
the aircraft engines which might lead to a total engine failure if exposed
over a long period of time. Volcanic SO2 also has an effect on the global
climate. When released into the atmosphere it is subject to wet and dry
decomposition as well as oxidisation to sulfate aerosols .
In the lower troposphere SO2 and sulfate aerosols have a lifetime of a few
days. When injected into the stratosphere by, e.g. explosive volcanic
eruptions, the SO2 lifetime is several weeks, whereas sulfate aerosols can
remain for over a year , affecting the Earth's radiative
forcing by reflecting the solar irradiation and by changing the albedo and
lifetime of clouds. For example the 1991 Pinatubo eruption caused an average
global cooling of about 0.3–0.5 ∘C for years (see e.g.
). Global SO2 emissions averaged over
the year 2015 are shown in Fig. .
The DOAS slant column retrieval of SO2 is performed in the UV wavelength
range 315–326 nm . The retrieved SO2 slant columns are
corrected for any systematic bias by applying a latitude and
surface-elevation dependent offset correction. Total vertical SO2 columns
are calculated by applying an air mass factor which depends on the
viewing geometry surface conditions and the SO2 profile shape. Since at
the time of the measurement the SO2 plume height is unknown, the total
vertical column is calculated for three scenarios: the passive
degassing of volcanoes and anthropogenic pollution (plume height: 2.5 km);
passive degassing of high altitude volcanoes and weak eruptions (6 km); and
explosive volcanic eruptions (15 km). Furthermore, in order to detect
volcanic eruptions, pixels with elevated SO2 columns are automatically
flagged when they fulfill certain threshold criteria . This
is especially important for the assimilation of the GOME-2 SO2 columns in
forecast models, such as in the CAMS system. Note that this flag will be
provided to the users with the release of the next version of the SO2
product (GDP4.8), which will be released in early 2016.
The validation of GOME-2 SO2 columns currently relies on inter-comparisons
with other satellite data sets, such as SCIAMACHY/Envisat and OMI/Aura as well
as inter-evaluation between the two GOME-2 instruments. The current
comparisons show that the GOME-2 SO2 data are within the 50 % target
accuracy (Table 1). An example of an inter-comparison of GOME-2A and GOME-2B
for the Copahue volcanic eruption on the 23 December 2012 is given in
Fig. , left, showing very consistent results between the two
sensors for their co-located measurements. Figure , right,
shows an example of anthropogenic SO2 comparisons, for a region in Eastern
China centralised over Beijing. The OMI/Aura PBL (planetary boundary layer) product (Version 003,
) which assumes an SO2 loading with a centre of mass
altitude of about 0.9 km , is compared to both GOME-2A and
GOME-2B observations considering an SO2 plume height at 2.5 km. A very
good correlation between GOME-2A and B results is shown in the scatter plot
(blue line) with r-squared of 0.74, to be expected since the same algorithm
is applied to both sensors. However, the GOME-2B retrievals result in lower
SO2 columns than the OMI retrievals for loadings over 0.5 DU as shown in
the equivalent scatter plot (red line), even though the absolute correlation
is very satisfactory at 0.80. The reason for this difference may be
attributed to the different assumptions on the a priori SO2 profile used
by the two different algorithms (see , for more details).
In the future, comparisons with ground-based MAXDOAS instruments at different
global locations are envisaged for strong anthropogenic and volcanic SO2
cases as this type of comparison allows the dependence of the retrievals on
the SO2 profile shape to be taken into account.
Global SO2 emissions detected by GOME-2A and GOME-2B, averaged
over 2015. Clearly visible are the year 2015 volcanic eruptions of Wolf
volcano (Galapagos Islands), Cotopaxi and Tungurahua (Ecuador), Ubinas
(Peru), the active volcanoes Popocatépetl (Mexico), Nyamuragira/Nyiragongo
(Congo), Ambrym (Vanuatu), as well as anthropogenic pollution areas in
Norilsk (Russia), Bohai (China), South Africa and in the Persian Gulf.
Example of SO2 validation activities: (a) comparisons of
SO2 columns retrieved from GOME-2A and GOME-2B for the Copahue eruption,
as a function of latitude and (b) scatter plot of anthropogenic
SO2 (assuming a 2.5 km plume height ) over eastern China from GOME-2B
(x axis) and, respectively, GOME-2A (blue) and OMI (red).
Monthly averaged total BrO columns (a) over the Arctic,
April 2007 and (b) Antarctic, October 2007.
The main users of the GOME-2 SO2 product are the volcanic hazard and air
quality communities. The GOME-2 SO2 product is used within the Support to
Aviation Control Service (SACS) (Brenot et al., 2014), that provides volcanic
plume information to the Volcanic Ash Advisory Centers (VAACs) and other
users. The GOME-2 SO2 columns are also used within the GMES service EVOSS,
which monitors volcanic activity and relevant hazards at a global scale using
Earth observation data products. Furthermore, the GOME-2 SO2 columns have
been used within the mobile volcano fast response system Exupéy
.
Total BrO column
BrO is present in the lower stratosphere, where it depletes ozone through
very efficient catalytic reactions. BrO is also released in the troposphere
from sea ice, at the interface of ocean, salt lakes and volcanoes.
The retrieval of total BrO is achieved by a DOAS analysis in the wavelength
region 332–359 nm , including five BrO absorption bands.
It is followed by an equatorial offset correction applied
to the retrieved slant columns, in order to minimize the impact of the
long-term instrumental degradation. The conversion into total BrO vertical
columns is made using air mass factors assuming representative stratospheric
BrO profiles. The main interest is on bromine emissions in the polar boundary
layer. GOME-2 measurements allow springtime BrO columns to be studied in both
the Arctic and Antarctic regions (as illustrated in Fig. ).
BrO production is related to heterogeneous photochemistry due to the presence
of sea salt, but the mechanisms are currently not fully characterized,
especially the link with meterological variables (e.g. wind) and the
importance of bromine for the deposition of mercury which impacts the polar
biosphere. Owing to its wide coverage, GOME-2 measurements enable long-range
transport of polar tropospheric BrO to be studied, and
also emissions from volcanic eruptions . In
addition there is an interest in the study of stratospheric BrO and its
long-term trend. However, strictly speaking, scientific studies of BrO from
GOME-2 measurements are only possible by separating the retrieved total BrO
column into its tropospheric and stratospheric components (see Sect. 6).
The validation of BrO columns relies on the comparison of the total columns
to other satellite data sets, such as the SCIAMACHY and GOME-2 scientific
products and on ground-based zenith-sky DOAS instruments
from NDACC stations, such as Harestua . The results for
the validation of GOME-2A and B BrO total columns can be found in
and on the O3M SAF BIRA validation pages
(http://cdop.aeronomie.be/validation/valid-results). Examples are shown
in Fig. . One can see that the satellite columns are very
consistent with each other at all latitudes and seasons. The comparison of
GOME-2A and GOME-2B with ground-based BrO columns at Harestua is also good for the absolute values and for the short-term variation of the BrO total
column. The conclusion is that the GOME-2A and -B total BrO columns have an
accuracy better than 30 % most of the time and hence the product reaches
its target accuracy.
Example of BrO validation: (a) Monthly averaged BrO VCD
relative difference between GOME-2B (red) and GOME-2A (black) against
SCIAMACHY as a function of SCIAMACHY/GOME-2A BrO VCD, for 14 sites from
pole-to-pole over the period December 2012–April 2013.
(b) Comparison of GOME-2 (A and B) and ground-based total BrO
columns at Harestua (60∘ N, 11∘ E) in February–April 2013.
The satellite results labelled “total AMF” are calculated using the
stratospheric and tropospheric AMFs weighted by the BrO column contribution
in both layers as retrieved from the ground-based measurements. The relative
differences (squares) and mean biases (solid lines) appear in the lower
plots. The number of coincidences is 55 for GOME-2A and 49 for GOME-2B.
Total water vapour column
Atmospheric water vapour plays a major role for meteorology as well as for
climate because it is an important greenhouse gas and via
its influence on the formation of clouds and precipitation and the growth of
aerosols . Hence, advancing in understanding of variability
and long-term changes in water vapour is vital, especially considering that
atmospheric water vapour exhibits a highly variable spatial and temporal
distribution. Total column water vapour (TCWV) from GOME-2 is the only data
product with the following combination of features: global coverage over land
and over sea, good sensitivity down to the surface (where most of the water
vapour column resides), independent of model input (no model-dependent
information in climatological data record), and retrievals insensitive to
instrument drift. Thus, the GOME-2 water vapour product is especially
valuable for long-term series and climatological studies . The example of the retrieved monthly mean
maps of total column water vapour in Fig. shows the global
distribution of TCWV in February and August 2008 retrieved by GOME-2A. The
algorithm used for the retrieval of GOME-2 TCWV is based on a classical
differential optical absorption spectroscopy (DOAS) performed in the
wavelength interval 614.0–683.2 nm and does not include explicit numerical
modelling of the atmospheric radiative transfer . It consists of three basic steps: in the first step, the
spectral DOAS fitting is carried out, taking into account absorption by O2
and O4, in addition to that of water vapour. In the second step, a
correction for absorption non-linearity effects is applied because the highly
fine-structured H2O (and O2) absorption bands cannot be
spectroscopically resolved by the GOME-2 instrument. In the last step, the
corrected water vapour slant columns determined with the DOAS fitting are
converted to geometry-independent vertical column densities (VCDs) through
division by an appropriate air mass factor (AMF), which is derived from the
measured O2 absorption.
Monthly mean maps of total column water vapour from GOME-2A for
February 2008 (on the top) and August 2008 (on the bottom). Only
cloud-screened data have been used.
To assess the quality of the GOME-2 water vapour columns, the TCWV products
were compared with corresponding model data from the European Centre for
Medium Range Weather Forecast (ECMWF) ERA-Interim reanalysis
and with SSMIS satellite F16 measurements during the full
period January 2007–June 2014 . A comparison between the
GOME-2A product and the combined SSM/I + MERIS GlobVapour data set in
2007 and 2008 was also carried out. Good general agreement was reported
between all three data sets with mean bias within 0.035 g cm2, although
some seasonal and regional biases have been identified.
Figure shows a time series of globally averaged total bias in
the TCWV distribution between GOME-2A and the data sets described above.
Since January 2013, the bias between the most recent GOME-2B results and the
ERA-Interim and SSMIS retrievals was also computed. It was found that the
combined SSM/I - MERIS sample and the ERA-Interim data set are typically
drier than the GOME-2 retrievals (0.032 and 0.035 g cm-2,
respectively), while on average GOME-2 data overestimate the SSMIS
measurements by only 0.006 g cm-2. However, the size of these biases
is seasonally dependent. Monthly average differences as large as
0.1 g cm-2 were observed in the analysis against SSMIS measurements,
but were not so evident in the comparison with ERA/Interim and
SSM/I + MERIS data, because of the compensating effect of having land and
ocean retrievals. Pronounced negative biases over land areas were identified
in regions with high humidity or a relatively large surface albedo
(0.3–0.5).
The water vapour product has also been validated against ground-based data
. In that study, the radiosonde data were from the
Integrated Global Radiosonde Archive (IGRA) maintained by National Climatic
Data Center (NCDC) and screened for soundings with incomplete tropospheric
column, whereas the ground-based GPS observations from COSMIC/SuomiNet network
were used as the second independent data source. The outcome described in the
paper was that the general agreement between GOME-2 and the ground-based
observations is good. The median relative difference to radiosonde
observations was found to be -2.7 % for GOME-2A and -0.3 % for
GOME-2B. Against GPS observations, the median relative differences were 4.9
and 3.2 % for GOME-2A and B, respectively. For water vapour total columns
below 10 kg m-2, large wet biases were observed, especially against
GPS observations. Conversely, at values above 50 kg m-2, GOME-2
generally underestimates both ground-based observations.
Aerosol products
The Absorbing Aerosol Index (AAI) product is derived from the reflectances
measured by GOME-2 at 340 and 380 nm . The AAI may
be used to detect absorbing aerosols over both land and sea surfaces, even in
the presence of clouds. The AAI retrieval algorithm compares the measured
reflectances with simulated clear-sky reflectances and calculates a residue
from these which represents the difference between measurement and
(clear-sky) simulation and takes the form of a single index.
A high radiometric stability of the Level-2 product is extremely important
for the AAI data record as a whole, because the AAI is very sensitive to
changes in the radiometric calibration of the instrument. Before
calculating the AAI from the Earth reflectances, the reflectances are
first corrected for the effects of instrument degradation. For this
pre-processing correction we make use of the method introduced in
for the SCIAMACHY instrument that was later applied
to the GOME-2 instrument . This correction for
instrument degradation is a function of time, wavelength and scan mirror
position, and it is instrument-specific. After application of the correction,
the errors caused by instrument degradation are removed to within 0.1
index point over the entire time period covered by the satellite.
Global monthly mean bias between GOME-2A and 3 independent TCWV data
sets for the period January 2007–June 2014, depending on availability of the
reference data. The comparison is performed against ECMWF ERA-Interim
reanalysis (blue points), SSMIS F16 satellite (magenta points, only over
ocean) and combined SSM/I + MERIS data set (green points). Coloured
squares and gray lines show the bias between the most recent GOME-2B
observations and the ECMWF and SSMIS data sets.
In the algorithm, the surface albedo is assumed to be constant over the
spectral range of the two selected wavelengths, and when the total ozone
column is taken into account in the simulations, deviations from the Rayleigh
scattering atmosphere are caused purely by clouds and/or aerosols. Negative
values for the AAI are caused by the presence of clouds and/or scattering
aerosol in the scene. However, a positive value for the AAI can only be
explained by the presence of absorbing aerosols. This makes the AAI ideally
suited for aerosol masking and the detection of smoke from forest fires or
volcanic eruptions. An example of the detection of a volcanic plume is shown
in Fig. , where the ash plume originating from the Puyehue
volcano can be seen to travel from its source eastward over the south
Atlantic Ocean. This event has been analysed in .
Absorbing aerosol index from the PMD bands from GOME-2A on
6 June 2011 over the south Atlantic Ocean. The plume of aerosol originates
from an eruption of the Puyehue volcano. The GOME-2A SO2 data are plotted
over the AAI values to show how the AAI and SO2 products see the
dispersions of the volcanic ash and SO2 clouds, respectively. The SO2
values are in Dobson Units with a different colour scale.
For the validation of the GOME-2 AAI product we rely on comparisons
with AAI products derived from other satellite instruments, such as
GOME-1, SCIAMACHY and OMI. The validation results show that the
GOME-2 AAI has reached the target accuracy of 0.5 index point
. Since the launch of Metop-B, the AAI products
from GOME-2A and GOME-2B can be compared, and the global means
of the two AAI products are nearly identical, with GOME-2B having AAI
values on average 0.2 index points higher than GOME-2A. Both AAI
products meet the target requirements. More detailed validation results can
be found in the mentioned validation report.
Lambertian-equivalent reflectivity surface albedo database
The Lambertian-equivalent reflectivity (LER) of the Earth's surface is based
on reflectance measurements taken by GOME-2A. It is the improved
follow-up of earlier surface LER databases based on GOME-1 (on the
ERS-2 satellite) and OMI (on the Aura satellite). As a result of this,
the algorithm was influenced strongly by the approaches followed for the
GOME-1 surface LER database and the OMI
surface LER database . The surface LER is an essential
input parameter for the retrieval of many trace gases, cloud properties and
aerosols.
The GOME-2 surface LER is retrieved from the main science channels for
15 pre-defined 1 nm-wide wavelength bands ranging from the UV to the
near-infrared. Additionally, we provide a surface LER product based on the
PMD (polarisation measurement device) measurements. The definition of these
PMD bands is fixed but the advantage is the much smaller footprint size
(10 km × 40 km instead of
80 km × 40 km) which results in better statistics.
The surface LER spectra are provided for each month of the year in a grid of
1∘×1∘ (MSC-LER) or
0.5∘ × 0.5∘ (PMD-LER).
The retrieval algorithm follows an approach in which the reflectance
measurements from the entire mission are transformed for each of the months
into scene LERs. The scene LERs are distributed into the grid cells of the
Earth grid and their histograms are analysed to find the representative
(cloud-free) scene LER, i.e. the spectral surface LER. For some surfaces the
mode of this distribution is taken (e.g. snow, desert), for others the
minimum value is taken (e.g. ocean). Cloud contamination over the oceans
caused by persistent cloud presence is corrected by looking for near-by grid
cells that can act as a surface LER donor. The surface LER is retrieved for
land and sea surfaces, including those covered by snow and ice.
Artificial trends in the Earth reflectances due to instrument degradation are
removed before the actual surface LER retrieval starts. The method that is
used is described in Sect. 5.8. A more extensive description of the algorithm
and the products can be found in . An example of the
surface LER product is presented in Fig. .
Example of the GOME-2 surface LER determined from PMD band 15
(centred around 799 nm) for March. The snow cover on northern latitudes as
well as the Sahara are clearly seen.
UV radiation products
Offline surface ultraviolet (UV) radiation products (OUVs) contain the most
important quantities of the solar radiation that can be harmful to life and
materials on the Earth. These quantities include daily doses and maximum dose
rates of integrated UVB and UVA radiation together with values obtained by
different biological weighting functions, solar noon UV index and quality
control flags. Recent additions are the photolysis frequencies of two key
reactions in the atmospheric chemistry of the troposphere: the
photodissociation of ozone and nitrogen dioxide. The photolysis frequency of
ozone refers to the rate constant jO(1D) of the following
reaction forming atomic oxygen in its exited 1D state from ozone
O3+hν(λ<320nm)→O(1D)+O2.
This is an important photodissociation route of ozone leading to production
of the hydroxyl radical, a key species in oxidation of hydrocarbons in the
troposphere. Figure shows, as an example, the daily maximum
jO(1D) at ground level on 10 April 2015.
Daily maximum photolysis frequency of ozone jO1D at the
ground level obtained from Metop-B and NOAA-19 data on 10 April 2015. Global
coverage of the product is limited by the swath of the GOME-2 instrument
leaving stripes at low latitudes. The polar night and the maximum solar
zenith angle for cloud processing limit the coverage at high latitudes while
cloud-free values are accepted for the Antarctic and Greenland ice sheets.
The OUV products are derived from the O3M SAF total ozone column product and
the visible channel reflectances of the third Advanced Very High Resolution
Radiometer (AVHRR/3), therefore combining data from two different instruments
aboard the Metop satellites . Sampling of the diurnal
cloud cycle is improved by complementing the morning orbit Metop AVHRR/3 data
with corresponding afternoon orbit data from the Polar Orbiting Environmental
Satellites (POES) of the National Oceanic and Atmospheric Administration
(NOAA), available through the data exchange between EUMETSAT and NOAA in
their Initial Joint Polar System (IJPS) programme. The offline UV products
are currently used by research institutes in Europe and Australia and the
main interest is in health and long-term applications.
The near-real-time UV product is a 1–5 day forecast of UV index on global
scale. The NUV/CLEAR product is based on GOME-2 assimilated total ozone (ATO)
from KNMI. The UV index is calculated from ATO applying climatologies for
surface albedo, aerosol optical depth etc. The final NUV/CLEAR index is valid
for clear-sky conditions at local noon, i.e. minimum solar zenith angle, thus
reflecting the maximum UV index to be expected for the current day. The
NUV/CLOUD product is the NUV/CLEAR product modified with an algorithm using
the cloud cover fraction forecast from ECMWF to reflect the actual UV index.
The UV fields are calculated on the same grid size as the input ATO fields,
with a sub-pixel resolution of 0.25∘ × 0.25∘. The
product may be highly customised for users, with regard to geographical
coverage, forecast time etc. The users are National Meteorological Institutes
as well as news groups for radiation warnings.
The NUV/CLEAR and NUV/CLOUD have been validated against ground-based
measurements of UV index. The most recent validation was performed on data
from 2011 for six locations with a total of 2064 measurements
. In Fig. the distribution of the difference
between measured and forecasted NUV/CLOUD product is shown. The red line is
the mean and the blue line the median of the distribution. The mean absolute
relative difference is 22.6 % for the whole NUV/CLOUD comparison, while the
NUV/CLEAR product shows a mean absolute relative difference of 8.5 %
Global map of the NRT cloud-corrected UV index on 2 November 2013.
Emerging products
The most of the existing O3M SAF GOME-2 L2 products will be reprocessed in
2016 in order to provide a consistent homogeneous data set to users that is
based on the latest state of the art algorithm.
The O3M SAF has recently released new tropospheric ozone products.
Furthermore, tropospheric BrO, glyoxal (CHOCHO), OClO and monthly climate
products of H2O and NO2 and absorbing aerosol height will be released
in 2016.
There are two different kinds of tropospheric ozone products. The first one
is a product called tropical tropospheric ozone columns (TTOCs) using a
convective-cloud-differential (CCD) method . The retrieval
is based on total ozone and cloud property data provided by the GDP 4.8 (see
Sect. 3.1), and uses above-cloud and clear-sky ozone column measurements to
derive a monthly mean TOC between 20∘ N and 20∘ S. Tropical
tropospheric ozone data from GOME-2 will provide significant input for
climate services and international assessment reports, such as the UNEP/WMO
Scientific Assessments of Ozone Depletion and the Climate Assessment Reports
of IPCC. The second tropospheric ozone product is based on the separation of
the tropospheric and stratospheric columns from the retrieved vertical ozone
profiles by splitting the atmosphere at the tropopause and adding the partial
ozone columns below and above it.
Satellite total BrO columns sometimes exhibit strong stratospheric
enhancements of BrO, making the interpretation of the results difficult
. In the frame of the O3M SAF, it is planned
to produce tropospheric BrO columns following the approach developed by
The retrieval of tropospheric BrO columns is achieved
through a stratospheric correction based on a BrO climatology that accounts
for the important dynamical and photochemical variations of stratospheric BrO
. The algorithm also treats the changes in sensitivity in
both tropospheric and stratospheric layers. By separating the large-scale BrO
structures (of tropospheric or stratospheric origin) in the total BrO field,
the method allows the polar emissions hotspots and global free-tropospheric
BrO background to be better studied.
Glyoxal (CHOCHO) is a short-lived volatile organic compound (VOC) produced in
the atmosphere mostly via the oxidation of other non-methane VOCs emitted by
natural and human activities, but also directly emitted by fire events and
combustion processes . Observations of glyoxal
atmospheric concentrations are therefore useful to further constrain
estimates of VOC emissions and also to improve the global budget of secondary
organic aerosols, for which it has been recognised as an important source
. Glyoxal has three absorption bands ranging between 420
and 460 nm, which may be exploited for detection based on the DOAS technique.
It has been observed for the first time from space by the SCIAMACHY
instrument aboard Envisat . Since then, the GOME-2A data
have also been used to retrieve glyoxal tropospheric columns by different
teams . Glyoxal retrievals from space are
particularly challenging owing to the weakness of its typical atmospheric
optical depth, which leads to strong interferences with other species
absorbing in this spectral range. In particular, significant spectral
interferences occur with liquid water absorption over remote oceanic areas.
designed an original 2-step fit method to limit the impact
of these interferences. This scientific algorithm will be used as the
baseline for implementing an operational tropospheric glyoxal product as part
of the O3M SAF activities in the next 2 years.
The OClO slant column (in molec cm-2) measurements will be available
under chlorine activated ozone hole conditions. Retrieval is only possible
under twilight conditions because this molecule is destroyed in full
daylight. The algorithm is based on the classical DOAS method. Slant columns
of OClO are derived from the differential absorption structures in a spectral
region from 365 to 389 nm.
Climate products, such as data sets of H2O and NO2, will consist of
monthly mean averages of GOME-2 products in the netCDF
format.