The surface roughness and planetary boundary layer

Applications of the entrainment process to layers at the boundary, which meet the self similarity requirements of the logarithmic profile, have been studied. By accepting that turbulence has dominating scales related in scale length to the height above the surface, a layer structure is postulated wherein exchange is rapid enough to keep the layers internally uniform. The diffusion rate is then controlled by entrainment between layers. It has been shown that theoretical relationships derived on the basis of using a single layer of this type give quantitatively correct factors relating the turbulence, wind and shear stress for very rough surface conditions. For less rough surfaces, the surface boundary layer can be divided into several layers interacting by entrainment across each interface. This analysis leads to the following quantitatively correct formula compared to published measurements. 1 $$\begin{gathered} \frac{{\sigma _w }}{{u^* }} = \left( {\frac{2}{{9Aa}}} \right)^{{1 \mathord{\left/ {\vphantom {1 4}} \right. \kern-\nulldelimiterspace} 4}} \left( {1 - 3^{{1 \mathord{\left/ {\vphantom {1 2}} \right. \kern-\nulldelimiterspace} 2}} \frac{a}{k}\frac{{d_n }}{z}\frac{{\sigma _w }}{{u^* }}\frac{z}{L}} \right)^{{1 \mathord{\left/ {\vphantom {1 4}} \right. \kern-\nulldelimiterspace} 4}} \hfill \\ = 1.28(1 - 0.945({{\sigma _w } \mathord{\left/ {\vphantom {{\sigma _w } {u^* }}} \right. \kern-\nulldelimiterspace} {u^* }})({z \mathord{\left/ {\vphantom {z L}} \right. \kern-\nulldelimiterspace} L})^{{1 \mathord{\left/ {\vphantom {1 4}} \right. \kern-\nulldelimiterspace} 4}} \hfill \\ \end{gathered} $$ where \(u^* = \left( {{\tau \mathord{\left/ {\vphantom {\tau \rho }} \right. \kern-0em} \rho }} \right)^{{1 \mathord{\left/ {\vphantom {1 2}} \right. \kern-0em} 2}} \) , σ _w is the standard deviation of the vertical velocity,z is the height andL is the Obukhov scale lenght. The constantsa, A, k andd _n are the entrainment constant, the turbulence decay constant, Von Karman's constant, and the layer depth derived from the theory. Of these,a andA, are universal constants and not empirically determined for the boundary layer. Thus the turbulence needed for the plume model of convection, which resides above these layers and reaches to the inversion, is determined by the shear stress and the heat flux in the surface layers. This model applies to convection in cool air over a warm sea. The whole field is now determined except for the temperature of the air relative to the water, and the wind, which need a further parameter describing sea surface roughness. As a first stop to describing a surface where roughness elements of widely varying sizes are combined this paper shows how the surface roughness parameter,z ₀, can be calculated for an ideal case of a random distribution of vertical cylinders of the same height. To treat a water surface, with various sized waves, such an approach modified to treat the surface by the superposition of various sized roughness elements, is likely to be helpful. Such a theory is particularly desirable when such a surface is changing, as the ocean does when the wind varies. The formula, 2 $$\frac{{0.118}}{{a_s C_D }}< z_0< \frac{{0.463}}{{a_s C_D (u^* )}}$$ is the result derived here. It applies to cylinders of radius,r, and number,m, per unit boundary area, wherea _s =2rm, is the area of the roughness elements, per unit area perpendicular to the wind, per unit distance downwind. The drag coefficient of the cylinders isC _D . The smaller value ofz _o is for large Reynolds numbers where the larger scale turbulence at the surface dominates, and the drag coefficient is about constant. Here the flow between the cylinders is intermittent. When the Reynolds number is small enough then the intermittent nature of the turbulence is reduced and this results in the average velocity at each level determining the drag. In this second case the larger limit forz ₀ is more appropriate.     

State of stress in the lithosphere: Inferences from the flow laws of olivine

The experimental flow data for rocks and minerals are reviewed and found to fit a law of the form $$\dot \varepsilon = A'\left[ {sinh (\alpha \sigma )} \right]^n \exp \left[ {{{ - (E * + PV * )} \mathord{\left/ {\vphantom {{ - (E * + PV * )} {RT}}} \right. \kern-\nulldelimiterspace} {RT}}} \right]$$ where \(\dot \varepsilon \) This law reduces to the familiar power-law stress dependency at low stress and to an exponential stress dependency at high stress. Using the material flow law parameters for olivine, stress profiles with depth and strain rate are computed for a representative range of temperature distributions in the lithosphere. The results show that the upper 15 to 25 km of the oceanic lithosphere must behave elastically or fail by fracture and that the remainder deforms by exponential law flow at intermediate depths and by power-law flow in the rest. A model computation of the gravitational sliding of a lithospheric plate using olivine rheology exhibits a very sharp decoupling zone which is a consequence of the combined effects of increasing stress and temperature on the flow law, which is a very sensitive function of both.     

An analytical method for the evaluation of the in-plan irregularity of non-regularly asymmetric buildings

This paper describes a new method for the evaluation of the static eccentricity $e_{s}$ and the ratio $\Omega _{\uptheta } $ of uncoupled torsional to lateral frequencies in real multi-storey buildings. The above-mentioned parameters greatly affect the lateral-to-torsional coupling of the response of asymmetric systems and thus are of paramount importance in the assessment of the in-plan irregularity of buildings. The proposed method, which is a generalization of that suggested by Calderoni et al. (Earthq Spectra 18(2):219–231, 2002), allows the calculation of the static eccentricity $e_{s}$ and the ratio $\Omega _{\uptheta } $ from the structural response to arbitrary distributions of forces and torsional couples. The effectiveness of the method is validated on some regularly and non-regularly asymmetric buildings characterised by different in-plan irregularity. The analyses demonstrate that the results of the method are rigorous in the case of regularly asymmetric systems and only slightly depend upon the heightwise distribution of the forces in the case of non-regularly asymmetric systems. Finally, the values of the static eccentricity $e_{s}$ and the ratio $\Omega _{\uptheta } $ resulting from the proposed method are compared to those obtained by means of the procedure suggested by Makarios and Anastassiadis in (Struct Des Tall Spec Build 7(1):33–55, 1998a; Struct Des Tall Spec Build 7(1):57–71, 1998b) .     

A Crustal Model for the Eastern Alps Region and a New Moho Map in Southeastern Europe

In the last two decades, south-central Europe and the Eastern Alps have been widely explored by many seismic refraction experiments (e.g., CELEBRATION 2000, ALP 2002, SUDETES 2003). Although quite detailed images are available along linear profiles, a comprehensive, three-dimensional crustal model of the region is still missing. This limitation makes this region a weak spot in continental-wide comprehensive representations of crustal structure. To improve on this situation, we select and collect 37 published active-source seismic lines in this region. After geo-referencing each line, we sample them along vertical profiles—every 50?km or less along the line—and derive P-wave velocities in a stack of homogeneous layers (separated by discontinuities: depth of crystalline basement, top of lower crust, and Moho). We finally merge the information using geostatistical methods, and infer S-wave velocity and density using empirical scaling relations. We present here the resulting crustal model for a region encompassing the Eastern Alps, Dinarides, Pannonian basin, Western Carpathians and Bohemian Massif, covering the region within $45^{\circ}\text{--}51^{\circ}\hbox{N}$ and $11^{\circ} \text{--} 22^{\circ}\hbox{E}$ with a resolution of $0.2^{\circ} \times 0.2^{\circ}.$ We are also able to extend and update the map of Moho depth in a wider region within $35^{\circ}\text{--}51^{\circ}\hbox{N}$ and $12^{\circ}\text{--}45^{\circ}\hbox{E},$ gathering Moho values from the collected seismic lines, other published dataset and using the European plate reference EPcrust as a background. All the digitized profiles and the resulting model are available online.     

Empirical ground-motion relations using moderate earthquakes recorded by Medellín–Aburrá Valley (Colombia) strong-motion networks

We tested attenuation relations obtained for different regions of the world to verify their suitability to predict strong-motion data recorded by Medellín and Aburrá Valley Accelerographic Networks. We used as comparison criteria, the average of the difference between the observed and the predicted data as a function of epicenter distance and its standard deviation. We also used the approach developed by Sherbaum et al. (Bull Seism Soc Am 94:2164–2185, 2004) that provides a method to evaluate the overall goodness-of-fit of ground-motion prediction equations. The predictive models selected use a generic focal depth. We found that this parameter has an important influence in the ground-motion predictions and must be taken into account as an independent variable. We also found important to characterize the local soil amplification to improve the attenuation relations. We found empirical relations for peak horizontal acceleration PGA and velocity PGV based on the Kamiyama and Yanagisawa (Soils Found 26:16–32, 1986) approach. $$\begin{aligned} \log _{10} (PGA)=0.5886M_L -1.0902\log _{10}(R)-0.0035H+C_{st}\pm 0.\text{29} \end{aligned}$$ $$\begin{aligned} \log _{10} (PGV)=0.7255M_L -1.8812\log _{10}(R)-0.0016H+C_{st}\pm 0.36 \end{aligned}$$ where PGA is measured in cm/s $^{2}$ and PGV in cm/s, $M_{L}$ is local magnitude in the range 2.8–6.5, $R$ is epicentral distance up to 290 km, $H$ is focal depth in km and $C_{st}$ is a coefficient that accounts for the site response due to soil conditions of each recording station. The introduction of focal depth and local site conditions as independent variables, minimize the residuals and the dispersion of the predicted data. We conclude that $H$ and $C_{st}$ are sensitive parameters, having a strong influence on the strong-motion predictions. Using the same functional form, we also propose an empirical relation for the root mean square acceleration a $_\mathrm{rms}$ : $$\begin{aligned} \log _{10} \left( {a_{rms} } \right)=0.4797M_L -1.1665\log _{10} (R)-0.00201H+C_{st}\pm 0.40 \end{aligned}$$ where a $_\mathrm{rms}$ is measured in cm/s $^{2}$ , from the S-wave arrival and using a window length equal to the rupture duration. The other variables are the same as those for PGA and PGV. The site correction coefficients $C_{st}$ found for PGA, PGV and a $_\mathrm{rms}$ show a similar trend indicating a good correlation with the soil conditions of the recording sites.     

The TKE dissipation rate in the northern South China Sea

The microstructure measurements taken during the summer seasons of 2009 and 2010 in the northern South China Sea (between 18°N and 22.5°N, and from the Luzon Strait to the eastern shelf of China) were used to estimate the averaged dissipation rate in the upper pycnocline 〈ε _p〉 of the deep basin and on the shelf. Linear correlation between 〈ε _p〉 and the estimates of available potential energy of internal waves, which was found for this data set, indicates an impact of energetic internal waves on spatial structure and temporal variability of 〈ε _p〉. On the shelf stations, the bottom boundary layer depth-integrated dissipation $ {\widehat{\varepsilon}}_{\mathrm{BBL}} $ reaches 17–19 mW/m², dominating the dissipation in the water column below the surface layer. In the pycnocline, the integrated dissipation $ {\widehat{\varepsilon}}_{\mathrm{p}} $ was mostly ～10–30 % of $ {\widehat{\varepsilon}}_{\mathrm{BBL}} $ . A weak dependence of bin-averaged dissipation $ \overline{\varepsilon} $ on the Richardson number was noted, according to $ \overline{\varepsilon}={\varepsilon}_0+\frac{\varepsilon_{\mathrm{m}}}{{\left(1+ Ri/R{i}_{\mathrm{cr}}\right)}^{1/2}} $ , where ε ₀ + ε _m is the background value of $ \overline{\varepsilon} $ for weak stratification and Ri _cr?=?0.25, pointing to the combined effects of shear instability of small-scale motions and the influence of larger-scale low frequency internal waves. The latter broadly agrees with the MacKinnon–Gregg scaling for internal-wave-induced turbulence dissipation.     

Electromagnetic induction in the earth due to stationary and moving sources

A new approach to the theory of electromagnetic induction is developed that is applicable to moving as well as stationary sources. The source field is considered to be a standing wave generated by two waves travelling in opposite directions along the surface of the earth. For a stationary source the incident waves have velocities of the same magnitude, however for a moving source the velocities of the two incident waves are respectively increased and decreased by the velocity of the source. Electromagnetic induction in the earth is then considered as refraction of these waves and gives, for both stationary and moving sources, the magnetotelluric relation: $$\frac{{ - E_y }}{{H_x }} = \left( {\frac{{i\omega \mu }}{\sigma }} \right)^{{1 \mathord{\left/ {\vphantom {1 2}} \right. \kern-\nulldelimiterspace} 2}} \left( {1 - i\frac{{v^2 }}{{\omega \mu \sigma }}} \right)^{ - {1 \mathord{\left/ {\vphantom {1 2}} \right. \kern-\nulldelimiterspace} 2}} $$ where ν is the wavenumber of the source, μ is the permeability (4π·10^?7) and σ is the conductivity of the earth. ω is the angular frequency of the variation observed on the earth. For a stationary source the observed frequency is the same as the source frequency, however the effect of moving a time-varying source is to make the observed frequency different from the frequency of the source. Failure to recognise this in previous studies led to some erroneous conclusions. This study shows that a moving source isnot “electromagnetically broader” than a stationary source as had been suggested.     

Near real-time automatic moment magnitude estimation

In this paper we describe a stable automatic method to estimate in real time the seismic moment, moment magnitude and corner frequency of events recorded by a network comprising broad-band and accelerometer sensors. The procedure produces reliable results even for small-magnitude events $\hbox {M}_{\mathrm{W}}\approx 3$ . The real-time data arise from both the Transfrontier network at the Alps-Dinarides junction and from the Italian National Accelerometric Network (RAN). The data is pre-processed and the S-wave train identified through the application of an automatic method, which estimates the arrival times based on the hypocenter location, recording site and regional velocity model. The transverse component of motion is used to minimize conversion effects. The source spectrum is obtained by correcting the signals for geometrical spreading and intrinsic attenuation. Source spectra for both velocity and displacement are computed and, following Andrews (1986), the seismic moment and the first estimate of the corner frequency, $f_{0}$ , derived. The procedure is validated using the recordings of some recent moderate earthquakes (Carnia 2002; Bovec 2004; Parma 2008; Aquila 2009; Macerata 2009; Emilia 2012) and the recordings of some minor events in the SE Alps area for which independent seismic moment and moment magnitude estimates are available. The results obtained with a dataset of 843 events recorded by the Transfrontier and RAN networks show that the procedure is reliable and robust for events with $\hbox {M}_{\mathrm{W}}\ge 3$ . The estimates of $f_{0}$ are less reliable. The results show a scatter, principally for small events with $\hbox {M}_{\mathrm{W}}\le 3$ , probably due to site effects and inaccurate locations.     

On the seismic response of under-designed caisson foundations

The seismic behaviour of caisson foundations supporting typical bridge piers is analysed with 3D finite elements, with due consideration to soil and interface nonlinearities. Single-degree-of freedom oscillators of varying mass and height, simulating heavily and lightly loaded bridge piers, founded on similar caissons are studied. Four different combinations of the static ( $\text{ FS }_\mathrm{V}$ FS V ) and seismic ( $\text{ FS }_\mathrm{E}$ FS E ) factors of safety are examined: (1) a lightly loaded ( $\text{ FS }_\mathrm{V}= 5$ FS V = 5 ) seismically under-designed ( $\text{ FS }_\mathrm{E} < 1$ FS E < 1 ) caisson, (2) a lightly loaded seismically over-designed ( $\text{ FS }_\mathrm{E} >1$ FS E > 1 ) caisson, (3) a heavily loaded ( $\text{ FS }_\mathrm{V} = 2.5$ FS V = 2.5 ) seismically under-designed ( $\text{ FS }_\mathrm{E} < 1$ FS E < 1 ) caisson and (4) a heavily loaded seismically over-designed caisson. The analysis is performed with use of seismic records appropriately modified so that the effective response periods (due to soil-structure-interaction effects) of the studied systems correspond to the same spectral acceleration, thus allowing their inelastic seismic performance to be compared on a fair basis. Key performance measures of the systems are then contrasted, such as: accelerations, displacements, rotations and settlements. It is shown that the performance of the lightly loaded seismically under-designed caisson is advantageous: not only does it reduce significantly the seismic load to the superstructure, but it also produces minimal residual displacements of the foundation. For heavily loaded foundations, however ( $\text{ FS }_{V} = 2.5$ FS V = 2.5 ), the performance of the two systems (over and under designed) is similar.     

Electric conductivities of a cracked solid

Calculations on the basis of the self-consistent approximation are used to study the effects of randomly distributed elliptical cracks and of non-randomly distributed circular cracks, either dry or saturated by a highly conductive material phase, on the electric conductivities of a cracked body. Analytic and numeric results are given for two special non-random distributions. In the first, the cracks are assumed randomly distributed in planes parallel to a given plane. In the second, the crack normals are randomly distributed in parallel planes. The results of the theoretical calculations indicate that the magnitudes of the crack induced variations of the dry cracked rock depend upon a crack density parameter ? rather than upon the crack porosity. Here, ? is defined as $$\varepsilon = \frac{{2N}}{\pi }< \frac{{A^2 }}{P} > $$ whereN is the average number of cracks per unit volume, andA andP are the crack area and perimeter respectively. (For circular cracks of radiusa, ?=N〈a³〉.) Although a straightforward relationship does connect ? with the porosity, it may be more meaningful for laboratory experiments to concentrate upon measuring crack-induced variations as functions of crack density rather than of porosity. For saturated cracked rocks, the results of the calculations indicate that, in addition to ?, variations in conductivity depend also upon a saturation parameter Ω, which relates crack aspect ratio α to matrix and fluid conductivities σ and σ_F $$\Omega = \frac{{{\sigma \mathord{\left/ {\vphantom {\sigma {\sigma _F }}} \right. \kern-\nulldelimiterspace} {\sigma _F }}}}{\alpha }.$$      

Estimates of fracture parameters of earthquakes

A new estimate of the fracture parameters of earthquakes is provided in this paper. By theMuskhelishvili method (1953) a number of basic relations among fracture-mechanics parameters are derived. A scheme is proposed to evaluate the slip weakening parameters in terms of fault dimension, average slip, and rise time, and the new results are applied to 49 events compiled in the earthquake catalogue ofPurcaru andBerckhemer (1982). The following empirical relations are found in the paper: $$\begin{gathered} \frac{{\tau _B - \tau _f }}{{\tau _\infty - \tau _f }} = 2.339 \hfill \\ {{\omega _c } \mathord{\left/ {\vphantom {{\omega _c } {W = 0.113}}} \right. \kern-\nulldelimiterspace} {W = 0.113}} \hfill \\ \log G_c \left( {{{dyne} \mathord{\left/ {\vphantom {{dyne} {cm}}} \right. \kern-\nulldelimiterspace} {cm}}} \right) = 2 \log L (km) + 6.167 \hfill \\ \log \delta _c (cm) = 2 \log L (km) - 1.652 \hfill \\ \end{gathered} $$ whereG _c is the specific fracture energy,ω _c the size of the slip weakening zone,δ _c the slip weakening displacement,τ _B ?τ _f the drop in strength in the slip weakening zone,τ _∞?τ _f the stress drop,L the fault length, andW the fault width. The investigation of 49 shocks shows that the range of strength dropτ _B ?τ _f is from several doze to several hundred bars at depthh<400 km, but it can be more than 10³ bars ath>500 km; besides, the range of the sizeω _c of the strength degradation zone is from a few tenths of a kilometer to several dozen kilometers, and the range of the slip weakening displacementδ _c is from several to several hundred centimeters. The specific fracture energyG _c is of the order of 10⁸ to 10¹¹ erg cm^?2 when the momentM ₀ is of the order of 10²³ to 10²⁹ dyne cm.     

Empirical ground-motion models for point- and extended-source crustal earthquake scenarios in Europe and the Middle East

This article presents the latest generation of ground-motion models for the prediction of elastic response (pseudo-) spectral accelerations, as well as peak ground acceleration and velocity, derived using pan-European databases. The models present a number of novelties with respect to previous generations of models (Ambraseys et al. in Earthq Eng Struct Dyn 25:371–400, 1996, Bull Earthq Eng 3:1–53, 2005; Bommer et al. in Bull Earthq Eng 1:171–203, 2003; Akkar and Bommer in Seismol Res Lett 81:195–206, 2010), namely: inclusion of a nonlinear site amplification function that is a function of $\text{ V }_\mathrm{S30}$ and reference peak ground acceleration on rock; extension of the magnitude range of applicability of the model down to $\text{ M }_\mathrm{w}$ 4; extension of the distance range of applicability out to 200 km; extension to shorter and longer periods (down to 0.01 s and up to 4 s); and consistent models for both point-source (epicentral, $\text{ R }_\mathrm{epi}$ , and hypocentral distance, $\text{ R }_\mathrm{hyp}$ ) and finite-fault (distance to the surface projection of the rupture, $\text{ R }_\mathrm{JB}$ ) distance metrics. In addition, data from more than 1.5 times as many earthquakes, compared to previous pan-European models, have been used, leading to regressions based on approximately twice as many records in total. The metadata of these records have been carefully compiled and reappraised in recent European projects. These improvements lead to more robust ground-motion prediction equations than have previously been published for shallow (focal depths less than 30 km) crustal earthquakes in Europe and the Middle East. We conclude with suggestions for the application of the equations to seismic hazard assessments in Europe and the Middle East within a logic-tree framework to capture epistemic uncertainty.     

Single-station standard deviation analysis of 2010–2012 strong-motion data from the Canterbury region, New Zealand

A systematic analysis was conducted of the different variability components that affect the prediction of $\text{ log }_{10}(PSA)$ (i.e., Pseudo-Spectral Acceleration) ordinates on (mostly) deep sedimentary soil sites using a sizable set of strong motion data recorded in the strong earthquake sequences of 2010 and 2012 in the Canterbury region of New Zealand. Following recent, well established approaches of residual analysis of ground motion predictions, as well as recent GMPEs based on a global dataset, it was found that the event-corrected single-station standard deviation (“sigma”) is strongly decreased, for all selected stations, with respect to the uncorrected sigma. Likewise, the event-corrected intraevent sigma estimated for the entire dataset is significantly reduced compared to the standard deviation associated to ground motion prediction models, i.e. the “ergodic” sigma, for all spectral periods. The event-corrected sigma values for the present dataset are surprisingly consistent with those recently derived using KiK-Net strong motion data from Japan and those by Boore and Atkinson (Earthq Spectra 34(1):99–138, 2008) GMPE, and remain fairly constant with respect to the spectral period at about $0.15\sim 0.2$ . An interpretation was provided of the physical meaning of the site correction term ( ${\delta }S2S)_{s}$ indicating a plausible correlation with prevailing geological conditions in the site area.     

A theoretical value for von Karman's constant

This paper extends the theory of the entity and entrainment model of turbulence to obtain a numerical value of von Karman's constant,k=0.37. The formula is, $$k = (2a^3 /A)^{{1 \mathord{\left/ {\vphantom {1 4}} \right. \kern-\nulldelimiterspace} 4}} \ln \beta $$ where,a=1/12 is the entrainment constant,A=1 is the turbulent decay constant, and β is the ratio in height of the successive self-similar layers of the theory, where β is evaluated as β=e ². These new values fork and β improve the surface roughness length estimates derived from this theory.     

A model for the simulation of turbulent and eddy diffusion processes at heights of 0–65 km

A generalized turbulent diffusion model has been developed which evaluates the time rate of growth of a simulated cloud of particles released into a turbulent (i.e. diffusive) atmosphere. The general model, in the form of second-order differential equations, computes the three-dimensional size of the cloud as a function of time. Parameters which influence the cloud growth, and which are accounted for in the model equations, are: (1) length scales and velocity magnitudes of the diffusive field, (2) rate of viscous dissipation , (3) vertical stability as characterized by the relative adiabatic lapse rate (1/T)(g/C _p +T/z), and (4) vertical shear in the mean horizontal winds , and , for a given height and of spatial extent equal to that of the diffusing cloud. Sample results for near ground level and for upper stratospheric heights are given. For the atmospheric boundary layer case, the diffusive field is microscale turbulence. In the upper stratospheric case it is considered to be a field of highly interactive and dispersive gravity waves.     

Towards fully data driven ground-motion prediction models for Europe

We have used the Artificial Neural Network method (ANN) for the derivation of physically sound, easy-to-handle, predictive ground-motion models from a subset of the Reference database for Seismic ground-motion prediction in Europe (RESORCE). Only shallow earthquakes (depth smaller than 25 km) and recordings corresponding to stations with measured $V_{s30}$ properties have been selected. Five input parameters were selected: the moment magnitude $M_{W}$ , the Joyner–Boore distance $R_{JB}$ , the focal mechanism, the hypocentral depth, and the site proxy $V_{S30}$ . A feed-forward ANN type is used, with one 5-neuron hidden layer, and an output layer grouping all the considered ground motion parameters, i.e., peak ground acceleration (PGA), peak ground velocity (PGV) and 5 %-damped pseudo-spectral acceleration (PSA) at 62 periods from 0.01 to 4 s. A procedure similar to the random-effects approach was developed to provide between and within event standard deviations. The total standard deviation ( $\sigma $ ) varies between 0.298 and 0.378 (log $_{10}$ unit) depending on the period, with between-event and within-event variabilities in the range 0.149–0.190 and 0.258–0.327, respectively. Those values prove comparable to those of conventional GMPEs. Despite the absence of any a priori assumption on the functional dependence, our results exhibit a number of physically sound features: magnitude scaling of the distance dependency, near-fault saturation distance increasing with magnitude, amplification on soft soils and even indications for nonlinear effects in softer soils.     

Interannual variability of the air–sea CO2 flux in the north Indian Ocean

A simple biogeochemical model coupled to an offline ocean tracer transport model driven by reanalysis ocean data is used to simulate the seasonal and interannual CO $_2$ flux variability in the northern Indian Ocean. The maximum of seasonal and interannual CO $_2$ emission variances in the northern Indian Ocean are located in the coastal Arabian Sea (AS) and Southern Peninsular India (SP) with a basin-wide seasonal amplitude and standard deviation of 0.044 $\pm $ 0.04 Pg C year $^{-1}$ . The area integrated CO $_2$ emissions from these two regions in the model are significantly correlated (above a 95 % level) with the observations of Takahashi et al. (Deep-Sea Res-II, 56:554–577, 2009). The interannual anomalies of CO $_2$ emission from the AS and SP are found as 40 and 30 % of their respective seasonal amplitudes. Both the Arabian Sea (AS) and Southern Peninsular India (SP) interannual CO $_2$ emission anomalies show a 3–4-year variability. The correlations of AS and SP CO $_2$ emission anomalies with the Indian Ocean Dipole/Zonal Mode (IODZM) and Southern Oscillation (SO) indices from 1980 to 1999 are 0.35, 0.21 and 0.32, 0.01 respectively. A 5-year window moving correlation analysis shows that the relationship of AS and SP CO $_2$ emission to the SO and IODZM are complementary to each other. During the years when the correlation of air–sea CO $_2$ emission with the IODZM is stronger, the corresponding correlation with the SO is weaker or opposite. The total change in pCO $_2$ is broken down into changes induced by the individual components such as dissolved inorganic carbon (DIC), sea surface temperature (SST), alkalinity, and salinity and found that (1) the effect of SST in the AS CO $_2$ emission increases (decreases) when the correlation of CO $_2$ emission with the IODZM is positive (negative), and (2) the SP CO $_2$ emission is strongly controlled by the circulation-driven DIC changes; however, this relation is found to be weaker when the SO correlates negatively with the SP CO $_2$ emission.