Prioritizing Natural and Nature-Based Features (NNBFs) that increase the resilience of Coastal Communities to Flooding

Presentation by Pamela Mason of VIMS and Ross Weaver of Wetlands Watch for the Hampton Roads Sea Level Rise/Flooding Adaptation Forum, July 9, 2021

Relativistic Broadening of Iron Emission Lines in a Sample of AGN

We present a uniform X-ray spectral analysis of eight type-1 active galactic nuclei (AGN) that have been previously observed with relativistically broadened iron emission lines. Utilizing data from the XMM-Newton European Photon Imaging Camera (EPIC-pn) we carefully model the spectral continuum, taking complex intrinsic absorption and emission into account. We then proceed to model the broad Fe K feature in each source with two different accretion disk emission line codes, as well as a self-consistent, ionized accretion disk spectrum convolved with relativistic smearing from the inner disk. Comparing the results, we show that relativistic blurring of the disk emission is required to explain the spectrum in most sources, even when one models the full reflection spectrum from the photoionized disk.Comment: 50 pages (preprint format), 24 figures. Accepted by Ap

Carbon-nitrogen feedbacks in the UVic ESCM

A representation of the terrestrial nitrogen cycle is introduced into the UVic Earth System Climate Model (UVic ESCM). The UVic ESCM now contains five terrestrial carbon pools and seven terrestrial nitrogen pools: soil, litter, leaves, stem and roots for both elements and ammonium and nitrate in the soil for nitrogen. Nitrogen cycles through plant tissue, litter, soil and the mineral pools before being taken up again by the plant. Biological N<sub>2</sub> fixation and nitrogen deposition represent external inputs to the plant-soil system while losses occur via leaching. Simulated carbon and nitrogen pools and fluxes are in the range of other models and observations. Gross primary production (GPP) for the 1990s in the CN-coupled version is 129.6 Pg C a<sup>−1</sup> and net C uptake is 0.83 Pg C a<sup>−1</sup>, whereas the C-only version results in a GPP of 133.1 Pg C a<sup>−1</sup> and a net C uptake of 1.57 Pg C a<sup>−1</sup>. At the end of a transient experiment for the years 1800–1999, where radiative forcing is held constant but CO<sub>2</sub> fertilisation for vegetation is permitted to occur, the CN-coupled version shows an enhanced net C uptake of 1.05 Pg C a<sup>−1</sup>, whereas in the experiment where CO<sub>2</sub> is held constant and temperature is transient the land turns into a C source of 0.60 Pg C a<sup>−1</sup> by the 1990s. The arithmetic sum of the temperature and CO<sub>2</sub> effects is 0.45 Pg C a<sup>−1</sup>, 0.38 Pg C a<sup>−1</sup> lower than seen in the fully forced model, suggesting a strong nonlinearity in the CN-coupled version. Anthropogenic N deposition has a positive effect on Net Ecosystem Production of 0.35 Pg C a<sup>−1</sup>. Overall, the UVic CN-coupled version shows similar characteristics to other CN-coupled Earth System Models, as measured by net C balance and sensitivity to changes in climate, CO<sub>2</sub> and temperature

A Simple Likelihood Method for Quasar Target Selection

We present a new method for quasar target selection using photometric fluxes and a Bayesian probabilistic approach. For our purposes we target quasars using Sloan Digital Sky Survey (SDSS) photometry to a magnitude limit of g=22. The efficiency and completeness of this technique is measured using the Baryon Oscillation Spectroscopic Survey (BOSS) data, taken in 2010. This technique was used for the uniformly selected (CORE) sample of targets in BOSS year one spectroscopy to be realized in the 9th SDSS data release. When targeting at a density of 40 objects per sq-deg (the BOSS quasar targeting density) the efficiency of this technique in recovering z>2.2 quasars is 40%. The completeness compared to all quasars identified in BOSS data is 65%. This paper also describes possible extensions and improvements for this techniqueComment: Updated to accepted version for publication in the Astrophysical Journal. 10 pages, 10 figures, 3 table

Characterizing unknown systematics in large scale structure surveys

Photometric large scale structure (LSS) surveys probe the largest volumes in the Universe, but are inevitably limited by systematic uncertainties. Imperfect photometric calibration leads to biases in our measurements of the density fields of LSS tracers such as galaxies and quasars, and as a result in cosmological parameter estimation. Earlier studies have proposed using cross-correlations between different redshift slices or cross-correlations between different surveys to reduce the effects of such systematics. In this paper we develop a method to characterize unknown systematics. We demonstrate that while we do not have sufficient information to correct for unknown systematics in the data, we can obtain an estimate of their magnitude. We define a parameter to estimate contamination from unknown systematics using cross-correlations between different redshift slices and propose discarding bins in the angular power spectrum that lie outside a certain contamination tolerance level. We show that this method improves estimates of the bias using simulated data and further apply it to photometric luminous red galaxies in the Sloan Digital Sky Survey as a case study.Comment: 24 pages, 6 figures; Expanded discussion of results, added figure 2; Version to be published in JCA

Contemporary Family Law, 6th Edition

Jessica Dixon Weaver: https://orcid.org/0000-0002-6960-1459https://scholar.smu.edu/facbooks/1071/thumbnail.jp