NSV 01450: a New Bright Classical Cepheid in the Milky Way Field

Photometric data extracted from more than 5000 CCD observations of theMilky Way field star NSV 01450, with galactic co-ordinates l =145^°.9and b=4^° .9, show that this object is a bright classical Cepheid witha period of 12.639 ± 0.020 days and an average V magnitude of 11.045± 0.016. The computed colour excess is E(B-V)= 0.553± 0.056, yielding a distance modulus m _V -M_V of 15.537 ± 0.212.In addition, it was found that the star GSC 3730_0797 in the field ofNSV 01450 is also variable.     

Speeding Up Image Reconstruction Methods in Coded Mask γ Cameras Using Neural Networks: Application to the EM Algorithm

When using γ-ray coded-mask cameras, one does not get a direct image as in classical optical cameras but the correlation of the mask response with the source. Therefore the data must be mathematically treated in order to reconstruct the original sky sources. Generally this reconstruction is based on linear methods, such as correlating the detector plane with a reconstruction array, or non-linear ones such as iterative or maximization methods (i.e. the EM algorithm). The latter have a better performance but they increase the computational complexity by taking a lot of time to reconstruct an image. Here we present a method for speeding up such kind of algorithms by making use of a neural network with a back-propagation learning rule. This revised version was published online in July 2006 with corrections to the Cover Date.     

Beyond maximum entropy: Fractal pixon-based image reconstruction

We have developed a new Bayesian image reconstruction method that has been shown to be superior to the best implementations of other methods, including Goodnessof-Fit (e.g. Least-Squares and Lucy-Richardson) and Maximum Entropy (ME). Our new method is based on the concept of the pixon, the fundamental, indivisible unit of picture information. Use of the pixon concept provides an improved image model, resulting in an image prior which is superior to that of standard ME.     

Single multipurpose reservoir design: a modified optimal control problem by chance-constrained programming

This paper presents a chance-constrained programming model for optimal control of a multipurpose reservoir and its modification to a model for single reservoir design. An algorithm is developed for solving complex stochastic problems of multipurpose reservoir planning and design. The complexity of the problem is resolved by a two-step algorithm: (1) transformation of chance constraints on the state and control variables is performed at the first step; and (2) the choice of optimum control or optimal reservoir storage is carried out in the second step. The method of iterative convolution is chosen for the first step, while linear programming is selected for the second step. The algorithm allows the use of random inflows and random demands together with other deterministic demands. The reservoir design problem is presented as a modified optimal control problem. The procedure is illustrated with an example of a hypothetical reservoir design problem with three different types of downstream releases (hydropower production, municipal water supply, and irrigation).     

Early Paleozoic orogeny in southern South America

In northwest Argentina, weakly metamorphic clastic and calcareous sedimentary rocks of latest Precambrian to Lower Cambrian age (Puncoviscana Formation and related units) contain an abundant ichnofauna of both chronostratigraphic and paleoenvironmental value. In the western and central Sierras Pampeanas, metasedimentary and metavolcanic rocks are considered to form part of the same geotectonic unit. This “Pampean orogenic cycle” includes geosynclinal sedimentation of latest Precambrian to Lower Cambrian age, as well as magmatism, metamorphism and deformation of Middle to Upper Cambrian age, documented by an angular unconformity below the Upper Cambrian to Devonian rocks of the “Famatinian orogenic cycle”. In some of the metamorphic rocks of the Pampean Cycle a pre-Ordovician folding is also distinguished from a later tectonic overprinting. Hence, the concept of a Pampean cycle differs from other concepts of late Precambrian orogenic cycles of South America which are only defined by radiometric ages. The Pampean orogenesis may be compared with the Ross orogenesis of the Transantarctic Mts., the Tyennan orogenesis of Australia and some of the deformation phases of the Damara orogen in Namibia.     

Proposal of a function for modelling the hourly frequency distributions of photosynthetically active radiation

Summary Solar irradiance is a key factor in the physiological processes of living beings. To obtain simple correlations for the estimation of the performance of biological systems, which transform the solar energy by photosynthesis, and to generate synthetic data, it is necessary to know the frequency distributions of photosynthetically active radiation (PAR). In this work we carried out an analysis of the properties of hourly values of PAR data, using 9 years of data collected in southern Spain. In particularly, its dependence on the optical mass, for all type of skies including cloudy skies, is studied. Results shows that, for a given value of the optical mass, the PAR density distributions are not symmetrical and have a certain degree of bimodality. The increment in the optical mass value has two effects on the PAR distributions, the first one is a shift toward lower values of the maximum and the second one is a decrease in the range of PAR values. Finally, a model of the frequency distribution of PAR values, based on a new kind of functions related to the Boltzmanns statistic, is proposed. The parameters of these functions depend just on the optical mass. Results show a very good agreement between the data and the model proposed.     

High CO2 Levels in Boreholes at El Teide Volcano Complex (Tenerife, Canary Islands): Implications for Volcanic Activity Monitoring

Emissions of CO₂ have been known for more than a hundred years as fumarolic activity at the terminal crater of El Teide volcano and as diffuse emissions at numerous water prospection drillings in the volcanic island of Tenerife. Large concentrations of CO₂ (>10% in volume) have been found inside galleries, long horizontal tunnels excavated for water mining. However, CO₂ concentrations of only 2900 ppm have been observed at the surface of the central region of the island (Las Cañadas del Teide caldera). In this work we analysed CO₂ concentrations in the subsurface of Las Cañadas caldera, in an attempt to study the vertical distribution of carbon dioxide and, in particular, the low emissions at the surface. This has been done through a series of 17 vertical profiles in two deep boreholes excavated in the Caldera. We found high levels of CO₂, varying in time from 13 vol% up to 40 vol% in different profiles directly above the water table, while no significant concentrations were detected above the thermal inversion that takes places in both boreholes at approximately 100 m from the water table. Water analyses also showed high dissolved CO₂ levels in equilibrium with the air, and an average 13C value in DIC of +4.7 (PDB), apparently induced by fast CO₂ degassing in the bicarbonated water.     

Heat budget, energy storage and hydrological regime in a coastal lagoon

For this paper, a physical heat budget model has been implemented using a fine-scale high-resolution meteorological data set in order to explore the influence of external factors, such as solar radiation and wind speed on the thermal regime and, therefore, the ecological dynamics of a shallow coastal ecosystem, Nueva lagoon (Southeast Spain). In addition, our results reveal that micrometeorological data (recorded with at least a bihourly frequency) are required to obtain reliable results from such a model. Net radiation accounted on average for around 95% of the non-advective fluxes and long wave radiation emitted accounted for around 70% of the non-advective losses. Evaporation was also a considerable component of the energy budget, accounting for about 20% of the total energy losses. In relation to advective heat fluxes, results from a water budget in Nueva lagoon have shown that groundwater discharge and irrigation surpluses contributed to the heat storage of Nueva lagoon, whereas the effect of heat advected via rainfall was negligible.     

Projection of future climate change conditions using IPCC simulations, neural networks and Bayesian statistics. Part 2: Precipitation mean state and seasonal cycle in South America

Evaluating the response of climate to greenhouse gas forcing is a major objective of the climate community, and the use of large ensemble of simulations is considered as a significant step toward that goal. The present paper thus discusses a new methodology based on neural network to mix ensemble of climate model simulations. Our analysis consists of one simulation of seven Atmosphere–Ocean Global Climate Models, which participated in the IPCC Project and provided at least one simulation for the twentieth century (20c3m) and one simulation for each of three SRES scenarios: A2, A1B and B1. Our statistical method based on neural networks and Bayesian statistics computes a transfer function between models and observations. Such a transfer function was then used to project future conditions and to derive what we would call the optimal ensemble combination for twenty-first century climate change projections. Our approach is therefore based on one statement and one hypothesis. The statement is that an optimal ensemble projection should be built by giving larger weights to models, which have more skill in representing present climate conditions. The hypothesis is that our method based on neural network is actually weighting the models that way. While the statement is actually an open question, which answer may vary according to the region or climate signal under study, our results demonstrate that the neural network approach indeed allows to weighting models according to their skills. As such, our method is an improvement of existing Bayesian methods developed to mix ensembles of simulations. However, the general low skill of climate models in simulating precipitation mean climatology implies that the final projection maps (whatever the method used to compute them) may significantly change in the future as models improve. Therefore, the projection results for late twenty-first century conditions are presented as possible projections based on the “state-of-the-art” of present climate modeling. First, various criteria were computed making it possible to evaluate the models’ skills in simulating late twentieth century precipitation over continental areas as well as their divergence in projecting climate change conditions. Despite the relatively poor skill of most of the climate models in simulating present-day large scale precipitation patterns, we identified two types of models: the climate models with moderate-to-normal (i.e., close to observations) precipitation amplitudes over the Amazonian basin; and the climate models with a low precipitation in that region and too high a precipitation on the equatorial Pacific coast. Under SRES A2 greenhouse gas forcing, the neural network simulates an increase in precipitation over the La Plata basin coherent with the mean model ensemble projection. Over the Amazonian basin, a decrease in precipitation is projected. However, the models strongly diverge, and the neural network was found to give more weight to models, which better simulate present-day climate conditions. In the southern tip of the continent, the models poorly simulate present-day climate. However, they display a fairly good convergence when simulating climate change response with a weak increase south of 45°S and a decrease in Chile between 30 and 45°S. Other scenarios (A1B and B1) strongly resemble the SRES A2 trends but with weaker amplitudes.     

Cloud cover analysis associated to cut-off low-pressure systems over Europe using Meteosat Imagery

Summary This paper reports a cloud cover analysis of cut-off low pressure systems (COL) using a pattern recognition method applied to IR and VIS bispectral histograms. 35 COL occurrences were studied over five years (1994–1998). Five cloud types were identified in COLs, of which high clouds (HCC) and deep convective clouds (DCC) were found to be the most relevant to characterize COL systems, though not the most numerous. Cloud cover in a COL is highly dependent on its stage of development, but a higher percentage of cloud cover is always present in the frontal zone, attributable due to higher amounts of high and deep convective clouds. These general characteristics are most marked during the first stage (when the amplitude of the geopotencial wave increases) and second stage (characterized by the development of a cold upper level low), closed cyclonic circulation minimizing differences between rearward and frontal zones during the third stage. The probability of heavy rains during this stage decreases considerably. The centres of mass of high and deep convective clouds move towards the COL-axis centre during COL evolution.