Temporal variations in the current structure and volume transport of the Coastal Oyashio revealed by direct current measurement

Direct current measurements by a shipboard and bottom-mounted acoustic Doppler current profiler and concurrent hydrographic observations with a CTD were conducted off southeastern Hokkaido, Japan, between January and May 2005 to reveal temporal variations in the current structure and volume transport of the Coastal Oyashio (CO). The CO, which has a baroclinic jet structure with southwestward speeds exceeding 90 cm s^?1 and a width of 7–8 km, was associated with a surface-to-bottom density front and was formed on the offshore side of the shelf break. The volume transport of CO (T _CO) was estimated by integrating the fluxes of lower-density water that was trapped against the coast along the density front represented by the 26.2 σ _θ isopycnal line. This transport decreased monotonously from 0.79 Sv (1 Sv = 10⁶ m³ s^?1) in January to 0.21 Sv in March and subsequently to 0.12 Sv in May, possibly due to the decay of the East Sakhalin Current Water in the Okhotsk Sea. Accompanied by a decrease in T _CO, the location of the jet structure associated with the density front moved toward the coast while the maximum speed of the jet decreased and the tilt of the front became more horizontal. Consequently, more saline offshore Oyashio water flowed into the deep part of the shelf area, and the current structure altered from relatively barotropic in winter to baroclinic in spring. This study is the first to estimate the observed volume transport of the CO from direct current measurements.     

Recent increase in surface fCO<Subscript>2</Subscript> in the western subtropical North Pacific

We observed unusually high levels (> 440 μatm) of carbon dioxide fugacity (fCO₂) in surface seawater in the western subtropical North Pacific, the area where Subtropical Mode Water is formed, during summer 2015. The NOAA Kuroshio Extension Observatory moored buoy located in this region also measured high CO₂ values, up to 500 μatm during this period. These high sea surface fCO₂ (fCO_2SW) values are explained by much higher normalized total dissolved inorganic carbon and slightly higher normalized total alkalinity concentrations in this region compared to the equatorial Pacific. Moreover, these values are much higher than the climatological CO₂ values, even considering increasing atmospheric CO₂, indicating a recent large increase in sea surface CO₂ concentrations. A large seasonal change in sea surface temperature contributed to higher surface fCO_2SW in the summer of 2015.     

Potential water sources for Late Quaternary Megalake Jilantai-Hetao,China, inferred from mollusk shell <Superscript>87</Superscript>Sr/<Superscript>86</Superscript>Sr ratios

Lake Jilantai-Hetao, a megalake, was formed some time before 60–50 ka, along the Great North Bend of the Yellow River. The basin is now dry, with most of the area covered by aeolian sand. We are investigating this profound hydrologic change using a number of research approaches. Paleoshorelines of this megalake are best preserved in the Jilantai area in the southwestern portion of the megalake basin. We collected aquatic mollusk shells from littoral sediments at different altitudes around Jilantai and measured their strontium isotope compositions. ⁸⁷Sr/⁸⁶Sr ratios in shell carbonates are different between the high lake phase (~1,080–1,050 m altitude) and the low lake phase (~1,044–1,030 m altitude), with a small shift in average strontium ratios to more radiogenic values during the low lake phase. Based on regional hydrology and physical geography, we conclude that water from the Yellow River was the dominant water source supplying this megalake. ⁸⁷Sr/⁸⁶Sr ratios of modern water samples suggest the Yellow River was the dominant water source during the high lake phase, but that the relative contribution of Yellow River water to the megalake was reduced, and that the relative contributions of local precipitation and groundwater increased, during the low lake phase.     

Using a regional numerical weather prediction model for GNSS positioning over Brazil

The global navigation satellite system (GNSS) can provide centimeter positioning accuracy at low costs. However, in order to obtain the desired high accuracy, it is necessary to use high-quality atmospheric models. We focus on the troposphere, which is an important topic of research in Brazil where the tropospheric characteristics are unique, both spatially and temporally. There are dry regions, which lie mainly in the central part of the country. However, the most interesting area for the investigation of tropospheric models is the wet region which is located in the Amazon forest. This region substantially affects the variability of humidity over other regions of Brazil. It provides a large quantity of water vapor through the humidity convergence zone, especially for the southeast region. The interconnection and large fluxes of water vapor can generate serious deficiencies in tropospheric modeling. The CPTEC/INPE (Center for Weather Forecasting and Climate Studies/Brazilian Institute for Space Research) has been providing since July 2012 a numerical weather prediction (NWP) model for South America, known as Eta. It has yield excellent results in weather prediction but has not been used in GNSS positioning. This NWP model was evaluated in precise point positioning (PPP) and network-based positioning. Concerning PPP, the best positioning results were obtained for the station SAGA, located in Amazon region. Using the NWP model, the 3D RMS are less than 10 cm for all 24 h of data, whereas the values reach approximately 60 cm for the Hopfield model. For network-based positioning, the best results were obtained mainly when the tropospheric characteristics are critical, in which case an improvement of up to 7.2 % was obtained in 3D RMS using NWP models.     

Applications of a GIS-based geotechnical tool to assess spatial earthquake hazards in an urban area

A geotechnical information system (GTIS) was constructed within a spatial geographic information system (GIS) framework to reliably predict geotechnical information and accurately estimate site effects at Gyeongju, an urban area in South Korea. The system was built based on both collected and performed site investigation data in addition to acquired geo-knowledge data. Seismic zoning maps were constructed using the site period (T _G) and mean shear wave velocity to a depth of 30 m (V _S30), and these maps were presented as a regional strategy to mitigate earthquake-induced risks in the study area. In particular, the T _G distribution map indicated the susceptibility to ground motion resonance in periods ranging from 0.2 to 0.5 s and the corresponding seismic vulnerability of buildings with two to five stories. Seismic zonation of site classification according to V _S30 values was also performed to determine the site amplification coefficients for seismic design and seismic performance evaluation at any site and administrative subunit in the study area. In addition, we investigated the site effects according to subsurface and surface ground irregularities at Gyeongju by seismic response analyses in time domains based on both two- and three-dimensional spatial finite element models, which were generated using spatial interface coordinates between geotechnical subsurface layers predicted by the GTIS. This practical study verified that spatial GIS-based geotechnical information can be a very useful resource in determining how to best mitigate seismic hazards, particularly in urban areas.     

Hydrothermal plume mapping as a prospecting tool for seafloor sulfide deposits: a case study at the Zouyu-1 and Zouyu-2 hydrothermal fields in the southern Mid-Atlantic Ridge

Seafloor hydrothermal polymetallic sulfide deposits are a new type of resource, with great potential economic value and good prospect development. This paper discusses turbidity, oxidation–reduction potential, and temperature anomalies of hydrothermal plumes from the Zouyu-1 and Zouyu-2 hydrothermal fields on the southern Mid-Atlantic Ridge. We use the known location of these vent fields and plume data collected in multiple years (2009, 2011, 2013) to demonstrate how real-time plume exploration can be used to locate active vent fields, and thus associated sulfide deposits. Turbidity anomalies can be detected 10 s of km from an active source, but the location precision is no better than a few kilometers because fine-grained particles are quasi-conservative over periods of many days. Temperature and oxidation–reduction potential anomalies provide location precision of a few hundred meters. Temperature anomalies are generally weak and difficult to reliably detect, except by chance encounters of a buoyant plume. Oxidation–reduction potential is highly sensitive (nmol concentrations of reduced hydrothermal chemicals) to discharges of all temperatures and responds immediately to a plume encounter. Real-time surveys using continuous tows of turbidity and oxidation–reduction potential sensors offer the most efficient and precise surface ship exploration presently possible.     

Fish Interactions with a Commercial-Scale Tidal Energy Device in the Natural Environment

Fish are a key part of the marine ecosystem likely to be affected by hydrokinetic tidal turbines, but little is known about their behavior around such obstacles in the natural environment. In September 2010, two DIDSON acoustic cameras were used to observe fish interactions with a commercial-scale turbine in Cobscook Bay, Maine. Twenty-two hours (nearly two tidal cycles) of footage were collected. Behaviors of individual fish and schools were classified (e.g., entering, avoiding, passing, or remaining in the wake of the turbine). We analyzed the effects of turbine motion (rotating or not rotating), diel condition (day or night), and fish size (small, ≤10 cm; large, >10 cm) on individual fish behaviors, and compared behaviors of individual fish to schools of fish. When the turbine was rotating, the probability of fish entering the turbine decreased by over 35 % from when it was not. The probability that fish would enter the turbine was higher at night than during the day, and this difference was greater for small fish than for large fish (probability of small fish entering?=?0.147 day, 0.513 night; large fish?=?0.043 day, 0.333 night). Fish were almost always present in the wake of the turbine. Schools of fish had a 56 % lower probability of entering the turbine than individual fish, and reacted at greater distances from the turbine (median distance of 2.5 m for schools, 1.7 m for individuals). This study indicates that fish behavior in response to tidal turbines appears to be similar to responses to obstacles such as trawls, and highlights the importance of environmental context in determining the effects of a tidal turbine on fish.     

Stable carbon isotopes (δ<Superscript>13</Superscript>C) of total organic carbon and long-chain <Emphasis Type="Italic">n</Emphasis>-alkanes as proxies for climate and environmental change in a sediment core from Lake Petén-Itzá, Guatemala

Sediment core PI-6 from Lake Petén Itzá, Guatemala, possesses an ~85-ka record of climate and environmental change from lowland Central America. Variations in sediment lithology suggest large and abrupt changes in precipitation during the last glacial and deglacial periods, and into the early Holocene. We measured stable carbon isotope ratios of total organic carbon and long-chain n-alkanes from the core, the latter representing a largely allochthonous (terrestrial) source of organic matter, to reveal past shifts in the relative proportion of C₃–C₄ terrestrial biomass. We sought to test whether stable carbon isotope results were consistent with other paleoclimate proxies measured in the PI-6 core, and if extraction and isotope analysis of n-alkanes is warranted. The largest δ¹³C variations are associated with Heinrich Events. Carbon isotope values in sediments deposited during the last glacial maximum indicate moderate precipitation with little fluctuation. The deglacial was a period of pronounced climate variability, e.g. a relatively warm and moist Bølling–Allerød, but a cool and dry Younger Dryas. Arid periods of the deglacial were inferred from samples with high δ¹³C values in total organic carbon, which reflect times of greater proportions of C₄ plants. These inferences are supported by stable isotope measurements on ostracod shells and relative abundance of grass pollen from the same depths in core PI-6. Similar trends in carbon stable isotopes measured on bulk organic carbon and n-alkanes suggest that carbon isotope measures on bulk organic carbon in sediments from this lake are sufficient to infer past climate-driven shifts in local vegetation.     

Data-Driven Predictive Modeling of Mineral Prospectivity Using Random Forests: A Case Study in Catanduanes Island (Philippines)

The Random Forests (RF) algorithm is a machine learning method that has recently been demonstrated as a viable technique for data-driven predictive modeling of mineral prospectivity, and thus, it is instructive to further examine its usefulness in this particular field. A case study was carried out using data from Catanduanes Island (Philippines) to investigate further (a) if RF modeling can be used for data-driven modeling of mineral prospectivity in areas with few (i.e., <20) mineral occurrences and (b) if RF modeling can handle predictor variables with missing values. We found that RF modeling outperforms evidential belief (EB) modeling of prospectivity for hydrothermal Au–Cu deposits in Catanduanes Island, where 17 hydrothermal Au–Cu prospects are known to exist. Moreover, just like EB modeling, RF modeling allows analysis of the spatial relationships between known prospects and individual layers of predictor data. Furthermore, RF modeling can handle missing values in predictor data through an RF-based imputation technique whereas in EB modeling, missing values are simply represented by maximum uncertainty. Therefore, the RF algorithm is a potentially useful method for data-driven predictive modeling of mineral prospectivity in regions with few (i.e., <20) occurrences of mineral deposits of the type sought. However, further testing of the method in other regions with few mineral occurrences is warranted to fully determine its usefulness in data-driven predictive modeling of mineral prospectivity.     

矢量地图数据数字水印抗拼接算法

地图拼接是矢量地图数据中的一种常见处理方式。为了正确提取水印信息,需要从拼接后的地图中确定出水印嵌入区域。利用水印嵌入后坐标点尾部数据分布发生变化的特点,提出了一种基于分布拟合检验的抗拼接算法。该算法利用四叉树算法将地图分成多个区域,然后利用单样本K-S检验判断每个区域内的坐标点尾部数据是否服从均匀分布,最终确定出水印嵌入区域。实验表明,该算法能够达到提取水印嵌入区域的目的。