Scaling Transition in Earthquake Sources: A Possible Link Between Seismic and Laboratory Measurements

We estimate the corner frequencies of 20 crustal seismic events from mainshock–aftershock sequences in different tectonic environments (mainshocks 5.7 < M _W < 7.6) using the well-established seismic coda ratio technique (Mayeda et al. in Geophys Res Lett 34:L11303, 2007; Mayeda and Malagnini in Geophys Res Lett, 2010), which provides optimal stability and does not require path or site corrections. For each sequence, we assumed the Brune source model and estimated all the events’ corner frequencies and associated apparent stresses following the MDAC spectral formulation of Walter and Taylor (A revised magnitude and distance amplitude correction (MDAC2) procedure for regional seismic discriminants, 2001), which allows for the possibility of non-self-similar source scaling. Within each sequence, we observe a systematic deviation from the self-similar \( M_{0} \propto \mathop f\nolimits_{\text{c}}^{ - 3} \) line, all data being rather compatible with \( M_{0} \propto \mathop f\nolimits_{\text{c}}^{ - (3 + \varepsilon )} \) , where ε > 0 (Kanamori and Rivera in Bull Seismol Soc Am 94:314–319, 2004). The deviation from a strict self-similar behavior within each earthquake sequence of our collection is indicated by a systematic increase in the estimated average static stress drop and apparent stress with increasing seismic moment (moment magnitude). Our favored physical interpretation for the increased apparent stress with earthquake size is a progressive frictional weakening for increasing seismic slip, in agreement with recent results obtained in laboratory experiments performed on state-of-the-art apparatuses at slip rates of the order of 1 m/s or larger. At smaller magnitudes (M _W < 5.5), the overall data set is characterized by a variability in apparent stress of almost three orders of magnitude, mostly from the scatter observed in strike-slip sequences. Larger events (M _W > 5.5) show much less variability: about one order of magnitude. It appears that the apparent stress (and static stress drop) does not grow indefinitely at larger magnitudes: for example, in the case of the Chi–Chi sequence (the best sampled sequence between M _W 5 and 6.5), some roughly constant stress parameters characterize earthquakes larger than M _W ~ 5.5. A representative fault slip for M _W 5.5 is a few tens of centimeters (e.g., Ide and Takeo in J Geophys Res 102:27379–27391, 1997), which corresponds to the slip amount at which effective lubrication is observed, according to recent laboratory friction experiments performed at seismic slip velocities (V ~ 1 m/s) and normal stresses representative of crustal depths (Di Toro et al. in Nature in press, 2011, and references therein). If the observed deviation from self-similar scaling is explained in terms of an asymptotic increase in apparent stress (Malagnini et al. in Pure Appl Geophys, 2014, this volume), which is directly related to dynamic stress drop on the fault, one interpretation is that for a seismic slip of a few tens of centimeters (M _W ~ 5.5) or larger, a fully lubricated frictional state may be asymptotically approached.     

A statistical framework of data fusion for spatial prediction of categorical variables

With rapid advances of geospatial technologies, the amount of spatial data has been increasing exponentially over the past few decades. Usually collected by diverse source providers, the available spatial data tend to be fragmented by a large variety of data heterogeneities, which highlights the need of sound methods capable of efficiently fusing the diverse and incompatible spatial information. Within the context of spatial prediction of categorical variables, this paper describes a statistical framework for integrating and drawing inferences from a collection of spatially correlated variables while accounting for data heterogeneities and complex spatial dependencies. In this framework, we discuss the spatial prediction of categorical variables in the paradigm of latent random fields, and represent each spatial variable via spatial covariance functions, which define two-point similarities or dependencies of spatially correlated variables. The representation of spatial covariance functions derived from different spatial variables is independent of heterogeneous characteristics and can be combined in a straightforward fashion. Therefore it provides a unified and flexible representation of heterogeneous spatial variables in spatial analysis while accounting for complex spatial dependencies. We show that in the spatial prediction of categorical variables, the sought-after class occurrence probability at a target location can be formulated as a multinomial logistic function of spatial covariances of spatial variables between the target and sampled locations. Group least absolute shrinkage and selection operator is adopted for parameter estimation, which prevents the model from over-fitting, and simultaneously selects an optimal subset of important information (variables). Synthetic and real case studies are provided to illustrate the introduced concepts, and showcase the advantages of the proposed statistical framework.     

Acoustic full waveform inversion of synthetic land and marine data in the Laplace domain

Elastic waves, such as Rayleigh and mode‐converted waves, together with amplitude versus offset variations, serve as noise in full waveform inversion using the acoustic approximation. Heavy preprocessing must be applied to remove elastic effects to invert land or marine data using the acoustic inversion method in the time or frequency domains. Full waveform inversion using the elastic wave equation should be one alternative; however, multi‐parameter inversion is expensive and sensitive to the starting velocity model. We implement full acoustic waveform inversion of synthetic land and marine data in the Laplace domain with minimum preprocessing (i.e., muting) to remove elastic effects. The damping in the Laplace transform can be thought of as an automatic time windowing. Numerical examples show that Laplace‐domain acoustic inversion can yield correct smooth velocity models even with the noise originating from elastic waves. This offers the opportunity to develop an accurate smooth starting model for subsequent inversion in the frequency domain.     

Application of bivariate frequency analysis to the derivation of rainfall–frequency curves

Bivariate distributions have been recently employed in hydrologic frequency analysis to analyze the joint probabilistic characteristics of multivariate storm events. This study aims to derive practical solutions of application for the bivariate distribution to estimate design rainfalls corresponding to the desired return periods. Using the Gumbel mixed model, this study constructed rainfall–frequency curves at sample stations in Korea which provide joint relationships between amount, duration, and frequency of storm events. Based on comparisons and analyses of the rainfall–frequency curves derived from univariate and bivariate storm frequency analyses, this study found that conditional frequency analysis provides more appropriate estimates of design rainfalls as it more accurately represents the natural relationship between storm properties than the conventional univariate storm frequency analysis.     

An assessment of the surface climate in the NCEP climate forecast system reanalysis

This paper analyzes surface climate variability in the climate forecast system reanalysis (CFSR) recently completed at the National Centers for Environmental Prediction (NCEP). The CFSR represents a new generation of reanalysis effort with first guess from a coupled atmosphere?Cocean?Csea ice?Cland forecast system. This study focuses on the analysis of climate variability for a set of surface variables including precipitation, surface air 2-m temperature (T2m), and surface heat fluxes. None of these quantities are assimilated directly and thus an assessment of their variability provides an independent measure of the accuracy. The CFSR is compared with observational estimates and three previous reanalyses (the NCEP/NCAR reanalysis or R1, the NCEP/DOE reanalysis or R2, and the ERA40 produced by the European Centre for Medium-Range Weather Forecasts). The CFSR has improved time-mean precipitation distribution over various regions compared to the three previous reanalyses, leading to a better representation of freshwater flux (evaporation minus precipitation). For interannual variability, the CFSR shows improved precipitation correlation with observations over the Indian Ocean, Maritime Continent, and western Pacific. The T2m of the CFSR is superior to R1 and R2 with more realistic interannual variability and long-term trend. On the other hand, the CFSR overestimates downward solar radiation flux over the tropical Western Hemisphere warm pool, consistent with a negative cloudiness bias and a positive sea surface temperature bias. Meanwhile, the evaporative latent heat flux in CFSR appears to be larger than other observational estimates over most of the globe. A few deficiencies in the long-term variations are identified in the CFSR. Firstly, dramatic changes are found around 1998?C2001 in the global average of a number of variables, possibly related to the changes in the assimilated satellite observations. Secondly, the use of multiple streams for the CFSR induces spurious jumps in soil moisture between adjacent streams. Thirdly, there is an inconsistency in long-term sea ice extent variations over the Arctic regions between the CFSR and other observations with the CFSR showing smaller sea ice extent before 1997 and larger extent starting in 1997. These deficiencies may have impacts on the application of the CFSR for climate diagnoses and predictions. Relationships between surface heat fluxes and SST tendency and between SST and precipitation are analyzed and compared with observational estimates and other reanalyses. Global mean fields of surface heat and water fluxes together with radiation fluxes at the top of the atmosphere are documented and presented over the entire globe, and for the ocean and land separately.     

Temperature trends in the skin/surface, mid-troposphere and low stratosphere near Korea from satellite and ground measurements

Various types of satellite (AIRS/AMSU, MODIS) and ground measurements are used to analyze temperature trends in the four vertical layers (skin/surface, mid-troposphere, and low stratosphere) around the Korean Peninsula (123–132°E, 33–44°N) during the period from September 2002 to August 2010. The ground-based observations include 72 Surface Meteorological Stations (SMSs), 6 radiosonde stations (RAOBs), 457 Automatic Weather Stations (AWSs) over the land, and 5 buoy stations over the ocean. A strong warming (0.052 K yr^?1) at the surface, and a weak warming (0.004～0.010 K yr^?1) in the mid-troposphere and low stratosphere have been found from satellite data, leading to an unstable atmospheric layer. The AIRS/AMSU warming trend over the ocean surface around the Korean Peninsula is about 2.5 times greater than that over the land surface. The ground measurements from both SMS and AWS over the land surface of South Korea also show a warming of 0.043～0.082 K yr^?1, consistent with the satellite observations. The correlation average (r = 0.80) between MODIS skin temperature and ground measurement is significant. The correlations between AMSU and RAOB are very high (0.91～0.95) in the anomaly time series, calculated from the spatial averages of monthly mean temperature values. However, the warming found in the AMSU data is stronger than that from the RAOB at the surface. The opposite feature is present above the mid-troposphere, indicating that there is a systematic difference. Warming phenomena (0.012～0.078 K yr^?1) are observed from all three data sets (SMS, AWS, MODIS), which have been corroborated by the coincident measurements at five ground stations. However, it should also be noted that the observed trends are subject to large uncertainty as the corresponding 95% confidence intervals tend to be larger than the observed signals due to large thermal variability and the relatively short periods of the satellitebased temperature records. The EOF analysis of monthly mean temperature anomalies indicates that the tropospheric temperature variability near Korea is primarily linked to the Arctic Oscillation (AO), and secondarily to ENSO (El Niño and Southern Oscillation). However, the low stratospheric temperature variability is mainly associated with Southern Oscillation and then additionally with Quasi-Biennial Oscillation (QBO). Uncertainties from the different spatial resolutions between satellite data are discussed in the trends.     

Elemental and mineralogical changes in soils due to bioturbation along an earthworm invasion chronosequence in Northern Minnesota

Minnesota forested soils have evolved without the presence of earthworms since the last glacial retreat. When exotic earthworms arrive, enhanced soil bioturbation often results in dramatic morphological and chemical changes in soils with negative implications for the forests’ sustainability. However, the impacts of earthworm invasion on geochemical processes in soils are not well understood. This study attempts to quantify the role of earthworm invasion in mineral chemical weathering and nutrient dynamics along an earthworm invasion chronosequence in a sugar maple forest in Northern Minnesota. Depth and rates of soil mixing can be tracked with atmospherically derived short lived radioisotopes ²¹⁰Pb and ¹³⁷Cs. Their radioactivities increase in the lower A horizon at the expense of the peak activities near the soil surface, which indicate that soil mixing rate and its depth reach have been enhanced by earthworms. Enhanced soil mixing by earthworms is consistent with the ways that the vertical profiles of elemental and mineralogical compositions were affected by earthworm invasion. Biologically cycled Ca and P have peak concentrations near the soil surface prior to earthworm invasion. However, these peak abundances significantly declined in the earthworm invaded soils presumably due to enhanced soil mixing. It is clear that enhanced soil mixing due to earthworms also profoundly altered the vertical distribution of most mineral species within A horizons. Though the mechanisms are not clear yet, earthworm invasion appears to have contributed to net losses of clay mineral species and opal from the A horizons. As much as earthworms vertically relocated minerals and elements, they also intensify the contacts between organic matter and cations as shown in the increased amount of Ca and Fe in organically complexed and in exchangeable pools. With future studies on soil mixing rates and elemental leaching, this study will quantitatively and mechanically address the role of earthworms in geochemical evolution of soils and forests’ nutrient dynamics.     

Investigation of CO2 behavior and study on design of optimal injection into Gorae-V aquifer

This study presents the Bottom-hole pressure (BHP) behavior with different wettabilities and the optimal design scheme to effectively inject CO₂ into the Gorae-V aquifer. As a result, the injection rate and injectivity were increased as the wettability condition became more water-wet. However, the more wettability condition becomes water-wet, the more the ultimate CO₂ injection volume decreases. When the injectivity was 346 ton/day/Mpa at the Gorae-V aquifer, the aquifer can sustain CO₂ injection at a rate of 2,425 tons per day over this time period. A design for a complete CCS system was developed based on the existing off-shore pipeline in combination with new on-shore CO₂ transport infrastructure, and a pressure of 12.8 MPa is required at the CO₂ source to maintain this injection rate.     

Evidence of gas hydrate from downhole logging data in the Ulleung Basin, East Sea

The Gas Hydrate Research and Development Organization (GHDO) of Korea successfully accomplished both coring (hydraulic piston and pressure coring) and logging (logging-while-drilling, LWD, and wireline logging) to investigate the presence of gas hydrate during the first deep drilling expedition in the Ulleung Basin, East Sea of Korea (referred to as UBGH1) in 2007. The LWD data from two sites (UBGH1-9, UBGH1-10) showed elevated electrical resistivity (>80 Ω-m) and P-wave velocity (>2000 m/s) values indicating the presence of gas hydrate. During the coring period, the richest gas hydrate accumulation was discovered at these intervals. Based on log data, the occurrence of gas hydrate is primarily controlled by the presence of fractures. The gas hydrate saturation calculated using Archie’s relation shows greater than 60% (as high as ∼90%) of the pore space, although Archie’s equation typically overestimates gas hydrate saturation in near-vertical fractures. The saturation of gas hydrate is also estimated using the modified Biot-Gassmann theory (BGTL) by Lee and Collett (2006). The saturation values estimated rom BGTL are much lower than those calculated from Archie’s equation. Based on log data, the hydrate-bearing sediment section is approximately 70 m (UBGH1-9) to 130 m (UBGH1-10) in thickness at these two sites. This was further directly confirmed by the recovery of gas hydrate samples and pore water freshening collected from deep drilling core during the expedition. LWD data also strongly support the interpretation of the seismic gas hydrate indicators (e.g., vent or chimney structures and bottom-simulating reflectors), which imply the probability of widespread gas hydrate presence in the Ulleung Basin.     

Empirical ocean-color algorithms to retrieve chlorophyll-a, total suspended matter, and colored dissolved organic matter absorption coefficient in the Yellow and East China Seas

A bio-optical dataset collected during the 1998?C2007 period in the Yellow and East China Seas (YECS) was used to provide alternative empirical ocean-color algorithms in the retrieval of chlorophyll-a (Chl-a), total suspended matter (TSM), and colored dissolved organic matter (CDOM) absorption coefficients at 440 nm (ag₄₄₀). Assuming that remote-sensing reflectance (Rrs) could be retrieved accurately, empirical algorithms for T_Chl (regionally tuned Tassan??s Chl-a algorithm) in case-1 waters (T_Chl2i in case-2 waters), T_TSM (regionally tuned Tassan??s TSM algorithm), and T_ag440 or C_ag440 (regionally tuned Tassan??s or Carder??s ag₄₄₀ algorithm) were able to retrieve Chl-a, TSM, and ag₄₄₀ with uncertainties as high as 35, 46, and 35%, respectively. Applying the standard SeaWiFS Rrs, T_Chl was not viable in the eastern part of the YECS, which was associated with an inaccurate SeaWiFS Rrs retrieval because of improper atmospheric correction. T_Chl behaved better than other algorithms in the turbid case-2 waters, although overestimation was still observed. To retrieve more reliable Chl-a estimates with standard SeaWiFS Rrs in turbid water (a proxy for case-2 waters), we modified T_Chl for data with SeaWiFS normalized water-leaving radiance at 555 nm (nLw₅₅₅) > 2 mW cm^?2 ??m^?1 sr^?1 (T_Chl2s). Finally, with standard SeaWiFS Rrs, we recommend switching algorithms from T_Chl2s (for case-2 waters) to MOC_Chl (SeaWiFS-modified NASA OC4v4 standard algorithm for case-1 waters) for retrieving Chl-a, which resulted in uncertainties as high as 49%. To retrieve TSM and ag₄₄₀ using SeaWiFS Rrs, we recommend empirical algorithms for T_TSM (pre-SeaWiFS-modified form) and MT_ag440 or MC_ag440 (SeaWiFS Rrs-modified forms of T_ag440 or C_ag440). These could retrieve with uncertainties as high as 82 and 52%, respectively.