The teleconnection of the tropical Atlantic to Indo-Pacific sea surface temperatures on inter-annual to centennial time scales: a review of recent findings

In this paper, the teleconnections from the tropical Atlantic to the Indo-Pacific region from inter-annual to centennial time scales will be reviewed. Identified teleconnections and hypotheses on mechanisms at work are reviewed and further explored in a century-long pacemaker coupled ocean-atmosphere simulation ensemble. There is a substantial impact of the tropical Atlantic on the Pacific region at inter-annual time scales. An Atlantic Niño (Niña) event leads to rising (sinking) motion in the Atlantic region, which is compensated by sinking (rising) motion in the central-western Pacific. The sinking (rising) motion in the central-western Pacific induces easterly (westerly) surface wind anomalies just to the west, which alter the thermocline. These perturbations propagate eastward as upwelling (downwelling) Kelvin-waves, where they increase the probability for a La Niña (El Niño) event. Moreover, tropical North Atlantic sea surface temperature anomalies are also able to lead La Niña/El Niño development. At multidecadal time scales, a positive (negative) Atlantic Multidecadal Oscillation leads to a cooling (warming) of the eastern Pacific and a warming (cooling) of the western Pacific and Indian Ocean regions. The physical mechanism for this impact is similar to that at inter-annual time scales. At centennial time scales, the Atlantic warming induces a substantial reduction of the eastern Pacific warming even under CO2 increase and to a strong subsurface cooling.

Advancing polar prediction capabilities on daily to seasonal time scales

It is argued that existing polar prediction systems do not yet meet users’ needs; and possible ways forward in advancing prediction capacity in polar regions and beyond are outlined. The polar regions have been attracting more and more attention in recent years, fuelled by the perceptible impacts of anthropogenic climate change. Polar climate change provides new opportunities, such as shorter shipping routes between Europe and East Asia, but also new risks such as the potential for industrial accidents or emergencies in ice-covered seas. Here, it is argued that environmental prediction systems for the polar regions are less developed than elsewhere. There are many reasons for this situation, including the polar regions being (historically) lower priority, with less in situ observations, and with numerous local physical processes that are less well-represented by models. By contrasting the relative importance of different physical processes in polar and lower latitudes, the need for a dedicated polar prediction effort is illustrated. Research priorities are identified that will help to advance environmental polar prediction capabilities. Examples include an improvement of the polar observing system; the use of coupled atmosphere-sea ice-ocean models, even for short-term prediction; and insight into polar-lower latitude linkages and their role for forecasting. Given the enormity of some of the challenges ahead, in a harsh and remote environment such as the polar regions, it is argued that rapid progress will only be possible with a coordinated international effort. More specifically, it is proposed to hold a Year of Polar Prediction (YOPP) from mid-2017 to mid-2019 in which the international research and operational forecasting community will work together with stakeholders in a period of intensive observing, modelling, prediction, verification, user-engagement and educational activities.

Inheritance of time to flowering in cowpea (Vigna unguiculata (L.) Walp.)

Time to flowering and maturity is an important adaptive feature in annual crops, including cowpeas (Vigna unguiculata (L.) Walp.). In West and Central Africa, photoperiod is the most important environmental variable affecting time to flowering in cowpea. The inheritance of time from sowing to flowering (f) in cowpeas was studied by crossing a photoperiod-sensitive genotype Kanannnado to a photoperiod-insensitive variety IT97D-941-1. Sufficient seed of F-1, F-2, F-3 and backcross populations were generated. The parental, F-1, F-2, F-3 and the backcross populations were screened for f under long natural days (mean daylength 13.4 h per day) in the field and the parents, F-1, F-2 and backcross populations under short day (10 h per day) conditions. The result of the screening showed that photoperiod in the field was long enough to delay flowering of photoperiod-sensitive genotypes. Photoperiod-sensitivity was found to be partially dominant to insensitivity. Frequency distribution of the trait in the various populations indicated quantitative inheritance. Additive (d) and additive x dominance (j) interactions were the most important gene actions conditioning time to flowering. A narrow sense heritability of 86% was estimated for this trait. This will result in 26 days gain in time to flowering with 5% selection intensity from the F-2 to F-3 generation. At least seven major gene pairs, with an average delay of 6 days each, were estimated to control time to flowering in this cross.

The application of Prony’s method to time-domain waveform data modeling in the presence of noise

In this paper,the Prony's method is applied to the time-domain waveform data modelling in the presence of noise.The following three problems encountered in this work are studied:(1)determination of the order of waveform;(2)de-termination of numbers of multiple roots;(3)determination of the residues.The methods of solving these problems are given and simulated on the computer.Finally,an output pulse of model PG-10N signal generator and the distorted waveform obtained by transmitting the pulse above mentioned through a piece of coaxial cable are modelled,and satisfactory results are obtained.So the effectiveness of Prony's method in waveform data modelling in the presence of noise is confirmed.

Overview and response to reviewers of The Singing Neanderthals

Why are humans musical? Why do people in all cultures sing or play instruments? Why do we appear to have specialized neurological apparatus for hearing and interpreting music as distinct from other sounds? And how does our musicality relate to language and to our evolutionary history? Anthropologists and archaeologists have paid little attention to the origin of music and musicality — far less than for either language or ‘art’. While art has been seen as an index of cognitive complexity and language as an essential tool of communication, music has suffered from our perception that it is an epiphenomenal ‘leisure activity’, and archaeologically inaccessible to boot. Nothing could be further from the truth, according to Steven Mithen; music is integral to human social life, he argues, and we can investigate its ancestry with the same rich range of analyses — neurological, physiological, ethnographic, linguistic, ethological and even archaeological — which have been deployed to study language. In The Singing Neanderthals Steven Mithen poses these questions and proposes a bold hypothesis to answer them. Mithen argues that musicality is a fundamental part of being human, that this capacity is of great antiquity, and that a holistic protolanguage of musical emotive expression predates language and was an essential precursor to it. This is an argument with implications which extend far beyond the mere origins of music itself into the very motives of human origins. Any argument of such range is bound to attract discussion and critique; we here present commentaries by archaeologists Clive Gamble and Iain Morley and linguists Alison Wray and Maggie Tallerman, along with Mithen's response to them. Whether right or wrong, Mithen has raised fascinating and important issues. And it adds a great deal of charm to the time-honoured, perhaps shopworn image of the Neanderthals shambling ineffectively through the pages of Pleistocene prehistory to imagine them humming, crooning or belting out a cappella harmonies as they went.

The point source method for inverse scattering in the time domain

Many recent inverse scattering techniques have been designed for single frequency scattered fields in the frequency domain. In practice, however, the data is collected in the time domain. Frequency domain inverse scattering algorithms obviously apply to time-harmonic scattering, or nearly time-harmonic scattering, through application of the Fourier transform. Fourier transform techniques can also be applied to non-time-harmonic scattering from pulses. Our goal here is twofold: first, to establish conditions on the time-dependent waves that provide a correspondence between time domain and frequency domain inverse scattering via Fourier transforms without recourse to the conventional limiting amplitude principle; secondly, we apply the analysis in the first part of this work toward the extension of a particular scattering technique, namely the point source method, to scattering from the requisite pulses. Numerical examples illustrate the method and suggest that reconstructions from admissible pulses deliver superior reconstructions compared to straight averaging of multi-frequency data. Copyright (C) 2006 John Wiley & Sons, Ltd.

Interannual to decadal climate predictability in the North Atlantic: A multimodel-ensemble study

Ensemble experiments are performed with five coupled atmosphere-ocean models to investigate the potential for initial-value climate forecasts on interannual to decadal time scales. Experiments are started from similar model-generated initial states, and common diagnostics of predictability are used. We find that variations in the ocean meridional overturning circulation (MOC) are potentially predictable on interannual to decadal time scales, a more consistent picture of the surface temperature impact of decadal variations in the MOC is now apparent, and variations of surface air temperatures in the North Atlantic Ocean are also potentially predictable on interannual to decadal time scales. albeit with potential skill levels that are less than those seen for MOC variations. This intercomparison represents a step forward in assessing the robustness of model estimates of potential skill and is a prerequisite for the development of any operational forecasting system.

The potential for the use of agent-based models in ecotoxicology

This chapter introduces ABMs, their construction, and the pros and cons of their use. Although relatively new, agent-basedmodels (ABMs) have great potential for use in ecotoxicological research – their primary advantage being the realistic simulations that can be constructed and particularly their explicit handling of space and time in simulations. Examples are provided of their use in ecotoxicology primarily exemplified by different implementations of the ALMaSS system. These examples presented demonstrate how multiple stressors, landscape structure, details regarding toxicology, animal behavior, and socioeconomic effects can and should be taken into account when constructing simulations for risk assessment. Like ecological systems, in ABMs the behavior at the system level is not simply the mean of the component responses, but the sum of the often nonlinear interactions between components in the system; hence this modeling approach opens the door to implementing and testing much more realistic and holistic ecotoxicological models than are currently used.

A novel approach to the detection of synchronisation in EEG based on empirical mode decomposition

Transient neural assemblies mediated by synchrony in particular frequency ranges are thought to underlie cognition. We propose a new approach to their detection, using empirical mode decomposition (EMD), a data-driven approach removing the need for arbitrary bandpass filter cut-offs. Phase locking is sought between modes. We explore the features of EMD, including making a quantitative assessment of its ability to preserve phase content of signals, and proceed to develop a statistical framework with which to assess synchrony episodes. Furthermore, we propose a new approach to ensure signal decomposition using EMD. We adapt the Hilbert spectrum to a time-frequency representation of phase locking and are able to locate synchrony successfully in time and frequency between synthetic signals reminiscent of EEG. We compare our approach, which we call EMD phase locking analysis (EMDPL) with existing methods and show it to offer improved time-frequency localisation of synchrony.

A statistical mechanical approach for the computation of the climatic response to general forcings

The climate belongs to the class of non-equilibrium forced and dissipative systems, for which most results of quasi-equilibrium statistical mechanics, including the fluctuation-dissipation theorem, do not apply. In this paper we show for the first time how the Ruelle linear response theory, developed for studying rigorously the impact of perturbations on general observables of non-equilibrium statistical mechanical systems, can be applied with great success to analyze the climatic response to general forcings. The crucial value of the Ruelle theory lies in the fact that it allows to compute the response of the system in terms of expectation values of explicit and computable functions of the phase space averaged over the invariant measure of the unperturbed state. We choose as test bed a classical version of the Lorenz 96 model, which, in spite of its simplicity, has a well-recognized prototypical value as it is a spatially extended one-dimensional model and presents the basic ingredients, such as dissipation, advection and the presence of an external forcing, of the actual atmosphere. We recapitulate the main aspects of the general response theory and propose some new general results. We then analyze the frequency dependence of the response of both local and global observables to perturbations having localized as well as global spatial patterns. We derive analytically several properties of the corresponding susceptibilities, such as asymptotic behavior, validity of Kramers-Kronig relations, and sum rules, whose main ingredient is the causality principle. We show that all the coefficients of the leading asymptotic expansions as well as the integral constraints can be written as linear function of parameters that describe the unperturbed properties of the system, such as its average energy. Some newly obtained empirical closure equations for such parameters allow to define such properties as an explicit function of the unperturbed forcing parameter alone for a general class of chaotic Lorenz 96 models. We then verify the theoretical predictions from the outputs of the simulations up to a high degree of precision. The theory is used to explain differences in the response of local and global observables, to define the intensive properties of the system, which do not depend on the spatial resolution of the Lorenz 96 model, and to generalize the concept of climate sensitivity to all time scales. We also show how to reconstruct the linear Green function, which maps perturbations of general time patterns into changes in the expectation value of the considered observable for finite as well as infinite time. Finally, we propose a simple yet general methodology to study general Climate Change problems on virtually any time scale by resorting to only well selected simulations, and by taking full advantage of ensemble methods. The specific case of globally averaged surface temperature response to a general pattern of change of the CO2 concentration is discussed. We believe that the proposed approach may constitute a mathematically rigorous and practically very effective way to approach the problem of climate sensitivity, climate prediction, and climate change from a radically new perspective.

Cyborg 1.0

I was born human. But this was an accident of fate - a condition merely of time and place. I believe it's something we have the power to change. I will tell you why. In August 1998, a silicon chip was implanted in my arm, allowing a computer to monitor me as I moved through the halls and offices of the Department of Cybernetics at the University of Reading, just west of London, where I've been a professor since 1988. My implant communicated via radio waves with a network of antennas throughout the department that in turn transmitted the signals to a computer programmed to respond to my actions. At the main entrance, a voice box operated by the computer said "Hello" when I entered; the computer detected my progress through the building, opening the door to my lab for me as I approached it and switching on the lights. For the nine days the implant was in place, I performed seemingly magical acts simply by walking in a particular direction. The aim of this experiment was to determine whether information could be transmitted to and from an implant. Not only did we succeed, but the trial demonstrated how the principles behind cybernetics could perform in real-life applications.