Simultaneous Multicolor Detection of Faint Galaxies in the Hubble Deep Field

We present a novel way to detect objects when multiband images are available. Typically, object detection is performed in one of the available bands or on a somewhat arbitrarily co-added image. Our technique provides an almost optimal way to use all the color information available. We build up a composite image of the N passbands where each pixel value corresponds to the probability that the given pixel is just sky. By knowing the probability distribution of sky pixels (a chi-square distribution with N degrees of freedom), the data can be used to derive the distribution of pixels dominated by object flux. From the two distributions an optimal segmentation threshold can be determined. Clipping the probability image at this threshold yields a mask, where pixels unlikely to be sky are tagged. After using a standard connected-pixel criterion, the regions of this mask define the detected objects. Applying this technique to the Hubble Deep Field data, we find that we can extend the detection limit of the data below that possible using linearly co-added images. We also discuss possible ways of enhancing object detection probabilities for certain well defined classes of objects by using various optimized linear combinations of the pixel fluxes (optimal subspace filtering).Comment: 8 pages, 5 figures (4 postscript, 1 JPEG). To be published in A

A Predictive Algorithm For Wetlands In Deep Time Paleoclimate Models

Methane is a powerful greenhouse gas produced in wetland environments via microbial action in anaerobic conditions. If the location and extent of wetlands are unknown, such as for the Earth many millions of years in the past, a model of wetland fraction is required in order to calculate methane emissions and thus help reduce uncertainty in the understanding of past warm greenhouse climates. Here we present an algorithm for predicting inundated wetland fraction for use in calculating wetland methane emission fluxes in deep time paleoclimate simulations. The algorithm determines, for each grid cell in a given paleoclimate simulation, the wetland fraction predicted by a nearest neighbours search of modern day data in a space described by a set of environmental, climate and vegetation variables. To explore this approach, we first test it for a modern day climate with variables obtained from observations and then for an Eocene climate with variables derived from a fully coupled global climate model (HadCM3BL-M2.2). Two independent dynamic vegetation models were used to provide two sets of equivalent vegetation variables which yielded two different wetland predictions. As a first test the method, using both vegetation models, satisfactorily reproduces modern data wetland fraction at a course grid resolution, similar to those used in paleoclimate simulations. We then applied the method to an early Eocene climate, testing its outputs against the locations of Eocene coal deposits. We predict global mean monthly wetland fraction area for the early Eocene of 8 to 10 × 106km2 with corresponding total annual methane flux of 656 to 909 Tg, depending on which of two different dynamic global vegetation models are used to model wetland fraction and methane emission rates. Both values are significantly higher than estimates for the modern-day of 4 × 106km2 and around 190Tg (Poulter et. al. 2017, Melton et. al., 2013

ENSO dynamics in current climate models: an investigation using nonlinear dimensionality reduction

International audienceLinear dimensionality reduction techniques, notably principal component analysis, are widely used in climate data analysis as a means to aid in the interpretation of datasets of high dimensionality. These linear methods may not be appropriate for the analysis of data arising from nonlinear processes occurring in the climate system. Numerous techniques for nonlinear dimensionality reduction have been developed recently that may provide a potentially useful tool for the identification of low-dimensional manifolds in climate data sets arising from nonlinear dynamics. Here, we apply Isomap, one such technique, to the study of El Niño/Southern Oscillation variability in tropical Pacific sea surface temperatures, comparing observational data with simulations from a number of current coupled atmosphere-ocean general circulation models. We use Isomap to examine El Niño variability in the different datasets and assess the suitability of the Isomap approach for climate data analysis. We conclude that, for the application presented here, analysis using Isomap does not provide additional information beyond that already provided by principal component analysis

Parameter estimation in an atmospheric GCM using the Ensemble Kalman Filter

International audienceWe demonstrate the application of an efficient multivariate probabilistic parameter estimation method to a spectral primitive equation atmospheric GCM. The method, which is based on the Ensemble Kalman Filter, is effective at tuning the surface air temperature climatology of the model to both identical twin data and reanalysis data. When 5 parameters were simultaneously tuned to fit the model to reanalysis data, the model errors were reduced by around 35% compared to those given by the default parameter values. However, the precipitation field proved to be insensitive to these parameters and remains rather poor. The model is computationally cheap but chaotic and otherwise realistic, and the success of these experiments suggests that this method should be capable of tuning more sophisticated models, in particular for the purposes of climate hindcasting and prediction. Furthermore, the method is shown to be useful in determining structural deficiencies in the model which can not be improved by tuning, and so can be a useful tool to guide model development. The work presented here is for a limited set of parameters and data, but the scalability of the method is such that it could easily be extended to a more comprehensive parameter set given sufficient observational data to constrain them

A Deep Multicolor Survey. VI. Near-Infrared Observations, Selection Effects, and Number Counts

I present near-infrared J (1.25um), H (1.65um), and K (2.2um) imaging observations of 185 square arcminutes in 21 high galactic latitude fields. These observations reach limiting magnitudes of J ~ 21 mag, H ~ 20 mag and K ~ 18.5 mag. The detection efficiency, photometric accuracy and selection biases as a function of integrated object brightness, size, and profile shape are quantified in detail. I evaluate several popular methods for measuring the integrated light of faint galaxies and show that only aperture magnitudes provide an unbiased measure of the integrated light that is independent of apparent magnitude. These J, H, and K counts and near-infrared colors are in best agreement with passive galaxy formation models with at most a small amount of merging (for Omega_M = 0.3, Omega_Lambda = 0.7).Comment: AJ Accepted (Feb 2001). 28 pages, 7 embedded ps figures, AASTEX5. Minor changes to submitted version. Also available at http://www.astronomy.ohio-state.edu/~martini/pubs

Early Type Galaxies in the Mid Infrared: a new flavor to their stellar populations

The mid infrared emission of early type galaxies traces the presence of intermediate age stellar populations as well as even tiny amounts of ongoing star formation. Here we discuss high S/N Spitzer IRS spectra of a sample of Virgo early type galaxies, with particular reference to NGC 4435. We show that, by combining mid infrared spectroscopic observations with existing broad band fluxes, it is possible to obtain a very clean picture of the nuclear activity in this galaxy.Comment: 4 pages; proceedings of IAU Symposium No. 241, "Stellar Populations as Building Blocks of Galaxies", editors A. Vazdekis and R. Peletie

Asteroid impact, not volcanism, caused the end-Cretaceous dinosaur extinction

The Cretaceous/Paleogene mass extinction, 66 Ma, included the demise of non-avian dinosaurs. Intense debate has focused on the relative roles of Deccan volcanism and the Chicxulub asteroid impact as kill mechanisms for this event. Here, we combine fossil-occurrence data with paleoclimate and habitat suitability models to evaluate dinosaur habitability in the wake of various asteroid impact and Deccan volcanism scenarios. Asteroid impact models generate a prolonged cold winter that suppresses potential global dinosaur habitats. Conversely, long-term forcing from Deccan volcanism (carbon dioxide [CO2]-induced warming) leads to increased habitat suitability. Short-term (aerosol cooling) volcanism still allows equatorial habitability. These results support the asteroid impact as the main driver of the non-avian dinosaur extinction. By contrast, induced warming from volcanism mitigated the most extreme effects of asteroid impact, potentially reducing the extinction severity

The Relationship Between Galaxies and Low Redshift Weak Lyman alpha Absorbers in the Directions of H1821+643 and PG1116+215

To study the nature of low z Lya absorbers in the spectra of QSOs, we have obtained high signal-to-noise UV spectra of H 1821+643 (z = 0.297) and PG 1116+215 (z = 0.177) with the GHRS on the HST. The spectra have minimum S/N of 70-100 and 3 sigma limiting equivalent widths of 50-75 mA. We detect 26 Lya lines with Wr > 50 mA toward H1821+643 and 13 toward PG1116+215, which implies a density of 102+/-16 lines per unit redshift. The two-point correlation function shows marginal evidence of clustering on ~500 km/s scales, but only if the weakest lines are excluded. We have also used the WIYN Observatory to measure galaxy redshifts in the ~1 degree fields centered on each QSO. We find 17 galaxy-absorber pairs within projected distances of 1 Mpc with velocity separations of 350 km/s or less. Monte Carlo simulations show that if the Lya lines are randomly distributed, the probability of observing this many close pairs is 3.6e-5. We find that all galaxies with projected distances of 600 kpc or less have associated Lya absorbers within 1000 km/s, and the majority of these galaxies have absorbers within 350 km/s. We also find that the Lya equivalent width is anticorrelated with the projected distance of the nearest galaxy out to at least 600 kpc, but this should be interpreted cautiously because there are potential selection biases. Statistical tests using the entire sample also indicate that the absorbers are not randomly distributed. We discuss the nature of the Lya absorbers in light of the new data.Comment: Accepted for publication in ApJ. 17 pages plus 11 tables and 17 figure

Quantifying the relative importance of land cover change from climate and land use in the representative concentration pathways

Climate change is projected to cause substantial alterations in vegetation distribution, but these have been given little attention in comparison to land-use in the Representative Concentration Pathway (RCP) scenarios. Here we assess the climate-induced land cover changes (CILCC) in the RCPs, and compare them to land-use land cover change (LULCC). To do this, we use an ensemble of simulations with and without LULCC in earth system model HadGEM2-ES for RCP2.6, RCP4.5 and RCP8.5. We find that climate change causes an expansion poleward of vegetation that affects more land area than LULCC in all of the RCPs considered here. The terrestrial carbon changes from CILCC are also larger than for LULCC. When considering only forest, the LULCC is larger, but the CILCC is highly variable with the overall radiative forcing of the scenario. The CILCC forest increase compensates 90% of the global anthropogenic deforestation by 2100 in RCP8.5, but just 3% in RCP2.6. Overall, bigger land cover changes tend to originate from LULCC in the shorter term or lower radiative forcing scenarios, and from CILCC in the longer term and higher radiative forcing scenarios. The extent to which CILCC could compensate for LULCC raises difficult questions regarding global forest and biodiversity offsetting, especially at different timescales. This research shows the importance of considering the relative size of CILCC to LULCC, especially with regard to the ecological effects of the different RCPs