Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004)

We assessed current status of multi-model ensemble (MME) deterministic and probabilistic seasonal prediction based on 25-year (1980–2004) retrospective forecasts performed by 14 climate model systems (7 one-tier and 7 two-tier systems) that participate in the Climate Prediction and its Application to Society (CliPAS) project sponsored by the Asian-Pacific Economic Cooperation Climate Center (APCC). We also evaluated seven DEMETER models’ MME for the period of 1981–2001 for comparison. Based on the assessment, future direction for improvement of seasonal prediction is discussed. We found that two measures of probabilistic forecast skill, the Brier Skill Score (BSS) and Area under the Relative Operating Characteristic curve (AROC), display similar spatial patterns as those represented by temporal correlation coefficient (TCC) score of deterministic MME forecast. A TCC score of 0.6 corresponds approximately to a BSS of 0.1 and an AROC of 0.7 and beyond these critical threshold values, they are almost linearly correlated. The MME method is demonstrated to be a valuable approach for reducing errors and quantifying forecast uncertainty due to model formulation. The MME prediction skill is substantially better than the averaged skill of all individual models. For instance, the TCC score of CliPAS one-tier MME forecast of Niño 3.4 index at a 6-month lead initiated from 1 May is 0.77, which is significantly higher than the corresponding averaged skill of seven individual coupled models (0.63). The MME made by using 14 coupled models from both DEMETER and CliPAS shows an even higher TCC score of 0.87. Effectiveness of MME depends on the averaged skill of individual models and their mutual independency. For probabilistic forecast the CliPAS MME gains considerable skill from increased forecast reliability as the number of model being used increases; the forecast resolution also increases for 2 m temperature but slightly decreases for precipitation. Equatorial Sea Surface Temperature (SST) anomalies are primary sources of atmospheric climate variability worldwide. The MME 1-month lead hindcast can predict, with high fidelity, the spatial–temporal structures of the first two leading empirical orthogonal modes of the equatorial SST anomalies for both boreal summer (JJA) and winter (DJF), which account for about 80–90% of the total variance. The major bias is a westward shift of SST anomaly between the dateline and 120°E, which may potentially degrade global teleconnection associated with it. The TCC score for SST predictions over the equatorial eastern Indian Ocean reaches about 0.68 with a 6-month lead forecast. However, the TCC score for Indian Ocean Dipole (IOD) index drops below 0.40 at a 3-month lead for both the May and November initial conditions due to the prediction barriers across July, and January, respectively. The MME prediction skills are well correlated with the amplitude of Niño 3.4 SST variation. The forecasts for 2 m air temperature are better in El Niño years than in La Niña years. The precipitation and circulation are predicted better in ENSO-decaying JJA than in ENSO-developing JJA. There is virtually no skill in ENSO-neutral years. Continuing improvement of the one-tier climate model’s slow coupled dynamics in reproducing realistic amplitude, spatial patterns, and temporal evolution of ENSO cycle is a key for long-lead seasonal forecast. Forecast of monsoon precipitation remains a major challenge. The seasonal rainfall predictions over land and during local summer have little skill, especially over tropical Africa. The differences in forecast skills over land areas between the CliPAS and DEMETER MMEs indicate potentials for further improvement of prediction over land. There is an urgent need to assess impacts of land surface initialization on the skill of seasonal and monthly forecast using a multi-model framework.     

Determination and application of the weights for landslide susceptibility mapping using an artificial neural network

The purpose of this study is the development, application, and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management and manipulation. Landslide locations and landslide-related factors such as slope, curvature, soil texture, soil drainage, effective thickness, wood type, and wood diameter were used for analyzing landslide susceptibility. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence. For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index (LSI) was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.     

Combined analyses of chemometrics and kriging for identifying groundwater contamination sources and origins at the Masan coastal area in Korea

Hydrogeochemical analyses including the basic statistics of chemical components, Piper??s trilinear diagram, and Mazor??s compositional bivariate diagram revealed that the main source and origin of groundwater contamination was seawater intrusion in the study area. However, the other sources and origins of groundwater contamination could be found by the combined analyses of chemometrics and kriging. Cluster analysis was helpful for the classification on the basis of the contamination characteristics of groundwater quality; however, it was not sufficient for the apportionment of groundwater contamination sources. Factor analysis (FA) determined three factors with 81.07% in total variance: Factor 1 for seawater contamination, Factor 2 for nitrate contamination, and Factor 3 for iron contamination. Factor analysis determined the sources of groundwater contamination; however, it could not discover the origins of contaminants except Factor 1. In backward stepwise mode, discriminant analysis decreased the number of parameters from 18 to 6 in discriminating the contaminant type with 96.2% correctness. TDS, Ca, NO₃, Mn, Fe, and Br were the most significant parameters for the discrimination of contaminants. Kriging analysis was very useful for the understanding of correlation and similarity between contaminants and factors of FA, and for the investigation of contaminant origins. It also showed that the similarity between factor scores and contaminant concentrations was proportional to the magnitudes of factor loadings for contaminants. This study represented that the combined analyses of chemometrics and kriging were very indispensable to the identification of groundwater contamination sources and origins, as well as for the spatial classification and assessment of groundwater quality.     

Hydrometallurgical processing and recovery of molybdenum trioxide from spent catalyst

Hydrometallurgical processing of spent hydrodesulphurisation (HDS) catalyst for the recovery of molybdenum using sodium carbonate and hydrogen peroxide mixtures was investigated. The results indicated that the recovery of molybdenum was largely dependent on the concentrations of Na₂CO₃ and H₂O₂ in the reaction medium, which controls the acidity of the leach liquor and carry over of impurities such as Al, Ni, P, Si and V. Leaching process was exothermic and leaching efficiency of molybdenum decreased with increasing solid to liquid ratio. Large scale leaching of spent catalyst, under optimum conditions: 20% pulp density, 85 g/L Na₂CO₃, 10 vol.% H₂O₂ and 1 h reaction, resulted a leaching efficiency of 84% Mo. The obtained leach liquor contained (g/L): Mo — 22.0, Ni — 0.015 and Al — 0.82, P — 1.1, Si — 0.094 and minor quantities of V — 8 mg/L, As and Co — < 1 mg/L. Recovery of Mo from leach solution as MoO₃ of 97.30% purity was achieved by ammonium molybdate precipitation method.     

Analysis of resistivity data obtained from cone penetrometer in contaminated soil layers

In horizontally layered soils of different electrical properties, electrical potential distribution becomes complex and the obtained resistivity data may be limited in reflecting the actual soil profile. Thus the objective of this study was to identify the factors that affect resistivity measurement on the cone penetrometer and further investigate the sensitivity of measured resistivity to different types and concentrations of contaminants at the subsurface level. First, a theoretical resistivity equation was derived to provide a means of computing the geometric factor. The effective volume of measurement on the cone penetrometer was investigated and laboratory soil box tests verified the dominance of partially high resistivity regions within the effective volume of measurement over the apparent resistivity. Such effect was found to lead to possible discrepancies between the recorded resistivity data and the actual depth of measurement. Measurements on contaminated soil layers indicated that resistivity cones are efffective in delineating inorganic contaminants in soils of high water contents, and detecting NAPLs floating above the groundwater table provided that soils adjacent to the plume are not dry of water. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

The Kyonggi Shear Zone of the Central Korean Peninsula: Late Orogenic Imprint of the North and South China Collision

The crustal-scale Kyonggi shear zone of central Korea has been identified as a major boundary between the Precambrian Kyonggi massif in the south and the Imjingang belt in the north. The latter is an eastward extension of the Qinling-Dabie-Sulu collisional belt of China. Field observations and microstructural analysis indicate that the extensional shear zone evolved from a deep crustal ductile regime to a shallow crustal brittle regime, associated with a rapid uplift of the Kyonggi massif following the Late Permian-Early Triassic collision between the Sino-Korean and Yangtze cratons. A Rb-Sr muscovite age (226+/-1.2 Ma) of the mylonite suggests that the extensional ductile shearing occurred during the Late Triassic.     

A Numerical Study on the Screening of Blast-Induced Waves for Reducing Ground Vibration

Blasting is often a necessary part of mining and construction operations, and is the most cost-effective way to break rock, but blasting generates both noise and ground vibration. In urban areas, noise and vibration have an environmental impact, and cause structural damage to nearby structures. Various wave-screening methods have been used for many years to reduce blast-induced ground vibration. However, these methods have not been quantitatively studied for their reduction effect of ground vibration. The present study focused on the quantitative assessment of the effectiveness in vibration reduction of line-drilling as a screening method using a numerical method. Two numerical methods were used to analyze the reduction effect toward ground vibration, namely, the “distinct element method” and the “non-linear hydrocode.” The distinct element method, by particle flow code in two dimensions (PFC 2D), was used for two-dimensional parametric analyses, and some cases of two-dimensional analyses were analyzed three-dimensionally using AUTODYN 3D, the program of the non-linear hydrocode. To analyze the screening effectiveness of line-drilling, parametric analyses were carried out under various conditions, with the spacing, diameter of drill holes, distance between the blasthole and line-drilling, and the number of rows of drill holes, including their arrangement, used as parameters. The screening effectiveness was assessed via a comparison of the vibration amplitude between cases both with and without screening. Also, the frequency distribution of ground motion of the two cases was investigated through fast Fourier transform (FFT), with the differences also examined. From our study, it was concluded that line-drilling as a screening method of blast-induced waves was considerably effective under certain design conditions. The design details for field application have also been proposed.     

Simultaneous stabilization of arsenic, lead, and copper in contaminated soil using mixed waste resources

In the present study, stabilization treatment using waste resource stabilizers was performed for soil contaminated with As and heavy metals (Pb and Cu). Calcined oyster shell (COS) and coal mine drainage sludge (CMDS) were used as a mixed stabilizing agent for a wet-curing duration of 28 days. After the stabilization treatment, the treatment process efficiency was evaluated by the results of various batch- and column-leaching tests. Neutral and weak acid extraction methods, such as water-soluble extraction and SPLP, did not exhibit satisfactory results for heavy metal stabilization, even if they showed very low leachability. On the other hand, TCLP and 0.1 M HCl extraction showed that the stabilizers significantly reduced the amount of heavy metals leached from the soil, which strongly supports the thesis that the stabilization treatment is efficient in the acidic leaching conditions that were explored. Specifically, in the 0.1 M HCl extraction, the reduction efficiencies of As, Pb, and Cu leachings were more than 90 %, compared with control experiments. This study demonstrates that the application of waste resources for the stabilization of As and heavy metals is feasible. However, some limitations observed in the experiments should be considered in future studies, such as the mobilization of alkali-soluble elements, and in particular, exchangeable fractions of Cu. In addition, the treatment efficiency can be evaluated by different leaching methods, which suggests that multidirectional approaches are required for the proper evaluation of stabilization treatment.