respiration model
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2020 ◽  
Author(s):  
Haimei Jiang ◽  
Haotian Ye ◽  
Yong Hao

<p>Eddy covariance data from Xilinhaote National Climatological Observatory in Xilin Gol League during growing seasons of 2010—2013 as well as MODIS data were used to validate an ecosystem respiration model based on enhanced vegetation index (EVI), land surface water index (LSWI) and land surface temperature (LST) in a semi-arid grassland of Inner Mongolia. The limitations of this remote sensing respiration model were also discussed. The results indicate that this model can successfully simulate the variations of nocturnal ecosystem respiration (Reco) in the growing seasons and between different years. The simulated nocturnal Reco also agreed remarkably with the observed Reco (R2=0.90, RMSE=0.02 mgCO2/(m2·s)). Moreover, the observed nocturnal Reco showed a good linear correlation with EVIs×Ws (R2=0.63), in which EVIs and Ws are response functions of EVI and LSWI on photosynthesis, respectively. The response of nocturnal Reco to LST was also found following the L-T equation (R2=0.39). In addition, the difference between responses of nocturnal Reco to EVIs×Ws and LST in the early, middle and late stages of the growing season is indicated as one principal source of the deviations of model results.</p>


2020 ◽  
Author(s):  
Saqr Munassar ◽  
Christoph Gerbig ◽  
Frank-Thomas Koch ◽  
Christian Rödenbeck

<p>Regional flux estimates over Europe have been calculated using the two-step inverse system of the Jena CarboScope Regional inversion (CSR) to estimate the annual CO<sub>2</sub> budgets for recent years, in cooperation with the research project VERIFY. The CSR system assimilates observational datasets of CO<sub>2</sub> mixing ratio provided by the Integrated Carbon Observation System (ICOS) across the European domain to optimize Net Ecosystem Exchange (NEE) fluxes computed from biosphere models at a spatial resolution of 0.25 degree. Ocean fluxes are assumed to be constant over time. Fossil fuel emissions are obtained from EDGAR_v4.3 and updated based on British Petroleum (BP) statistics. Therefore, only biosphere-atmosphere exchange fluxes are considered to be optimized against the atmospheric data.</p><p>In this study we focus on the impact of using a-priori fluxes from different biosphere and ocean models on the annual CO<sub>2</sub> budget of posterior fluxes. Results calculated using the Vegetation and Photosynthesis Respiration Model (VPRM) and Simple Biosphere/Carnegie-Ames Stanford Approach (SiBCASA) models show a consistent posterior interannual variability, largely independent of which prior fluxes are used, even though those prior fluxes show considerable differences on annual scales.</p>


2020 ◽  
Author(s):  
Yong Hao ◽  
Haimei Jiang ◽  
Haotian Ye

<p>Turbulent flux data observed in surface layer during growing seasons at Xilinhaote National Climatic Observatory and Jinzhou Agroecosystem Observatory and remote sensing data were analyzed to acquire main environmental factors and biological factors which drive the ecosystem respiration (R<sub>eco</sub>). Then the key driven factors of R<sub>eco</sub> were selected to optimize a semi-empirical ecosystem respiration model. Based on the new ecosystem respiration model, respiration part of Vegetation Photosynthesis and Respiration Model (VPRM) was optimized and its simulation effect of net ecosystem exchange (NEE) was validated in a semi-arid grassland ecosystem and a maize cropland ecosystem.</p><p>Compared to the linear temperature model, the nocturnal R<sub>eco</sub> simulated by the new ecosystem respiration model agreed remarkably better with the observed R<sub>eco</sub> (at Xilinhaote site, R<sup>2</sup> increased from 0.08 to 0.61 in 2010-2012; at Jinzhou site, R<sup>2</sup> increased from 0.13 to 0.55 in 2010). And the new ecosystem respiration model showed similar performance in predicting nocturnal R<sub>eco</sub> (at Xilinhaote site, R<sup>2</sup> increased from 0.32 to 0.57 in 2013; at Jinzhou site, R<sup>2</sup> increased from 0.33 to 0.61 in 2011).</p><p>This study also indicates that optimization of the respiration part of VPRM can improve the simulation effect of NEE during nighttime of the growing seasons in a semi-arid grassland ecosystem and a maize cropland ecosystem, R<sup>2</sup> between the modeled NEE and the observed NEE increased from 0.30 to 0.57 in the semi-arid grassland ecosystem and<sup> </sup>increased from 0.03 to 0.48 in the maize cropland ecosystem. However, in the whole time of the growing seasons, little difference was found between the modelled NEE by the original VPRM model and that by our modified VPRM model, probably for the reason that daytime NEE is mainly dominated by vegetation photosynthesis.</p>


2019 ◽  
Vol 225 (5) ◽  
pp. 2214-2230 ◽  
Author(s):  
Roberto L. Salomón ◽  
Linus De Roo ◽  
Jacek Oleksyn ◽  
Dirk J. W. De Pauw ◽  
Kathy Steppe

2019 ◽  
Vol 222 (3) ◽  
pp. 1167-1170 ◽  
Author(s):  
Michael G. Ryan ◽  
Shinichi Asao
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