Seismic study of the Mesozoic carbonate basement around Mt. Somma–Vesuvius, Italy

Fifteen seismic reflection lines from AGIP surveys, in and around the Campanian Plain and Mt. Somma–Vesuvius (south Italy) have been interpreted. The attention has been focused to the horizon pertinent to the top of the Mesozoic carbonate sequence and the Quaternary faults dissecting it. As a matter of fact, both are very important elements for understanding the origin of the volcanic activity in the area, that often in the past, has been the topic of debates not supported by reliable data. In the study area, referring to the depth of the carbonate basement, comparison between the result achieved by the seismic prospecting and previous gravity studies has been made. It shows coherence in some areas but large discrepancy within others. Near the town of S. Anastasia, the gravity and seismic depth estimates differ as much as 1000 m or more. Furthermore, the seismic data show that the source of the greatest volcanic eruption in the area (the so-called ‘Campanian Ignimbrite') is probably not located in the Acerra depression, as suggested by other authors. A main NE–SW fault directed toward Vesuvius, considered as playing a primary role on volcanogenetic processes and previously recognised only offshore by marine seismic survey, has been now identified also inland using this new seismic information. The results presented here strengthen the hypothesis that Mt. Vesuvius is located at the crossing point of two regional Quaternary sets of fault heading NW–SE and NE–SW.     

Use of the Geometric Elements in Numerical Simulations

We derive the transformations to convert the state vector in cartesian coordinates into geometric orbital elements (and conversely the geometric elements into the state vector) for a test particle moving around an oblate planet. These transformations arise from the epicyclic theory and are accurate to second order in eccentricity and inclination. This paper is written to be directly used for computational purposes, such as the numerical study of ring dynamics.     

Role of fronts in the formation of Arabian Sea barrier layers during summer monsoon

The barrier layer (BL) — a salinity stratification embedded in the upper warm layer — is a common feature of the tropical oceans. In the northern Indian Ocean, it has the potential to significantly alter the air–sea interactions. In the present paper, we investigate the spatio-temporal structure of BL in the Arabian Sea during summer monsoon. This season is indeed a key component of the Asian climate. Based on a comprehensive dataset of Conductivity–Temperature–Depth (CTD) and Argo in situ hydrographic profiles, we find that a BL exists in the central Arabian Sea during summer. However, it is highly heterogeneous in space, and intermittent, with scales of about ～100 km or less and a couple of weeks. The BL patterns appear to be closely associated to the salinity front separating two water masses (Arabian Sea High Salinity Water in the Northern and Eastern part of the basin, fresher Bay of Bengal Water to the south and to the west). An ocean general circulation model is used to infer the formation mechanism of the BL. It appears that thick (more than 40 m) BL patterns are formed at the salinity front by subduction of the saltier water mass under the fresher one in an area of relatively uniform temperature. Those thick BL events, with variable position and timing, result in a broader envelope of thinner BL in climatological conditions. However, the individual patterns of BL are probably too much short-lived to significantly affect the monsoonal air–sea interactions.     

Observation-based blended projections from ensembles of regional climate models

We consider the problem of projecting future climate from ensembles of regional climate model (RCM) simulations using results from the North American Regional Climate Change Assessment Program (NARCCAP). To this end, we develop a hierarchical Bayesian space-time model that quantifies the discrepancies between different members of an ensemble of RCMs corresponding to present day conditions, and observational records. Discrepancies are then propagated into the future to obtain high resolution blended projections of 21st century climate. In addition to blended projections, the proposed method provides location-dependent comparisons between the different simulations by estimating the different modes of spatial variability, and using the climate model-specific coefficients of the spatial factors for comparisons. The approach has the flexibility to provide projections at customizable scales of potential interest to stakeholders while accounting for the uncertainties associated with projections at these scales based on a comprehensive statistical framework. We demonstrate the methodology with simulations from the Weather Research & Forecasting regional model (WRF) using three different boundary conditions. We use simulations for two time periods: current climate conditions, covering 1971 to 2000, and future climate conditions under the Special Report on Emissions Scenarios (SRES) A2 emissions scenario, covering 2041 to 2070. We investigate and project yearly mean summer and winter temperatures for a domain in the South West of the United States.     

Validation of climate model output using Bayesian statistical methods

The growing interest in and emphasis on high spatial resolution estimates of future climate has demonstrated the need to apply regional climate models (RCMs) to that problem. As a consequence, the need for validation of these models, an assessment of how well an RCM reproduces a known climate, has also grown. Validation is often performed by comparing RCM output to gridded climate datasets and/or station data. The primary disadvantage of using gridded climate datasets is that the spatial resolution is almost always different and generally coarser than climate model output. We have used a Bayesian statistical model derived from observational data to validate RCM output. We used surface air temperature (SAT) data from 109 observational stations in California, all with records of approximately 50 years in length, and created a statistical model based on this data. The statistical model takes into account the elevation of the station, distance from coastline, and the NOAA climate region in which the station resides. Analysis indicates that the statistical model provides reliable estimates of the mean monthly SAT at any given station. In our method, the uncertainty in the estimates produced by the statistical model are directly determined by obtaining probability density functions for predicted SATs. This statistical model is then used to estimate average SATs corresponding to each of the climate model grid cells. These estimates are compared to the output of the RCM to assess how well the RCM matches the observed climate as defined by the statistical model. Overall, the match between the RCM output and the statistical model is good, with some deficiencies likely due in part to the representation of topography in the RCM.     

Some results and comments on the Tidal Flow Forum exercise

Two approaches are followed to estimate the fit between ‘observations’ and the results obtained with different numerical models within the frame of the Tidal Flow Forum exercise. The first approach (i.e. the computation of the RMS errors on the timeseries for a specific day) is shown to be insufficient because the RMS error computed over a short period of time is strongly dependent on the selected test period. Such RMS values are significant if and only if they are computed over a sufficiently long period of time, T. Hence, the model validation must be done on the basis of the results of long term simulations. The limit of the RMS values as T becomes arbitrarily large is related to the maximum error made on each constituent. Those maximum errors are easily calculated from the harmonic constants (computed versus observed) of the constituents. The results of the calculation of the maximum errors indicate that the M₂, S₂, N₂ and M₄ components are the largest contributors to the overall error for the area under consideration. On the basis of maximum errors, the TFF results obtained so far are almost of the same order of accuracy. The errors affecting the TFF results are not much larger than those affecting most reported results of similar models used in similar applications     

Perturbations of the Kepler Problem in Global Coordinates: A Program

The present paper is a brief report of how, along the lines of a previous paper, the implementation of the program KEPLER¹, for the numerical integration of the perturbations of the Kepler problem, has been carried out.     

Effectiveness of sulfate-reducing passive bioreactors for treating highly contaminated acid mine drainage: I. Effect of hydraulic retention time

Sulfate-reducing passive bioreactors have proved to be an effective technology for the treatment of acid mine drainage (AMD) contaminated waters over relatively short periods of time (1–5 a). However, long-term efficiency can be limited by several factors including problems related to the hydraulic properties of the reactive mixture. In this study, the effect of two hydraulic retention times (HRTs) of 7.3 d and 10 d on the performance of passive bioreactors was evaluated over an 11-month period for the treatment of a highly contaminated AMD. Evolution of the porosity and hydraulic conductivity of the reactive mixture was also evaluated during the 15-month operation of two bioreactors. Results indicated that bioreactors were effective at both HRTs for increasing the pH and alkalinity of contaminated water and for SO₄ and metal removal (60–82% for Fe and up to 99.9% for Cd, Ni and Zn). Although the quality of treated effluent was significantly improved with the 10 d HRT compared to the 7.3 d HRT, results showed that the higher HRT reduced the porosity and the permeability of the reactive mixture which might lead to hydraulic related problems and, eventually, to limited efficiency in long-term operation compared to a shorter HRT. The choice of HRT for a passive bioreactor must therefore consider both the desired quality of treated effluent and the potential for deterioration of hydraulic properties in the reactive mixture.