Quantifying weathering on variable rocks,an extension of geochemical mass balance: Critical zone and landscape evolution

We present a statistical model of soil and rock weathering in deep profiles to expand the capacity to assess weathering to heterogeneous bedrock types, which are common at the Earth's surface. We developed the Weathering Trends (WT) model by extending the fractional mass change calculation (tau) of the geochemical mass balance model in two important ways. First, WT log transforms the elemental ratio data, to discern the log‐linear patterns that naturally develop from thermodynamic and kinetic laws of chemistry. Second, WT statistically fits log‐transformed element concentration ratio data – log(c_j/c_i), the only depth‐varying term in tau – as a function of depth to determine characteristic depths of transitions in weathering processes, along with confidence intervals. With no prior assumptions, WT estimates average parent material composition, average composition of the upper weathered zone and mean fractional mass change of each element over the entire weathering profile. WT displays the mean shape of weathering profiles of log‐transformed geochemical data bounded by calculated confidence intervals. We share the WT model code as an open‐source R package ( https://github.com/fisherba/WeatheringTrends ). The WT model was designed to interpret two 21 m cores from the Laurels Schist bedrock in the Christina River Basin Critical Zone Observatory in the Pennsylvania Piedmont, where our morphological and elemental data provided inconclusive estimates of bedrock depth. The WT model differentiated between rock variability and weathering to delineate the maximum extent of weathering at 12.3 m (CI 95% [9.2, 21.3]) in Ridge Well 1 and 7.2 m (CI 95% [4.3, 13.0]) in Interfluve Well 2. The water table was 5–8 m below fresh rock at Ridge Well 1, but at the same depth as fresh rock at the lower elevation interfluve. We assess statistical approaches to identify the best immobile element for use in WT and tau calculations. Copyright © 2017 John Wiley & Sons, Ltd.     

Quality of hybrid location data drawn from GPS‐enabled mobile phones: Does it matter?

Despite their increasing popularity in human mobility studies, few studies have investigated the geo‐spatial quality of GPS‐enabled mobile phone data in which phone location is determined by special queries designed to collect location data with predetermined sampling intervals (hereafter “active mobile phone data”). We focus on two key issues in active mobile phone data—systematic gaps in tracking records and positioning uncertainty—and investigate their effects on human mobility pattern analyses. To address gaps in records, we develop an imputation strategy that utilizes local environment information, such as parcel boundaries, and recording time intervals. We evaluate the performance of the proposed imputation strategy by comparing raw versus imputed data with participants’ online survey responses. The results indicate that imputed data are superior to raw data in identifying individuals’ frequently visited places on a weekly basis. To assess the location accuracy of active mobile phone data, we investigate the spatial and temporal patterns of the positional uncertainty of each record and examine via Monte Carlo simulation how inaccurate location information might affect human mobility pattern indicators. Results suggest that the level of uncertainty varies as a function of time of day and the type of land use at which the position was determined, both of which are closely related to the location technology used to determine the location. Our study highlights the importance of understanding and addressing limitations of mobile phone derived positioning data prior to their use in human mobility studies.     

Cross-section restoration and one-dimensional basin modeling of the Central Subbasin in the southern Kunsan Basin,Yellow Sea

The petroleum system of the Kunsan Basin in the Northern South Yellow Sea Basin is not well known, compared to other continental rift basins in the Yellow Sea, despite its substantial hydrocarbon potential. Restoration of two depth-converted seismic profiles across the Central Subbasin in the southern Kunsan Basin shows that extension was interrupted by inversions in the Late Oligocene-Middle Miocene that created anticlinal structures. One-dimensional basin modeling of the IIH-1Xa well suggests that hydrocarbon expulsion in the northeastern margin of the depocenter of the Central Subbasin peaked in the Early Oligocene, predating the inversions. Hydrocarbon generation at the dummy well location in the depocenter of the subbasin began in the Late Paleocene. Most source rocks in the depocenter passed the main expulsion phase except for the shallowest source rocks. Hydrocarbons generated from the depocenter are likely to have migrated southward toward the anticlinal structure and faults away from the traps along the northern and northeastern margins of the depocenter because the basin-fill strata are dipping north. Faulting that continued during the rift phase (∼ Middle Miocene) of the subbasin probably acted as conduits for the escape of hydrocarbons. Thus, the anticlinal structure and associated faults to the south of the dummy well may trap hydrocarbons that have been charged from the shallow source rocks in the depocenter since the Middle Miocene.     

Molecular characterization and morphology of the photosynthetic dinoflagellate Bysmatrum caponii from two solar saltons in western Korea

Species belonging to the genus Bysmatrum are peridinoid, thecate, photosynthetic dinoflagellates. The plate formula of Bysmatrum spp., arranged in a Kofoidian series, is almost identical to that of Scrippsiella spp. Bysmatrum spp., which were originally classified as Scrippsiella spp., but were transferred to the genus Bysmatrum spp. because of separation of the intercalary plates 2a and 3a by plate 3??. Whether this transfer from Scrippsiella spp. to Bysmatrum spp. is reasonable should be genetically confirmed. Dinoflagellates were isolated from 2 solar saltons located in western Korea in 2009?C2010 and 3 clonal cultures from Sooseong solar saltons and 2 clonal cultures from Garolim solar saltons were successfully established. All of these dinoflagellates were identified as Bysmatrum caponii based on morphology analysis by light and electron microscopy. The plates of all Korean strains of B. caponii were arranged in a Kofoidian series of Po, X, 4??, 3a, 7??, 6c, 4s, 5?, 0 (p), and 24??. When properly aligned, the ribosomal DNA (rDNA) sequences of the 3 Sooseong strains of B. caponii were identical, as were those of the 2 Garolim strains. Furthermore, the sequences of the 3 Sooseong strains were 0.01% different from those of the Garolim strains. However, the sequences of SSU rDNA of these Korean B. caponii strains were 9% different from that of Bysmatrum subsalsum and > 10% from that of any other dinoflagellate thus far reported. In the phylogenetic trees generated using SSU and LSU rDNA sequences, these Korean B. caponii strains formed a clade with B. subsalsum which was clearly divergent from the Scrippsiella clade. However, this Bysmatrum clade was phylogenetically close to the Protoperidinium and/or Peridinium clades. The results of the present study suggest that Bysmatrum spp. are markedly different genetically from Scrippsiella spp..     

Seismic behavior of an inverted T-shape flexible retaining wall via dynamic centrifuge tests

In the design procedure for a retaining wall, the pseudo-static method has been widely used and dynamic earth pressure is calculated by the Mononobe–Okabe method, which is an extension of Coulomb’s earth pressure theory computed by force equilibrium. However, there is no clear empirical basis for treating the seismic force as a static force, and recent experimental research has shown that the Mononobe–Okabe method is quite conservative, and there exists a discrepancy between the assumed conditions and real seismic behavior during an earthquake. Two dynamic centrifuge tests were designed and conducted to reexamine the Mononobe–Okabe method and to evaluate the seismic lateral earth pressure on an inverted T-shape flexible retaining wall with a dry medium sand backfill. Results from two sets of dynamic centrifuge experiments show that inertial force has a significant impact on the seismic behavior on the flexible retaining wall. The dynamic earth pressure at the time of maximum moment during the earthquake was not synchronized and almost zero. The relationship between the back-calculated dynamic earth pressure coefficient at the time of maximum dynamic wall moment and the peak ground acceleration obtained from the wall base peak ground acceleration indicates that the seismic earth pressure on flexible cantilever retaining walls can be neglected at accelerations below 0.4 g. These results suggest that a wall designed with a static factor of safety should be able to resist seismic loads up to 0.3–0.4 g.     

Environmental characterization of periphyton community

The present paper deals with the behavior of the Attached Microbial Community （AMC） for water self-purification at different riverbeds in a typical local river. The study quantitatively investigated the problem starting with in-situ sampling. It was found that more biomass of AMC was at riffles with wider distribution than in pools. High current velocity （HCV） plays a negative role at the initial stage of attachment on the riverbed, but HCV aids the community proliferation after stable attachment. External disturbances such as rainfalls and discharges from dams or reservoirs would detach the periphyton depending on the intensity of turbulence in water. However, it was discovered that the flock of periphyton could be restored very quickly because it was not completely removed. Thus, in order to enhance self-purification by periphyton, a suitable configuration of the riverbed must be constructed, and occasional appropriate repair along the channels would improve the decontamination of the river.     

Distribution of Changjiang Diluted Water detected by satellite chlorophyll-a and its interannual variation during 1998–2007

Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll-a distribution in summer in the East China Sea during 1998–2007 was analyzed. Statistical analysis with K-means clustering technique allowed us to define the proper satellite chlorophyll-a concentration indicating the Changjiang Diluted Water (CDW). The spatial distributions of the higher satellite chlorophyll-a concentrations (>0.48 mg m⁻³) corresponded well with the distributions of lower salinity CDW (<30–32) every year. Interannual variation of the CDW area, indicated by the high satellite chlorophyll-a, correlated with the interannual variation of the Changjiang summer freshwater discharge. The correlation analysis indicated that the CDW spread eastward in the East China Sea with a time lag of 1 to 2 months after the discharge.     

Examination of multi-model ensemble seasonal prediction methods using a simple climate system

A simple climate model was designed as a proxy for the real climate system, and a number of prediction models were generated by slightly perturbing the physical parameters of the simple model. A set of long (240 years) historical hindcast predictions were performed with various prediction models, which are used to examine various issues of multi-model ensemble seasonal prediction, such as the best ways of blending multi-models and the selection of models. Based on these results, we suggest a feasible way of maximizing the benefit of using multi models in seasonal prediction. In particular, three types of multi-model ensemble prediction systems, i.e., the simple composite, superensemble, and the composite after statistically correcting individual predictions (corrected composite), are examined and compared to each other. The superensemble has more of an overfitting problem than the others, especially for the case of small training samples and/or weak external forcing, and the corrected composite produces the best prediction skill among the multi-model systems.     

Diagnosis and testing of low-level cloud parameterizations for the NCEP/GFS model using satellite and ground-based measurements

The objective of this study is to investigate the quality of clouds simulated by the National Centers for Environmental Prediction global forecast system (GFS) model and to examine the causes for some systematic errors seen in the simulations through use of satellite and ground-based measurements. In general, clouds simulated by the GFS model had similar spatial patterns and seasonal trends as those retrieved from passive and active satellite sensors, but large systematic biases exist for certain cloud regimes especially underestimation of low-level marine stratocumulus clouds in the eastern Pacific and Atlantic oceans. This led to the overestimation (underestimation) of outgoing longwave (shortwave) fluxes at the top-of-atmosphere. While temperature profiles from the GFS model were comparable to those obtained from different observational sources, the GFS model overestimated the relative humidity field in the upper and lower troposphere. The cloud condensed water mixing ratio, which is a key input variable in the current GFS cloud scheme, was largely underestimated due presumably to excessive removal of cloud condensate water through strong turbulent diffusion and/or an improper boundary layer scheme. To circumvent the problem associated with modeled cloud mixing ratios, we tested an alternative cloud parameterization scheme that requires inputs of atmospheric dynamic and thermodynamic variables. Much closer agreements were reached in cloud amounts, especially for marine stratocumulus clouds. We also evaluate the impact of cloud overlap on cloud fraction by applying a linear combination of maximum and random overlap assumptions with a de-correlation length determined from satellite products. Significantly better improvements were found for high-level clouds than for low-level clouds, due to differences in the dominant cloud geometry between these two distinct cloud types.     

The CLIVAR C20C project: skill of simulating Indian monsoon rainfall on interannual to decadal timescales. Does GHG forcing play a role?

The ability of atmospheric general circulation models (AGCMs), that are forced with observed sea surface temperatures (SSTs), to simulate the Indian monsoon rainfall (IMR) variability on interannual to decadal timescales is analyzed in a multimodel intercomparison. The multimodel ensemble has been performed within the CLIVAR International “Climate of the 20th Century” (C20C) Project. This paper is part of a C20C intercomparison of key climate time series. Whereas on the interannual timescale there is modest skill in reproducing the observed IMR variability, on decadal timescale the skill is much larger. It is shown that the decadal IMR variability is largely forced, most likely by tropical sea surface temperatures (SSTs), but as well by extratropical and especially Atlantic Multidecadal Oscillation (AMO) related SSTs. In particular there has been a decrease from the late 1950s to the 1990s that corresponds to a general warming of tropical SSTs. Using a selection of control integrations from the World Climate Research Programme’s (WCRP’s) Coupled Model Intercomparison Project phase 3 (CMIP3), it is shown that the increase of greenhouse gases (GHG) in the twentieth century has not significantly contributed to the observed decadal IMR variability.