Energy demands for seismic design against low‐cycle fatigue

A seismic design procedure that does not take into account the maximum and cumulative plastic deformation demands that a structure is likely to undergo during severe ground motion could lead to unsatisfactory performance. In spite of this, current design procedures do not take into account explicitly the effect of low‐cycle fatigue. Based on the high correlation that exists between the strength reduction factor and the energy demand in earthquake‐resistant structures, simple procedures can be formulated to estimate the cumulative plastic deformation demands for design purposes. Several issues should be addressed during the use of plastic energy within a practical performance‐based seismic design methodology. Copyright © 2006 John Wiley & Sons, Ltd.     

Flow and deposition of pyroclastic granular flows: A type example from the 1975 Ngauruhoe eruption,New Zealand

Small-volume pyroclastic density currents (PDCs) are generated frequently during explosive eruptions with little warning. Assessing their hazard requires a physical understanding of their transport and sedimentation processes which is best achieved by the testing of experimental and numerical models of geophysical mass flows against natural flows and/or deposits. To this end we report on one of the most detailed sedimentological studies ever carried out on a series of pristine small-volume PDC deposits from the 1975 eruption of Ngauruhoe volcano, whose emplacement were also witnessed during eruption. Using high-resolution GPS surveys, a series of lateral excavations across the deposits, and bulk sedimentological analysis we constrained the geomorphology, internal structure and texture of the deposits with respect to laterally varying modes of deposition.     

GPS network monitors the Western Alps' deformation over a five-year period: 1993–1998

  The Western Alps are among the best studied collisional belts with both detailed structural mapping and also crustal geophysical investigations such as the ECORS and EGT seismic profile. By contrast, the present-day kinematics of the belt is still largely unknown due to small relative motions and the insufficient accuracy of the triangulation data. As a consequence, several tectonic problems still remain to be solved, such as the amount of N–S convergence in the Occidental Alps, the repartition of the deformation between the Alpine tectonic units, and the relation between deformation and rotation across the Alpine arc. In order to address these problems, the GPS ALPES group, made up of French, Swiss and Italian research organizations, has achieved the first large-scale GPS surveys of the Western Alps. More than 60 sites were surveyed in 1993 and 1998 with a minimum observation of 3 days at each site. GPS data processing has been done by three independent teams using different software. The different solutions have horizontal repeatabilities (N–E) of 4–7 mm in 1993 and 2–3 mm in 1998 and compare at the 3–5-mm level in position and 2-mm/yr level in velocity. A comparison of 1993 and 1998 coordinates shows that residual velocities of the GPS marks are generally smaller than 2 mm/yr, precluding a detailed tectonic interpretation of the differential motions. However, these data seem to suggest that the N–S compression of the Western Alps is quite mild (less than 2 mm/yr) compared to the global convergence between the African and Eurasian plate (6 mm/yr). This implies that the shortening must be accomodated elsewhere by the deformation of the Maghrebids and/or by rotations of Mediterranean microplates. Also, E–W velocity components analysis supports the idea that E–W extension exists, as already suggested by recent structural and seismotectonic data interpretation. Received: 27 November 2000 / Accepted: 17 September 2001     

Laser-based validation of GLONASS orbits by short-arc technique

 The International GLONASS Experiment (IGEX-98) was carried out between 19 October 1998 and 19 April 1999. Among several objectives was the precise orbit determination of GPS and GLONASS satellites and its validation by laser ranging observations. Local laser-based orbit corrections (radial, tangential and normal components in a rotating orbital local reference frame) are computed using a geometrical short-arc technique. The order of magnitude of these corrections is at the level of few decimeters, depending on the considered components. The orbit corrections are analyzed as a function of several parameters (date, orbital plane, geographical area). The mean corrections are at the level of several centimeters. However, when averaging over the entire campaign and for all the satellites, no mean radial, tangential and normal orbit corrections are found. The origin of the observed corrections is considered (errors due to the geocentric gravitational constant, the non-gravitational forces, the thermal equilibrium of on-board equipment, the reference systems, the location and the signature of the retroreflector array, and the precision of the satellite laser ranges). Some features are also due to errors in the radio-tracking GLONASS orbits. Further investigations will be needed to better understand the origin of various biases. Received: 17 February 2000 / Accepted: 31 January 2001     

Comparison of Agricultural Impacts of Climate Change Calculated from High and Low Resolution Climate Change Scenarios: Part I. The Uncertainty Due to Spatial Scale

We investigated the effect of two different spatial scales of climate change scenarios on crop yields simulated by the EPIC crop model for corn, soybean, and wheat, in the central Great Plains of the United States. The effect of climate change alone was investigated in Part I. In Part II (Easterling et al., 2001) we considered the effects ofCO₂ fertilization effects and adaptation in addition to climate change. The scenarios were formed from five years of control and 2 ×CO₂ runs of a high resolution regional climate model (RegCM) and the same from an Australian coarse resolution general circulation model (GCM), which provided the initial and lateral boundary conditions for the regional model runs. We also investigated the effect of two different spatial resolutions of soil input parameters to the crop models. We found that for corn and soybean in the eastern part of the study area, significantly different mean yield changes were calculated depending on the scenario used. Changes in simulated dryland wheat yields in the western areas were very similar, regardless of the scale of the scenario. The spatial scale of soils had a strong effect on the spatial variance and pattern of yields across the study area, but less effect on the mean aggregated yields. We investigated what aspects of the differences in the scenarios were most important for explaining the different simulated yield responses. For instance, precipitation changes in June were most important for corn and soybean in the eastern CSIRO grid boxes. We establish the spatial scale of climate changescenarios as an important uncertainty for climate change impacts analysis.     

Global-Scale Relationships between Climate and the Dengue Fever Vector, Aedes Aegypti

Considerable interest exists inthe potential role climate may play in human healthissues, especially regarding the effect of climatechange on vector-borne disease. The Aedesaegypti mosquito, the principal vector for dengue,considered the most important vector-borne viraldisease in the world, is particularly susceptible toclimate variability and climatic change. Here wepresent a modeling analysis focusing on global-scaleassociations between climate and the development,potential distribution, and population dynamics ofAe. aegypti. We evaluate the model by comparingand contrasting model data with observed mosquitodensities. There is good agreement between theobserved and modeled global distribution of themosquito; however, the model results suggest thepotential for increased latitudinal distributionsduring warmer months. Seasonal fluctuations inmosquito abundance also compare well to observed data. Discrepancies possibly reflect the relatively lowresolution of the climate data and model output andthe inability of the model to account for localmicroclimate effects, especially in coastal areas.Future modeling efforts will involve study ofinterannual variability in mosquito dynamics.     

Multivariate ENSO index and Indian monsoon rainfall: relationships on monthly and subdivisional scales

Summary El Ni?o/Southern Oscillation (ENSO) is known to cause world-wide weather anomalies. It influences the Indian Monsoon Rainfall (IMR) also. But due to large spatial and temporal variability of monsoon rains, it becomes difficult to state any single uniform relationship between the ENSO and IMR that holds good over different subdivisions of India, though the general type of relationship between all India monsoon rainfall and ENSO is known since long. The selection of the most suitable ENSO index to correlate with the IMR is another problem. The purpose of the present study is twofold, namely, to examine the relationship between the ENSO and IMR for entire monsoon season by using an ENSO index which represents the ENSO phenomenon in a comprehensive way, namely, the Multivariate ENSO Index (MEI) and to establish the relationships between MEI and IMR for every meteorological subdivision of India for each monsoon month; i.e. June, July, August and September. A comparison of MEI/IMR correlations has been made with Southern Oscillation Index (SOI)/IMR correlations. The result may find applications in the long range forecasting of IMR on monthly and subdivisional scales, especially over the high monsoon rainfall variability regions of Northwestern and the Peninsular India. Received October 27, 2000     

Internal variability of regional climate models

 Two regional climate models have been applied to the task of generating an ensemble of realizations of the year 1982 with observed boundary conditions in areas covering parts of the Mediterranean countries. These realizations were generated by applying boundary conditions from the ECMWF ERA reanalysis project consecutively, carrying over the soil variables from the regional models from one iteration to the next. Monthly mean fields for six iterations of each model have been used as statistical ensembles in order to investigate the internal variability of the regional model dynamics. This internal variability is a necessary consequence of the non-linear physical feedback mechanisms of the RCM being active. A small value of internal variability will give better statistics for climate sensitivity signals, but will make these results less credible. The internal variability is important for the quantitative assessment of a climate sensitivity signal. With the present choice of models and integration domains the internal variabilities of surface fields and precipitation do reach levels that are less than, but in summer of comparable order of magnitude to, corresponding atmospheric variabilities of an atmospheric general circulation model. Received: 26 October 1999 / Accepted: 18 December 2000