MILES extended: Stellar population synthesis models from the optical to the infrared

We present the first single-burst stellar population models which covers the optical and the infrared wavelength range between 3500 and 50000 Angstrom and which are exclusively based on empirical stellar spectra. To obtain these joint models, we combined the extended MILES models in the optical with our new infrared models that are based on the IRTF (Infrared Telescope Facility) library. The latter are available only for a limited range in terms of both age and metallicity. Our combined single-burst stellar population models were calculated for ages larger than 1 Gyr, for metallicities between [Fe/H] = -0.40 and 0.26, for initial mass functions of various types and slopes, and on the basis of two different sets of isochrones. They are available to the scientific community on the MILES web page. We checked the internal consistency of our models and compared their colour predictions to those of other models that are available in the literature. Optical and near infrared colours that are measured from our models are found to reproduce the colours well that were observed for various samples of early-type galaxies. Our models will enable a detailed analysis of the stellar populations of observed galaxies.Comment: 9 pages, 10 figures, published in A&

The star formation activity in cosmic voids

Using a sample of cosmic voids identified in the Sloan Digital Sky Survey Data Release 7, we study the star formation activity of void galaxies. The properties of galaxies living in voids are compared with those of galaxies living in the void shells and with a control sample, representing the general galaxy population. Void galaxies appear to form stars more efficiently than shell galaxies and the control sample. This result cannot be interpreted as a consequence of the bias towards low masses in underdense regions, as void galaxy subsamples with the same mass distribution as the control sample also show statistically different specific star formation rates. This highlights the fact that galaxy evolution in voids is slower with respect to the evolution of the general population. Nevertheless, when only the star-forming galaxies are considered, we find that the star formation rate is insensitive to the environment, as the main sequence is remarkably constant in the three samples under consideration. This fact implies that environmental effects manifest themselves as fast quenching mechanisms, while leaving the non-quenched galaxies almost unaffected, as their star formation activity is largely regulated by the mass of their halo. We also analyse galaxy properties as a function of void-centric distance and find that the enhancement in the star formation activity with respect to the control sample is observable up to a radial distance 1.5Rvoid. This result can be used as a suitable definition of void shells. Finally, we find that larger voids show an enhanced star formation activity in the shells with respect to their smaller counterparts, which could be related to the different dynamical evolution experienced by voids of different size

A statistical approach for rain intensity differentiation using Meteosat Second Generation-Spinning Enhanced Visible and InfraRed Imager observations

Abstract. This study exploits the Meteosat Second Generation (MSG)–Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations to evaluate the rain class at high spatial and temporal resolutions and, to this aim, proposes the Rain Class Evaluation from Infrared and Visible observation (RainCEIV) technique. RainCEIV is composed of two modules: a cloud classification algorithm which individuates and characterizes the cloudy pixels, and a supervised classifier that delineates the rainy areas according to the three rainfall intensity classes, the non-rainy (rain rate value < 0.5 mm h-1) class, the light-to-moderate rainy class (0.5 mm h−1 ≤ rain rate value < 4 mm h-1), and the heavy–to-very-heavy-rainy class (rain rate value ≥ 4 mm h-1). The second module considers as input the spectral and textural features of the infrared and visible SEVIRI observations for the cloudy pixels detected by the first module. It also takes the temporal differences of the brightness temperatures linked to the SEVIRI water vapour channels as indicative of the atmospheric instability strongly related to the occurrence of rainfall events. The rainfall rates used in the training phase are obtained through the Precipitation Estimation at Microwave frequencies, PEMW (an algorithm for rain rate retrievals based on Atmospheric Microwave Sounder Unit (AMSU)-B observations). RainCEIV's principal aim is that of supplying preliminary qualitative information on the rainy areas within the Mediterranean Basin where there is no radar network coverage. The results of RainCEIV have been validated against radar-derived rainfall measurements from the Italian Operational Weather Radar Network for some case studies limited to the Mediterranean area. The dichotomous assessment related to daytime (nighttime) validation shows that RainCEIV is able to detect rainy/non-rainy areas with an accuracy of about 97% (96%), and when all the rainy classes are considered, it shows a Heidke skill score of 67% (62%), a bias score of 1.36 (1.58), and a probability of detection of rainy areas of 81% (81%)

Molecular analysis of endocrine disruption in hornyhead turbot at wastewater outfalls in southern california using a second generation multi-species microarray.

Sentinel fish hornyhead turbot (Pleuronichthysverticalis) captured near wastewater outfalls are used for monitoring exposure to industrial and agricultural chemicals of ~ 20 million people living in coastal Southern California. Although analyses of hormones in blood and organ morphology and histology are useful for assessing contaminant exposure, there is a need for quantitative and sensitive molecular measurements, since contaminants of emerging concern are known to produce subtle effects. We developed a second generation multi-species microarray with expanded content and sensitivity to investigate endocrine disruption in turbot captured near wastewater outfalls in San Diego, Orange County and Los Angeles California. Analysis of expression of genes involved in hormone [e.g., estrogen, androgen, thyroid] responses and xenobiotic metabolism in turbot livers was correlated with a series of phenotypic end points. Molecular analyses of turbot livers uncovered altered expression of vitellogenin and zona pellucida protein, indicating exposure to one or more estrogenic chemicals, as well as, alterations in cytochrome P450 (CYP) 1A, CYP3A and glutathione S-transferase-α indicating induction of the detoxification response. Molecular responses indicative of exposure to endocrine disruptors were observed in field-caught hornyhead turbot captured in Southern California demonstrating the utility of molecular methods for monitoring environmental chemicals in wastewater outfalls. Moreover, this approach can be adapted to monitor other sites for contaminants of emerging concern in other fish species for which there are few available gene sequences

Validation of satellite OPEMW precipitation product with ground-based weather radar and rain gauge networks

Abstract. The Precipitation Estimation at Microwave Frequencies (PEMW) algorithm was developed at the Institute of Methodologies for Environmental Analysis of the National Research Council of Italy (IMAA-CNR) for inferring surface rain intensity (sri) from satellite passive microwave observations in the range from 89 to 190 GHz. The operational version of PEMW (OPEMW) has been running continuously at IMAA-CNR for two years. The OPEMW sri estimates, together with other precipitation products, are used as input to an operational hydrological model for flood alert forecast. This paper presents the validation of OPEMW against simultaneous ground-based observations from a network of 20 weather radar systems and a network of more than 3000 rain gauges distributed over the Italian Peninsula and main islands. The validation effort uses a data set covering one year (July 2011–June 2012). The effort evaluates dichotomous and continuous scores for the assessment of rain detection and quantitative estimate, respectively, investigating both spatial and temporal features. The analysis demonstrates 98% accuracy in correctly identifying rainy and non-rainy areas; it also quantifies the increased ability (with respect to random chance) to detect rainy and non-rainy areas (0.42–0.45 Heidke skill score) or rainy areas only (0.27–0.29 equitable threat score). Performances are better than average during summer, fall, and spring, while worse than average in the winter season. The spatial–temporal analysis does not show seasonal dependence except over the Alps and northern Apennines during winter. A binned analysis in the 0–15 mm h−1 range suggests that OPEMW tends to slightly overestimate sri values below 6–7 mm h−1 and underestimate sri above those values. With respect to rain gauges (weather radars), the correlation coefficient is larger than 0.8 (0.9). The monthly mean difference and standard deviation remain within ±1 and 2 mm h−1 with respect to rain gauges (respectively −2–0 and 4 mm h−1 with respect to weather radars)

An updated MILES stellar library and stellar population models

(Aims) We present a number of improvements to the MILES library and stellar population models. We correct some small errors in the radial velocities of the stars, measure the spectral resolution of the library and models more accurately, and give a better absolute flux calibration of the models. (Methods) We use cross-correlation techniques to correct the radial velocities of the offset stars and the penalised pixel-fitting method, together with different sets of stellar templates, to re-assess the spectral resolution of the MILES stellar library and models. We have also re-calibrated the zero-point flux level of the models using a new calibration scheme. (Results) The end result is an even more homogeneously calibrated stellar library than the originally released one, with a measured spectral resolution of ~2.5\AA, almost constant with wavelength, for both the MILES stellar library and models. Furthermore, the new absolute flux calibration for the spectra excellently agrees with predictions based on independent photometric libraries. (Conclusions) This improved version of the MILES library and models (version 9.1) is available at the project's website (http://miles.iac.es).Comment: 7 pages, 8 figures. Accepted for publication in Astronomy & Astrophysics (Research Note

A Feedforward Neural Network Approach for the Detection of Optically Thin Cirrus From IASI-NG

The identification of optically thin cirrus is crucial for their accurate parameterization in climate and Earth's system models. This study exploits the characteristics of the infrared atmospheric sounding interferometer-new generation (IASI-NG) to develop an algorithm for the detection of optically thin cirrus. IASI-NG has been designed for the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar system second-generation program to continue the service of its predecessor IASI from 2024 onward. A thin-cirrus detection algorithm (TCDA) is presented here, as developed for IASI-NG, but also in parallel for IASI to evaluate its performance on currently available real observations. TCDA uses a feedforward neural network (NN) approach to detect thin cirrus eventually misidentified as clear sky by a previously applied cloud detection algorithm. TCDA also estimates the uncertainty of "clear-sky" or "thin-cirrus" detection. NN is trained and tested on a dataset of IASI-NG (or IASI) simulations obtained by processing ECMWF 5-generation reanalysis (ERA5) data with the s-IASI radiative transfer model. TCDA validation against an independent simulated dataset provides a quantitative statistical assessment of the improvements brought by IASI-NG with respect to IASI. In fact, IASI-NG TCDA outperforms IASI TCDA by 3% in probability of detection (POD), 1% in bias, and 2% in accuracy, and the false alarm ratio (FAR) passes from 0.02 to 0.01. Moreover, IASI TCDA validation against state-of-the-art cloud products from Cloudsat/CPR and CALIPSO/Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) real observations reveals a tendency for IASI TCDA to underestimate the presence of thin cirrus (POD = 0.47) but with a low FAR (0.07), which drops to 0.0 for very thin cirrus