An adaptive finite element water column model using the Mellor-Yamada level 2.5 turbulence closure scheme

A one-dimensional water column model using the Mellor and Yamada level 2.5 parameterization of vertical turbulent fluxes is presented. The model equations are discretized with a mixed finite element scheme. Details of the finite element discrete equations are given and adaptive mesh refinement strategies are presented. The refinement criterion is an "a posteriori" error estimator based on stratification, shear and distance to surface. The model performances are assessed by studying the stress driven penetration of a turbulent layer into a stratified fluid. This example illustrates the ability of the presented model to follow some internal structures of the flow and paves the way for truly generalized vertical coordinates. (c) 2005 Elsevier Ltd. All rights reserved.

Alterations in receptor binding properties of recent human influenza H3N2 viruses are associated with reduced natural killer cell lysis of infected cells

Natural killer (NK) cell recognition of influenza virus-infected cells involves hemagglutinin (HA) binding to sialic acid (SA) on activating NK receptors. SA also acts as a receptor for the binding of influenza virus to its target host cells. The SA binding properties of H3N2 influenza viruses have been observed to change during circulation in humans: recent isolates are unable to agglutinate chicken red blood cells and show reduced affinity for synthetic glycopolymers representing SA-alpha-2,3-lactose (3'SL-PAA) and SA-alpha-2,6-N-acetyl lactosamine (6'SLN-PAA) carbohydrates. Here, NK lysis of cells infected with human H3N2 influenza viruses isolated between 1969 and 2003 was analyzed. Cells infected with recent isolates (1999 to 2003) were found to be lysed less effectively than cells infected with older isolates (1969 to 1996). This change occurred concurrently with the acquisition of two new potential glycosylation site motifs in RA. Deletion of the potential glycosylation site motif at 133 to 135 in HA1 from a recent isolate partially restored the agglutination phenotype to a recombinant virus, indicating that the HA-SA interaction is inhibited by the glycosylation modification. Deletion of either of the recently acquired potential glycosylation sites from HA led to increased NK lysis of cells infected with recombinant viruses carrying modified HA. These results indicate that alterations in RA glycosylation may affect NK cell recognition of influenza virus-infected cells in addition to virus binding to host cells.

Alterations in receptor binding properties of recent human influenza H3N2 viruses are associated with reduced natural killer cell lysis of infected cells

Natural killer (NK) cell recognition of influenza virus-infected cells involves hemagglutinin (HA) binding to sialic acid (SA) on activating NK receptors. SA also acts as a receptor for the binding of influenza virus to its target host cells. The SA binding properties of H3N2 influenza viruses have been observed to change during circulation in humans: recent isolates are unable to agglutinate chicken red blood cells and show reduced affinity for synthetic glycopolymers representing SA-alpha-2,3-lactose (3'SL-PAA) and SA-alpha-2,6-N-acetyl lactosamine (6'SLN-PAA) carbohydrates. Here, NK lysis of cells infected with human H3N2 influenza viruses isolated between 1969 and 2003 was analyzed. Cells infected with recent isolates (1999 to 2003) were found to be lysed less effectively than cells infected with older isolates (1969 to 1996). This change occurred concurrently with the acquisition of two new potential glycosylation site motifs in RA. Deletion of the potential glycosylation site motif at 133 to 135 in HA1 from a recent isolate partially restored the agglutination phenotype to a recombinant virus, indicating that the HA-SA interaction is inhibited by the glycosylation modification. Deletion of either of the recently acquired potential glycosylation sites from HA led to increased NK lysis of cells infected with recombinant viruses carrying modified HA. These results indicate that alterations in RA glycosylation may affect NK cell recognition of influenza virus-infected cells in addition to virus binding to host cells.

The APE atlas

This Atlas presents statistical analyses of the simulations submitted to the Aqua-Planet Experiment (APE) data archive. The simulations are from global Atmospheric General Circulation Models (AGCM) applied to a water-covered earth. The AGCMs include ones actively used or being developed for numerical weather prediction or climate research. Some are mature, application models and others are more novel and thus less well tested in Earth-like applications. The experiment applies AGCMs with their complete parameterization package to an idealization of the planet Earth which has a greatly simplified lower boundary that consists of an ocean only. It has no land and its associated orography, and no sea ice. The ocean is represented by Sea Surface Temperatures (SST) which are specified everywhere with simple, idealized distributions. Thus in the hierarchy of tests available for AGCMs, APE falls between tests with simplified forcings such as those proposed by Held and Suarez (1994) and Boer and Denis (1997) and Earth-like simulations of the Atmospheric Modeling Intercomparison Project (AMIP, Gates et al., 1999). Blackburn and Hoskins (2013) summarize the APE and its aims. They discuss where the APE fits within a modeling hierarchy which has evolved to evaluate complete models and which provides a link between realistic simulation and conceptual models of atmospheric phenomena. The APE bridges a gap in the existing hierarchy. The goals of APE are to provide a benchmark of current model behaviors and to stimulate research to understand the cause of inter-model differences., APE is sponsored by the World Meteorological Organization (WMO) joint Commission on Atmospheric Science (CAS), World Climate Research Program (WCRP) Working Group on Numerical Experimentation (WGNE). Chapter 2 of this Atlas provides an overview of the specification of the eight APE experiments and of the data collected. Chapter 3 lists the participating models and includes brief descriptions of each. Chapters 4 through 7 present a wide variety of statistics from the 14 participating models for the eight different experiments. Additional intercomparison figures created by Dr. Yukiko Yamada in AGU group are available at http://www.gfd-dennou.org/library/ape/comparison/. This Atlas is intended to present and compare the statistics of the APE simulations but does not contain a discussion of interpretive analyses. Such analyses are left for journal papers such as those included in the Special Issue of the Journal of the Meteorological Society of Japan (2013, Vol. 91A) devoted to the APE. Two papers in that collection provide an overview of the simulations. One (Blackburn et al., 2013) concentrates on the CONTROL simulation and the other (Williamson et al., 2013) on the response to changes in the meridional SST profile. Additional papers provide more detailed analysis of the basic simulations, while others describe various sensitivities and applications. The APE experiment data base holds a wealth of data that is now publicly available from the APE web site: http://climate.ncas.ac.uk/ape/. We hope that this Atlas will stimulate future analyses and investigations to understand the large variation seen in the model behaviors.

Hurricanes and climate: the U.S. CLIVAR working group on hurricanes

While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. This article summarizes published research from the idealized experiments of the Hurricane Working Group of U.S. CLIVAR (CLImate VARiability and predictability of the ocean-atmosphere system). This work, combined with results from other model simulations, has strengthened relationships between tropical cyclone formation rates and climate variables such as mid-tropospheric vertical velocity, with decreased climatological vertical velocities leading to decreased tropical cyclone formation. Systematic differences are shown between experiments in which only sea surface temperature is increased versus experiments where only atmospheric carbon dioxide is increased, with the carbon dioxide experiments more likely to demonstrate the decrease in tropical cyclone numbers previously shown to be a common response of climate models in a warmer climate. Experiments where the two effects are combined also show decreases in numbers, but these tend to be less for models that demonstrate a strong tropical cyclone response to increased sea surface temperatures. Further experiments are proposed that may improve our understanding of the relationship between climate and tropical cyclone formation, including experiments with two-way interaction between the ocean and the atmosphere and variations in atmospheric aerosols.