Stellar clusters in the nuclear regions of AGN with the Advanced Camera for Surveys

We explore the role of star clusters in the nuclear regions of galaxies through their connection with active galactic nuclei (AGN). Nuclear star clusters (NCs) are conspicuous in the centers of most nearby galaxies, all along the Hubble sequence. These clusters are probably the faint-end distribution of the central supermassive black holes (SMBHs) in massive bulges. On the other hand, star formation is known to be ongoing in the majority of Seyfert nuclei and in many low-luminosity active galactic nuclei (LLAGN). We study two samples of AGN galaxies (75 Seyferts and 26 LLAGN) in the near-ultraviolet with the Hubble Space Telescope’s Advanced Camera for Surveys. We aim to better understand the connection between the growing of the SMBH and the build-up of the bulge, and we also intend to make statistical progress and determine the properties of the population of NCs coexisting with growing SMBHs.     

On the initial cluster mass distribution inferred from synthesis models

In this contribution we examine the problem of inferring ages and initial cluster masses from synthesis models at the limit of low-mass clusters (M≤ a few ×10⁴ M_⊙). We show that it is not possible to apply directly synthesis models using standard methods to such clusters, since the basic hypothesis implicit in the models (a fixed proportionality between the number of stars in different evolutionary phases) is not fulfilled due to an insufficient number of stars for a reliable sampling of the stellar initial mass function. The consequence of this incomplete sampling is a non-Gaussian distribution of the mass–luminosity relation for clusters that share the same evolutionary conditions (age, metallicity and stellar initial mass distribution function). We review some tests, that can be performed before the start of the analysis, to estimate if the observed cluster can be analyzed with synthesis models following traditional procedures (like χ ² minimization) or if it is necessary make use of synthesis models in a probabilistic framework. Finally, we show the implications of these results for estimating the low-mass tail in the initial cluster mass distribution function.     

Groundwater temperature and electrical conductivity as tools to characterize flow patterns in carbonate aquifers: The Sierra de las Nieves karst aquifer, southern Spain

In carbonate massifs, flow patterns are conditioned by karstification processes which develop a conduit network and preserve low permeability microfractured blocks. The Sierra de las Nieves karst massif (southern Spain) is subjected to a given climatic and geological context, and thus it is possible to analyse the spatial and temporal variability of the water temperature and electrical conductivity at its main karst outlets, which display different responses to rainfall episodes. In this experimental field area, conduit flow and diffuse flow drainage patterns have been distinguished by combining groundwater temperature and electrical conductivity data. Both parameters show large variations in water coming from conduit flow systems and low variations in water drained by springs draining diffuse flow systems. However, groundwater temperature displays the smallest variations, which seems to indicate that this parameter is less sensitive as regards characterising the degree of karstification, which is a key question in characterising the aquifer functioning.     

Temporal Trends of Dissolved Trace Metals in Jamaica Bay,NY: Importance of Wastewater Input and Submarine Groundwater Discharge in an Urban Estuary

Jamaica Bay, NY, is a highly urbanized estuary within the boroughs of New York City conspicuously lacking published information on dissolved trace metal concentrations. The current study examines the distribution and cycling of trace metals in that embayment with data gathered during cruises in November 2004, April 2005, and June 2006. Most of the metal distributions (Fe, Zn, Co, Ag, Cu, Pb, Ni) in the water column are explained by the input of substantial volumes of treated wastewater effluent. However, several lines of evidence suggest that submarine groundwater discharge (SGD) is also an important source of dissolved Fe, Zn, Co, Ni, and isotopically distinct stable Pb ratios (²⁰⁶Pb, ²⁰⁷Pb, ²⁰⁸Pb) in the Bay. Conversely, the recirculated seawater component of SGD is an apparent sink for dissolved Mo. This study provides the first measurements of dissolved trace metals in the Jamaica Bay water column and subterranean estuary and provides evidence for trace metal input due to SGD.     

Execution management in the GRID, for sensitivity studies of global climate simulations

Recent trends in climate modeling find in GRID computing a powerful way to achieve results by sharing geographically distributed computing and storage resources. In particular, ensemble prediction experiments are based on the generation of multiple model simulations to explore, statistically, the existing uncertainties in weather and climate forecast. In this paper, we present a GRID application consisting of a state-of-the-art climate model. The main goal of the application is to provide a tool that can be used by a climate researcher to run ensemble-based predictions on the GRID for sensitivity studies. One of the main duties of this tool is the management of a workflow involving long-term jobs and data management in a user-friendly way. In this paper we show that, due to weaknesses of current GRID middleware, this management is complex task. Those weaknesses made necessary the development of a robust workflow adapted to the requirements of the climate application. As an illustrative scientific challenge, the application is applied to study the El Niño phenomenon, by simulating an El Niño year with different forcing conditions and analyzing the precipitation response over south-American countries subject to flooding risk.     

Comments on “An approximation to short-term evolution and sediment transport pathways along the littoral of Cadiz Bay (SW Spain)” by Anfuso and et al. (Environ Geol 56:69–79)

Environmental Earth Sciences -     

The response of playa and sabkha hydraulics and mineralogy to climate forcing

Dry playa lakes and sabkhat often represent the terminus of large ground water flow systems and act as integrators of both upgradient (recharge) and downgradient discharge (evaporation). Ground water levels beneath playa/sabkha systems show a variety of surprising responses driven by large evaporation demands and chemical processes not typically encountered in more humid regions. When the water table is very close to the land surface, almost instantaneous rises can be observed with little observed change in either upgradient ground water recharge or potential evaporation. Conversely, when water tables are several meters below the playa surface, water table responses to interannual variability of recharge can be damped and lag significantly behind such changes. This review of the dynamics of shallow water tables in playa lakes and sabkhat discusses the pertinent hydraulic and solute processes and extracts a simple but comprehensive model based on soil physics for predicting the water table response to either upstream recharge changes or changes in potential evaporation at the playa/sabkha. Solutes and associated authigenic minerals are also shown to be important in discriminating both the causes and effects of water level fluctuations.     

Regional droughts in southern South America

From a regional inventory of monthly droughts, which was evaluated in six regions of southern South America, the seasonal occurrence of the phenomenon and its persistence together with the duration of monthly and annual sequences, extreme events, and other statistical estimates of the proposed index have been studied. In a primary analysis, it is possible to observe that regions present different behaviors regarding the duration of dry sequences, with more persistence in the Argentinean continental region. Temporal behaviors of the annual indexes have also been analyzed, in the attempt to determine any aspects of the impact of global warming. Through this analysis, the presence of long favorable tendencies regarding precipitations or the inverse of droughts occurrence are confirmed for the eastern Andes Mountains in Argentina (ARG) with its five sub-regions (Northwest Argentina-NWA, Northeast Argentina-NEA, Humid Pampa-HP, West-Centre Provinces-WC and Patagonia-PAT, and the inverse over the central region of Chile (CHI). Other climatic great-scale changes are interdecadales variations and variances explained according to ENSO.     

Extreme normalised residuals of daily temperatures in Catalonia (NE Spain): sampling strategies, return periods and clustering process

Extreme normalised residuals, defined as departures from the average values, of 65 daily maximum, T _max, and minimum, T _min, temperature series recorded in Catalonia (NE Spain) during 1950–2004 are analysed. Similarly to the sampling strategies applied to long dry spells, the partial duration series (PDS) offer some advantages in comparison with the annual extreme series. Instead of using a common percentile threshold for all temperature series, PDS are chosen according to the mean excess plot procedure. Series of extreme residuals are modelled, in terms of the L-moments formulation, by the generalised Pareto distribution. Extreme residuals of T _max and T _min are estimated for return periods ranging from 2 to 50 years and their spatial distribution is represented for selected return periods of 2, 5, 10, 25 and 50 years. Two daily extreme temperatures events, a hot episode (in August) and a cold episode (in February), are simulated taking into account the average T _max (T _min) for a day in August (February), their standard deviations and the extremes for a 50-year return period. Both simulations are compared with outstanding real episodes recorded on August 13th 2003 and February 11th 1956. Additionally, a spatial regionalisation of Catalonia in several clusters, in terms of the extreme residuals for return periods from 2 to 50 years, is done. A principal component analysis is applied to the extreme residual curves characterising every temperature series and, using as variables the principal components, the regionalisation is obtained by applying the average linkage clustering algorithm. Finally, each cluster is characterised by its average extreme residual curve for return periods ranging from 2 to 50 years at 1-year interval.