Journal of Integrative Environmental Sciences
2012, 1–14, iFirst article
Global reactive gases forecasts and reanalysis in the MACC project
Olaf Steina*, Johannes Flemmingb, Antje Innessb, Johannes W. Kaiserb and
Martin G. Schultza
a
Forschungszentrum Jülich, IEK-8 (Troposphere), 52425 Jülich, Germany; bECMWF, Shinfield
Park, RG2 9AX Reading, UK
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(Received 15 November 2011; final version received 18 May 2012)
The EU FP7 projects MACC (Monitoring Atmospheric Composition and
Climate, 2009–2011) prepared for the operational Global Monitoring for
Environment and Security (GMES) atmospheric core service on greenhouse
gases, reactive gases and aerosols which is envisaged to start in 2014. This paper
describes the data assimilation and modelling system which has been implemented
for global monitoring of reactive gases in the troposphere and stratosphere. The
MACC reactive gases system uses a coupling software to integrate the Model for
Ozone And Related Tracers, version 3 (MOZART-3) chemistry transport model
with the Integrated Forecast System (IFS) of the European Centre for Mediumrange Weather Forecasts (ECMWF). The focus is placed on the tropospheric
simulations with this MACC-IFS-MOZ model. The MACC reanalysis (2003–
2010) and the forecasts performed in near real time (NRT) benefit from the multisensor approach for data assimilation of total columns, tropospheric columns and
vertically resolved observations of ozone, CO and NO2. Daily biomass burning
emissions are integrated in real time using the global fire assimilation system
(GFAS) that was developed within MACC. Other emissions are taken from a
state-of-the-art global inventory that was developed across several EU projects.
The MACC reanalysis and tracer forecasts are routinely evaluated with groundbased and airborne in-situ observations and independent satellite retrieval
products. We present the system set-up for reactive gases, give an overview on the
service and technical developments during the project, and indicate how MACC
global reactive gases products could provide information on non-CO2 greenhouse
gases.
Keywords: GMES; reactive gases; monitoring; forecast; air quality; emissions
1. Introduction
While tropospheric ozone is a direct greenhouse gas, other short-lived atmospheric
trace gases like carbon monoxide, volatile organic compounds and nitrogen oxides
act as indirect greenhouse gases by controlling ozone and the abundance of the OH
radical, which itself affects also the atmospheric burden of methane (e.g. Prather and
Ehhalt 2001; Rigby et al. 2008; Montzka et al. 2011). In order to better understand
this complex chemical interplay, it is essential to monitor the key reactive gas species
on a global scale.
*Corresponding author. Email: [email protected]
ISSN 1943-815X print/ISSN 1943-8168 online
! 2012 Taylor & Francis
http://dx.doi.org/10.1080/1943815X.2012.696545
http://www.tandfonline.com
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O. Stein et al.
Under the framework of the European initiative Global Monitoring for
Environment and Security (GMES), an operational atmospheric monitoring and
forecast service will be established which is envisaged to start in 2014. The EU
research projects GEMS (Global and regional Earth-system Monitoring using
Satellite and in-situ data, 2005–2009; Hollingsworth et al. 2008), MACC
(Monitoring Atmospheric Composition and Climate, 2009–2011) and MACC-II
(2011–2014) have been designed to prepare for this novel and comprehensive service
which will comprise monitoring of greenhouse gases as well as reanalysis and
forecasts of aerosols and reactive gases, both on the European and on the global
scale. The global and regional service lines provided from the MACC project are in a
pre-operational state and already provide valuable services to various users. MACC
products featured prominently during the eruption of the Eyjafjallajökull volcano in
2010 and during the arctic ozone hole in the winter of 2011. They will emerge into a
fully operational GMES atmospheric service for monitoring and forecast of global
and regional air quality, aerosols and greenhouse gases during the coming years.
The overall structure of the MACC project is shown in Figure 1. Satellite and insitu data from various agencies and institutions as well as other research projects and
global networks are collected and processed to be fed into a comprehensive data
assimilation and modelling framework consisting of the Integrated Forecast System
(IFS) at the European Centre for Medium-range Weather Forecast (ECMWF) and
various chemistry transport models. Special emphasis is put on the development of
an up-to-date inventory of emissions including the near real time (NRT) monitoring
and processing of satellite data on open burning of biomass. The main service lines
on the global scale constitute daily NRT forecasts (up to 96 h into the future) for
stratospheric ozone and a variety of tropospheric trace gases, greenhouse gases and
aerosols, and a comprehensive reanalysis covering the period 2003–2010. In the
following, we will describe the pre-operational MACC services for tropospheric
reactive gases with emphasis on the model system using the Model for Ozone And
Related Tracers, version 3 (MOZART-3) chemistry transport model. Further
information about the project, data products and links to external validation
activities can be found at the MACC website http://www.gmes-atmosphere.eu
Figure 1.
MACC project structure and data flow.
Journal of Integrative Environmental Sciences
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2.
3
Modelling and assimilation approach
The meteorological forecast and data assimilation system IFS (Integrated Forecast
System, http://www.ecmwf.int/research/ifsdocs) at the ECMWF has been coupled to an
updated version of the global chemistry transport model MOZART-3 (Kinnison et al.
2007) in order to build the coupled MACC system MACC-IFS-MOZ (Flemming et al.
2009). For a coupled simulation, both models are running in parallel and exchange
several two- and three-dimensional fields every hour using the OASIS4 coupling
software developed in the PRISM project (Valcke and Redler 2006). Data assimilation
of the MACC species O3, CO, NOx, HCHO and SO2 takes place in IFS, which provides
basic meteorological data and species initial concentrations to MOZART. Chemical
reaction equations, emissions and deposition are calculated in MOZART. Transport
processes are parameterised in both models. MOZART provides updated tendency
terms for chemistry, emission and deposition sources and sinks for the MACC species,
which are then used to constrain the data assimilation in the next cycle.
MOZART uses the same 60 vertical hybrid layers as in current IFS simulations
reaching from the surface to 0.1 hPa. The MOZART system of chemical reactions
consists of 115 species, 71 photolysis reactions, 223 gas phase reactions and 21
heterogeneous reactions.
Both the global reanalysis and the NRT forecasts benefit from the multi-sensor
approach for data assimilation: total columns, tropospheric columns and vertically
resolved observations from different satellite sensors and platforms are assimilated
and are pivotal to improve the simulations by removing biases; for example, with
respect to polar stratospheric ozone chemistry or during exceptional pollution
episodes. Integrated Forecast System (IFS) uses an incremental formulation of 4dimensional variational (4D-Var) data assimilation. In 4D-Var, a cost function J is
minimised to combine the model background and the observations to obtain the best
possible forecast by adjusting the initial conditions (Courtier et al. 1994). The
background error statistics for ozone currently used in the IFS were also used for the
assimilation of the MACC ozone as part of the coupled system. The background
error statistics for the other species were calculated with the National Meteorological
Center (NMC) method (Parrish and Derber 1992). The assimilation experiments in
MACC apply averaging kernels for CO and NO2 observations and use the
variational bias correction scheme for O3 and CO observations (Dee 2004; McNally
et al. 2006; Auligné et al. 2007). For a far more detailed description of the ECMWF
data assimilation approach for trace gases the reader is referred to Inness et al.
(2012). The satellite data assimilated in the forecasts and in the reanalysis are
summarised in Tables 1 and 2, respectively.
3.
Global forecasts
Global 96-h daily forecasts for concentrations of ozone and several other reactive
gases together with meteorological parameters are generated with MACC-IFS-MOZ
using a horizontal resolution of 1.1258 for IFS and 1.8758 for the chemistry transport
model. Currently, these forecasts are running with a time lag of one day to the
operational weather forecast simulations. The daily forecasts started in September
2009 and have run with almost no interruption since then. For graphical forecast
products, see http://www.gmes-atmosphere.eu/services/gac/nrt
Validation of O3, CO and NO2 is carried out regularly using various independent
in-situ and satellite observational data sets (see e.g. Elguindi et al. 2010; Flemming
Satellite
AURA
AURA
NOAA
Envisat
MetOp-A
MSG
MetOp-A
TERRA
MetOp-A
AURA
Envisat
Instrument
MLS
OMI
SBUV
SCIAMACHY
GOME-2
SEVIRI
IASI
MOPITT
GOME-2
OMI
SCIAMACHY
NASA
NASA
NOAA
KNMI
Eumetsat/DLR
Eumetsat
LATMOS
NCAR
Eumetsat/DLR
KNMI
BIRA
Provider
V4
V003
V883
V003
V02
V883
V8
Version
O3
O3
O3
O3
O3
O3
CO
CO
NO2
NO2
SO2
Species
Profiles
Total column
Six layer profiles
Total column
Total column
Total column
Total column
Total column
Tropospheric column
Tropospheric column
Total column
Type
20090901
20090901
20090901
20090916
20090901
20090901
20090901
20100330
20100714
20090913
20090901
Period
-
Active
Active
Active
Active
Passive
Passive
Active
Passive
Passive
Passive
Passive
Status
Table 1. Reactive gases data assimilation in the MACC NRT analysis. Data labelled active are assimilated in the analysis. Data labelled passive are only
monitored, which means that the observations are not fed back into the model system as part of the assimilation. This allows for detection of potential
satellite instrument biases or drifts without influencing the quality of the model analysis.
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4
O. Stein et al.
GOME
MIPAS
MLS
OMI
SBUV
SBUV
SBUV
SCIAMACHY
MOPITT
IASI
OMI
SCIAMACHY
OMI
SCIAMACHY
OMI
SCIAMACHY
ERS-2
Envisat
AURA
AURA
NOAA-16
NOAA-17
NOAA-18
Envisat
TERRA
METOP-A
AURA
Envisat
AURA
Envisat
AURA
Envisat
Satellite
RAL
ESA
NASA
NASA
NOAA
NOAA
NOAA
KNMI
NCAR
LATMOS/ULB
KNMI
KNMI
NASA
BIRA
NASA
BIRA
Provider
V003
V2
Col. 3
V1.1
V003
V4
V02
V003
V8
V8
V8
Version
Reactive gases data assimilation in the MACC reanalysis.
Instrument
Table 2.
O3
O3
O3
O3
O3
O3
O3
O3
CO
CO
NO2
NO2
SO2
SO2
HCHO
HCHO
Species
Period
20030101–20030531
20030127–20040326
20040808–20101231
20041001–20101231
20040101–20101231
20030101–20101231
20050604–20101231
20030101–20101231
20030101–20101231
20080401-20101231
20041001–20101231
20030101–20101231
20040817–20101231
20040104–20101231
20040827–20101231
20030101–20101231
Type
Profiles
Profiles
Profiles
Total column
Six layer profiles
Six layer profiles
Six layer profiles
Total column
Total column
Total column
Tropospheric column
Tropospheric column
Total column
Total column
Total column
Total column
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Active
Active
Active
Active
Active
Active
Active
Active
Active
Active
Passive
Active
Passive
Passive
Passive
Passive
Status
Journal of Integrative Environmental Sciences
5
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O. Stein et al.
Figure 2. Near real time validation with CO data from GAW station Hohenpeißenberg,
Germany for August 2011. OBS: Observational data; black line: NRT analysis; coloured lines
depict the concentrations forecasted from simulations started one, two and three days before
the analysis. Please note that station data are of preliminary status as they have not been
quality checked extensively.
et al. 2011). On a dedicated verification web page, the daily simulation results are
evaluated with surface station, aircraft and independent satellite data in NRT. Since
the start of the MACC-II successor project, a detailed validation report is produced
every three months. Observational data that are available in NRT are sparse and
currently consist of surface observations for ozone and CO from the global
atmospheric watch (GAW) programme as well as NO2 tropospheric columns from
SCIAMACHY. Figure 2 shows a validation example of CO concentrations from the
NRT MACC-IFS-MOZ forecasts with observations from the Hohenpeissenberg
observatory, Germany. The model captures most of the synoptic features that are
present in the measured data. In most cases, the 24-h forecast (black line) is superior
to the longer-range forecasts (coloured lines). Altogether, 12 GAW stations provided
data to MACC with much faster turnaround time than usual (between one day and
three months). Beginning in 2012, NRT validation is also provided for vertical
profiles of ozone and carbon monoxide from ascending and descending In-service
Aircraft for a Global Observing System (IAGOS) aircraft (http://www.iagos.fr/
macc/).
While CO is generally reproduced well during the summer the MACC forecasts
underestimate observed CO concentrations for European and Asian GAW stations
in winter with biases of up to 750%, consistent with IAGOS CO profile validation
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Journal of Integrative Environmental Sciences
7
(not shown). This is a feature that is found in many current chemistry transport
models. It is presently unclear if this low bias results from underestimated
anthropogenic emissions of CO or volatile organic compounds or is due to other
factors associated with biomass burning or natural emissions. For ozone, the model
results are mostly in good agreement with measured surface concentrations for
European and Asian GAW stations in spring, with relative biases of around 10%
and a mean RMSE of less than 10 ppb. Only for the northern summer period, O3
concentrations are predominantly overestimated by all model runs with mean
relative biases of up to 30%. Tropospheric NO2 columns agree well with
SCIAMACHY retrievals, except for an underestimation over East Asia during
autumn and winter, which is most likely originating from the use of too low
emissions for China.
In order to ease access of the daily MACC reactive gases (and aerosol) data
products for regional modelling teams worldwide, a fully interoperable, Open
Geospatial Consortium-compliant data server (‘‘MACC boundary condition
service’’) has been established at Forschungszentrum Jülich. A graphical web
interface (http://macc.icg.kfa-juelich.de:50080/) allows users to select the data sets,
region, time period and variables they require and then provides data as NetCDF
files for download or allows for interactive visualisation. Due to the concept of
interoperability, the MACC data can be directly compared to other data available on
web coverage servers anywhere in the world. The web interface is still in
construction. Presently, the model results can be compared to surface observations
from more than 400 stations of the German Umweltbundesamt (UBA), which
delivers air quality data in NRT. An example is shown in Figure 3, where MACC 96h ozone forecasts for four consecutive days in April 2012 are compared to the
observations at the station Hamburg Flughafen Nord. The general level of
compliance is mostly dependent on the meteorological situation and on the
representativeness of the station.
4.
Reanalysis
A retrospective reanalysis for the years 2003–2010 was carried out in MACC using a
similar configuration as for the NRT forecasts but with enhanced horizontal
resolution of 0.78 (IFS) and 1.1258 (MOZART). This reanalysis assimilates more
satellite data than the NRT run, because it allows for inclusion of data sets not
delivered in NRT (Table 2). In contrast to the NRT analysis, SCIAMACHY NO2
tropospheric columns are also actively assimilated. Graphical reanalysis products are
available at http://www.gmes-atmosphere.eu/d/services/gac/reanalysis/macc, and
monthly mean data can be downloaded from the Jülich boundary condition server.
Verification is done against surface station data from global networks (EMEP,
GAW, NOAA GMDL), vertical profiles from ascents/descents of MOZAIC aircraft
at international airports (Elguindi et al. 2010), ozone sondes and independent
satellite data. Figure 4 shows as example how ozone from the MACC reanalysis
compares to MOZAIC profile observations over Frankfurt for the period January
2003–April 2005. For this period, the tropospheric bias is reduced by about 25%
compared to the previous reanalysis from the GEMS project, which is mostly due to
the improvements in the data assimilation system and the increased amount of
vertically resolved satellite data used in MACC. The remaining tropospheric biases
are found in the surface boundary layer and around the tropopause, where vertical
8
O. Stein et al.
ozone gradients are large and are not always well captured by both the Chemistry
Transport Model (CTM) and the satellite observations. The MACC reanalysis and
its validation with independent observational data are described in detail in Inness
et al. (2012).
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5.
Surface boundary conditions
The accuracy of the IFS-MOZART simulations depends on the quality of the surface
boundary conditions, which control the tracer surface fluxes, notably emission and dry
deposition fluxes as the major source and sink terms. With the MACC reanalysis, an
updated anthropogenic and natural emission inventory has been introduced. Based
upon a review of existing historical and actual emission inventories, a consistent
inventory for anthropogenic emissions has been set up for the base year 2000
(Lamarque et al. 2010; Granier et al. 2011). It was originally designed for the IPCC
AR5 assessment (ACCMIP emissions). These emissions are extrapolated for years after
2000 with the Representative Concentration Pathway RCP8.5 scenario (Moss et al.
2010; van Vuuren et al. 2011) and are called MACCity emission inventory. Biogenic
emissions are from MEGAN-v2 (Guenther et al. 2006) and other natural emissions are
from the POET project (Granier et al. 2005) and the Global Emissions Initiative
(GEIA).
For the biomass burning emission inventory, a novel method has been developed
using a bottom-up approach: within MACC, a global fire assimilation system
(GFAS) for wildfires observed from space has been developed (Kaiser et al. 2012).
Figure 3. Screenshot from the graphical web interface of the interoperable MACC boundary
condition server. Comparison of MACC 24-h ozone forecasts to UBA observational data for
station Hamburg Airport Nord, Germany for four consecutive days in April 2012.
Figure 4. Comparison of ozone from MACC and GEMS reanalysis to MOZAIC profiles over Frankfurt for the period January 2003–April 2005. Top:
monthly mean reanalysis profiles. Bottom: relative bias (observations – model).
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Journal of Integrative Environmental Sciences
9
Figure 5.
MACC daily fire product for 30 August 2011. Emissions fluxes are derived from these fire radiative power observations.
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O. Stein et al.
Journal of Integrative Environmental Sciences
11
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Global daily fields of observed fire radiative power (FRP) based on MODIS
observations (Figure 5) are converted into fire emissions, which are available in NRT
and as a retrospective data set since 2003. The two consistent products are available
with horizontal resolution of 0.58 lat/lon (GFASv1.0) and 0.18 lat/lon (GFASv1.1).
They represent for the first time the large temporal variability of biomass
burning emissions. A global wildfire data description and graphical products can
be found at http://www.gmes-atmosphere.eu/services/gac/fire, the wildfire emission
data GFASv1.0 can be downloaded from the Jülich boundary condition server. They
are used for the years 2009–2010 of the reanalysis and will soon also be used for the
global NRT forecasts of MACC. For the earlier years of the reanalysis, a
combination of GFAS FRP and a preliminary version of Global Fire Emission
Database, version 3 (GFEDv3) emissions (van der Werf et al. 2010) is being used.
6. Use of MACC reactive gases products to assess concentrations and trends of
non-CO2 greenhouse gases
Short-lived atmospheric gases are closely linked to the overall abundance and the
variablility of non-CO2 greenhouse gases, most notably via the hydroxyl radical.
Reaction with OH acts as the major sink for methane and other greenhouse gases.
On the other hand, the atmospheric lifetime of methane is a measure for the
tropospheric burden of OH and thus for the oxidising capacity of the atmosphere.
Interestingly, a large uncertainty in the estimate of this important parameter still
exists between global chemistry models (Shindell et al. 2006; Duncan et al. 2007,
Hoor et al. 2009). Moreover, the role of OH for the interannual variablility of
methane is not completely understood yet (Rigby et al. 2008; Dlugokencky et al.
2009; Montzka et al. 2011). As a consequence, there is now rising interest from the
greenhouse gas community in the OH concentrations derived from the MACC
reanalysis and its interannual variability. The mean chemical methane lifetime in the
reanalysis is 10.0 years which is close to the IPCC TAR recommendation of 9.6+1.4
years (Prather and Ehhalt 2001). However, the varying amount of trace gas data
assimilated during the reanalysis period induces spurious variability in the data
record which limits the usefulness of these data to assess the evolution of the year-toyear variability of the methane lifetime.
As an alternative product, MACC provides OH concentrations from a pure
MOZART simulation run in parallel to the reanalysis. This simulation has the same
set-up for meteorology and emissions and uses the high CTM resolution as in the
reanalysis but does not assimilate any reactive gases. A preliminary analysis shows
that the absolute methane lifetime (10.8 year) is somewhat higher than in the
reanalysis but the interannual variability 2003–2010 is well captured by this
simulation when compared to the study of Montzka et al. (2011). The influence of
the potentially low biased wintertime CO emissions in the current inventories on the
OH concentrations need to be further evaluated but first results from sensitivity
simulations with increased CO emissions show only small reductions in OH,
resulting in an increase of methane lifetime of less than 0.2 years.
7.
Summary and outlook
The data assimilation and modelling of global reactive gases in the MACC project
has achieved a mature state which is ready to be transformed into a fully operational
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O. Stein et al.
service under the European GMES initiative. This paper provides an overview about
the main product lines and services of the reactive gases component in MACC
including the efforts to validate such products. The focus here has been placed on the
pre-operational MACC-IFS-MOZ system, but we would like to point out that a
second forecast stream with a different model set-up – using the TM5 chemistry
transport model (Huijnen et al. 2010) instead of MOZART – was run in a research
mode almost throughout the entire project duration (Huijnen et al. 2011a).
Furthermore, the reactive gases team started to integrate the codes of the chemistry
modules of MOZART, TM5 and the French MOCAGE model (Peuch et al. 1999)
directly into the weather model IFS in order to avoid inconsistencies that are due to
the duplication of transport processes in IFS and the chemistry transport model
occurring in the present set-up that uses a coupling software (Huijnen et al. 2011b).
This C-IFS model also makes more efficient use of computing resources and will
facilitate the coupling of reactive gases, aerosol and greenhouse gases processes,
which will improve the overall consistency of the MACC data assimilation and
forecasting system.
The main output from the reactive gases project in MACC are daily NRT
forecasts and a comprehensive, validated reanalysis for the period 2003–2010.
Ozone, carbon monoxide and to some extent also NOx in these runs are constrained
by 4D-Var data assimilation. In the context of non-CO2 greenhouse gas emission
and concentration trends, the MACC reanalysis is only of limited value, because it
spans a relatively short period and suffers from some inconsistencies in the time
series due to changes in the assimilated observations. The project can offer results
from a standalone MOZART simulation, which appears to capture the interannual
variability of the methane lifetime rather well. Data sets and graphical products from
the reanalysis and the NRT forecasts are made available through the MACC project
web pages and via a fully interoperable data service with interactive plotting
capabilities at the Forschungszentrum Jülich. Validation of the MACC-IFS-MOZ
system has been performed using various ground-based, aircraft and satellite data
sets. The validation of the NRT system remains challenging, because only very few
data that are suitable for evaluating model systems with grid resolutions of several 10
kms are transmitted in NRT, and such data cannot often be freely accessed.
Due to the relatively poor information content that current satellite data products
can provide on tropospheric reactive gases concentrations and their vertical structure,
the quality of the MACC system is also strongly dependant on the availability of
accurate emissions inventories. The MACC project contributed to the development of
new inventories on emissions of short-lived gases from anthropogenic activities and
developed a new system to monitor emissions from open burning of biomass (GFAS).
The interplay between data assimilation, emissions and the model system remains an
active area of research in the successor project MACC-II.
Acknowledgements
We acknowledge all colleagues from the MACC project for their contributions to building,
running and validating the MACC data assimilation and modelling system. This study was
funded by the European Commission under the framework programme 7 (contract number
218793). ECMWF and Forschungszentrum Jülich are gratefully acknowledged for the
provision of computer hardware and computer time. The ground-based data presented in this
paper were obtained from the Global Atmospheric Watch (GAW) network and from
Umweltbundesamt (UBA), Germany. Aircraft data are from the European MOZAIC project.
Journal of Integrative Environmental Sciences
13
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