Nanoplanktonic assemblages in the upwelling area off Concepción (∼36°S), central Chile: Abundance, biomass, and grazing potential during the annual cycle

The structure and functioning of nanoplanktonic assemblages in coastal upwelling areas have usually been overlooked in explorations of the productivity of these areas. As part of a multidisciplinary, time-series station in the coastal area off Concepción, seasonal variations (upwelling and non-upwelling) in the abundance and biomass of these assemblages were investigated. Hydrographic measurements and biological samples were taken monthly over a 2-year period (18 August 2004-28 July 2006). Nanoflagellates dominated the total integrated abundance (3-317 × 10⁹ cells m⁻²; 0-80 m). Diatoms and dinoflagellates usually contributed to a lesser degree (<20%) but sporadically made important contributions to the total integrated nanoplankton biomass (0.02-10.6 g C m⁻²). Most of the nanoplankton was concentrated in surface waters (<30 m) during all the samplings and no seasonal differences in abundance or biomass were found in this layer, although the mean values and dispersions around them were highest during the upwelling period along with maximum integrated (0-80 m) chlorophyll-a values, as total or in the <20 μm fraction. Changes in nanoplankton abundance were significantly but weakly (r < 0.4) correlated with changes in the hydrographic variables; the highest correlation values were positive for temperature and oxygen, factors that varied with depth and date. The potential grazing rates of heterotrophic nano-predators (flagellates and dinoflagellates) on prokaryotic prey, estimated with a generic model, ranged from 3 to 242 bacterioplankton predator⁻¹ h⁻¹ and from 0.1 to 14 cyanobacteria predator⁻¹ h⁻¹. Our results imply a small impact of seasonal hydrographic variability on the abundance and biomass of nanoplanktonic assemblages and suggest that grazing by nanoheterotrophs might control the prokaryotic picoplankton populations in the upwelling area off Concepción.     

Co–rich Mn crusts from the Magellan Seamount cluster: the long journey through time

The Magellan seamounts began forming as large submarine shield volcanoes south of the equator during the Cretaceous. These volcanoes formed as a cluster on the small Pacific plate in a period when tectonic stress was absent. Thermal subsidence of the seafloor led to sinking of these volcanoes and the formation of guyots as the seamounts crossed the equatorial South Pacific (10–0°S) sequentially and ocean surface temperatures became too high for calcareous organisms to survive. Guyot formation was completed between about 59 and 45 Ma and the guyots became phosphatized at about 39–34 and 27–21 Ma. Ferromanganese crusts began formation as proto-crusts on the seamounts and guyots of the Magellan Seamount cluster towards the end of the Cretaceous up to 55 Ma after the formation of the seamounts themselves. The chemical composition of these crusts evolved over time in a series of steps in response to changes in global climate and ocean circulation. The great thickness of these crusts (up to 15–20 cm) reflects their very long period of growth. The high Co contents of the outer parts of the crusts are a consequence of the increasing deep circulation of the ocean and the resulting deepening of the oxygen minimum zone with time. Growth of the Co-rich Mn crusts in the Magellan Seamount cluster can be considered to be the culmination of a long journey through time.     

Estimating the geostrophic velocity obtained by HF radar observations in the upstream area of the Kuroshio

A method to extract geostrophic current in the daily mean HF radar data in the Kuroshio upstream region is established by comparison with geostrophic velocity determined from the along-track altimetry data. The estimated Ekman current in the HF velocity is 1.2% (1.5%) and 48° (38°)-clockwise rotated with respect to the daily mean wind in (outside) the Kuroshio. Furthermore, additional temporal smoothing is found necessary to remove residual ageostrophic currents such as the inertial oscillation. After removal of the ageostrophic components, the HF geostrophic velocity agrees well with that from the altimetry data with rms difference 0.14 (0.12) m/s in (outside) the Kuroshio.     

Simulation experiment on hydrocarbon generating potential of various source rocks on the northern margin of the Qaidam Basin,Qinghai, China

The northern margin of the Qaidam Basin is one of the main oil-gas exploration areas in western China, where source rocks are composed mostly of Middle and Lower Jurassic dark mud shale, carbargillite and coal. A large number of subsurface and outcrop samples differing in lithology with different types of organic matter were selected for resource evaluation, research and calculation. And among them, 13 samples were used for simulation experiment on hydrocarbon generating potential of various source rocks. At first, two kinds of heating modes were compared through simulation experiment, including single temperature-step heating and continual heating. Perhaps, the process of hydrocarbon generation and expulsion occurred naturally between a close system and an open system. In addition, the first heating mode was convenient, and all its reaction products were involved in the whole thermal evolution, and the final simulation experimental results were basically in consistency with the natural evolution trend Therefore, the first heating mode was adopted and the hydrocarbon yield of every sample was worked out. According to the type and lithology of organic matter and the hydrocarbon yield of samples for simulation experiment, hydrocarbon generation and expulsion mode with three kinds of lithology and five types of source rock has been established to provide the basis for hydrocarbon generation evaluation, research and resource calculation.     

A study on the polarimetric properties of various features using SIR-C data

Spaceborne Imaging Radar (SIR-C) data acquired over Gujarat, India in 1994 were processed and analysed using differnet techniques applicable to polarimetric SAR data such as polarization signatures, polarization index, decomposition of the signal and polarization phase difference and limited groundtruth data. It has been observed that multi-frequency polarimetric data enhances the potential of retrieving geo-physical parameters. The polarization signatures are found to vary with the nature of the target. Target decomposition of the returned signal will be useful for the classification of various features. Polarization Phase Difference (PPD) gives good information about the vegetation parameters.     

The Bayesian detection of discontinuities in a polynomial regression and its application to the cycle-slip problem

This paper deals with the problem of detecting and correcting cycle-slips in Global Navigation Satellite System (GNSS) phase data by exploiting the Bayesian theory. The method is here applied to undifferenced observations, because repairing cycle-slips already at this stage could be a useful pre-processing tool, especially for a network of permanent GNSS stations. If a dual frequency receiver is available, the cycle-slips can be easily detected by combining two phase observations or phase and range observations from a single satellite to a single receiver. These combinations, expressed in a distance unit form, are completely free from the geometry and depend only on the ionospheric effect, on the electronic biases and on the initial integer ambiguities; since these terms are expected to be smooth in time, at least in a short period, a cycle-slip in one or both the two carriers can be modelled as a discontinuity in a polynomial regression. The proposed method consists in applying the Bayesian theory to compute the marginal posterior distribution of the discontinuity epoch and to detect it as a maximum a posteriori (MAP) in a very accurate way. Concerning the cycle-slip correction, a couple of simultaneous integer slips in the two carriers is chosen by maximazing the conditional posterior distribution of the discontinuity amplitude given the detected epoch. Numerical experiments on simulated and real data show that the discontinuities with an amplitude 2 or 3 times larger than the noise standard deviation are successfully identified. This means that the Bayesian approach is able to detect and correct cycle-slips using undifferenced GNSS observations even if the slip occurs by one cycle. A comparison with the scientific software BERNESE 5.0 confirms the good performance of the proposed method, especially when data sampled at high frequency (e.g. every 1 s or every 5 s) are available.     

Geodetic intersection on the ellipsoid

Through each of two known points on the ellipsoid a geodesic is passing in a known azimuth. We solve the problem of intersection of the two geodesics. The solution for the latitude is obtained as a closed formula for the sphere plus a small correction, of the order of the eccentricity of the ellipsoid, which is determined by numerical integration. The solution is iterative. Once the latitude is obtained, the longitude is determined without iteration.     

Prediction of UT1–UTC,LOD and AAM χ<Subscript>3</Subscript> by combination of least-squares and multivariate stochastic methods

This article presents the application of a multivariate prediction technique for predicting universal time (UT1–UTC), length of day (LOD) and the axial component of atmospheric angular momentum (AAM χ ₃). The multivariate predictions of LOD and UT1–UTC are generated by means of the combination of (1) least-squares (LS) extrapolation of models for annual, semiannual, 18.6-year, 9.3-year oscillations and for the linear trend, and (2) multivariate autoregressive (MAR) stochastic prediction of LS residuals (LS + MAR). The MAR technique enables the use of the AAM χ ₃ time-series as the explanatory variable for the computation of LOD or UT1–UTC predictions. In order to evaluate the performance of this approach, two other prediction schemes are also applied: (1) LS extrapolation, (2) combination of LS extrapolation and univariate autoregressive (AR) prediction of LS residuals (LS + AR). The multivariate predictions of AAM χ ₃ data, however, are computed as a combination of the extrapolation of the LS model for annual and semiannual oscillations and the LS + MAR. The AAM χ ₃ predictions are also compared with LS extrapolation and LS + AR prediction. It is shown that the predictions of LOD and UT1–UTC based on LS + MAR taking into account the axial component of AAM are more accurate than the predictions of LOD and UT1–UTC based on LS extrapolation or on LS + AR. In particular, the UT1–UTC predictions based on LS + MAR during El Niño/La Niña events exhibit considerably smaller prediction errors than those calculated by means of LS or LS + AR. The AAM χ ₃ time-series is predicted using LS + MAR with higher accuracy than applying LS extrapolation itself in the case of medium-term predictions (up to 100 days in the future). However, the predictions of AAM χ ₃ reveal the best accuracy for LS + AR.