Understanding the interactions between atmosphere and vegetation in changing climatic conditions is important so that we can predict the carbon sequestration potential of ecosystems. Helpful tools here are the terrestrial biosphere models (TBMs), since they include detailed ecophysiological process descriptions, e.g. the manifold interactions between the carbon and nitrogen cycles. However, the modelling of the nitrogen cycle poses challenges and having observational constraints on nitrogen cycle is crucial. Current remote sensing products offer estimates of leaf chlorophyll (Cab), that is related to the nitrogen cycle. In this study we want to assess how useful Cab observations are at site scale to constrain a TBM.   In this work we are studying a temperate mixed forest, Borden, located in Canada. We use a TBM QUantifying Interactions between terrestrial Nutrient Cycles, QUINCY, to model this site. From the site we have long-term (20 years) flux tower and LAI (from PAR measurements) observations together with leaf level observations of leaf chlorophyll (Cab), leaf nitrogen, and photochemical parameters of maximum carboxylation rate (Vcmax) and maximum potential electron transport rate (Jmax).    The QUINCY model was predicting too late leaf senescence, which we tuned using the site level data. The amount of leaf nitrogen was originally quite successfully simulated by QUINCY, but the amount of simulated Cab was too low. Matching the simulated Cab values with the observations did not have a pronounced effect on the GPP. Additionally, the development of LAI and Cab were originally fully coupled in QUINCY, whereas the observations showed a delayed development of Cab compared to LAI. When we implemented this decoupling between LAI and Cab, an improvement of simulated GPP compared to the observations was found. Also then the simulated Vcmax and Jmax showed better correspondence to the observations.    Assessment of the long-term behaviour of the model at the site showed that the model was able to capture the drought-induced drawdown of carbon fluxes taking place in 2007. The observations showed an increase in the component fluxes of carbon during the time period, but this was not replicated by the model. The start of season (SOS) and end of season (EOS) were estimated from both the simulated and observed GPP and LAI using a simple threshold method. The model was more successful in capturing the changes in the growing season metrics estimated by LAI than by GPP. The model was predicting too late onset of GPP in many years, but captured largely the interannual variation of SOS in observed GPP.    This study paves the way for work using remotely sensed leaf chlorophyll in evaluation and improvement of the QUINCY model.
Abstract. Advances in Earth Observation capabilities mean that there is now a multitude of spatially resolved data sets available that can support the quantification of water and carbon pools and fluxes at the land surface. However, such quantification ideally requires efficient synergistic exploitation of those data, which in turn requires carbon and water land-surface models with the capability to simultaneously assimilate several of such data streams. The present article discusses the requirements for such a model and presents one such model based on the combination of the existing DALEC land vegetation carbon cycle model with the BETHY land-surface and terrestrial vegetation scheme. The resulting D&B model, made available as a community model, is presented together with a comprehensive evaluation for two selected study sites of widely varying climate. We then demonstrate the concept of land surface modelling aided by data streams that are available from satellite remote sensing. Here we present D&B with four observation operators that translate model-derived variables into measurements available from such data streams, namely: fraction of photosynthetically active radiation (FAPAR), solar-induced chlorophyll fluorescence (SIF), vegetation optical depth (VOD) at microwave frequencies, and near-surface soil moisture, also available from microwave measurements. As a first step, we evaluate the combined model system using local observations, and finally discuss the potential of the system presented for multi-stream data assimilation in the context of Earth Observation systems.
Slowing down climate change calls for a strengthening of natural carbon sinks. Estimating current carbon stocks and the carbon storage potential of natural ecosystems necessitates a good understanding of carbon and nitrogen cycles. As the increase of land carbon sink is likely to be nitrogen-limited in temperate and boreal ecosystems, it is important to constrain the uncertainties related to the carbon and nitrogen processes in the ecosystems. Leaf chlorophyll (chlleaf) and leaf nitrogen allocated to photosynthetic fractions are closely related, as plants optimise their nitrogen resources between light harvesting and the reactions of the Calvin cycle. chlleaf is consequently one of the key factors in determining leaf photosynthetic rates and a strong proxy for photosynthetic capacity. The recent advances in remote sensing (RS) provide a novel opportunity for benchmarking the modelled terrestrial nitrogen cycle through leaf chlorophyll content. In this study, we utilize a terrestrial biosphere model, QUINCY, for simulating the chlleaf content for different ecosystems in a global scale. QUINCY includes a comprehensive representation of coupled carbon and nitrogen cycles, and also diagnostics for chlleaf. We use a satellite-based leaf chlorophyll RS product for evaluating how well QUINCY captures spatial and temporal patterns of chlleaf. The evaluation is conducted for a selection of 400 locations distributed world-wide to represent all major global biomes. In addition, we analyse the accuracy of chlorophyll and productivity (GPP) simulation at 169 sites of the FLUXNET eddy covariance. Our initial results reveal that on global scale, QUINCY chlleaf matches well with the RS chlleaf observations. However, the QUINCY chlleaf values seem to be constrained to a more narrow numerical range than the RS observations, indicating that not all factors contributing to the observed variation are considered in the modeling framework. For instance, the modeled grassland chlleaf shows much smaller variation between different locations when compared to RS observations at different sites. For the FLUXNET sites, the mean annual GPP values from QUINCY are slightly underestimated (on average, ~-260 gC m-2 yr-1) when compared to flux observations. Nevertheless, the QUINCY mean annual GPP for different sites correlates with the ground station data reasonably well (r=0.67).  Our study paves way for more versatile use of satellite observations within terrestrial biosphere models. Harnessing satellite products to model evaluation helps to improve model parametrizations related to carbon and nitrogen cycles, which in turn would allow more precise modeling of the terrestrial carbon budget.
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