Carbon flux bias estimation employing Maximum Likelihood Ensemble Filter (MLEF)

We evaluate the capability of an ensemble based data assimilation approach, referred to as Maximum Likelihood Ensemble Filter (MLEF), to estimate biases in the CO2 photosynthesis and respiration fluxes. We employ an off-line Lagrangian Particle Dispersion Model (LPDM), which is driven by the carbon fluxes, obtained from the Simple Biosphere - Regional Atmospheric Modeling System (SiB-RAMS). The SiB-RAMS carbon fluxes are assumed to have errors in the form of multiplicative biases. Our goal is to estimate and reduce these biases and also to assign reliable posterior uncertainties to the estimated biases. Experiments of this study are performed using simulated CO2 observations, which resemble real CO2 concentrations from the Ring of Towers in northern Wisconsin. We evaluate the MLEF results with respect to the 'truth' and the Kalman Filter (KF) solution. The KF solution is considered theoretically optimal for the problem of this study, which is a linear data assimilation problem involving Gaussian errors. We also evaluate the impact of forecast error covariance localization based on a new 'distance' defined in the space of information measures. Experimental results are encouraging, indicating that the MLEF can successfully estimate carbon flux biases and their uncertainties. As expected, the estimated biases are closer to the 'true' biases in the experiments with more ensemble members and more observations. The data assimilation algorithm has a stable performance and converges smoothly to the KF solution when the ensemble size approaches the size of the model state vector (i.e., the control variable of the data assimilation problem

Interactions between the atmosphere and terrestrial ecosystems: influence on weather and climate

This paper overviews the short-term (biophysical) and long-term tout to around 100 year timescales; biogeochemical and biogeographical) influences of the land surface on weather and climate. From our review of the literature, the evidence is convincing that terrestrial ecosystem dynamics on these timescales significantly influence atmospheric processes. In studies of past and possible future climate change, terrestrial ecosystem dynamics are as important as changes in atmospheric dynamics and composition, ocean circulation, ice sheet extent, and orbit perturbations

Accurate Simulation of Both Sensitivity and Variability for Amazonian Photosynthesis: Is It Too Much to Ask?

Estimates of Amazon rainforest gross primary productivity (GPP) differ by a factor of 2 across a suite of three statistical and 18 process models. This wide spread contributes uncertainty to predictions of future climate. We compare the mean and variance of GPP from these models to that of GPP at six eddy covariance (EC) towers. Only one model's mean GPP across all sites falls within a 99% confidence interval for EC GPP, and only one model matches EC variance. The strength of model response to climate drivers is related to model ability to match the seasonal pattern of the EC GPP. Models with stronger seasonal swings in GPP have stronger responses to rain, light, and temperature than does EC GPP. The model to data comparison illustrates a trade-off inherent to deterministic models between accurate simulation of a mean (average) and accurate responsiveness to drivers. The trade-off exists because all deterministic models simplify processes and lack at least some consequential driver or interaction. If a model's sensitivities to included drivers and their interactions are accurate, then deterministically predicted outcomes have less variability than is realistic. If a GPP model has stronger responses to climate drivers than found in data, model predictions may match the observed variance and seasonal pattern but are likely to overpredict GPP response to climate change. High or realistic variability of model estimates relative to reference data indicate that the model is hypersensitive to one or more drivers. © 2021. The Authors. Journal of Advances in Modeling Earth Systems published by Wiley Periodicals LLC on behalf of American Geophysical Union.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

A three‐dimensional synthesis study of δ18O in atmospheric CO2 1. Surface fluxes

International audienceThe isotope 18O in CO2 is of particular interest in studying the global carbon cycle because it is sensitive to the processes by which the global land biosphere absorbs and respires CO2. Carbon dioxide and water exchange isotopically both in leaves and in soils, and the 18O character of atmospheric CO2 is strongly influenced by the land biota, which should constrain the gross primary productivity and total respiration of land ecosystems. In this study we calculate the global surface fluxes of 18O for vegetation and soils using the SiB2 biosphere model coupled with the Colorado State University general circulation model. This approach makes it possible to use physiological variables that are consistently weighted by the carbon assimilation rate and integrated through the vegetation canopy. We also calculate the air‐sea exchange of 18O and the isotopic character of fossil emissions and biomass burning. Global mean values of the isotopic exchange with each reservoir are used to close the global budget of 18O in CO2. Our results confirm the fact that the land biota exert a dominant control on the δ18O of the atmospheric reservoir. At the global scale, exchange with the canopy produces an isotopic enrichment of CO2, whereas exchange with soils has the opposite effect

Formal verification of a type flaw attack on a security protocol using object-z

We have identified a type flaw attack on the Amended Need-ham Schroeder Protocol with Conventional Keys due to a potential over-sight at the presentation layer of the network architecture. Using Object-Z, a formal specification of the protocol is presented allowing us to state the assumed properties of the presentation layer explicitly. Object-Z's schema calculus is used to verify the attack we have found and the weaknesses upon which the attack depends, thus enabling us to minimise the effort required to prevent the attack and to specify this as part of the model accordingly

Evaluation of the antitumoral effect mediated by IL-12 and HSV-tk genes when delivered by a novel lipid-based system

In the present work, we used a novel albumin-associated lipoplex formulation, containing the cationic lipid 1-palmitoyl-2-oleoyl-sn-glycero-3-ethylphosphocholine (EPOPC) and cholesterol (Chol), to evaluate the antitumoral efficacy of two gene therapy strategies: immuno-gene therapy, mediated by IL-12 gene expression, and "suicide" gene therapy, mediated by HSV-tk gene expression followed by ganciclovir (GCV) treatment. Our data show that, in an animal model bearing a subcutaneous TSA (mouse mammary adenocarcinoma) tumor, intratumoral administration of the albumin-associated complexes containing the plasmid encoding IL-12 results in a strong antitumoral effect, as demonstrated by the smaller tumor size, the higher T-lymphocyte tumor infiltration and the more extensive tumor necrotic and hemorrhagic areas, as compared to that observed in animals treated with control complexes. On the other hand, the application of the "suicide" gene therapy strategy results in a significant antitumoral activity, which is similar to that achieved with the immuno-gene therapy strategy, although involving different antineoplastic mechanisms. For the tested model, albumin-associated complexes were shown to efficiently mediate intratumoral delivery of therapeutic genes, thus leading to a significant antitumoral effect. This finding is particularly relevant since TSA tumors are characterized for being poorly immunogenic, aggressive and exhibiting high proliferation capacity.http://www.sciencedirect.com/science/article/B6T1T-4MS9RH3-1/1/f38229393d64061d6859bfebb61b8d8