Independent land flux products
Global spatial-temporal patterns of ecosystem carbon fluxes were estimated using
different sources of observational data. These data-oriented estimates will be used as an
independent dataset to evaluate gross carbon flux estimates from CARBONES.
1) Description of the products
Global spatial-temporal patterns of carbon and energy fluxes were created using a
machine-learning algorithm that upscales site-level eddy covariance measurements to
the globe based on satellite and meteorological observations (Jung et al. 2011). Using
this algorithm, patterns of gross primary productivity, ecosystem respiration and latent
and sensible heat at 0.5° x 0.5° spatial resolution and monthly time step (1982-2010)
were produced (Fig. 1).
Figure 1: Maps of upscaled gross primary productivity for January and July 1982 (Jung et al. 2011)
Site-level estimates of gross primary productivity (GPP) and ecosystem respiration
(Reco) were derived from the FLUXNET eddy covariance measurements according to
the method of Lasslop et al. (2010). A model tree ensemble (MTE) was trained against
these site-level GPP estimates based on satellite observations of FAPAR (fraction of
photosynthetic active radiation) and meteorological data as explanatory variables. In a
next step the trained MTEs have been applied to gridded patterns of these explanatory
variables to derive global patterns of GPP and Reco (Jung et al. 2009, Jung et al. 2011).
Upscaled estimates of gross primary productivity and ecosystem respiration can be used
to benchmark results of the CARBONES CCDAS. These datasets can be used to compare
mean annual spatial patterns, the seasonality or relationships between carbon fluxes
and climate patterns.
2) Product uncertainties
The main source of uncertainty in the MTE upscaling products originates from the
representativeness of the FLUXNET eddy covariance station network. Some wide
geographical regions are not represented by measurement stations (e.g. Africa, Siberia,
South America, Tropical Asia). Nevertheless, the FLUXNET stations cover a wide range
of climatological conditions. Hence, the environmental representativeness is better than
the geographical representativeness. The extrapolation of carbon fluxes to
environmental conditions that are not represented by the FLUXNET dataset mainly
causes the uncertainty in flux estimates.
The uncertainty of upscaled fluxes was estimated based on the distribution of the
predicted fluxes from the model tree ensemble (Jung et al. 2009). Additionally, the error
of upscaled fluxes was estimated against eddy covariance site observation using crossvalidation (Jung et al. 2011). Based on these validation studies uncertain aspects and
robust patterns of the MTE upscaled patterns were identified.
Uncertain aspects are trends and anomalies of GPP estimates as well as estimates of net
ecosystem exchange and ecosystem respiration. The magnitude of anomalies and interannual variability is substantially underestimated as comparisons with ecosystem
models, atmospheric inversions and cross-validation have shown (Jung et al. 2011). As
trends are usually calculated based on anomalies, trend estimates from this dataset are
uncertain as well. Estimates of mean annual upscaled ecosystem respiration have higher
certainty than anomalies but still cannot be considered as robust patterns and they
might have an underestimation bias of 5-10%. Thus, anomalies and trends of GPP and
Reco from MTE should not be used as a robust benchmark dataset of CARBONES result.
Robust patterns that can be extracted from the MTE dataset are mean annual patterns
and the mean seasonal cycle of GPP. Mean annual GPP estimates from MTE compare
well with satellite-derived fluorescence measurements that are directly linked to
photosynthesis (Frankenberg et al. 2011). The uncertainty of mean annual GPP was
quantified based on the spread of GPP estimates from the ensemble (Fig. 2).
Uncertainties are high in some tropical regions and in regions with low vegetation cover
like in inner Australia or Siberian Tundra (Fig. 2). Considering these uncertainties, mean
annual and seasonal patterns of gross primary productivity can be used as independent
datasets to evaluate process-model simulations (e.g. Bonan et al. 2011) or CCDAS results
of gross primary production.
Figure 2: Spatial distribution of mean annual GPP (top) and associated uncertainties (bottom) as upscaled from the
FLUXNET by the MTE.
3) Product policy
The MTE upscaled patterns of carbon and water fluxes are available for scientific use on
request to Max Planck Institute for Biogeochemistry, Jena, Germany (Martin Jung).
Users of the dataset should consider and refer to results as described in Jung et al.
(2009, 2010 and 2011).
4) References
Bonan, G.B., Lawrence, P.J., Oleson, K.W., Levis, S., Jung, M., Reichstein, M., Lawrence,
D.M., Swenson, S.C. (2011): Improving canopy processes in the Community Land
Model version 4 (CLM4) using global flux patterns empirically inferred from
FLUXNET data. Journal of Geophysical Research - Biogeosciences, 116, G02014.
Frankenberg, C., Fisher, J.B., Worden, J., Badgley, G., Saatchi, S.S., Lee, J.-E., Toon, G.C.,
Butz, A., Jung, M., Kuze, A., Yokota, T. (2011): New global observations of the
terrestrial carbon cycle from GOSAT: Patterns of plant fluorescence with gross
primary
productivity.
Geophysical
Research
Letters,
38,
L17706,
doi:10.1029/2011GL048738.
Jung, M., Reichstein, M., Bondeau, A. (2009): Towards global empirical upscaling of
FLUXNET eddy covariance observations: validation of a model tree ensemble
approach using a biosphere model. Biogeosciences, 6, 2001-2013.
Jung, M., Reichstein, M., Ciais, P., Seneviratne, S.I., Sheffield, J., Goulden, M.L., Bonan, G.,
Cescatti, A., Chen, J., de Jeu, R., Dolman, A.J., Eugster, W., Gerten, D., Gianelle, D.,
Gobron, N., Heinke, J., Kimball, J., Law, B.E., Montagnani, L., Mu, Q., Mueller, B., Oleson,
K., Papale, D., Richardson, A.D., Roupsard, O., Running, S., Tomelleri, E., Viovy, N.,
Weber, U., Williams, C., Wood, E., Zaehle, S., Zhang, K. (2010): Recent decline in the
global land evapotranspiration trend due to limited moisture supply. Nature, 467,
951-954.
Jung, M., Reichstein, M., Margolis, H.A., Cescatti, A., Richardson, A.D., Arain, M.A., Arneth,
A., Bernhofer, C., Bonal, D., Chen, J., Gianelle, D., Gobron, N., Kiely, G., Kutsch, W.,
Lasslop, G., Law, B.E., Lindroth, A., Merbold, L., Montagnani, L., Moors, E.J., Papale, D.,
Sottocornola, M., Vaccari, F., Williams, C. (2011): Global patterns of land-atmosphere
fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance,
satellite, and meteorological observations. Journal of Geophysical Research Biogeosciences, 116, doi:10.1029/2010JG001566.