Effect of snow cover on pan-Arctic permafrost thermal regimes

This study quantitatively evaluated how insulation by snow depth (SND) affected the soil thermal regime and permafrost degradation in the pan-Arctic area, and more generally defined the characteristics of soil temperature (T_SOIL) and SND from 1901 to 2009. This was achieved through experiments performed with the land surface model CHANGE to assess sensitivity to winter precipitation as well as air temperature. Simulated T_SOIL, active layer thickness (ALT), SND, and snow density were generally comparable with in situ or satellite observations at large scales and over long periods. Northernmost regions had snow that remained relatively stable and in a thicker state during the past four decades, generating greater increases in T_SOIL. Changes in snow cover have led to changes in the thermal state of the underlying soil, which is strongly dependent on both the magnitude and the timing of changes in snowfall. Simulations of the period 2001–2009 revealed significant differences in the extent of near-surface permafrost, reflecting differences in the model’s treatment of meteorology and the soil bottom boundary. Permafrost loss was greater when SND increased in autumn rather than in winter, due to insulation of the soil resulting from early cooling. Simulations revealed that T_SOIL tended to increase over most of the pan-Arctic from 1901 to 2009, and that this increase was significant in northern regions, especially in northeastern Siberia where SND is responsible for 50 % or more of the changes in T_SOIL at a depth of 3.6 m. In the same region, ALT also increased at a rate of approximately 2.3 cm per decade. The most sensitive response of ALT to changes in SND appeared in the southern boundary regions of permafrost, in contrast to permafrost temperatures within the 60°N–80°N region, which were more sensitive to changes in snow cover. Finally, our model suggests that snow cover contributes to the warming of permafrost in northern regions and could play a more important role under conditions of future Arctic warming.     

Radio Emission from Masuda Sources

We note that different models, providing comparably good interpretation of the hard X-ray properties of so-called Masuda sources, can make distinctly different predictions for the radio emission produced at the Masuda source by the same population of accelerated electrons. Accordingly, we calculate the radio emission within a few competing models, i.e., those involving magnetic, turbulent, and collisional trapping of the fast electrons in the coronal source. We show that even available incomplete radio observations of the classical Masuda event and a Masuda-like event on 31 December 2007, recently reported by Krucker et al. (Astrophys. J. 714, 1108, 2010) are highly valuable in restricting the physical model of the source. Furthermore, our study proposes that combination of more complete high-resolution X-ray and radio observations can allow unambiguous distinction between the competing Masuda source models.     

Aerobic oxidation of mackinawite (FeS) and its environmental implication for arsenic mobilization

Oxidation of mackinawite (FeS) and concurrent mobilization of arsenic were investigated as a function of pH under oxidizing conditions. At acidic pH, FeS oxidation is mainly initiated by the proton-promoted dissolution, which results in the release of Fe(II) and sulfide in the solution. While most of dissolved sulfide is volatilized before being oxidized, dissolved Fe(II) is oxidized into green rust-like precipitates and goethite (α-FeOOH). At basic pH, the development of Fe(III) (oxyhydr)oxide coating on the FeS surface inhibits the solution-phase oxidation following FeS dissolution. Instead, FeS is mostly oxidized into lepidocrocite (γ-FeOOH) via the surface-mediated oxidation without dissolution. At neutral pH, FeS is oxidized via both the solution-phase oxidation following FeS dissolution and the surface-mediated oxidation mechanisms. The mobilization of arsenic during FeS oxidation is strongly affected by FeS oxidation mechanisms. At acidic pH (and to some extent at neutral pH), the rapid FeS dissolution and the slow precipitation of Fe (oxyhydr)oxides results in arsenic accumulation in water. In contrast, the surface-mediated oxidation of FeS at basic pH leads to the direct formation of Fe (oxyhydr)oxides, which provides effective adsorbents for As under oxic conditions. At acidic and neutral pH, the solution-phase oxidation of dissolved Fe(II) accelerates the oxidation of the less adsorbing As(III) to the more adsorbing As(V). This study reveals that the oxidative mobilization of As may be a significant pathway for arsenic enrichment of porewaters in sulfidic sediments.     

Geostatistical integration using 2-D electrical resistivity and 3-D gravity methods for detecting cavities in a karst area

Two-dimensional (2-D) electrical resistivity and three-dimensional (3-D) gravity explorations were undertaken to estimate the 3-D distribution of karst cavities at the area of Yongweol-ri in Korea where ground subsidence has occurred. Although the gravity method is a low-cost way of analyzing a 3-D continuous structure, its vertical resolving power is poor. In contrast, the electrical resistivity method can provide a 2-D and/or 3-D subsurface structure with a much higher lateral and vertical resolution than the gravity method. Accordingly, geostatistical methods and density information were used to enhance the 2-D resistivity structure revealed by the electrical resistivity method into a 3-D structure. The assumptions are, first, that each data set senses the same underlying geological structure in terms of different material properties and, secondly, that two different material properties are correlated locally or globally throughout the entire target area. As a result, the distribution of limestone cavities can be estimated under the assumption that they are mostly filled with groundwater and clayey soils and have abnormally low levels of resistivity and density. The estimated distribution corresponds with the grouting, borehole imaging and monitoring data. In this example, it can be seen that the integration analysis of 2-D electrical resistivity and 3-D gravity methods is a very powerful tool for 3-D subsurface imaging and that the method can provide enhanced imaging capabilities for 3-D cavities.     

Effects of natural and calcined oyster shells on Cd and Pb immobilization in contaminated soils

In Korea, soils adjacent to abandoned mines are commonly contaminated by heavy metals present in mine tailings. Further, the disposal of oyster shell waste by oyster farm industries has been associated with serious environmental problems. In this study, we attempted to remediate cadmium (Cd)- and lead (Pb)-contaminated soils typical of those commonly found adjacent to abandoned mines using oyster shell waste as a soil stabilizer. Natural oyster shell powder (NOSP) and calcined oyster shell powder (COSP) were applied as soil amendments to immobilize Cd and Pb. The primary components of NOSP and COSP are calcium carbonate (CaCO₃) and calcium oxide (CaO), respectively. X-ray diffraction, X-ray fluorescence and scanning electron microscope analyses conducted in this study revealed that the calcination of NOSP at 770°C converted the less reactive CaCO₃ to the more reactive CaO. The calcination process also decreased the sodium content in COSP, indicating that it was advantageous to use COSP as a liming material in agricultural soil. After 30 days of incubation, we found that the 0.1 N HCl-extractable Cd and Pb contents in soil decreased significantly as a result of an increase in the soil pH and the formation of metal hydroxides. COSP was more effective in immobilizing Cd and Pb in the contaminated soil than NOSP. Overall, the results of this study suggest that oyster shell waste can be recycled into an effective soil ameliorant.     

Place Meanings and Participatory Planning Intentions

Interest in integrating human connections and natural areas into resource management decision making has steadily increased. While efforts to validate place meaning dimensions have identified meanings beyond established place dependence and identity concepts, further research to identify tangible and intangible meanings of nature-based recreation areas is needed. This study sought to examine place meanings as a second-order construct consisting of ecological integrity, economic dependency, place dependence, family identity, community identity, and place identity and to determine the influence of place meanings on participatory planning intentions (PPI). Data were collected from Florida Fish and Wildlife Conservation area visitors. Confirmatory factor analysis revealed that six factors were reliable and valid, representing place meanings as an overarching concept. Structural equation modeling showed a significant association between place meanings and PPI. These findings demonstrated the importance of understanding place meanings that influence behavioral intentions, which is relevant to understanding participation in planning processes.     

Grain size trend and hydrodynamic condition of tirumalairajan River estuary,east coast of India

The estuary can be considered as environments characterized by high productivity and uncommensurable ecological value. However, marine ecosystems are also subjected to high human pressures that increase their vulnerability. The aim of this work is to analyze grain size trend of sediment due to the action of the main hydrodynamic condition. The spatial distribution patterns of sediments were monitored according to season. The grain-size trend of surficial sediments revealed a dominant sediment transport trend towards the eastern and south eastern part of study area. This study shows that there is an agreement among sediments path ways, hydrodynamic condition and the sediment spatial distribution in the estuarine environment. The agitation by waves is an important sorting mechanism in the study area. The findings are based on the grain size trend and also corroborated by short term observations of the estuarine sediment dynamics and transport during the monsoon, postmonsoon, summer and premonson seasons in Tirumalairajan River estuary.     

The variability of the East Asian summer monsoon and its relationship to ENSO in a partially coupled climate model

The variability of the East Asian summer monsoon (EASM) is studied using a partially coupled climate model (PCCM) in which the ocean component is driven by observed monthly mean wind stress anomalies added to the monthly mean wind stress climatology from a fully coupled control run. The thermodynamic coupling between the atmospheric and oceanic components is the same as in the fully coupled model and, in particular, sea surface temperature (SST) is a fully prognostic variable. The results show that the PCCM simulates the observed SST variability remarkably well in the tropical and North Pacific and Indian Oceans. Analysis of the rainfall-SST and rainfall-SST tendency correlation shows that the PCCM exhibits local air-sea coupling as in the fully coupled model and closer to what is seen in observations than is found in an atmospheric model driven by observed SST. An ensemble of experiments using the PCCM is analysed using a multivariate EOF analysis to identify the two major modes of variability of the EASM. The PCCM simulates the spatial pattern of the first two modes seen in the ERA40 reanalysis as well as part of the variability of the first principal component (correlation up to 0.5 for the model ensemble mean). Different from previous studies, the link between the first principal component and ENSO in the previous winter is found to be robust for the ensemble mean throughout the whole period of 1958–2001. Individual ensemble members nevertheless show the breakdown in the relationship before the 1980’s as seen in the observations.     

Winter precipitation variability over Korean Peninsula associated with ENSO

In this study, winter precipitation variability associated with the El Niño-Southern Oscillation (ENSO) over the Korean Peninsula was investigated using a 5-pentad running mean data because significant correlation pattern cannot be revealed using seasonal-mean data. It was found a considerably significant positive correlation between Niño3 sea-surface temperature and precipitation during early winter (from Mid-November to early-December), when the correlation coefficient is close to 0.8 in early-December; the correlation is distinctively weakened during late winter. It is demonstrated that such sudden intraseasonal change in relation to ENSO is associated with the presence of anticyclonic flow over the Kuroshio extension region (Kuroshio anticyclone). In early winter, there is strong southerly wind over the Korean Peninsula, which is induced by the Philippine Sea anticyclone and Kuroshio anticyclone. However, in January, although the Philippine Sea anticyclone develops further, the Kuroshio anticyclone suddenly disappears; as a result, the impact of ENSO is considerably weakened over the Korean Peninsula. These results indicate that the Kuroshio anticyclone during El Niño peak phase plays a critical role by strongly affecting Northeast Asia climate, including the Korean Peninsula. In addition, it is also found that there are distinctive interdecadal changes of the relationship between ENSO and precipitation over the Korean Peninsula. In particular, the strong correlation in early winter is clearer in the recent 30 years than that in the previous period of 1950–1979.     

A dissection of the surface temperature biases in the Community Earth System Model

Based upon the climate feedback-responses analysis method, a quantitative attribution analysis is conducted for the annual-mean surface temperature biases in the Community Earth System Model version 1 (CESM1). Surface temperature biases are decomposed into partial temperature biases associated with model biases in albedo, water vapor, cloud, sensible/latent heat flux, surface dynamics, and atmospheric dynamics. A globally-averaged cold bias of ?1.22 K in CESM1 is largely attributable to albedo bias that accounts for approximately ?0.80 K. Over land, albedo bias contributes ?1.20 K to the averaged cold bias of ?1.45 K. The cold bias over ocean, on the other hand, results from multiple factors including albedo, cloud, oceanic dynamics, and atmospheric dynamics. Bias in the model representation of oceanic dynamics is the primary cause of cold (warm) biases in the Northern (Southern) Hemisphere oceans while surface latent heat flux over oceans always acts to compensate for the overall temperature biases. Albedo bias resulted from the model’s simulation of snow cover and sea ice is the main contributor to temperature biases over high-latitude lands and the Arctic and Antarctic region. Longwave effect of water vapor is responsible for an overall warm (cold) bias in the subtropics (tropics) due to an overestimate (underestimate) of specific humidity in the region. Cloud forcing of temperature biases exhibits large regional variations and the model bias in the simulated ocean mixed layer depth is a key contributor to the partial sea surface temperature biases associated with oceanic dynamics. On a global scale, biases in the model representation of radiative processes account more for surface temperature biases compared to non-radiative, dynamical processes.