Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice: the Larcform 1 single column model intercomparison

Weather and climate models struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Arctic winter, partly because they lack or misrepresent physical processes that are specific to high latitudes. Observations have revealed two preferred states of the Arctic winter boundary layer. In the cloudy state, cloud liquid water limits surface radiative cooling, and temperature inversions are weak and elevated. In the radiatively clear state, strong surface radiative cooling leads to the build-up of surface-based temperature inversions. Many large-scale models lack the cloudy state, and some substantially underestimate inversion strength in the clear state. Here, the transformation from a moist to a cold dry air mass is modeled using an idealized Lagrangian perspective. The trajectory includes both boundary layer states, and the single-column experiment is the first Lagrangian Arctic air formation experiment (Larcform 1) organized within GEWEX GASS (Global atmospheric system studies). The intercomparison reproduces the typical biases of large-scale models: some models lack the cloudy state of the boundary layer due to the representation of mixed-phase microphysics or to the interaction between micro- and macrophysics. In some models, high emissivities of ice clouds or the lack of an insulating snow layer prevent the build-up of surface-based inversions in the radiatively clear state. Models substantially disagree on the amount of cloud liquid water in the cloudy state and on turbulent heat fluxes under clear skies. Observations of air mass transformations including both boundary layer states would allow for a tighter constraint of model behavior

Quantitative trait loci and somatostatin

The disclosure relates to the use of genetic traits in livestock for determining breeding characteristics of livestock progeny, and for optimizing the management and marketing of livestock for improving feedlot performance and meat quality. The disclosure specifically relates to genetic markers and single nucleotide polymorphisms (SNPs) in the bovine somatostatin locus, as well as haplotypes that include the somatostatin locus, which are associated with certain quantitative trait loci (QTLs), such as marbling, meat quality grade, and yield grade. In a preferred embodiment, the SNPs and haplotypes are predictive of the increased or decreased amount of tissue marbling in the animal.U

Quantitative trait loci and somatostatin

The disclosure relates to the use of genetic traits in livestock for determining breeding characteristics of livestock progeny, and for optimizing the management and marketing of livestock for improving feedlot performance and meat quality. The disclosure specifically relates to genetic markers and single nucleotide polymorphisms (SNPs) in the bovine somatostatin locus, as well as haplotypes that include the somatostatin locus, which are associated with certain quantitative trait loci (QTLs), such as marbling, meat quality grade, and yield grade. In a preferred embodiment, the SNPs and haplotypes are predictive of the increased or decreased amount of tissue marbling in the animal.U

Quantitative trait loci and somatostatin

The disclosure relates to the use of genetic traits in livestock for determining breeding characteristics of livestock progeny, and for optimizing the management and marketing of livestock for improving feedlot performance and meat quality. The disclosure specifically relates to genetic markers and single nucleotide polymorphisms (SNPs) in the bovine somatostatin locus, as well as haplotypes that include the somatostatin locus, which are associated with certain quantitative trait loci (QTLs), such as marbling, meat quality grade, and yield grade. In a preferred embodiment, the SNPs and haplotypes are predictive of the increased or decreased amount of tissue marbling in the animal.U

Angle-based formation shape control with velocity alignment

With the rapid development of sensor technology, bearing/angle measurements are becoming cheaper and more reliable, which motivates the study of angle-based formation shape control. This work studies how to achieve angle-based formation control and velocity alignment at the same time, in which all agents can form a desired angle-rigid formation and translate with the same velocity simultaneously. The agents' communication topology for the achievement of velocity alignment is described by a connected graph, while the formation shape is determined by a set of angles that are associated with triangles within the formation and computed using bearing measurements. A simulation example validates the effectiveness of the theoretical results

Distributed feedback control on the SIS network model: An impossibility result

This paper considers the deterministic Susceptible-Infected-Susceptible (SIS) epidemic network model, over strongly connected networks. It is well known that there exists an endemic equilibrium (the disease persists in all nodes of the network) if and only if the effective reproduction number of the network is greater than 1. In fact, the endemic equilibrium is unique and is asymptotically stable for all feasible nonzero initial conditions. We consider the recovery rate of each node as a control input. Using results from differential topology and monotone systems, we establish that it is impossible for a large class of distributed feedback controllers to drive the network to the healthy equilibrium (where every node is disease free) if the uncontrolled network has a reproduction number greater than 1. In fact, a unique endemic equilibrium exists in the controlled network, and it is exponentially stable for all feasible nonzero initial conditions. We illustrate our impossibility result using simulations, and discuss the implications on the problem of control over epidemic networks

LSST data management software development practices and tools

International audienceThe Large Synoptic Survey Telescope (LSST) is an 8.4m optical survey telescope being constructed on Cerro Pach´on in Chile. The data management system being developed must be able to process the nightly alert data, 20,000 expected transient alerts per minute, in near real time, and construct annual data releases at the petabyte scale. The development team consists of more than 90 people working in six different sites across the US developing an integrated set of software to realize the LSST science goals. In this paper we discuss our agile software development methodology and our API and developer decision making process. We also discuss the software tools that we use for continuous integration and deployment

Mixed-phase clouds cause climate model biases in Arctic wintertime temperature inversions

Temperature inversions are a common feature of the Arctic wintertime boundary layer. They have important impacts on both radiative and turbulent heat fluxes and partly determine local climate-change feedbacks. Understanding the spread in inversion strength modelled by current global climate models is therefore an important step in better understanding Arctic climate and its present and future changes. Here, we show how the formation of Arctic air masses leads to the emergence of a cloudy and a clear state of the Arctic winter boundary layer. In the cloudy state, cloud liquid water is present, little to no surface radiative cooling occurs and inversions are elevated and relatively weak, whereas surface radiative cooling leads to strong surface-based temperature inversions in the clear state. Comparing model output to observations, we find that most climate models lack a realistic representation of the cloudy state. An idealised single-column model experiment of the formation of Arctic air reveals that this bias is linked to inadequate mixed-phase cloud microphysics, whereas turbulent and conductive heat fluxes control the strength of inversions within the clear state