Spatial and Seasonal Patterns of Salinity in a Large and Shallow Tropical Estuary of the Western Caribbean

Salinity profiles and meteorological data were analyzed during February, May, and September 2006 in Chetumal Bay, a large, shallow estuary of the Western Caribbean. Local meteorological conditions revealed three seasons: (1) a dry season (March–May); (2) a wet season (June–October); and (3) the nortes season, with northerly wind events (October–February). During the nortes and wet seasons, salinity ranged between 13 and 16 psu, and salinity was highest in the dry season, ranging between 18 and 22 psu over most of the area; a strong stratification and a significant contribution of salty water characterized this season. Strong horizontal gradients were observed near Rio Hondo during the three seasons. Deep and narrow peculiar bathymetric features called the pozas showed a strong stratification and a relatively high salinity. The northern part of Chetumal Bay and probably the entire system are far from being homogeneous.     

Graph theory for analyzing pair-wise data: application to geophysical model parameters estimated from interferometric synthetic aperture radar data at Okmok volcano,Alaska

Graph theory is useful for analyzing time-dependent model parameters estimated from interferometric synthetic aperture radar (InSAR) data in the temporal domain. Plotting acquisition dates (epochs) as vertices and pair-wise interferometric combinations as edges defines an incidence graph. The edge-vertex incidence matrix and the normalized edge Laplacian matrix are factors in the covariance matrix for the pair-wise data. Using empirical measures of residual scatter in the pair-wise observations, we estimate the relative variance at each epoch by inverting the covariance of the pair-wise data. We evaluate the rank deficiency of the corresponding least-squares problem via the edge-vertex incidence matrix. We implement our method in a MATLAB software package called GraphTreeTA available on GitHub (https://github.com/feigl/gipht). We apply temporal adjustment to the data set described in Lu et al. (Geophys Res Solid Earth 110, 2005) at Okmok volcano, Alaska, which erupted most recently in 1997 and 2008. The data set contains 44 differential volumetric changes and uncertainties estimated from interferograms between 1997 and 2004. Estimates show that approximately half of the magma volume lost during the 1997 eruption was recovered by the summer of 2003. Between June 2002 and September 2003, the estimated rate of volumetric increase is \((6.2 \, \pm \, 0.6) \times 10^6~\mathrm{m}^3/\mathrm{year} \). Our preferred model provides a reasonable fit that is compatible with viscoelastic relaxation in the five years following the 1997 eruption. Although we demonstrate the approach using volumetric rates of change, our formulation in terms of incidence graphs applies to any quantity derived from pair-wise differences, such as range change, range gradient, or atmospheric delay.     

Surface-Based 3D Modeling of Geological Structures

Building a 3D geological model from field and subsurface data is a typical task in geological studies involving natural resource evaluation and hazard assessment. However, there is quite often a gap between research papers presenting case studies or specific innovations in 3D modeling and the objectives of a typical class in 3D structural modeling, as more and more is implemented at universities. In this paper, we present general procedures and guidelines to effectively build a structural model made of faults and horizons from typical sparse data. Then we describe a typical 3D structural modeling workflow based on triangulated surfaces. Our goal is not to replace software user guides, but to provide key concepts, principles, and procedures to be applied during geomodeling tasks, with a specific focus on quality control.     

Assessment of the pseudo total metal content in alluvial sediments from Danube River,Serbia

We used elemental carbon, nitrogen, hydrogen and sulfur as well as ratios of hydrogen and nitrogen with total organic carbon for investigation of source and conditions of organic matter in alluvial Danube sediments. We also determined the pseudo total concentrations of metals presented as a sum of extracted concentration after five sequential extraction steps. The pseudo total metal concentrations were found to be (mg kg⁻¹) for Mn, 666; Fe, 25,852; Mg, 16,193; K, 2,063; Ni, 32.4; Zn, 72.2; Pb, 15.0; Cu, 26.0 and for Cr, 15.9. Correlation analysis and two multivariate analysis methods (principal component and cluster analysis) were helpful in determining the associations between the pseudo total extracted fractions of metals and with elemental carbon, hydrogen, nitrogen, sulfur, total inorganic and organic carbon. These correlations will help us to identify substrates of trace metals in different oxic/anoxic conditions. The correlation results of the trace metals and Fe, K, Mg and Mn suggest their adsorption, mainly onto Fe and Mn (hydro)oxides and K alumosilicates, whereas correlations of metals with sulfur indicate that they were precipitated as Fe-sulfides.     

Adaptive filtering of GOCE-derived gravity gradients of the disturbing potential in the context of the space-wise approach

Filtering and signal processing techniques have been widely used in the processing of satellite gravity observations to reduce measurement noise and correlation errors. The parameters and types of filters used depend on the statistical and spectral properties of the signal under investigation. Filtering is usually applied in a non-real-time environment. The present work focuses on the implementation of an adaptive filtering technique to process satellite gravity gradiometry data for gravity field modeling. Adaptive filtering algorithms are commonly used in communication systems, noise and echo cancellation, and biomedical applications. Two independent studies have been performed to introduce adaptive signal processing techniques and test the performance of the least mean-squared (LMS) adaptive algorithm for filtering satellite measurements obtained by the gravity field and steady-state ocean circulation explorer (GOCE) mission. In the first study, a Monte Carlo simulation is performed in order to gain insights about the implementation of the LMS algorithm on data with spectral behavior close to that of real GOCE data. In the second study, the LMS algorithm is implemented on real GOCE data. Experiments are also performed to determine suitable filtering parameters. Only the four accurate components of the full GOCE gravity gradient tensor of the disturbing potential are used. The characteristics of the filtered gravity gradients are examined in the time and spectral domain. The obtained filtered GOCE gravity gradients show an agreement of 63–84 mEötvös (depending on the gravity gradient component), in terms of RMS error, when compared to the gravity gradients derived from the EGM2008 geopotential model. Spectral-domain analysis of the filtered gradients shows that the adaptive filters slightly suppress frequencies in the bandwidth of approximately 10–30 mHz. The limitations of the adaptive LMS algorithm are also discussed. The tested filtering algorithm can be connected to and employed in the first computational steps of the space-wise approach, where a time-wise Wiener filter is applied at the first stage of GOCE gravity gradient filtering. The results of this work can be extended to using other adaptive filtering algorithms, such as the recursive least-squares and recursive least-squares lattice filters.     

Early solar system aqueous activity: K isotope evidence from Allende

The alkali element K is moderately volatile and fluid mobile; thus, it can be influenced by both primary processes (evaporation and recondensation) in the solar nebula and secondary processes (thermal and aqueous alteration) in the parent body. Since these primary and secondary processes would induce different isotopic fractionations, K isotopes could become a potential tracer to distinguish them. Using recently developed methods with improved precision (0.05‰, 95% confidence interval), we systematically measured the K isotopic compositions and major/trace elemental compositions of chondritic components (18 chondrules, 3 CAIs, 2 matrices, and 5 bulks) in the carbonaceous chondrite fall Allende. Among all the components analyzed in this study, CAIs, which formed initially under high‐temperature conditions in the solar nebula and were dominated by nominally K‐free refractory minerals, have the highest K₂O content (average 0.53 wt%) and have K isotope compositions most enriched in heavy isotopes (δ⁴¹K: ?0.30 to ?0.25‰). Such an observation is consistent with previous petrologic studies that show CAIs in Allende have undergone alkali enrichment during metasomatism. In contrast, chondrules contain lower K₂O content (0.003–0.17 wt%) and generally lighter K isotope compositions (δ⁴¹K: ?0.87‰ to ?0.24‰). The matrix and bulks are nearly identical in K₂O content and K isotope compositions (0.02–0.05 wt%; δ⁴¹K: ?0.62 to ? 0.46‰), which are, as expected, right in the middle of CAIs and chondrules. This strongly indicates that most of the chondritic components of Allende suffered aqueous alteration and their K isotopic compositions are the ramification of Allende parent‐body processing instead of primary nebular signatures. Nevertheless, we propose the small K isotope fractionations observed (< 1‰) among Allende components are likely similar to the overall range of K isotopic fractionation that occurred in nebular environment. Furthermore, the K isotope compositions seen in the components of Allende in this study are consistent with MC‐ICP‐MS analyses of the components in ordinary chondrites, which also show an absence of large (10‰) isotope fractionations. This is not expected as evaporation experiments in nebular conditions suggest there should be large K isotopic fractionations. Nevertheless, possible nebular processes such as chondrules back exchanging with ambient gas when they formed could explain this lack of large K isotopic variation.     

Indonesian rainfall variability during Western North Pacific and Australian monsoon phase related to convectively coupled equatorial waves

The Indonesian archipelago which has over 15,000 islands, lies in the tropics between Asia and Australia. This eventually alters the rainfall variability over the region, which was influenced by the Asian-Australian monsoon and controlled by intraseasonal variabilities such as convectively coupled equatorial waves (CCEW), i.e., Kelvin, n?=?1 equatorial Rossby (ER), mixed Rossby gravity (MRG), and n?=?1 Westward inertio gravity (WIG), including the Madden–Julian Oscillation (MJO). This study examines a 15-year 3B42 data for trapping CCEW and MJO in the region of Indonesia during both active and extreme Western North Pacific (WNP) and Australian (AU) monsoon phases, which are then compared with 30-year rainfall anomalies among 38 synoptic stations over Indonesia. The space–time spectral analysis is employed to filter each wave including the MJO in the equator, then proceeding with the empirical orthogonal function (EOF) method to seek each wave peak which then coincides with WNP and AU monsoon peaks over Indonesia. It is concluded that an extreme monsoon classification has proven to control rainfall activity related to the CCEW and MJO at 60.66% during December through February (DJF)-WNP for only the significant wave perturbation value. Meanwhile, the CCEW and MJO significantly increase/decrease precipitation at Day 0 for about 37.88% from the total of Day 1st to Day end. Although the contribution of the CCEW and MJO does not profoundly influence rainfall activity during monsoon phase over Indonesia, they still modulate weather condition for more than 50%. On the other hand, a complex topography with a number of land–sea complexities is capable of influencing the rainfall variability in the region as a negative relationship is associated with the CCEW and MJO either during DJF-WNP or July through August (JAS)-AU monsoon phase.     

Hydrothermal hexahydrite spherules erupted during the 2008–2010 summit eruption of Kīlauea Volcano,Hawai`i

Small (1–3 mm), hollow spherules of hexahydrite have been collected falling out of the magmatic gas plume downwind of Kīlauea’s summit vent. The spherules were observed on eight separate occasions during 2009–2010 when a lake of actively spattering lava was present ~150–200 m below the rim of the vent. The shells of the spherules have a fine bubbly foam structure less than 0.1 mm thick, composed almost entirely of hexahydrite [MgSO₄·6H₂O] Small microspherules of lava (<5 μm across) along with mineral and rock fragments from the magmatic plume adhered to the outside of the hexahydrite spherules. Phase relationships and the particulate matter in the magmatic plume indicate that the spherules originated as a bubbly solution injected into and mixed with the magmatic plume. The most likely mechanism for production of hexahydrite spherules is boiling of MgSO₄-saturated meteoric water in the walls of the conduit above the surface of the lava lake. Solfataric sulfates may thus be recycled and reinjected into the plume, creating particulates of sulfate minerals that can be distributed far from their original source.     

Conditional nonlinear optimal perturbation: Applications to stability,sensitivity, and predictability

Conditional nonlinear optimal perturbation (CNOP) is a nonlinear generalization of linear singular vector (LSV) and features the largest nonlinear evolution at prediction time for the initial perturbations in a given constraint. It was proposed initially for predicting the limitation of predictability of weather or climate. Then CNOP has been applied to the studies of the problems related to predictability for weather and climate. In this paper, we focus on reviewing the recent advances of CNOP’s applications, which involves the ones of CNOP in problems of ENSO amplitude asymmetry, block onset, and the sensitivity analysis of ecosystem and ocean’s circulations, etc. Especially, CNOP has been primarily used to construct the initial perturbation fields of ensemble forecasting, and to determine the sensitive area of target observation for precipitations. These works extend CNOP’s applications to investigating the nonlinear dynamical behaviors of atmospheric or oceanic systems, even a coupled system, and studying the problem of the transition between the equilibrium states. These contributions not only attack the particular physical problems, but also show the superiority of CNOP to LSV in revealing the effect of nonlinear physical processes. Consequently, CNOP represents the optimal precursors for a weather or climate event; in predictability studies, CNOP stands for the initial error that has the largest negative effect on prediction; and in sensitivity analysis, CNOP is the most unstable (sensitive) mode. In multi-equilibrium state regime, CNOP is the initial perturbation that induces the transition between equilibriums most probably. Furthermore, CNOP has been used to construct ensemble perturbation fields in ensemble forecast studies and to identify sensitive area of target observation. CNOP theory has become more and more substantial. It is expected that CNOP also serves to improve the predictability of the realistic predictions for weather and climate events plays an increasingly important role in exploring the nonlinear dynamics of atmospheric, oceanic and coupled atmosphere-ocean system. Supported by National Basic Research Program of China (Grant Nos. 2006CB403606, 2007CB411800), National Natural Science Foundation of China (Grant Nos. 40830955, 40675030, 40505013), Institute of Atmospheric Physics, Chinese Academy of Sciences (Grant No. IAP07202), and LASG State Key Laboratory Special Fund