Atmosphere feedbacks during ENSO in a coupled GCM with a modified atmospheric convection scheme

The too diverse representation of ENSO in a coupled GCM limits one’s ability to describe future change of its properties. Several studies pointed to the key role of atmosphere feedbacks in contributing to this diversity. These feedbacks are analyzed here in two simulations of a coupled GCM that differ only by the parameterization of deep atmospheric convection and the associated clouds. Using the Kerry–Emanuel (KE) scheme in the L’Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL CM4; KE simulation), ENSO has about the right amplitude, whereas it is almost suppressed when using the Tiedke (TI) scheme. Quantifying both the dynamical Bjerknes feedback and the heat flux feedback in KE, TI, and the corresponding Atmospheric Model Intercomparison Project (AMIP) atmosphere-only simulations, it is shown that the suppression of ENSO in TI is due to a doubling of the damping via heat flux feedback. Because the Bjerknes positive feedback is weak in both simulations, the KE simulation exhibits the right ENSO amplitude owing to an error compensation between a too weak heat flux feedback and a too weak Bjerknes feedback. In TI, the heat flux feedback strength is closer to estimates from observations and reanalysis, leading to ENSO suppression. The shortwave heat flux and, to a lesser extent, the latent heat flux feedbacks are the dominant contributors to the change between TI and KE. The shortwave heat flux feedback differences are traced back to a modified distribution of the large-scale regimes of deep convection (negative feedback) and subsidence (positive feedback) in the east Pacific. These are further associated with the model systematic errors. It is argued that a systematic and detailed evaluation of atmosphere feedbacks during ENSO is a necessary step to fully understand its simulation in coupled GCMs.

The role of atmosphere feedbacks during ENSO in the CMIP3 models

Several studies using ocean-atmosphere GCMs suggest that the atmospheric component plays a dominant role in the modelled ENSO. To help elucidate these findings, the two main atmosphere feedbacks relevant to ENSO, the Bjerknes positive feedback (µ) and the heat flux negative feedback (), are analysed here in 12 coupled GCMs. We find that the models generally underestimate both feedbacks, leading to an error compensation. The strength of is inversely related to the ENSO amplitude in the models and the latent heat and shortwave flux components of this feedback dominate. Furthermore, the shortwave component could help explain the model diversity in both overall and ENSO amplitude.

Quantifying carbon-cycle feedbacks

Perturbations to the carbon cycle could constitute large feedbacks on future changes in atmospheric CO2 concentration and climate. This paper demonstrates how carbon cycle feedback can be expressed in formally similar ways to climate feedback, and thus compares their magnitudes. The carbon cycle gives rise to two climate feedback terms: the concentration–carbon feedback, resulting from the uptake of carbon by land and ocean as a biogeochemical response to the atmospheric CO2 concentration, and the climate–carbon feedback, resulting from the effect of climate change on carbon fluxes. In the earth system models of the Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP), climate–carbon feedback on warming is positive and of a similar size to the cloud feedback. The concentration–carbon feedback is negative; it has generally received less attention in the literature, but in magnitude it is 4 times larger than the climate–carbon feedback and more uncertain. The concentration–carbon feedback is the dominant uncertainty in the allowable CO2 emissions that are consistent with a given CO2 concentration scenario. In modeling the climate response to a scenario of CO2 emissions, the net carbon cycle feedback is of comparable size and uncertainty to the noncarbon–climate response. To quantify simulated carbon cycle feedbacks satisfactorily, a radiatively coupled experiment is needed, in addition to the fully coupled and biogeochemically coupled experiments, which are referred to as coupled and uncoupled in C4MIP. The concentration–carbon and climate–carbon feedbacks do not combine linearly, and the concentration–carbon feedback is dependent on scenario and time.

General derivative relations for anharmonic force fields

The brace notation, introduced by Allen and Csaszar (1993, J. chem. Phys., 98, 2983), provides a simple and compact way to deal with derivatives of arbitrary non-tensorial quantities. One of its main advantages is that it builds the permutational symmetry of the derivatives directly into the formalism. The brace notation is applied to formulate the general nth-order Cartesian derivatives of internal coordinates, and to provide closed forms for general, nth-order transformation equations of anharmonic force fields, expressed as Taylor series, from internal to Cartesian or normal coordinate spaces.

Optimality analysis of Th1/Th2 immune responses during microparasite-macroparasite co-infection, with epidemiological feedbacks

Individuals are typically co-infected by a diverse community of microparasites (e.g. viruses or protozoa) and macroparasites (e.g. helminths). Vertebrates respond to these parasites differently, typically mounting T helper type 1 (Th1) responses against microparasites and Th2 responses against macroparasites. These two responses may be antagonistic such that hosts face a 'decision' of how to allocate potentially limiting resources. Such decisions at the individual host level will influence parasite abundance at the population level which, in turn, will feed back upon the individual level. We take a first step towards a complete theoretical framework by placing an analysis of optimal immune responses under microparasite-macroparasite co-infection within an epidemiological framework. We show that the optimal immune allocation is quantitatively sensitive to the shape of the trade-off curve and qualitatively sensitive to life-history traits of the host, microparasite and macroparasite. This model represents an important first step in placing optimality models of the immune response to co-infection into an epidemiological framework. Ultimately, however, a more complete framework is needed to bring together the optimal strategy at the individual level and the population-level consequences of those responses, before we can truly understand the evolution of host immune responses under parasite co-infection.

X-ray crystallographic study of DNA duplex cross-linking: simultaneous binding to two d(CGTACG)(2) molecules by a bis(9-aminoacridine-4-carboxamide) derivative

Acridine-4-carboxamides form a class of known DNA mono-intercalating agents that exhibit cytotoxic activity against tumour cell lines due to their ability to inhibit topoisomerases. Previous studies of bis-acridine derivatives have yielded equivocal results regarding the minimum length of linker necessary between the two acridine chromophores to allow bis-intercalation of duplex DNA. We report here the 1.7 angstrom resolution X-ray crystal structure of a six-carbon-linked bis(acridine-4-carboxamide) ligand bound to d(CGTACG)(2) molecules by non-covalent duplex cross-linking. The asymmetric unit consists of one DNA duplex containing an intercalated acridine-4-carboxamide chromophore at each of the two CG steps. The other half of each ligand is bound to another DNA molecule in a symmetry-related manner, with the alkyl linker threading through the minor grooves. The two crystallographically independent ligand molecules adopt distinct side chain interactions, forming hydrogen bonds to either O6 or N7 on the major groove face of guanine, in contrast to the semi-disordered state of mono-intercalators bound to the same DNA molecule. The complex described here provides the first structural evidence for the non-covalent cross-linking of DNA by a small molecule ligand and suggests a possible explanation for the inconsistent behaviour of six-carbon linked bis-acridines in previous assays of DNA bis-intercalation.

Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

Electronic energy transfer in a dinuclear Ru/Os complex containing a photoresponsive dithienylethene derivative as bridging ligand

In order to build up a multicomponent system able to perform useful light-induced functions, a dithienylethene-bridged heterodinuclear metal complex (Ru/Os) has been prepared. The compound was characterized and its photophysical properties studied in detail.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

Self-tuning proportional, integral and derivative controller based on genetic algorithm least squares

A self-tuning proportional, integral and derivative control scheme based on genetic algorithms (GAs) is proposed and applied to the control of a real industrial plant. This paper explores the improvement in the parameter estimator, which is an essential part of an adaptive controller, through the hybridization of recursive least-squares algorithms by making use of GAs and the possibility of the application of GAs to the control of industrial processes. Both the simulation results and the experiments on a real plant show that the proposed scheme can be applied effectively.

Eliminativism about derivative prima facie duties

Ross divides prima facie duties into derivative and foundational ones, but seems to understand the notion of a derivative prima facie duty in two very different ways. Sometimes he understands them in a non-eliminativist way. According to this understanding, basic prima facie duties ground distinct derivative ones. According to the eliminativist understanding, basic duties do not ground distinct derivative duties, but replace (eliminate) them. On the eliminativist view, discovering that a prima facie duty is derivative is discovering that it is not genuine. The genuine one is the basic one. I argue that Ross is best understood as an eliminativist.

The synthesis of dicobalt and dinickel complexes of trimethylsilylethynyl-1, 2-dihydrofullerene; characterisation by n.m.r. and structure of the first acyclic metal fullerene derivative: molecular structure of [η2-{2-H-1-(Me3SiC ≡ C)-C60}Ni2(η-C5H5)2]

The synthesis and characterisation of the complexes [η2-{2-H-1-(Me3SiC ≡ C)-C60}Co2(CO)6] (2)} and [η-2-{2-H-1-(Me3SiC ≡ C)-C60}Ni2η-C5H5)2] (3)} is reported, together with a single-crystal molecular structure for (3). This provides the first structural data for an acyclic metal derivative of [60]-fullerene.