Quantification of Long-Range Persistence in Geophysical Time Series: Conventional and Benchmark-Based Improvement Techniques

Time series in the Earth Sciences are often characterized as self-affine long-range persistent, where the power spectral density, S, exhibits a power-law dependence on frequency, f, S(f) ~ f ^?β , with β the persistence strength. For modelling purposes, it is important to determine the strength of self-affine long-range persistence β as precisely as possible and to quantify the uncertainty of this estimate. After an extensive review and discussion of asymptotic and the more specific case of self-affine long-range persistence, we compare four common analysis techniques for quantifying self-affine long-range persistence: (a) rescaled range (R/S) analysis, (b) semivariogram analysis, (c) detrended fluctuation analysis, and (d) power spectral analysis. To evaluate these methods, we construct ensembles of synthetic self-affine noises and motions with different (1) time series lengths N = 64, 128, 256, …, 131,072, (2) modelled persistence strengths β _model = ?1.0, ?0.8, ?0.6, …, 4.0, and (3) one-point probability distributions (Gaussian, log-normal: coefficient of variation c _v = 0.0 to 2.0, Levy: tail parameter a = 1.0 to 2.0) and evaluate the four techniques by statistically comparing their performance. Over 17,000 sets of parameters are produced, each characterizing a given process; for each process type, 100 realizations are created. The four techniques give the following results in terms of systematic error (bias = average performance test results for β over 100 realizations minus modelled β) and random error (standard deviation of measured β over 100 realizations): (1) Hurst rescaled range (R/S) analysis is not recommended to use due to large systematic errors. (2) Semivariogram analysis shows no systematic errors but large random errors for self-affine noises with 1.2 ≤ β ≤ 2.8. (3) Detrended fluctuation analysis is well suited for time series with thin-tailed probability distributions and for persistence strengths of β ≥ 0.0. (4) Spectral techniques perform the best of all four techniques: for self-affine noises with positive persistence (β ≥ 0.0) and symmetric one-point distributions, they have no systematic errors and, compared to the other three techniques, small random errors; for anti-persistent self-affine noises (β < 0.0) and asymmetric one-point probability distributions, spectral techniques have small systematic and random errors. For quantifying the strength of long-range persistence of a time series, benchmark-based improvements to the estimator predicated on the performance for self-affine noises with the same time series length and one-point probability distribution are proposed. This scheme adjusts for the systematic errors of the considered technique and results in realistic 95 % confidence intervals for the estimated strength of persistence. We finish this paper by quantifying long-range persistence (and corresponding uncertainties) of three geophysical time series—palaeotemperature, river discharge, and Auroral electrojet index—with the three representing three different types of probability distribution—Gaussian, log-normal, and Levy, respectively.     

Note on the evolution of massive stars

By use of the fluctuation theory the mass of the massive stars can be calculated from the ‘observed’ luminosity, effective temperature and mass-loss rate. These masses differ from those obtained by fits to the ‘conventional’ evolution-tracks and they are used to construct alternative evolution-tracks.     

Upper Holocene sea-level changes: Paleogeographic evolution and its impact on coastal archaeological sites and monuments

The paper presents the evolution of the geographic environment imposed by sea-level changes in selected sites of the Aegean Sea region during the Upper Holocene. The changes are due, mainly, to paroxysmic phases of the actual neotectonic evolution and to differential—in time and space—block movements, and emerged or submerged coasts. The reconstitution of these coasts is presented and, in some cases, natural harbor morphology is revealed. The use and evolution of these sites is discussed. Other sites concern coastal or inland ancient settlements or constructions affected by submersion by the sea, by the rise of the groundwater table, or by uplift movements. A general discussion on engineering measures to be applied for protection of the antiquities affected by these geographic changes closes the presentation.     

Modeling rhamnolipids production by Pseudomonas aeruginosa from immiscible carbon source in a batch system

A mathematical model to predict the rhamnolipids production by Pseudomonas aeruginosa from oleic acid in a two phase liquid-liquid batch reaction system, was developed in this study. The model was based on two theoretical assumptions: 1) the convective oleic acid mass transfer is coupled to a bioreaction in the aqueous liquid bulk, and 2) the volume of the immiscible oleic acid drops and the saturation concentration at the interface are a function of rhamnolipids production. The model was able to accurately predict the experimental growth of the Pseudomonas aeruginosa strain, and the rhamnolipids production data with oleic acid as carbon source. This mathematical approach indicated a high correspondence between the saturation dimensionless profiles of oleic acid at the interface and the experimental profiles of surface tension difference. This modeling approach may constitute a useful tool in the design and scaling-up of bioreactors applied to the production of biosurfactants with immiscible carbon sources.     

Past,present and future vegetation-cloud feedbacks in the Amazon Basin

To begin exploring the underlying mechanisms that couple vegetation to cloud formation processes, we derive the lifting condensation level (LCL) to estimate cumulus cloud base height. Using a fully coupled land–ocean–atmosphere general circulation model (HadCM3LC), we investigate Amazonian forest feedbacks on cloud formation over three geological periods; modern-day (a.d. 1970–1990), the last glacial maximum (LGM; 21 kya), and under a future climate scenario (IS92a; a.d. 2070–2090). Results indicate that for both past and future climate scenarios, LCL is higher relative to modern-day. Statistical analyses indicate that the 800 m increase in LCL during the LGM is related primarily to the drier atmosphere promoted by lower tropical sea surface temperatures. In contrast, the predicted 1,000 m increase in LCL in the future scenario is the result of a large increase in surface temperature and reduced vegetation cover.     

Degradation of native wheat straw lignin by Streptomyces viridosporus T7A

Lignin is one of the major contributing factors toward the recalcitrance of lignocellulosic biomass. Understanding the process of lignin degradation in natural biological processes will provide useful information to develop novel biomass conversion technologies. Functional group changes in the lignin entities during the process may contribute to the cellulose degradation (utilization) by the microorganisms. In this study, compositional and advanced Fourier transform infrared, pyrolysis gas chromatography/mass spectrometry and ¹³C cross polarization/magic angle spinning nuclear magnetic resonance analysis were performed to explore the mechanism of biodegradation of wheat straw by Streptomyces viridosporus T7A. The results indicated that S. viridosporus T7A removed lignin and hemicelluloses as indicated by the increased carbohydrate/lignin ratio. Significant modification of carbonyl and methoxyl groups in the complex lignin structure was also evident. Most importantly, the quantitative results showed that lignin degradation was featured by deduction of guaiacyl unit. The results provide new insight for understanding lignin degradation by bacteria.     

MoisturEC: A New R Program for Moisture Content Estimation from Electrical Conductivity Data

Noninvasive geophysical estimation of soil moisture has potential to improve understanding of flow in the unsaturated zone for problems involving agricultural management, aquifer recharge, and optimization of landfill design and operations. In principle, several geophysical techniques (e.g., electrical resistivity, electromagnetic induction, and nuclear magnetic resonance) offer insight into soil moisture, but data‐analysis tools are needed to “translate” geophysical results into estimates of soil moisture, consistent with (1) the uncertainty of this translation and (2) direct measurements of moisture. Although geostatistical frameworks exist for this purpose, straightforward and user‐friendly tools are required to fully capitalize on the potential of geophysical information for soil‐moisture estimation. Here, we present MoisturEC, a simple R program with a graphical user interface to convert measurements or images of electrical conductivity (EC) to soil moisture. Input includes EC values, point moisture estimates, and definition of either Archie parameters (based on experimental or literature values) or empirical data of moisture vs. EC. The program produces two‐ and three‐dimensional images of moisture based on available EC and direct measurements of moisture, interpolating between measurement locations using a Tikhonov regularization approach.     

The Askervein hill project: A finite control volume prediction of three-dimensional flows over the hill

A three-dimensional nonlinear numerical model, that has been extensively used previously to predict environmental water flows, was applied to predict the flow over an isolated hill, Askervein. Predictions are reported for winds approaching the hill from 210 ° and 180 ° clockwise from north, both under almost neutral atmospheric conditions.The model predictions were compared with data collected during a major field study in 1983. From the comparisons it was concluded that the model predicts the mean flow variables with good accuracy. Larger discrepancies were found for quantities related to the turbulence, pointing to deficiencies in the turbulence model, and perhaps in some of the measurements.