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Report on the benchmarking of the GMES Core Services
Table of content
1
Introduction ____________________________________________________________ 2
2
Benchmarking of MACC-2 carbon fluxes_____________________________________ 3
2.1
Global annual totals ________________________________________________________ 3
2.2
Long term means __________________________________________________________ 4
2.3
Inter-annual variability _____________________________________________________ 7
2.4
Long term trend ___________________________________________________________ 8
2.5
Seasonal flux variations ____________________________________________________ 11
3
Benchmarking of GEOLAND2 Leaf Area Index ______________________________ 12
4
Conclusions____________________________________________________________ 15
5
References _____________________________________________________________ 17
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1 Introduction
The objectives of this deliverable are to analyse the information brought by CARBONES in
comparison to existing GMES core services that provide information on the carbon cycle. For
that we have only compared CARBONES products against two services, MACC-2 and
GEOLAND2. We did not include MYOCEAN as this project currently does not provide
carbon cycle product (only in progress). We briefly detail the two products that are compared
and benchmarked:
MACC-2:
This product provides CO2 surface fluxes over more than three decades, from 1979 to 2011,
at resolution 3.75° x 2.5° (longitude-latitude) and 3-hourly, based on 136 CO2 mole fraction
station records from several large databases. The four databases include both in situ
measurements made by automated quasi-continuous analysers and irregular air samples
collected in flasks and later analyzed in central facilities.
The flux inversion builds on a variational Bayesian inversion system, like the 4D-Var data
assimilation system used in MACC-II, which allows the fluxes to be estimated at relatively
high resolution over the globe. It uses a single 33-year inversion window, therefore enforcing
the physical and statistical consistency of the inverted fluxes. Fluxes and mole fractions are
linked in the system by a global atmospheric transport model. A series of flux inventories,
flux climatologies and flux error models regularizes the solution to the flux inference
problem. The references for that product are Chevallier et al. 2005, 2007, 2010.
The inversion results can be downloaded in the form of NetCDF files from: http://wwwlscedods.cea.fr/invsat/PYVAR11_MACC/V1/
Most importantly MACC-2 shares the same transport model as CARBONES and use as a
background the fluxes from ORCHIDEE but without any prior optimization. These
similarities should be kept in mind when comparing CARBONES to MACC-2 below.
GEOLAND2:
We use the Geoland2 Biophysical Parameter (BioPar) LAI product and not the GEOLAND2 net
ecosystem carbon flux as this later product was not directly available and does not represent the
most robust outcome of this project. For the recent period (1999-present) it is derived from
SPOT/VEGETATION reflectances, using a neural network (Baret et al., 2010). This product has been
shown to be more accurate than its competitors (Camacho et al., 2010). It is available at global scale,
at
a
1km
spatial
resolution,
on
a
decadal
time
frequency
(http://www.geoland2.eu/portal/service/ListService.do?serviceCategoryId=CA80C981).
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Below we only compare for one year, 2008, CARBONES estimated LAI against GELOAND
LAI. A more complete comparison over a longer period is underway.
Similarly to the report D610 on the information content brought by CARBONES, we provide
for the net carbon flux comparison (MACC2) a description of:

The global net annual carbon balance by apportioning between key regions of the
globe like North America, Europe, North Eurasia, the Tropics and key ocean basins

The inter-annual variability of the sub-continental regions and ocean basins

The trend in the net carbon uptake of the lands in comparison with that of the oceans

The spatial distribution of the forest carbon stocks compared with “observations”
mapped globally (produced by CARBONES)
We also stress that the report mainly evaluates the last version of the CARBONES product
(Version V2.0). When making the comparison of CARBONES products, the uncertainties in
both CARBONES and GMES products are not considered yet, because of lack of time.
2 Benchmarking of MACC-2 carbon fluxes
We will only discuss below the main differences between CARBONES results and MACC-2
fluxes. Note that CARBONES and MACC-2 have used different fossil fuel emissions so that
a direct comparison of the natural fluxes, which should be considered as a residual flux, are
biased. In order to cope with that problem we applied a correction to both products: we took
the total estimated flux (natural + fossil) and then subtract a common fossil fuel emission
(EDGAR v4.1). In the remaining we thus compare the so-called “fossil corrected fluxes”.
Note that the EDGARv4.1 is very close to the emissions used by IER to derive the
CARBONES fossil fuel product.
2.1
Global annual totals
Figure 2.1 displays for both products the natural global total fluxes (land plus ocean), and the
global fossil fuel fluxes. The year-to-year variations of the global total flux (land plus ocean)
reflect the variations in global atmospheric CO2 growth rate. Surprisingly, they are significant
differences across the two products although they have seen similar atmospheric observations.
These differences in terms of global annual growth rate are still under investigations as no
clear explanation has been found yet. However, we still find the same large fluctuations
associated with the occurrence of El Niño and La Niña conditions. For instance, in 1998,
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2002, 2007, the El Niño conditions led to a smaller carbon uptake by the land and ocean
ecosystems. Compared to a comparison with other atmospheric inversions in D610 reports,
only small differences in prescribed fossil fuel emissions are present (note that this is taken
care with the “fossil correction” mentioned above).
As for the global land versus ocean partition, the main difference arises from the ocean
component. In the case of CARBONES, the increase of carbon uptake by the ocean after 2002
and the large uptake prior to 1995 are not present in MACC-2. Note that MACC-2 only uses a
climatological air-sea flux as prior (Takashi et al., 2009) with relatively small errors. The
MACC-2 thus only introduces small year-to-year ocean flux variations. Whether
CARBONES ocean flux is more realistic still needs to be proven by independent data, but at
least the product fits the surface pCO2 data. As a consequence the mean land uptake in
CARBONES after 2002 is significantly smaller than in MACC-2.
Figure 2.1: Annual mean posterior flux estimate for CARBONES (in red) and MACC2 (in black).
Shown here are a) natural “fossil corrected” global total carbon exchange, b) fossil fuel emission, c)
natural “fossil corrected” total land, and d) natural total ocean fluxes.
2.2
Long term means
We computed the long-term mean fluxes for the two products over the 1990-2009 period.
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Figure 2.2 displays the total fluxes for the globe and three latitudinal bands as well as the
partition between the land and ocean. From the perspective of the long-term mean, the ocean
flux difference is significant with more uptake in CARBONES (around 0.4 to 0.5 PgC/year)
over the period, that is due mainly to a small tropical outgassing. As a consequence, the land
carbon uptake in CARBONES is smaller than in MACC-2. The difference concerns all three
latitudinal bands with 0.5 PgC/year less uptake in the north, 0.2 PgC/year in the south, and a
decrease of the tropical source of around 0.2 PgC/yr.
Figure 2.2: Mean natural fluxes for the period 1991-2008 of CARBONES (red) and MACC2 (black).
Shown here are total (first column), natural “fossil corrected” land (second column) and natural
ocean (third column) carbon exchange aggregated over the Globe, the Northern hemisphere (roughly
> 25N), the tropic (roughly 25S-25N) and the southern hemisphere (roughly < 25S).
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We briefly investigate the long term mean natural fluxes within continental/basin-scale
subdivisions for a breakdown of the northern hemisphere into three selected continental/basin
regions: North America, Europe, North Asia, and North Atlantic, North Pacific (Figure 2.3).
For the ocean basin, CARBONES provide a slightly larger sink over the North Pacific. On the
other hand, for the land regions CARBONES provides a smaller sink in Europe and North
Asia of around 0.25 PgC/year for both regions. From a biogeochemical point of view the sink
obtained by MACC-2 over Europe, around 0.6 PgC/year, is at the upper limit of admitted
ranges. For instance two recent synthesis on the European carbon uptake by Schulze et al.
2009 and more recently by Luyssaert et al. 2012 provide typical CO2 sink of 0.35 +/- 0.3
PgC/year on average using an ensemble of approaches, from in situ inventories (forest
biomass inventories for instance) to ecosystem models. CARBONES seems thus to be more
in line with these estimates. The correction of the ORCHIDEE model parameters with a
shortening of the growing season, had thus an impact on the final estimates (with the use of
atmospheric observations).
Figure 2.3: As for Figure 2.2, but for three continental/basin-scale regions: North America,
Europe, North Asia, North Atlantic and North Pacific.
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Inter-annual variability
Figure 2.4 shows the inter-annual variability of land and ocean fluxes for the northern,
tropical and southern aggregates. The results represent annual means with the individual
model long-term means removed (a long-term mean defined over the 20 years). For the ocean,
the differences between the two products provide mainly from the southern ocean, with no
specific large year-to-year variations but mainly oscillations over few years, discussed in
section 2.1. For the land, the IAV in the net ecosystem fluxes differ mainly over the tropics
and the southern land. The larger southern variations in CARBONES are likely due to a larger
sensitivity of the ecosystem model ORCHIDEE to climate fluctuations after the optimization
against FluxNet data. Possible reasons are:

First there is much fewer FluxNet sites in the southern hemisphere than in the
northern hemisphere

The plant species in the southern hemisphere slightly differ than those in the northern
hemisphere,

Given these two points, we suspect that the optimization of ORCHIDEE parameters
for 10 Plant Functional Types was less effective for these southern hemisphere
ecosystems and may have led to a too large model sensitivity to climate anomalies in
the southern land
However, these points are under investigations and the true flux IAV might also be larger than
predicted by MACC-2.
For the tropical land, a mark difference appear in 2001, 2002 and 2003, with CARBONES
estimating an ecosystem carbon uptake compensating for the emission through biomass
burning while MACC-2 has a positive flux toward the atmosphere of around 0.5 PgC/year.
Overall, the pictures are similar with larger IAV over the tropics than in the north in both
estimates and similar phasing. However, CARBONES indicate a larger IAV in the southern
land that needs to be further investigated.
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Figure 2.4: Annual mean average of the CARBONES (red) and MACC2 (black) flux estimates. Shown
here are land fluxes for northern, tropics and south regions as well as for the global total, for land and
ocean.
2.4
Long term trend
In order to investigate possible trend in the net carbon exchange, we further investigated the
smooth mean annual fluxes for the large latitudinal bands (3 years smoothing window). The
results in figures 2.5, indicate that:

As mentioned above the global increase of the land carbon uptake after 2002 is not
present in CARBONES but with a rather similar trend in the ocean flux.

No clear differences occur in the long term trend of the northern land carbon uptake,
with relatively similar pattern between CARBONES and MACC-2. The increased
carbon uptake in the second half the 2000s is present in both products.
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
The Tropical pattern significantly differs between MACC-2 and CARBONES with no
trend in CARBONES while MACC-2 provide a large increase of the land sink in the
2000s. The use of few tropical FluxNet sites and MODIS-NDVI data changed
sufficiently the photosynthesis and respiration parameters in ORCHIDEE to decrease
the sensitivity of the ORCHIDEE land model to the recent climate trends. Such
patterns is currently under investigation with the data acquired over the Amazon basin
(Amazonica project).

Finally for the southern land, no clear long term trend differences are visible
Figure 2.5: Annual mean smooth average (smoothing with a 3 year window) of the CARBONES (red)
and MACC2 (black) flux estimates. Shown here are land fluxes for northern, tropics and south regions
as well as for the global total, for land and ocean.
We further investigated the results for the continental breakdown of the northern land (Figure
2.6). Over North America, CARBONES provides a small trend toward increased carbon sink
during the 2000s not present in MACC-2, of around 0.5 PgC/yr between the beginning and
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late 2000s. Reversely, CARBONES provides nearly no long-term trend over Europe while
MACC-2 would indicate an increase of the carbon sink in the 2000s as in CARBONES for
North America. There are clearly compensating effects between North America and Europe,
that results from the assimilation of the atmospheric CO2 data, an overall large scale
constraint. Interestingly, North Asia shows a similar significant increase of the land carbon
uptake over the whole 20 years period in both products, although slightly larger in MACC-2.
Such trend is currently debated. Indeed it is directly linked to the estimated increase of fossil
fuel emissions over North Asia. Recently Guan et al. 2012, estimated that around the 2000,
reported emission in china might have been underestimated by 1 Pg over few year. Such bias
could directly transfer into a roughly equivalent additional land carbon sink around years
2000 and thus change the pattern of the long term trend. The investigation of such long term
trend will be further investigated with the results of the version V3 of CARBONES where
only the land model parameters are optimized with the atmospheric data. This test will
indicate whether climate induced effects currently modelled in ORCHIDEE could indeed
explain such increase in the land carbon sink over north Asia.
Figure 2.6: As for Figure 2.5, but for three continental scale regions: North America, Europe
and North Asia.
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Seasonal flux variations
Figure 2.7 shows the mean seasonal cycle on land and ocean for the latitudinal aggregate
regions. Note that the land and ocean panels use different numerical scales. The only major
differences between the two products arise in the northern land with a significantly smaller
amplitude of the seasonal cycle in CARBONES. This is due to the assimilation of FluxNet
NEE data in CARBONES that led to reduction of the maximum photosynthetic capacity
(Vcmax) for some northern plant functional types. Note that the phase correction through the
assimilation of MODIS-NDVI data in CARBONES is coherent with the constraint brought by
the assimilation of atmospheric CO2 data only in MACC-2.
Figure 2.7: Mean seasonal cycle of the carbon exchange for CARBONES (red) and MACC2 (black) flux
estimates. Shown here are the natural land (first column) and natural ocean (second column) carbon
exchange aggregated over the Northern hemisphere (> 30N), the tropic (30S-30N) and the southern
hemisphere (< 30S).
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3 Benchmarking of GEOLAND2 Leaf Area Index
Figure 1: CARBONES monthly averaged LAI (weighted by PFT fraction) for January to December 2008.
Figure 2: GEOLAND2 monthly averaged LAI for January to December 2008.
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Figures 1 and 2 show the monthly averaged LAI for the CARBONES and GEOLAND2
products respectively (with the difference shown in Figure 3) for 2008. Overall CARBONES
has a higher monthly LAI both in the summer months in northern temperate and boreal
regions and throughout the year in the tropical rainforest regions. In contrast to this, in July
and August the GEOLAND2 product contains higher LAI values for the midlatitudes of
Eurasia and patches of North America, roughly corresponding to regions dominated by
temperate and boreal needleleaf evergreen and temperate broadleaved deciduous PFTs. In
addition, areas where the fractions of tropical raingreen and C4 crop PFTs are high tend to
have a lower LAI value in the CARBONES product between October to March, and the same
is true in August and September in regions with a high fraction of C4 grasses.
Figure 3: Difference maps of monthly averaged LAI between GEOLAND2 and CARBONES (GEOLAND2 –
CARBONES) for January to December 2008.
Discerning which of the two products gives a more accurate estimate of the absolute LAI
value will require further investigation and comparison with ground-based measurements.
LAI products derived from satellite data have been shown to vary widely in their absolute
values (Garrigues et al. 2008); indeed this was the reason for not using these products in the
CARBONES optimizations, and for using normalized satellite-derived NDVI and simulated
fAPAR instead. The GEOLAND2 product represents one of the most advanced algorithms in
that it utilizes the advantages of two existing algorithms that are used to produce the MODIS
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and CYCLOPES LAI products. It has been shown in preliminary investigations to be an
improvement on existing products, both in terms of spatial distribution and absolute values, as
well as inter-annual variability, when compared to several available ground-truth maps
(Camacho et al., 2010; 2011).
However, the BioPar validation report (Baret at al., 2010) mentions that lower scores against
ground truth data are obtained for Evergreen Broadleaf Forest and Needleleaf Forest. This is
explained by the fact that these biomes present a high clumping index and therefore the
effective LAI derived from satellite measurements underestimates the actual LAI. This
probably explains the fact that even in winter the northern temperate latitudes show a higher
modeled LAI. The non-zero modeled LAI may be attributed to mostly therefore to the
evergreen or needleleaf PFTs, and the lower observed LAI could be underestimated because
of this clumping effect.
At the same time, the maximum LAI parameter is not well constrained by the fluxes for any
PFT in the CARBONES optimizations, and it is sometimes correlated with other parameters
that control photosynthesis in ORCHIDEE. Therefore the maximum LAI, and therefore the
absolute values, in ORCHIDEE perhaps cannot be fully trusted and may be overestimated.
Potentially it may be useful in the future to use the new GEOLAND2 product in conjunction
with the FluxNet data in the assimilations, in order to provide more information to constrain
the absolute magnitude of the LAI in ORCHIDEE. However satellite-derived LAI has been
shown to saturate at high LAI, and thus until complete validation studies of the GEOLAND2
product have been published, further analyses and more definitive conclusions cannot be
achieved.
For temperate and boreal evergreen regions where the CARBONES LAI tends to be lower
than that of GEOLAND2, it is possible that this highlights a structural error in the model
relating to the modeling of evergreen leaf phenology, which isn’t explicitly taken into
account. The same may be true for tropical deciduous PFTs (tropical raingreen trees and C4
grasses), as the phenology schemes in ORCHIDEE sometimes result in markedly different
temporal variations when compared to satellite-derived NDVI. Determining which
meteorological or environmental driver is the dominant control over tropical leaf phenology is
a complex and continuing area of investigation.
However, there is a high positive temporal correlation (>~0.6) globally between the
GEOLAND2 and CARBONES monthly LAI time series (figure 4), which gives confidence in
the temporal consistency of the two products. The correlation is lower in areas where there is
a high fraction of boreal deciduous trees (NE Eurasia), which may again point to a missing
process in the model phenology, perhaps relating to the role of photoperiod as a phenological
driver. The strong negative correlation seen in southern Brazil and the Congo Basin may also
be due to the lack of representation of evergreen leaf phenology in the model. Other areas of
low correlation are dominated by croplands (south of the Great Lakes in the USA and parts of
India) where the physical processes describing crop dynamics may be missing or incorrect.
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Figure 3.4: Correlation between the GEOLAND2 monthly averaged LAI product and CARBONES
monthly averaged LAI optimized simulations.
4 Conclusions
We presented in this report a first comparison of CARBONES products against the MACC-2
net ecosystem carbon exchange and the GEOLAND-2 LAI product. This comparison was
performed to highlight the information content brought by CARBONES and can be taken as a
possible benchmarking of the GMES core product. First one should resume the main
differences between the systems that could explain the product differences:

MACC2 : Such product is similar to CARBONES in the sense that it uses the same transport
model (LMDz) and the same set of atmospheric observations and inverse set up to optimize
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the fluxes from atmospheric CO2 gradients. However, MACC-2 did not use the information
content from the FluxNet sites (net ecosystem carbon exchange and latent heat flux) and the
satellite information (in this case MODIS-NDVI) to constrain the time of the photosynthesis
activity.

GEOLAND2: We only used the Leaf Area Index from that project given that the net land
carbon uptake was not the primary objective of GEOLAND2. In the comparison we
considered that GEOLAND2 provides one of the most advanced product for LAI currently
available.
Overall, the comparison highlighted several significant differences that should (and will) be further
investigated before drawing specific conclusion about the strengths and weaknesses of each
approach and the land/ocean carbon budgets. As for the net carbon fluxes (comparison with MACC2) the ocean year-to-year flux variations estimated from the surface pCO2 measurements (Takahashi
database) with a statistical model (Neural network) in CARBONES and further corrected by the
atmospheric CO2 data significantly differ from those obtained in MACC-2. Although they are driven
by pCO2 measurements the variations in CARBONES need to be further confirmed by independent
proxies before drawing strong conclusion about possible weaknesses of MACC-2 for the air-sea flux
inter-annual variations. Over land, the CARBONES product provides net flux variations that are
coherent with MACC-2 with some latitudinal/continental differences. These differences, although
larger over the southern and tropical regions also concern the northern continental regions. They are
tightly linked to the constraints brought by the FluxNet and MODIS-NDVI data, with a direct impact
on the year-to-year flux variations and to a lower extend the long-term trend, through the
adjustment of the land model sensitivity to climate anomalies. These changes are currently under
deeper investigation, to specifically draw the recommendation about the future model multi-data
fusion schemes.
As for the LAI product of GEOLAND2, the comparison is only preliminary and will be extend over a
longer period (several years corresponding to GEOLAND2 product). Overall, we obtain higher LAI
values in CARBONES compared to GEOLAND2 during the peak of the growing season (for northern
and southern ecosystems) that do not however bias the simulated photosynthesis fluxes (the net
land carbon fluxes weakly depend on the maximum LAI above at high values). More importantly the
timing of the LAI appears to be rather similar between the two products. This feature will be
investigated in more details using “10-day” mean LAI values as originally produced in GEOLAND2 in
order to analyse in details possible small phase shift between the two products.
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