Estimation of periodicities in hydrologic data

Periodicites in hydrologic data are frequently estimated and studied. In some cases the periodic components are subtracted from the data to obtain the stochastic components. In other cases the physical reasons for the occurrence of these periodicities are investigated. Apart from the annual cycle in the hydrologic data, periods corresponding to the 11 year sunspot cycle, the Hale cycle and others have been detected.The conclusions from most of these studies depend on the reliability and robustness of the methods used to detect these periodicities. Several spectral analysis methods have been proposed to investigate periodicities in time series data. Several of these have been compared to each other. The methods by Siddiqui and Wang and by Damsleth and Spjotvoll, which are stepwise procedures of spectrum estimation, have not been evaluated.     

The effect of weathering on optically stimulated luminescence dating

Optically stimulated luminescence (OSL) dating was applied to quartz samples recovered from the gravel sediments of deformed marine terrace at the Suryum site, southeastern Korea, but has yielded stratigraphically inconsistent ages. Micromorphological, chemical, and mineralogical analyses of the gravels indicate the possible influence of chemical weathering on the apparent OSL ages. In the course of weathering after emerging from beach environments, originally permeable gravels underwent infilling by halloysite-rich clays in their voids, export and import of radioactive elements, and loss of mechanical strength with the creation of a porosity within pebbles. Calculation based on the evolution of the weathering profile showed a severe fluctuation of dose rate caused by the change of water content and radioactive element concentrations. Samples recovered from the weathering profile inevitably include quartz grains derived from mechanically weakened pebbles or illuviated from the upper layer, making it difficult to determine the equivalent dose (D_e) values of exclusively depositional quartz sands. Quantitative evaluation of the change of fabric and chemistry of the sediments on the basis of pedologic insight significantly aids in the derivation of OSL ages consistent with geomorphology and other independent age controls.     

Star formation and figure rotation in the early-type galaxy NGC 2974

We present Galaxy Evolution Explorer ( GALEX ) far-ultraviolet (FUV) and near-ultraviolet (NUV) imaging of the nearby early-type galaxy NGC 2974, along with complementary ground-based optical imaging. In the ultraviolet, the galaxy reveals a central spheroid-like component and a newly discovered complete outer ring of radius 6.2 kpc, with suggestions of another partial ring at an even larger radius. Blue FUV–NUV and UV-optical colours are observed in the centre of the galaxy and from the outer ring outwards, suggesting young stellar populations (≲1 Gyr) and recent star formation in both locations. This is supported by a simple stellar population model which assumes two bursts of star formation, allowing us to constrain the age, mass fraction and surface mass density of the young component pixel by pixel. Overall, the mass fraction of the young component appears to be just under 1 per cent (lower limit, uncorrected for dust extinction). The additional presence of a nuclear and an inner ring (radii 1.4 and 2.9 kpc, respectively), as traced by [O  iii ] emission, suggests ring formation through resonances. All three rings are consistent with a single pattern speed of  78 ± 6  km s⁻¹ kpc⁻¹, typical of S0 galaxies and only marginally slower than expected for a fast bar if traced by a small observed surface brightness plateau. This thus suggests that star formation and morphological evolution in NGC 2974 at the present epoch are primarily driven by a rotating asymmetry (probably a large-scale bar), despite the standard classification of NGC 2974 as an E4 elliptical.     

Aerobic oxidation of mackinawite (FeS) and its environmental implication for arsenic mobilization

Oxidation of mackinawite (FeS) and concurrent mobilization of arsenic were investigated as a function of pH under oxidizing conditions. At acidic pH, FeS oxidation is mainly initiated by the proton-promoted dissolution, which results in the release of Fe(II) and sulfide in the solution. While most of dissolved sulfide is volatilized before being oxidized, dissolved Fe(II) is oxidized into green rust-like precipitates and goethite (α-FeOOH). At basic pH, the development of Fe(III) (oxyhydr)oxide coating on the FeS surface inhibits the solution-phase oxidation following FeS dissolution. Instead, FeS is mostly oxidized into lepidocrocite (γ-FeOOH) via the surface-mediated oxidation without dissolution. At neutral pH, FeS is oxidized via both the solution-phase oxidation following FeS dissolution and the surface-mediated oxidation mechanisms. The mobilization of arsenic during FeS oxidation is strongly affected by FeS oxidation mechanisms. At acidic pH (and to some extent at neutral pH), the rapid FeS dissolution and the slow precipitation of Fe (oxyhydr)oxides results in arsenic accumulation in water. In contrast, the surface-mediated oxidation of FeS at basic pH leads to the direct formation of Fe (oxyhydr)oxides, which provides effective adsorbents for As under oxic conditions. At acidic and neutral pH, the solution-phase oxidation of dissolved Fe(II) accelerates the oxidation of the less adsorbing As(III) to the more adsorbing As(V). This study reveals that the oxidative mobilization of As may be a significant pathway for arsenic enrichment of porewaters in sulfidic sediments.     

A copula-based multivariate analysis of Canadian RCM projected changes to flood characteristics for northeastern Canada

In the present work, climate change impacts on three spring (March–June) flood characteristics, i.e. peak, volume and duration, for 21 northeast Canadian basins are evaluated, based on Canadian regional climate model (CRCM) simulations. Conventional univariate frequency analysis for each flood characteristic and copula based bivariate frequency analysis for mutually correlated pairs of flood characteristics (i.e. peak–volume, peak–duration and volume–duration) are carried out. While univariate analysis is focused on return levels of selected return periods (5-, 20- and 50-year), the bivariate analysis is focused on the joint occurrence probabilities P1 and P2 of the three pairs of flood characteristics, where P1 is the probability of any one characteristic in a pair exceeding its threshold and P2 is the probability of both characteristics in a pair exceeding their respective thresholds at the same time. The performance of CRCM is assessed by comparing ERA40 (the European Centre for Medium-Range Weather Forecasts 40-year reanalysis) driven CRCM simulated flood statistics and univariate and bivariate frequency analysis results for the current 1970–1999 period with those observed at selected 16 gauging stations for the same time period. The Generalized Extreme Value distribution is selected as the marginal distribution for flood characteristics and the Clayton copula for developing bivariate distribution functions. The CRCM performs well in simulating mean, standard deviation, and 5-, 20- and 50-year return levels of flood characteristics. The joint occurrence probabilities are also simulated well by the CRCM. A five-member ensemble of the CRCM simulated streamflow for the current (1970–1999) and future (2041–2070) periods, driven by five different members of a Canadian Global Climate Model ensemble, are used in the assessment of projected changes, where future simulations correspond to A2 scenario. The results of projected changes, in general, indicate increases in the marginal values, i.e. return levels of flood characteristics, and the joint occurrence probabilities P1 and P2. It is found that the future marginal values of flood characteristics and P1 and P2 values corresponding to longer return periods will be affected more by anthropogenic climate change than those corresponding to shorter return periods but the former ones are subjected to higher uncertainties.     

A dissection of the surface temperature biases in the Community Earth System Model

Based upon the climate feedback-responses analysis method, a quantitative attribution analysis is conducted for the annual-mean surface temperature biases in the Community Earth System Model version 1 (CESM1). Surface temperature biases are decomposed into partial temperature biases associated with model biases in albedo, water vapor, cloud, sensible/latent heat flux, surface dynamics, and atmospheric dynamics. A globally-averaged cold bias of ?1.22 K in CESM1 is largely attributable to albedo bias that accounts for approximately ?0.80 K. Over land, albedo bias contributes ?1.20 K to the averaged cold bias of ?1.45 K. The cold bias over ocean, on the other hand, results from multiple factors including albedo, cloud, oceanic dynamics, and atmospheric dynamics. Bias in the model representation of oceanic dynamics is the primary cause of cold (warm) biases in the Northern (Southern) Hemisphere oceans while surface latent heat flux over oceans always acts to compensate for the overall temperature biases. Albedo bias resulted from the model’s simulation of snow cover and sea ice is the main contributor to temperature biases over high-latitude lands and the Arctic and Antarctic region. Longwave effect of water vapor is responsible for an overall warm (cold) bias in the subtropics (tropics) due to an overestimate (underestimate) of specific humidity in the region. Cloud forcing of temperature biases exhibits large regional variations and the model bias in the simulated ocean mixed layer depth is a key contributor to the partial sea surface temperature biases associated with oceanic dynamics. On a global scale, biases in the model representation of radiative processes account more for surface temperature biases compared to non-radiative, dynamical processes.     

Improvement of daily precipitation estimations using PRISM with inverse-distance weighting

Improved daily precipitation estimations were attempted using the parameter-elevation regressions on a parameter-elevation regression on independent slopes model (PRISM) with inverse-distance weighting (IDW) and a precipitation-masking algorithm for precipitation areas. The PRISM (PRISM_ORG) suffers two overestimation problems when the daily precipitation is estimated: overestimation of the precipitation intensity in mountainous regions and overestimation of the local precipitation areas. In order to solve the problem of overestimating the precipitation intensity, we used the IDW technique that employs the same input stations as those used in the PRISM regression (PRISM_IDW). A precipitation-masking algorithm that selectively masks the precipitation estimation grid points was additionally applied to the PRISM_IDW results (PRISM_MSK). For 6 months from March to August 2012, daily precipitation data were produced in a horizontal resolution of 1 km based on the above two experiments and PRISM_ORG. Afterwards, each experiment was evaluated for improvements. The monthly root mean squared errors (RMSEs) of PRISM_IDW and PRISM_MSK were reduced by 0.83 mm/day and 0.86 mm/day, respectively, compared to PRISM_ORG.