Analyzing the causes and spatial pattern of the European 2003 carbon flux anomaly using seven models

Vetter, M.; Churkinа, Galina; Jung, Martin; Reichstein, Markus; Zaehle, Sönke; Bondeau, Alberte; Chen, Y.; Ciais, Philippe; Feser, Frauke; Freibauer, Annette; Geyer, Ralf; Jones, Chris D.; Papale, Dario; Tenhunen, John; Tomelleri, Enrico; Trusilova, Kristina; Viovy, Nicolas; Heimann, Martin

doi:10.5194/bg-5-561-2008

Cited by 148 publications

(134 citation statements)

References 77 publications

(85 reference statements)

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“…The comparison of the fluxes simulated by the two models shows that ORCHIDEE and ISBA-A-gs tend to simulate high and low GPP values, respectively. Less discrepancies are observed for the net ecosystem flux (NEE) and the differences between the two models have the same magnitude as the local differences found by Vetter et al (2008) using four vegetation models over Europe. Both models use equilibrium assumptions between the plant productivity and Reco.…”

Section: Carbon Fluxesmentioning

confidence: 75%

Modelling LAI, surface water and carbon fluxes at high-resolution over France: comparison of ISBA-A-gs and ORCHIDEE

et al. 2012

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Abstract. The Leaf Area Index (LAI) is a measure of the amount of photosynthetic leaves and governs the canopy conductance to water vapor and carbon dioxide. Four different estimates of LAI were compared over France: two LAI products derived from satellite remote sensing, and two LAI simulations derived from land surface modelling. The simulated LAI was produced by the ISBA-A-gs model and by the ORCHIDEE model (developed by CNRM-GAME and by IPSL, respectively), for the 1994-2007 period. The two models were driven by the same atmospheric variables and used the same land cover map (SAFRAN and ECOCLIMAP-II, respectively). The MODIS and CYCLOPES satellite LAI products were used. Both products were available from 2000 to 2007 and this relatively long period allowed to investigate the interannual and the seasonal variability of monthly LAI values. In particular the impact of the 2003 and 2005 droughts were analyzed. The two models presented contrasting results, with a difference of one month between the average leaf onset dates simulated by the two models, and a maximum interannual variability of LAI simulated at springtime by ORCHIDEE and at summertime by ISBA-Ags. The comparison with the satellite LAI products showed that, in general, the seasonality was better represented by ORCHIDEE, while ISBA-A-gs tended to better represent the interannual variability, especially for grasslands. While the two models presented comparable values of net carbon fluxes, ORCHIDEE simulated much higher photosynthesis rates than ISBA-A-gs (+70 %), while providing lower transpiration estimates (−8 %).

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Section: Carbon Fluxesmentioning

confidence: 75%

Modelling LAI, surface water and carbon fluxes at high-resolution over France: comparison of ISBA-A-gs and ORCHIDEE

et al. 2012

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“…The estimated carbon fluxes are also hardly examined by comparing with the bottom-up modeling results because there is little consensus among different terrestrial ecosystem models in terms of simulating the net ecosystem productivity. Different models could occasionally exhibit a reasonable correspondence regarding the NEP anomaly, such as the anomaly caused by the 2003 heat wave in Europe, but it is generated by partly different processes in different models (Vetter et al, 2008). The simulated components, for example, GPP and Respiration, of the terrestrial carbon cycle often exhibit better correlation between models, a comparison of GPP among four models (LPJmL, MOD17+, ANN, and FPA + LC), however, still show signs of fundamental differences (Jung et al, 2007).…”

Section: Discussionmentioning

confidence: 99%

“…9b). The reported positive anomaly in 2003 has been attributed to a continent-wide heat wave during the summer Vetter et al, 2008), although Rayner et al (2008) deduced from a multi-year inversion that a significant anomaly was centered in February 2003, rather than in the summer time of that year. Our inverted monthly CO 2 flux shows that positive anomalies in April-June and July-September (Fig.…”

Section: Variation Of Inverted Terrestrial Fluxes With Climatic Condimentioning

confidence: 99%

Recent global CO<sub>2</sub> flux inferred from atmospheric CO<sub>2</sub> observations and its regional analyses

Deng

Chen

2011

Biogeosciences

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Abstract. The net surface exchange of CO 2 for the years 2002-2007 is inferred from 12 181 atmospheric CO 2 concentration data with a time-dependent Bayesian synthesis inversion scheme. Monthly CO 2 fluxes are optimized for 30 regions of the North America and 20 regions for the rest of the globe. Although there have been many previous multiyear inversion studies, the reliability of atmospheric inversion techniques has not yet been systematically evaluated for quantifying regional interannual variability in the carbon cycle. In this study, the global interannual variability of the CO 2 flux is found to be dominated by terrestrial ecosystems, particularly by tropical land, and the variations of regional terrestrial carbon fluxes are closely related to climate variations. These interannual variations are mostly caused by abnormal meteorological conditions in a few months in the year or part of a growing season and cannot be well represented using annual means, suggesting that we should pay attention to finer temporal climate variations in ecosystem modeling. We find that, excluding fossil fuel and biomass burning emissions, terrestrial ecosystems and oceans absorb an average of 3.63 ± 0.49 and 1.94 ± 0.41 Pg C yr −1 , respectively. The terrestrial uptake is mainly in northern land while the tropical and southern lands contribute 0.62 ± 0.47, and 0.67 ± 0.34 Pg C yr −1 to the sink, respectively. In North America, terrestrial ecosystems absorb 0.89 ± 0.18 Pg C yr −1 on average with a strong flux density found in the south-east of the continent.

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“…Upscaling exercises of eddy covariance based carbon fluxes to large regions has been conducted for the US (Xiao et al, 2008, Yang et al, 2007 and Europe Papale and Valentini, 2003;Vetter et al, 2008), which are both characterized by a comparatively dense network of towers. The upscaling principle generally employs the training of a machine learning algorithm to predict carbon flux estimates based on measured meteorological data, remotely sensed vegetation properties, and vegetation type.…”

Section: Introductionmentioning

confidence: 99%

Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model

2009

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Abstract. Global, spatially and temporally explicit estimates of carbon and water fluxes derived from empirical up-scaling eddy covariance measurements would constitute a new and possibly powerful data stream to study the variability of the global terrestrial carbon and water cycle. This paper introduces and validates a machine learning approach dedicated to the upscaling of observations from the current global network of eddy covariance towers (FLUXNET). We present a new model TRee Induction ALgorithm (TRIAL) that performs hierarchical stratification of the data set into units where particular multiple regressions for a target variable hold. We propose an ensemble approach (Evolving tRees with RandOm gRowth, ERROR) where the base learning algorithm is perturbed in order to gain a diverse sequence of different model trees which evolves over time.We evaluate the efficiency of the model tree ensemble (MTE) approach using an artificial data set derived from the Lund-Potsdam-Jena managed Land (LPJmL) biosphere model. We aim at reproducing global monthly gross primary production as simulated by LPJmL from 1998-2005 using only locations and months where high quality FLUXNET data exist for the training of the model trees. The model trees are trained with the LPJmL land cover and meteorological input data, climate data, and the fraction of absorbed photosynthetic active radiation simulated by LPJmL. Given that we know the "true result" in the form of global LPJmL simulations we can effectively study the performance of the MTE upscaling and associated problems of extrapolation capacity.We show that MTE is able to explain 92% of the variability of the global LPJmL GPP simulations. The mean spatial pattern and the seasonal variability of GPP that constitute the largest sources of variance are very well reproduced Correspondence to: M. Jung (mjung@bgc-jena.mpg.de) (96% and 94% of variance explained respectively) while the monthly interannual anomalies which occupy much less variance are less well matched (41% of variance explained). We demonstrate the substantially improved accuracy of MTE over individual model trees in particular for the monthly anomalies and for situations of extrapolation. We estimate that roughly one fifth of the domain is subject to extrapolation while MTE is still able to reproduce 73% of the LPJmL GPP variability here. This paper presents for the first time a benchmark for a global FLUXNET upscaling approach that will be employed in future studies. Although the real world FLUXNET upscaling is more complicated than for a noise free and reduced complexity biosphere model as presented here, our results show that an empirical upscaling from the current FLUXNET network with MTE is feasible and able to extract global patterns of carbon flux variability.

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Analyzing the causes and spatial pattern of the European 2003 carbon flux anomaly using seven models

Cited by 148 publications

References 77 publications

Modelling LAI, surface water and carbon fluxes at high-resolution over France: comparison of ISBA-A-gs and ORCHIDEE

Modelling LAI, surface water and carbon fluxes at high-resolution over France: comparison of ISBA-A-gs and ORCHIDEE

Recent global CO<sub>2</sub> flux inferred from atmospheric CO<sub>2</sub> observations and its regional analyses

Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model

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Analyzing the causes and spatial pattern of the European 2003 carbon flux anomaly using seven models

Cited by 148 publications

References 77 publications

Modelling LAI, surface water and carbon fluxes at high-resolution over France: comparison of ISBA-A-gs and ORCHIDEE

Modelling LAI, surface water and carbon fluxes at high-resolution over France: comparison of ISBA-A-gs and ORCHIDEE

Recent global CO&lt;sub&gt;2&lt;/sub&gt; flux inferred from atmospheric CO&lt;sub&gt;2&lt;/sub&gt; observations and its regional analyses

Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model

Contact Info

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Recent global CO<sub>2</sub> flux inferred from atmospheric CO<sub>2</sub> observations and its regional analyses