The minimum gap-opening planet mass in an irradiated circumstellar accretion disc

We consider the minimum mass planet, as a function of radius, that is capable of opening a gap in an α-accretion disc. We estimate that a half-Jupiter mass planet can open a gap in a disc with accretion rate     for viscosity parameter  α= 0.01  , and solar mass and luminosity. The minimum mass is approximately proportional to     . This estimate can be used to rule out the presence of massive planets in gapless accretion discs. We identify two radii at which an inwardly migrating planet may become able to open a gap and so slow its migration; the radius at which the heating from viscous dissipation is similar to that from stellar radiation in a flared disc, and the radius at which the disc becomes optically thin in a self-shadowed disc. In the inner portions of the disc, we find that the minimum planet mass required to open a gap is only weakly dependent on radius. If a migrating planet is unable to open a gap by the time it reaches either of the transition radii, then it is likely to be lost on to the star. If a gap-opening planet cuts off disc accretion allowing the formation of a central hole or clearing in the disc then we would estimate that the clearing radius would approximately be proportional to the stellar mass.     

CO2 concentration and its spatiotemporal variation in the troposphere using multi-sensor satellite data,carbon tracker,and aircraft observations

Satellite-based atmospheric CO₂ observations have provided a great opportunity to improve our understanding of the global carbon cycle. However, thermal infrared (TIR)-based satellite observations, which are useful for the investigation of vertical distribution and the transport of CO₂, have not yet been studied as much as the column amount products derived from shortwave infrared data. In this study, TIR-based satellite CO₂ products – from Atmospheric Infrared Sounder, Tropospheric Emission Spectrometer (TES), and Thermal And Near infrared Sensor for carbon Observation – and carbon tracker mole fraction data were compared with in situ Comprehensive Observation Network for Trace gases by AIrLiner (CONTRAIL) data for different locations. The TES CO₂ product showed the best agreement with CONTRAIL CO₂ data resulting in R² ~ 0.87 and root-mean-square error ~0.9. The vertical distribution of CO₂ derived by TES strongly depends on the geophysical characteristics of an area. Two different climate regions (i.e., southeastern Japan and southeastern Australia) were examined in terms of the vertical distribution and transport of CO₂. Results show that while vertical distribution of CO₂ around southeastern Japan was mainly controlled by horizontal and vertical winds, horizontal wind might be a major factor to control the CO₂ transport around southeastern Australia. In addition, the vertical transport of CO₂ also varies by region, which is mainly controlled by anthropogenic CO₂, and horizontal and omega winds. This study improves our understanding of vertical distribution and the transport of CO₂, both of which vary by region, using TIR-based satellite CO₂ observations and meteorological variables.     

Hydraulic and Thermal Conductivities of Kaolin–Silica Mixtures under Different Consolidation Stresses

Stable backfill materials for the heat sensitive structures of buried power cables, hot water pipes, and gas pipelines are suggested to have low permeability and high heat transfer characteristics. The hydraulic and thermal conductivities of backfill materials or clay liners are important parameters in proper design and construction of geotechnical structures involved with heat transfers. In this study, to investigate the optimal natural backfill or liner materials, thermal and hydraulic conductivities of kaolin–silica mixtures examined based on the results from laboratory tests under different consolidation conditions. From the experiment results, the thermal conductivity increases while hydraulic conductivity decreases with increasing density during consolidation process. As a result, back-fill materials with high kaolin content under low consolidation stress were desirable materials for burial of heat sensitive structures.     

Growth dynamics of the deep-water Asian eelgrass, <Emphasis Type="Italic">Zostera asiatica</Emphasis>, in the eastern coastal waters of Korea

Among the seagrasses that occur along the coast of Korea, Zostera asiatica inhabits the deepest depth; however, to date, there is limited information on its ecology. This study presents the first quantitative data on the seasonal growth dynamics of Z. asiatica in Korea. We measured seasonal growth and morphological characteristics, as well as environmental factors, including underwater irradiance, water temperature, salinity and nutrient concentrations of the water column and sediment pore water, bimonthly from July 2012 to May 2015. Underwater irradiance showed clear seasonal trends, increasing in the spring and summer and decreasing in the fall and winter, ranging from 2.4 ± 0.2 mol photons m^-2 d^-1 in November 2012 to 12.8 ± 1.3 mol photons m^-2 d^-1 in July 2014. Water temperature also followed a strong seasonal trend similar to underwater irradiance, ranging from 9.8 ± 0.1°C in January 2013 to 20.5 ± 0.2°C in September 2013. Nutrient availability fluctuated substantially, but there was no evidence of distinct seasonal variations. Shoot density, biomass, leaf productivity, and morphological characteristics of Z. asiatica exhibited significant seasonal variations: maximum values of these variables occurred in summer, and the minima were recorded in winter. Total shoot density was highest (218.8 ± 18.8 shoots m^-2) in July 2012 and lowest (106.3 ± 6.3 shoots m^-2) in January 2013. Total biomass ranged from 182.6 ± 16.9 g dry weight (DW) m^-2 in January 2015 to 310.9 ± 6.4 g DW m^-2 in July 2014.Areal leaf production was highest (4.9 ± 0.0 g DW m^-2 d^-1) in July 2012 and lowest (1.4 ± 0.2 g DW m^-2 d^-1) in January 2013. The optimum water temperature for the growth of Z. asiatica was between 16-19°C. Growth of Z. asiatica was more strongly correlated with underwater irradiance than water temperature, suggesting that light is the most important factor determining seasonality of Z. asiatica at the study site.     

Performance of Weibull function as a diameter distribution model for <Emphasis Type="Italic">Pinus thunbergii</Emphasis> stands in the eastern coast of South Korea

This study was carried out to determine the performance of percentile-based Weibull diameter distribution model for Pinus thunbergii stands thriving along the eastern coast of South Korea. The parameter recovery technique was used to estimate the three parameters of the Weibull model. The analysis demonstrated satisfactory results based on the following test statistics for the principal percentile models: fit index (FI) range from 0.501 (minimum diameter) to 0.932 (50th diameter percentiles) and root mean square error (RMSE) range from 0.112 (quadratic mean diameter) to 3.572 (minimum diameter). The developed model was further evaluated by determining the mean bias (ē) in trees per ha (TPH) for each diameter class, and the results showed highest over-prediction in the 20 cm, and under-prediction in the 16 cm and 24 cm diameter classes. The goodness of fit tested by Kolmogorov-Smirnov (KS) test showed no significant differences (p>0.05) between the observed and predicted diameter distributions for almost all plots. Using site index and aboveground biomass (AGB) models developed for P. thunbergii in South Korea, a model to predict the AGB per ha for each diameter class and subsequently the total AGB of the stand was created. An application guide was also created, which will serve as a decision-support tool for forest managers in quantifying the future total AGB in P. thunbergii stands located in the eastern coast of South Korea and, subsequently, the quantification of potential carbon stocks aside from being a vital input in designing efficient management and protection strategies for these stands.     

Biomass growth characteristics of 13-year-old <Emphasis Type="Italic">Pinus densiflora</Emphasis> S. et Z. in a post-fire plantation on different contour conditions in Samcheuk,Korea

We used preliminary data to estimate the growth volume of artificially reforested Pinus densiflora in a post-fire area on three different contour conditions. We compared the growth of P. densiflora on a south-facing slope (S_sth), north-facing slope (S_nth) and ridge area (Ridge), using 7 trees selected from each stand aspect. The tree height, diameter and growth volume were measured and the dry weight of each plant part were compared and analyzed. The results revealed that the total dry weight was highest on S_sth (5992.3 g), followed by S_nth (4833.2 g) and lowest on Ridge (3160.1 g). The height growth was highest on S_nth (285.8 cm), followed by S_sth (274.5 cm) and lowest on Ridge (211.5 cm). The diameter growth was greatest on S_sth (7.37 cm), followed by S_nth (7.10 cm) and lowest on Ridge (5.72 cm). The volume growth was highest on S_sth (4257.7 cm³), followed by S_nth (3750.7 cm³) and lowest on Ridge (2093.7 cm³). Therefore, we should consider and include the concept of slope orientation together with differences in habitat environments in afforestation projects when creating artificial forests with P. densiflora. These study results can serve as important preliminary data for future establishment of artificial forest of P. densiflora in a post-fire plantation.     

Assessment of shallow landslide susceptibility using the transient infiltration flow model and GIS-based probabilistic approach

This study proposes a probabilistic analysis method for modeling rainfall-induced shallow landslide susceptibility by combining a transient infiltration flow model and Monte Carlo simulations. The spatiotemporal change in pore water pressure over time caused by rainfall infiltration is one of the most important factors causing landslides. Therefore, the transient infiltration hydrogeological model was adopted to estimate the pore water pressure within the hill slope and to analyze landslide susceptibility. In addition, because of the inherent uncertainty and variability caused by complex geological conditions and the limited number of available soil samples over a large area, this study utilized probabilistic analysis based on Monte Carlo simulations to account for the variability in the input parameters. The analysis was performed in a geographic information system (GIS) environment because GIS can deal efficiently with a large volume of spatial data. To evaluate its effectiveness, the proposed analysis method was applied to a study area that had experienced a large number of landslides in July 2006. For the susceptibility analysis, a spatial database of input parameters and a landslide inventory map were constructed in a GIS environment. The results of the landslide susceptibility assessment were compared with the landslide inventory, and the proposed approach demonstrated good predictive performance. In addition, the probabilistic method exhibited better performance than the deterministic alternative. Thus, analysis methods that account for uncertainties in input parameters are more appropriate for analysis of an extensive area, for which uncertainties may significantly affect the predictions because of the large area and limited data.