格列菲列岛的地质地球物理研究

本文是中、韩国际合作项目“黄海地质地球物理场特征研究”的一部分 .具体研究了格列菲列岛的基础地质问题及地球物理场特征 .格列菲列岛是由三个小岛组成的位于黄海中部的一组群岛 ,位于朝鲜半岛布格重力异常正值区 ,莫霍面埋深在 2 9km左右 .三个岛屿主要由安山集块岩构成 .安山集块岩是由大小不同的火成岩碎块和熔岩混合而成 .火成岩的碎块成分主要为石英岩、片岩、片麻岩、玄武岩、安山岩和流纹岩 .主要节理方向为NE10°～NE2 0°,倾角近乎垂直 ;另一组节理为NW70°～NW80° ,倾角也近垂直 .本研究为我们了解这个地区的基础地质情况 ,岩石物性和随后进行的黄海海域典型剖面的地球物理物性反演工作以及地质模型的建立 ,打下重要基础 .     

Constraints of Housing Age and Migration on Residential Mobility

This paper investigates the role of housing age in constraining residential mobility, measured as the percent of households that have moved into their homes in the past 15 months. The leading explanation for why mobility rates differ so much among regions of the United States has been the overall level of growth. The present analysis shows that the growth effect operates through both the newness of population (migration) and the newness of housing available for occupancy by all local residents. The posited explanation for this housing age effect is that progressively older units contain increasingly settled occupants, yielding fewer opportunities for in-movers in areas with older housing. It is empirically demonstrated that households in older housing have lower likelihood of recent mobility even after controlling for age, tenure, migration status, and state location of residence. The analysis reveals the temporal interdependency of mobility, migration, person age, and housing age.     

Persistent high concentration of ozone during windstorm conditions in southern Korea

Summary Prior to and following the development of a windstorm in the mountainous coastal area of southern Korea, ground level ozone (O₃)-concentrations near Kangnung city, on the lee side of the mountains, show a maximum value at approximately 1300 LST, owing to a photolytic cycle of NO₂–NO–O₃ during the day and a minimum in concentrations at night as a result of the reverse cycle. During the development period of the windstorm, ozone concentrations are generally high all day, and slightly higher during the night. This distribution pattern of ozone is very different from the typical distribution of ozone in the absence of windstorms. High daytime concentrations of ozone during the windstorm are due to both the increase in the amount of ozone from photochemical reactions involving NO_x and the increase in O₃-concentration due to a decrease in the convective boundary layer thickness under the influence of downslope windstorm conditions on the lee-side of the mountains. At night, the windstorm increases in intensity as the westerly winds combine with a katabatic wind blowing downslope toward the surface at the coast. This causes momentum transport of air parcels in the upper levels toward the surface at the coast and the development of internal gravity waves, which generate a hydraulic jump directed upward over the coast and the East sea, thereby reducing to very thin the thickness of the nocturnal surface inversion layer (NSIL). The higher O₃-concentration at night depends mainly upon the shallow NSIL and on some O₃ being transported by the momentum transfer from the upper troposphere toward the ground in windstorm conditions.     

Mineral chemistry of spinel peridotite xenoliths from Baengnyeong Island, South Korea, and its implications for the paleogeotherm of the uppermost mantle

Abstract   The mantle-derived xenoliths entrained in the Pliocene basanite from Baengnyeong Island, South Korea, are spinel lherzolites and spinel harzburgites. The overall compositional range of the Baengnyeong xenoliths matches that of the post-Archean xenoliths of lithospheric mantle origin from eastern China, but without any compositional evidence for a refractory Archean mantle root. Mineral compositions of the xenoliths have been used to estimate the equilibrium temperatures and pressures, and to construct a paleogeothermal gradient of the source region. The xenolith-derived paleogeotherm is constrained from about 820°C at 7.3 kbar to 1000°C at 20.6 kbar. Like those from the post-Archean Chinese xenoliths of lithospheric mantle origin, the Baengnyeong geotherm is considerably elevated relative to the conductive models at the depth of the crust–mantle boundary, reflecting a thermal perturbation probably related to lithospheric thinning. There is no significant P / T difference between harzburgite and lherzolite, which suggests that the harzburgites are interlayered with lherzolites within the depth interval beneath Baengnyeong Island.     

Characterization of hydrogeologic properties for a multi-layered alluvial aquifer using hydraulic and tracer tests and electrical resistivity survey

A multi-layered aquifer, typical of riverbank alluvial deposits in Korea, was studied to determine the hydrologic properties. The geologic logging showed that the subsurface of the study site was comprised of four distinctive hydrogeologic units: silt, sand, highly weathered and fresh bedrock layers. The electrical resistivity survey supplied information on lateral extension of hydrogeologic strata only partially identified by a limited number of the geologic loggings. The laboratory column tracer test for the recovered core of the sand layer resulted in a hydraulic conductivity of 5.00×10⁻² cm/s. The slug tests performed in the weathered rock layer yielded hydraulic conductivities of 4.32–7.72×10⁻⁴ cm/s. Hydraulic conductivities for the sand layer calculated from the breakthrough curves of bromide ranged between 2.08×10⁻³ and 2.44×10⁻² cm/s with a geometric mean of 6.89×10⁻³ cm/s, which is 7 times smaller than that from the laboratory column experiment. The trend of increasing hydraulic conductivity with an increase in tracer travel length is likely a result of the increased likelihood of encountering a high conductivity zone as more of the aquifer is tested. The combined hydrogeologic site characterization using hydraulic tests, tracer tests, and column test with geologic loggings and geophysical survey greatly enhanced the understanding of the hydrologic properties of the multi-layered alluvial aquifer.     

Comparison of prediction performance using statistical postprocessing methods

As the 2018 Winter Olympics are to be held in Pyeongchang, both general weather information on Pyeongchang and specific weather information on this region, which can affect game operation and athletic performance, are required. An ensemble prediction system has been applied to provide more accurate weather information, but it has bias and dispersion due to the limitations and uncertainty of its model. In this study, homogeneous and nonhomogeneous regression models as well as Bayesian model averaging (BMA) were used to reduce the bias and dispersion existing in ensemble prediction and to provide probabilistic forecast. Prior to applying the prediction methods, reliability of the ensemble forecasts was tested by using a rank histogram and a residualquantile-quantile plot to identify the ensemble forecasts and the corresponding verifications. The ensemble forecasts had a consistent positive bias, indicating over-forecasting, and were under-dispersed. To correct such biases, statistical post-processing methods were applied using fixed and sliding windows. The prediction skills of methods were compared by using the mean absolute error, root mean square error, continuous ranked probability score, and continuous ranked probability skill score. Under the fixed window, BMA exhibited better prediction skill than the other methods in most observation station. Under the sliding window, on the other hand, homogeneous and non-homogeneous regression models with positive regression coefficients exhibited better prediction skill than BMA. In particular, the homogeneous regression model with positive regression coefficients exhibited the best prediction skill.     

Development of statistical seasonal prediction models of Arctic Sea Ice concentration using CERES absorbed solar radiation

Statistical seasonal prediction models for the Arctic sea ice concentration (SIC) were developed for the late summer (August-October) when the downward trend is dramatic. The absorbed solar radiation (ASR) at the top of the atmosphere in June has a significant seasonal leading role on the SIC. Based on the lagged ASR-SIC relationship, two simple statistical models were established: the Markovian stochastic and the linear regression models. Crossvalidated hindcasts of SIC from 1979 to 2014 by the two models were compared with each other and observation. The hindcasts showed general agreement between the models as they share a common predictor, ASR in June and the observed SIC was well reproduced, especially over the relatively thin-ice regions (of one- or multi-year sea ice). The robust predictability confirms the functional role of ASR in the prediction of SIC. In particular, the SIC prediction in October was quite promising probably due to the pronounced icealbedo feedback. The temporal correlation coefficients between the predicted SIC and the observed SIC were 0.79 and 0.82 by the Markovian and regression models, respectively. Small differences were observed between the two models; the regression model performed slightly better in August and September in terms of temporal correlation coefficients. Meanwhile, the prediction skills of the Markovian model in October were higher in the north of Chukchi, the East Siberian, and the Laptev Seas. A strong non-linear relationship between ASR in June and SIC in October in these areas would have increased the predictability of the Markovian model.