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Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations
Jonathan G. Martin,Markus Reichstein +1 more
- Vol. 2012
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Abstract:
We upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (MTE). We trained MTE to predict site-level gross primary productivity (GPP), terrestrial ecosystem respiration (TER), net ecosystem exchange (NEE), latent energy (LE), and sensible heat (H) based on remote sensing indices, climate and meteorological data, and information on land use. We applied the trained MTEs to generate global flux fields at a 0.5 degrees x 0.5 degrees spatial resolution and a monthly temporal resolution from 1982 to 2008. Cross-validation analyses revealed good performance of MTE in predicting among-site flux variability with modeling efficiencies (MEf) between 0.64 and 0.84, except for NEE (MEf = 0.32). Performance was also good for predicting seasonal patterns (MEf between 0.84 and 0.89, except for NEE (0.64)). By comparison, predictions of monthly anomalies were not as strong (MEf between 0.29 and 0.52). Improved accounting of disturbance and lagged environmental effects, along with improved characterization of errors in the training data set, would contribute most to further reducing uncertainties. Our global estimates of LE (158 +/- 7 J x 10(18) yr(-1)), H (164 +/- 15 J x 10(18) yr(-1)), and GPP (119 +/- 6 Pg C yr(-1)) were similar to independent estimates. Our global TER estimate (96 +/- 6 Pg C yr(-1)) was likely underestimated by 5-10%. Hot spot regions of interannual variability in carbon fluxes occurred in semiarid to semihumid regions and were controlled by moisture supply. Overall, GPP was more important to interannual variability in NEE than TER. Our empirically derived fluxes may be used for calibration and evaluation of land surface process models and for exploratory and diagnostic assessments of the biosphere.read more
Citations
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The large mean body size of mammalian herbivores explains the productivity paradox during the Last Glacial Maximum
Dan Zhu,Philippe Ciais,Jinfeng Chang,Jinfeng Chang,Gerhard Krinner,Shushi Peng,Nicolas Viovy,Josep Peñuelas,Sergey A. Zimov +8 more
TL;DR: It is found that the larger mean body size of mammalian herbivores than today is the crucial clue to explain the productivity paradox, due to a more efficient exploitation of grass production by grazers with a large body size.
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Modeling Evapotranspiration over China's Landmass from 1979 to 2012 Using Multiple Land Surface Models: Evaluations and Analyses
Shaobo Sun,Baozhang Chen,Quanqin Shao,Jing M. Chen,Jiyuan Liu,Xuejun Zhang,Huifang Zhang,Xiaofeng Lin +7 more
TL;DR: In this article, a multiple-LSM ensemble-averaged evapotranspiration (ET) product (LSMs-ET) was developed and its spatial-temporal variations were analyzed for the China landmass over the period 1979-2012.
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Effects of atmospheric aerosols on terrestrial carbon fluxes and CO2 concentrations in China
TL;DR: In this article, the authors used a regional climate model, RegCM4, coupled with the Yale Interactive terrestrial Biosphere model (YIBs) to assess the effects of the current aerosol loading on terrestrial carbon fluxes and atmospheric CO2 concentrations during 2006-2015 over China.
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Spatial pattern of GPP variations in terrestrial ecosystems and its drivers : Climatic factors, CO2 concentration and land-cover change, 1982-2015
Zhongyi Sun,Xiufeng Wang,Haruhiko Yamamoto,Hiroshi Tani,Guosheng Zhong,Shuai Yin,Enliang Guo +6 more
TL;DR: This study applied C-Fix model to estimate the net effect of each factor on GPP trends of 1982–2015, used an unsupervised classifier to group similar GPP trend behaviors, and analyzed the responses of GPP to changes in climatic, atmospheric and environmental drivers.
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Monitoring boreal forest biomass and carbon storage change by integrating airborne laser scanning, biometry and eddy covariance data
TL;DR: In this article, a comparison and integration of three methods commonly used to estimate the amount of forest ecosystem carbon (C) available for storage is presented, in particular, the representation of living above-and below-ground biomass change (net accumulation) using plot-level biometry and repeat airborne laser scanning (ALS) of three dimensional forest plot structure.
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