A robust data cleaning procedure for eddy covariance flux measurements

Abstract. The sources of systematic error responsible for introducing significant biases in the eddy covariance (EC) flux computation are manifold, and their correct identification is made difficult by the lack of reference values, by the complex stochastic dynamics, and by the high level of noise characterizing raw data. This work contributes to overcoming such challenges by introducing an innovative strategy for EC data cleaning. The proposed strategy includes a set of tests aimed at detecting the presence of specific sources of systematic error, as well as an outlier detection procedure aimed at identifying aberrant flux values. Results from tests and outlier detection are integrated in such a way as to leave a large degree of flexibility in the choice of tests and of test threshold values, ensuring scalability of the whole process. The selection of best performing tests was carried out by means of Monte Carlo experiments, whereas the impact on real data was evaluated on data distributed by the Integrated Carbon Observation System (ICOS) research infrastructure. Results evidenced that the proposed procedure leads to an effective cleaning of EC flux data, avoiding the use of subjective criteria in the decision rule that specifies whether to retain or reject flux data of dubious quality. We expect that the proposed data cleaning procedure can serve as a basis towards a unified quality control strategy for EC datasets, in particular in centralized data processing pipelines where the use of robust and automated routines ensuring results reproducibility constitutes an essential prerequisite

The stochastic quantization method and its application to the numerical simulation of volcanic conduit dynamics under random conditions

Stochastic Quantization (SQ) is a method for the approximation of a continuous probability distribution with a discrete one. The proposal made in this paper is to apply this technique to reduce the number of numerical simulations for systems with uncertain inputs, when estimates of the output distribution are needed. This question is relevant in volcanology, where realistic simulations are very expensive and uncertainty is always present. We show the results of a benchmark test based on a one-dimensional steady model of magma flow in a volcanic conduit

Influences of observation errors in eddy flux data on inverse model parameter estimation

Eddy covariance data are increasingly used to estimate parameters of ecosystem models. For proper maximum likelihood parameter estimates the error structure in the observed data has to be fully characterized. In this study we propose a method to characterize the random error of the eddy covariance flux data, and analyse error distribution, standard deviation, cross- and autocorrelation of CO<sub>2</sub> and H<sub>2</sub>O flux errors at four different European eddy covariance flux sites. Moreover, we examine how the treatment of those errors and additional systematic errors influence statistical estimates of parameters and their associated uncertainties with three models of increasing complexity – a hyperbolic light response curve, a light response curve coupled to water fluxes and the SVAT scheme BETHY. In agreement with previous studies we find that the error standard deviation scales with the flux magnitude. The previously found strongly leptokurtic error distribution is revealed to be largely due to a superposition of almost Gaussian distributions with standard deviations varying by flux magnitude. The crosscorrelations of CO<sub>2</sub> and H<sub>2</sub>O fluxes were in all cases negligible (<i>R</i><sup>2</sup> below 0.2), while the autocorrelation is usually below 0.6 at a lag of 0.5 h and decays rapidly at larger time lags. This implies that in these cases the weighted least squares criterion yields maximum likelihood estimates. To study the influence of the observation errors on model parameter estimates we used synthetic datasets, based on observations of two different sites. We first fitted the respective models to observations and then added the random error estimates described above and the systematic error, respectively, to the model output. This strategy enables us to compare the estimated parameters with true parameters. We illustrate that the correct implementation of the random error standard deviation scaling with flux magnitude significantly reduces the parameter uncertainty and often yields parameter retrievals that are closer to the true value, than by using ordinary least squares. The systematic error leads to systematically biased parameter estimates, but its impact varies by parameter. The parameter uncertainty slightly increases, but the true parameter is not within the uncertainty range of the estimate. This means that the uncertainty is underestimated with current approaches that neglect selective systematic errors in flux data. Hence, we conclude that potential systematic errors in flux data need to be addressed more thoroughly in data assimilation approaches since otherwise uncertainties will be vastly underestimated

Non-Newtonian rheology of crystal-bearing magmas and implications for magma ascent dynamics

The eruptive dynamics of volcanic systems are largely controlled by the viscosity of deforming magma. Here we report the results of a series of high-temperature, high-pressure experiments at conditions relevant for volcanic conduits (250 MPa confining pressure and temperature between 500 °C and 900 °C) that were undertaken to investigate the rheology of magma with crystal fractions varying between 0.5 and 0.8 (50 to 80 wt.%) at different strain-rate conditions. The experiments demonstrate that the presence of crystals increases the relative viscosity (ratio between the viscosity of the mixture and the viscosity of the melt phase) of magmas and additionally induces a decrease of the relative viscosity with increasing strain-rate (shear thinning, non-Newtonian behavior). The experimental results, combined with existing data at low crystal fractions (0–0.3), were used to develop a semi-empirical parameterization that describes the variations of relative viscosity for crystal fractions between 0 and 0.8 and accounts for the complex non-Newtonian rheology of crystal-bearing magmas. The new parameterization, included into numerical models simulating the magma ascent dynamics, reveals that strain-rate-dependent rheology significantly modifies the dynamic behavior inside volcanic conduits, particularly affecting the magma fragmentation conditions

Pyroclastic flow dynamics and hazard in a caldera setting: application to Phlegrean Fields

Numerical simulation of pyroclastic density currents has developed significantly in recent years and is increasingly applied to volcanological research. Results from physical modeling are commonly taken into account in volcanic hazard assessment and in the definition of hazard mitigation strategies. In this work, we modeled pyroclastic density currents in the Phlegrean Fields caldera, where flows propagating along the flat ground could be confined by the old crater rims that separate downtown Naples from the caldera. The different eruptive scenarios (mass eruption rates, magma compositions, and water contents) were based on available knowledge of this volcanic system, and appropriate vent conditions were calculated for each scenario. Simulations were performed along different topographic profiles to evaluate the effects of topographic barriers on flow propagation. Simulations highlighted interesting features associated with the presence of obstacles such as the development of backflows. Complex interaction between outward moving fronts and backflows can affect flow propagation; if backflows reach the vent, they can even interfere with fountain dynamics and induce a more collapsing behavior. Results show that in the case of large events ( 108 kg/s), obstacles affect flow propagation by reducing flow velocity and hence dynamic pressure in distal regions, but they cannot stop the advancement of flows. Deadly conditions (in terms of temperature and ash concentration) characterize the entire region invaded by pyroclastic flows. In the case of small events (2.5 107 kg/s), flows are confined by distal topographic barriers which provide valuable protection to the region beyond

Antarctic Salt-Cones: An Oasis of Microbial Life? The Example of Boulder Clay Glacier (Northern Victoria Land)

The evaporation of a localized, highly saline water body of the Boulder Clay debris-covered glacier, in the Northern Victoria Land, probably generated the accumulation of mirabilite (Na2SO4 × 10H2O) and thenardite (Na2SO4) in a glacier salt-cone. Such an extremely cold and salty environment resembles the conditions on Mars, so it can be considered a terrestrial analog. The study was aimed at gaining a first glimpse at the prokaryotic community associated with Antarctic mirabilite and thenardite minerals and also to find clues about the origin of the salts. For this purpose, samples were analyzed by a next generation approach to investigate the prokaryotic (Bacteria and Archaea) diversity. Phylogenetic analysis allowed the identification of Bacteroidota, Actinobacteriota, Firmicutes, and Gammaproteobacteria as the main bacterial lineages, in addition to Archaea in the phylum Halobacterota. The genera Arthrobacter, Rhodoglobus, Gillisia, Marinobacter and Psychrobacter were particularly abundant. Interestingly, several bacterial and archaeal sequences were related to halotolerant and halophilic genera, previously reported in a variety of marine environments and saline habitats, also in Antarctica. The analyzed salt community also included members that are believed to play a major role in the sulfur cycle

Hypoxia, inflammation and necrosis as determinants of glioblastoma cancer stem cells progression

Tumor hypoxic microenvironment causes hypoxia inducible factor 1 alpha (HIF-1ff) activation and necrosis with alarmins release. Importantly, HIF-1ff also controls the expression of alarmin receptors in tumor cells that can bind to and be activated by alarmins. Human tumor tissues possess 1-2% of cancer stem cells (CSCs) residing in hypoxic niches and responsible for the metastatic potential of tumors. Our hypothesis is that hypoxic CSCs express alarmin receptors that can bind alarmins released during necrosis, an event favoring CSCs migration. To investigate this aspect, glioblastoma stem-like cell (GSC) lines were kept under hypoxia to determine the expression of hypoxic markers as well as receptor for advanced glycation end products (RAGE). The presence of necrotic extracts increased migration, invasion and cellular adhesion. Importantly, HIF-1ff inhibition by digoxin or acriflavine prevented the response of GSCs to hypoxia alone or plus necrotic extracts. In vivo, GSCs injected in one brain hemisphere of NOD/SCID mice were induced to migrate to the other one in which a necrotic extract was previously injected. In conclusion, our results show that hypoxia is important not only for GSCs maintenance but also for guiding their response to external necrosis. Inhibition of hypoxic pathway may therefore represent a target for preventing brain invasion by glioblastoma stem cells (GSCs)