Resource Assessment of Polymetallic Nodules Using Acoustic Backscatter Intensity Data from the Korean Exploration Area,Northeastern Equatorial Pacific

A high level of confidence in resource data is a key prerequisite for conducting a reliable economic feasibility study in deep water seafloor mining. However, the acquisition of accurate resource data is difficult when employing traditional point-sampling methods to assess the resource potential of polymetallic nodules, given the vast size of the survey area and high spatial variability in nodule distribution. In this study, we analyzed high-resolution acoustic backscatter intensity images to estimate nodule abundance and increase confidence levels in nodule abundance data. We operated a 120 kHz deep-towed sidescan sonar (DSL-120) system (1×1 m resolution) across a 75 km² representative area in the Korean Exploration Area for polymetallic nodules in the Northeastern Equatorial Pacific. A deep-towed camera system was also run along two tracks in the same area to estimate the abundance of polymetallic nodules on the seafloor. Backscatter data were classified into four facies based on intensity. The facies with the weakest and strongest backscatter intensities occurred in areas of high slope gradient and basement outcrops, respectively. The backscatter intensities of the two other facies correlated well with the nodule abundances estimated from still-camera images. A linear fit between backscatter intensity and mean nodule abundance for 10 zones in the study area yielded an excellent correlation (r² = 0.97). This allowed us to compile a map of polymetallic nodule abundance that shows greater resolution than a map derived from the extrapolation of point-sampling data. Our preliminary analyses indicate that it is possible to greatly increase the confidence level of nodule resource data if the relationship between backscatter intensity and nodule abundance is reliably established. This approach has another key advantage over point sampling and image analyses in that detailed maps of mining obstacles along the seafloor are produced when acquiring data on the abundance of polymetallic nodules. The key limitation of this work is a poor correlation between nodule coverage, as observed from photographs, and nodule abundance. Significant additional ground truth sampling using well located box cores should be completed to determine whether or not there is a real correlation between the backscatter and abundance.     

Harmful Dinoflagellate Prorocentrum donghaiense Lu is Widely Distributed Along the East China Sea and Korean Coastal Area

Ocean Science Journal - There have been controversies regarding the taxonomy of Prorocentrum donghaiense, however Zhang et al. (2016) recently developed a probe with a quantitative real-time PCR...     

Rainfall estimation using raingages and radar — A Bayesian approach: 1. Derivation of estimators

Procedures for estimating rainfall from radar and raingage observations are constructed in a Bayesian framework. Given that the number of raingage measurements is typically very small, mean and variance of gage rainfall are treated as uncertain parameters. Under the assumption that log gage rainfall and log radar rainfall are jointly multivariate normal, the estimation problem is equivalent to lognormal co-kriging with uncertain mean and variance of the gage rainfall field.The posterior distribution is obtained under the assumption that the prior for the mean and inverse of the variance of log gage rainfall is normal-gamma 2. Estimate and estimation variance do not have closed-form expressions, but can be easily evaluated by numerically integrating two single integrals. To reduce computational burden associated with evaluating sufficient statistics for the likelihood function, an approximate form of parameter updating is given. Also, as a further approximation, the parameters are updated using raingage measurements only, yielding closed-form expressions for estimate and estimation variance in the Gaussian domain.     

Wave-like wind fluctuations observed in the stable surface layer over a plant canopy

Observations of wind velocity and temperature fluctuations were made in the nocturnal surface inversion layer over a paddy field. A remarkable wave-like motion of about 8 min period was seen in horizontal wind speed and standard deviation of vertical wind velocity. In addition, fluctuations of horizontal wind speed and anticlockwise rotation of wind direction with a period of about 30 min were found by power spectral analysis. The phenomena persisted for more than 2 hours. Similar phenomena were also observed at a coastal site at a distance of about 10 km from the paddy field.     

Numerical analysis on ship maneuvering coupled with ship motion in waves

This paper considers a numerical analysis of ship maneuvering performance in the presence of incident waves and resultant ship motion responses. To this end, a time-domain ship motion program is developed to solve the wave–body interaction problem with the ship slip speed and rotation, and it is coupled with a modular-type 4-DOF maneuvering problem. In this coupled problem, the second-order mean drift force, which can play an important role in the ship maneuvering trajectory, is estimated by using a direct pressure integration method. The developed method is validated by observing the second-order mean drift force, and planar trajectories in maneuvering tests with and without the presence of incident waves. The comparisons are made for two ship models, Series 60 with block coefficient 0.7 and the S-175 containership, with existing experimental data. The maneuvering tests observed in this study include a zig-zag test in calm water, and turning tests in calm water and in regular waves. The present results show a fair agreement of overall tendency in maneuvering trajectories.     

Application of Gibbs’ model to urban drainage networks: a case study in southwestern Chicago,USA

Hydrologic analysis of urban drainage networks often encounters a number of issues, including data acquisition and preparation for modelling, which can be costly and time‐consuming processes. Moreover, it can get more challenging with missing data and complex loops inside networks. In this article, Gibbs’ model is applied to urban drainage networks to investigate the possibility of replacing an actual existing urban drainage network in terms of the shape and peak flow of the hydrographs at the outlet. The characteristic network configuration is given as a value of a parameter β of Gibbs’ model. Instead of the actual network, stochastic networks from Monte‐Carlo simulation are utilized to obtain a synthetic width function from the generated networks, and runoff hydrographs are estimated based on it. The results show that the synthetic width function and the resulting hydrographs obtained from the networks simulated by Gibbs’ model are close to those from the actual network. The result also shows that even the behaviour of a looped network can be approximated by equivalent dendritic networks generated by Gibbs’ model. The applicability of a stochastic network model in urban catchment implies a complement to modelling approaches in case of data unavailability. Moreover, the network property (β) is utilized not only to estimate the discharge hydrograph of a catchment but also as a key link to evaluate the effect from rainstorm movement in urban catchments. Copyright © 2012 John Wiley & Sons, Ltd.     

A case study of temperature fluctuations within and above a wheat field before and after sunset

Temperature fluctuations in the stable air layer before and after sunset were measured at 4 heights within and above a wheat field. Large positive temperature fluctuations were frequently observed within the plant canopy. The standard deviations, skewness factors and flatness factors of temperature fluctuations within the canopy showed peculiar time variations, having remarkable positive skewness factors. The occurrence of large positive temperature fluctuations was probably related to the difference of temperature gradients below and above the observation height, i.e., these fluctuations frequently occurred when the temperature gradient above the observation height was greater than that below the observation height. Furthermore, the vertical mixing associated with the penetration of downdrafts from the air layer above the canopy was requisite for the occurrence of the phenomenon.     

Estimating fractional green vegetation cover of Mongolian grasslands using digital camera images and MODIS satellite vegetation indices

ABSTRACT

Fractional green vegetation cover (FVC) is a useful indicator for monitoring grassland status. Satellite imagery with coarse spatial but high temporal resolutions has been preferred to monitor seasonal and inter-annual FVC dynamics in wide geographic area such as Mongolian steppe. However, the coarse spatial resolution can cause a certain uncertainty in the satellite-based FVC estimation, which calls attention to develop a robust statistical test for the relationship between field FVC and satellite-derived vegetation indices. In the arid and semi-arid Mongolian steppe, nadir pointing digital camera images (DCI) were collected and used to produce a FVC dataset to support the evaluation of satellite-based FVC retrievals. An optimal DCI processing method was determined with respect to three color spaces (RGB, HIS, L*a*b*) and six green pixel classification algorithms, from which a country-wide dataset of DCI-FVC was produced and used for evaluating the accuracy of satellite-based FVC estimates from MODIS vegetation indices. We applied three empirical and three semi-empirical MODIS-FVC retrieval models. DCI data were collected from 96 sites across the Mongolian steppe from 2012 to 2014. The histogram algorithm using the hue (H) value of the HIS color space was the optimal DCI method (r² = 0.94, percent root-mean-square-error (RMSE) = 7.1%). For MODIS-FVC retrievals, semi-empirical Baret model was the best-performing model with the highest r² (0.69) and the lowest RMSE (49.7%), while the lowest MB (+1.1%) was found for the regression model with normalized difference vegetation index (NDVI). The high RMSE (>50% or so) is an issue requiring further enhancement of satellite-based FVC retrievals accounting for key plant and soil parameters relevant to the Mongolian steppe and for scale mismatch between sampling and MODIS data.     

Impacts of Aerosol Loading on Surface Precipitation from Deep Convective Systems over North Central Mongolia

The impacts of aerosol loading on surface precipitation from mid-latitude deep convective systems are examined using a bin microphysics model. For this, a precipitation case over north central Mongolia, which is a high-altitude inland region, on 21 August 2014 is simulated with aerosol number concentrations of 150, 300, 600, 1200, 2400, and 4800 cm^?3. The surface precipitation amount slightly decreases with increasing aerosol number concentration in the range of 150–600 cm^?3, while it notably increases in the range of 600–4800 cm^?3 (22% increase with eightfold aerosol loading). We attempt to explain why the surface precipitation amount increases with increasing aerosol number concentration in the range of 600–4800 cm^?3. A higher aerosol number concentration results in more drops of small sizes. More drops of small sizes grow through condensation while being transported upward and some of them freeze, thus increasing the mass content of ice crystals. The increased ice crystal mass content leads to an increase in the mass content of small-sized snow particles largely through deposition, and the increased mass content of small-sized snow particles leads to an increase in the mass content of large-sized snow particles largely through riming. In addition, more drops of small sizes increase the mass content of supercooled drops, which also leads to an increase in the mass content of large-sized snow particles through riming. The increased mass content of large-sized snow particles resulting from these pathways contributes to a larger surface precipitation amount through melting and collision-coalescence.