Variation in copepod species assemblage distributions: The utility of the log-normal approach

Pelagic copepod species distributions were found to vary in relation to an environmental gradient. As suggested by Gray, systematic changes were noted in the skewness of the log-normal. However, no systematic changes in the standard of deviation of the log-normal were noted. The data indicate that such assemblages ill-fit Preston's ‘canonical’ expectation. Further, analysis of changes in the evenness function yielded similar conclusions.     

Climate change and energy security: an analysis of policy research

The literature on climate change’s impacts on energy security is scattered across disparate fields of research and schools of thought. Much of this literature has been produced outside of the academy by scholars and practitioners working in “think tanks,” government agencies, and international/multilateral institutions. Here we reviewed a selected set of 58 articles and reports primarily from such sources and performed textual analysis of the arguments. Our review of this literature identifies three potential mechanisms for linking climate change and energy security: Climate change may 1) create second-order effects that may exacerbate social instability and disrupt energy systems; 2) directly impact energy supply and/or systems or 3) influence energy security through the effects of climate-related policies. We identify emerging risks to energy security driven by climate mitigation technology choices but find less evidence of climate change’s direct physical impacts. We used both empirical and qualitative selection factors for choosing the grey literature sample. The sources we selected were published in the last 5 years, available through electronic media and were written in language accessible to general policy or academic readers. The organizations that published the literature had performed previous research in the general fields of energy and/or climate change with some analytical content and identified themselves as non-partisan. This literature is particularly valuable to scholars because identifies understudied relationships that can be rigorously assessed through academic tools and methodologies and informs a translational research agenda that will allow scholars to engage with practitioners to address challenges that lie at the nexus of climate change and energy security.     

A Framework for Quantitative Assessment of Impacts Related to Energy and Mineral Resource Development

Natural resource planning at all scales demands methods for assessing the impacts of resource development and use, and in particular it requires standardized methods that yield robust and unbiased results. Building from existing probabilistic methods for assessing the volumes of energy and mineral resources, we provide an algorithm for consistent, reproducible, quantitative assessment of resource development impacts. The approach combines probabilistic input data with Monte Carlo statistical methods to determine probabilistic outputs that convey the uncertainties inherent in the data. For example, one can utilize our algorithm to combine data from a natural gas resource assessment with maps of sage grouse leks and piñon-juniper woodlands in the same area to estimate possible future habitat impacts due to possible future gas development. As another example: one could combine geochemical data and maps of lynx habitat with data from a mineral deposit assessment in the same area to determine possible future mining impacts on water resources and lynx habitat. The approach can be applied to a broad range of positive and negative resource development impacts, such as water quantity or quality, economic benefits, or air quality, limited only by the availability of necessary input data and quantified relationships among geologic resources, development alternatives, and impacts. The framework enables quantitative evaluation of the trade-offs inherent in resource management decision-making, including cumulative impacts, to address societal concerns and policy aspects of resource development.     

The coupling of quasi-linear pitch angle and energy diffusion

Wave–particle interactions are described in the quasi-linear formulation by bounce-averaged diffusion coefficients for equatorial pitch angle α₀ and for momentum p, along with a mixed or cross diffusion coefficient D_α0p. Because the cross terms complicate the associated time-dependent diffusion equation, and because D_α0p has a somewhat unfamiliar character (e.g., it may be negative), it has frequently been omitted in numerical simulations of multidimensional diffusion. Generally, D_α0p becomes increasingly important for small values of f_pe/f_ce, as does D_pp, and for small widths of the wave frequency and wavenormal angle distributions. Here we use very simple models of diffusion to investigate the effect of the cross terms, and to demonstrate numerical problems associated with them.     

Optimizing spectral wave estimates with adjoint-based sensitivity maps

A discrete numerical adjoint has recently been developed for the stochastic wave model SWAN. In the present study, this adjoint code is used to construct spectral sensitivity maps for two nearshore domains. The maps display the correlations of spectral energy levels throughout the domain with the observed energy levels at a selected location or region of interest (LOI/ROI), providing a full spectrum of values at all locations in the domain. We investigate the effectiveness of sensitivity maps based on significant wave height (H _s ) in determining alternate offshore instrument deployment sites when a chosen nearshore location or region is inaccessible. Wave and bathymetry datasets are employed from one shallower, small-scale domain (Duck, NC) and one deeper, larger-scale domain (San Diego, CA). The effects of seasonal changes in wave climate, errors in bathymetry, and multiple assimilation points on sensitivity map shapes and model performance are investigated. Model accuracy is evaluated by comparing spectral statistics as well as with an RMS skill score, which estimates a mean model–data error across all spectral bins. Results indicate that data assimilation from identified high-sensitivity alternate locations consistently improves model performance at nearshore LOIs, while assimilation from low-sensitivity locations results in lesser or no improvement. Use of sub-sampled or alongshore-averaged bathymetry has a domain-specific effect on model performance when assimilating from a high-sensitivity alternate location. When multiple alternate assimilation locations are used from areas of lower sensitivity, model performance may be worse than with a single, high-sensitivity assimilation point.     

The trigonometric parallax of the neutron star Geminga

We obtained a series of four observations of the isolated neutron star Geminga over an 18 month period using the Advanced Camera for Surveys (ACS) Wide Field Camera (WFC) on the Hubble Space Telescope in order to determine its trigonometric parallax. We find the parallax π=4.0±1.3 mas, corresponding to a distance to Geminga of 250 _?62 ⁺¹²⁰  pc, a result 60% larger than the previously published value. The proper motion is 178.2±1.8 mas/year. In this paper, we describe the analysis techniques in detail since the amplitude of the parallactic shift is smaller than the camera’s pixel size. We fit each star in the images with an appropriate effective PSF and applied a distortion correction to generate stellar positions accurate to 0.01 pixels (～0.5 mas). The 134 stars common to all images serve to establish a reference frame for alignment of the image series. Our observations were made around the times of maximum parallactic shift. We discuss the implications of this new distance measurement for the inferred radius of Geminga, and the neutron star equation of state.     

Development and testing of a coupled ocean–atmosphere mesoscale ensemble prediction system

A coupled ocean–atmosphere mesoscale ensemble prediction system has been developed by the Naval Research Laboratory. This paper describes the components and implementation of the system and presents baseline results from coupled ensemble simulations for two tropical cyclones. The system is designed to take into account major sources of uncertainty in: (1) non-deterministic dynamics, (2) model error, and (3) initial states. The purpose of the system is to provide mesoscale ensemble forecasts for use in probabilistic products, such as reliability and frequency of occurrence, and in risk management applications. The system components include COAMPS® (Coupled Ocean/Atmosphere Mesoscale Prediction System) and NCOM (Navy Coastal Ocean Model) for atmosphere and ocean forecasting and NAVDAS (NRL Atmospheric Variational Data Assimilation System) and NCODA (Navy Coupled Ocean Data Assimilation) for atmosphere and ocean data assimilation. NAVDAS and NCODA are 3D-variational (3DVAR) analysis schemes. The ensembles are generated using separate applications of the Ensemble Transform (ET) technique in both the atmosphere (for moving or non-moving nests) and the ocean. The atmospheric ET is computed using wind, temperature, and moisture variables, while the oceanographic ET is derived from ocean current, temperature, and salinity variables. Estimates of analysis error covariance, which is used as a constraint in the ET, are provided by the ocean and atmosphere 3DVAR assimilation systems. The newly developed system has been successfully tested for a variety of configurations, including differing model resolution, number of members, forecast length, and moving and fixed nest options. Results from relatively coarse resolution (～27-km) ensemble simulations of Hurricanes Hanna and Ike demonstrate that the ensemble can provide valuable uncertainty information about the storm track and intensity, though the ensemble mean provides only a small amount of improved predictive skill compared to the deterministic control member.