Forced signal and predictability in a prototype climate model: Implications for fingerprinting based detection in the presence of multidecadal natural variability

Advanced numerical models used for climate prediction are known to exhibit biases in their simulated climate response to variable concentrations of the atmospheric greenhouse gases and aerosols that force a non-uniform, in space and time, secular global warming. We argue here that these biases can be particularly pronounced due to misrepresentation, in these models, of the multidecadal internal climate variability characterized by large-scale, hemispheric-to-global patterns. This point is illustrated through the development and analysis of a prototype climate model comprised of two damped linear oscillators, which mimic interannual and multidecadal internal climate dynamics and are set into motion via a combination of stochastic driving, representing weather noise, and deterministic external forcing inducing a secular climate change. The model time series are paired with pre-specified patterns in the physical space and form, conceptually, a spatially extended time series of the zonal-mean near-surface temperature, which is further contaminated by a spatiotemporal noise simulating the rest of climate variability. The choices of patterns and model parameters were informed by observations and climate-model simulations of the 20th century near-surface air temperature. Our main finding is that the intensity and spatial patterns of the internal multidecadal variability associated with the slow-oscillator model component greatly affect (i) the ability of modern pattern-recognition/fingerprinting methods to isolate the forced response of the climate system in the 20th century ensemble simulations and (ii) climate-system predictability, especially decadal predictability, as well as the estimates of this predictability using climate models in which the internal multidecadal variability is underestimated or otherwise misrepresented.

Applying interval stability concept to empirical model of middle Pleistocene transition

Interval stability is a novel method for the study of complex dynamical systems, allowing for the estimation of their stability to strong perturbations. This method describes how large perturbation should be to disrupt the stable dynamical regime of the system (attractor). In our work, interval stability is used for the first time to study the properties of a real natural system: to analyze the stability of the earth's climate system during the last 2.6×10⁶ years. The main abrupt shift in global climate during this period is the middle Pleistocene transition (MPT), which occurred about 1×10⁶ years ago as a change of the periodicity of glacial cycles from 41 to 100 kyr. On the basis of the empirical nonlinear stochastic model proposed in our recent work, we demonstrate that the global climate stability to any perturbations decreases throughout the Pleistocene period (including the MPT), enhancing its response to fast (with a millennial scale or less) internal disturbances.

Data-driven stochastic model for cross-interacting processes with different time scales

In this work, we propose a new data-driven method for modeling cross-interacting processes with different time scales represented by time series with different sampling steps. It is a generalization of a nonlinear stochastic model of an evolution operator based on neural networks and designed for the case of time series with a constant sampling step. The proposed model has a more complex structure. First, it describes each process by its own stochastic evolution operator with its own time step. Second, it takes into account possible nonlinear connections within each pair of processes in both directions. These connections are parameterized asymmetrically, depending on which process is faster and which process is slower. They make this model essentially different from the set of independent stochastic models constructed individually for each time scale. All evolution operators and connections are trained and optimized using the Bayesian framework, forming a multi-scale stochastic model. We demonstrate the performance of the model on two examples. The first example is a pair of coupled oscillators, with the couplings in both directions which can be turned on and off. Here, we show that inclusion of the connections into the model allows us to correctly reproduce observable effects related to coupling. The second example is a spatially distributed data generated by a global climate model running in the middle 19th century external conditions. In this case, the multi-scale model allows us to reproduce the coupling between the processes which exists in the observed data but is not captured by the model constructed individually for each process.

Analysis of 20th century surface air temperature using linear dynamical modes

A Bayesian Linear Dynamical Mode (LDM) decomposition method is applied to isolate robust modes of climate variability in the observed surface air temperature (SAT) field. This decomposition finds the optimal number of internal modes characterized by their own time scales, which enter the cost function through a specific choice of prior probabilities. The forced climate response, with time dependence estimated from state-of-the-art climate-model simulations, is also incorporated in the present LDM decomposition and shown to increase its optimality from a Bayesian standpoint. On top of the forced signal, the decomposition identifies five distinct LDMs of internal climate variability. The first three modes exhibit multidecadal scales, while the remaining two modes are attributable to interannual-to-decadal variability associated with El Niño-Southern oscillation; all of these modes contribute to the secular climate signal-the so-called global stadium wave-missing in the climate-model simulations. One of the multidecadal LDMs is associated with Atlantic multidecadal oscillation. The two remaining slow modes have secular time scales and patterns exhibiting regional-to-global similarities to the forced-signal pattern. These patterns have a global scale and contribute significantly to SAT variability over the Southern and Pacific Oceans. In combination with low-frequency modulation of the fast LDMs, they explain the vast majority of the variability associated with interdecadal Pacific oscillation. The global teleconnectivity of the secular climate modes and their possible crucial role in shaping the forced climate response are the two key dynamical questions brought about by the present analysis.

The IGH locus relocalizes to a "recombination compartment" in the perinucleolar region of differentiating B-lymphocytes

The immunoglobulin heavy chain (IGH) gene loci are subject to specific recombination events during B-cell differentiation including somatic hypermutation and class switch recombination which mark the end of immunoglobulin gene maturation in germinal centers of secondary lymph nodes. These two events rely on the activity of activation-induced cytidine deaminase (AID) which requires DNA double strand breaks be created, a potential danger to the cell. Applying 3D-fluorescence in situ hybridization coupled with immunofluorescence staining to a previously described experimental system recapitulating normal B-cell differentiation ex vivo, we have kinetically analyzed the radial positioning of the two IGH gene loci as well as their proximity with the nucleolus, heterochromatin and γH2AX foci. Our observations are consistent with the proposal that these IGH gene rearrangements take place in a specific perinucleolar “recombination compartment” where AID could be sequestered thus limiting the extent of its potentially deleterious off-target effects.

In vivo formaldehyde cross-linking: it is time for black box analysis

Formaldehyde cross-linking is an important component of many technologies, including chromatin immunoprecipitation and chromosome conformation capture. The procedure remains empirical and poorly characterized, however, despite a long history of its use in research. Little is known about the specificity of in vivo cross-linking, its efficiency and chemical adducts induced by the procedure. It is time to search this black box.

Shadowing and mask opening effects during selective-area vapor-liquid-solid growth of InP nanowires by metalorganic molecular beam epitaxy

Indium phosphide nanowires were grown by metalorganic molecular beam epitaxy using the selective-area vapor-liquid-solid method. We show experimentally and theoretically that the size of the annular opening around the nanowire has a major impact on nanowire growth rate. In addition, we observed a considerable reduction of the growth rate in dense two-dimensional arrays, in agreement with a calculation of the shadowing of the scattered precursors. Due to the impact of these effects on growth, they should be considered during selective-area vapor-liquid-solid nanowire epitaxy.

Evaluation of the local temperature of conductive filaments in resistive switching materials

The resistive switching effect in metal oxides and other dielectric materials is among the leading future non-volatile memory technologies. Resistive switching is widely ascribed to the formation and rupture of conductive filaments in the oxide, which are generated by temperature-enhanced nano-scale ion migration or other thermal effects. In spite of the central role of the local filament temperature on the switching effect, as well as on the conduction and reliability physics, no measurement methods of the filament temperature are yet available. In this work, we report on a method for evaluating the conducting filament temperature, using a metal-insulator-semiconductor bipolar transistor structure. The filament temperature is obtained by analyzing the thermal excitation rate of electrons from the filament Fermi level into the conduction band of a p-type semiconductor electrode. Measurements were carried out to obtain the conductive filament temperature in hafnia at varying ambient temperatures in the range of 3-300 K. Significant Joule heating of the filament was observed across the entire measured ambient temperature range. The extracted temperatures provide physical insight into the resistive switching effect.

Chromosome conformation capture (from 3C to 5C) and its ChIP-based modification

Chromosome conformation capture (3C) methodology was developed to study spatial organization of long genomic regions in living cells. Briefly, chromatin is fixed with formaldehyde in vivo to cross-link interacting sites, digested with a restriction enzyme and ligated at a low DNA concentration so that ligation between cross-linked fragments is favored over ligation between random fragments. Ligation products are then analyzed and quantified by PCR. So far, semi-quantitative PCR methods were widely used to estimate the ligation frequencies. However, it is often important to estimate the ligation frequencies more precisely which is only possible by using the real-time PCR. At the same time, it is equally necessary to monitor the specificity of PCR amplification. That is why the real-time PCR with TaqMan probes is becoming more and more popular in 3C studies. In this chapter, we describe the general protocol for 3C analysis with the subsequent estimation of ligation frequencies by using the real-time PCR technology with TaqMan probes. We discuss in details all steps of the experimental procedure paying special attention to weak points and possible ways to solve the problems. A special attention is also paid to the problems in interpretation of the results and necessary control experiments. Besides, in theory, we consider other approaches to analysis of the ligation products used in frames of the so-called 4C and 5C methods. The recently developed chromatin immunoprecipitation (ChIP)-loop assay representing a combination of 3C and ChIP is also discussed.

A CTCF-dependent silencer located in the differentially methylated area may regulate expression of a housekeeping gene overlapping a tissue-specific gene domain

The tissue-specific chicken alpha-globin gene domain represents one of the paradigms, in terms of its constitutively open chromatin conformation and the location of several regulatory elements within the neighboring housekeeping gene. Here, we show that an 0.2-kb DNA fragment located approximately 4 kb upstream to the chicken alpha-globin gene cluster contains a binding site for the multifunctional protein factor CTCF and possesses silencer activity which depends on CTCF binding, as demonstrated by site-directed mutagenesis of the CTCF recognition sequence. CTCF was found to be associated with this recognition site in erythroid cells but not in lymphoid cells where the site is methylated. A functional promoter directing the transcription of the apparently housekeeping ggPRX gene was found 120 bp from the CTCF-dependent silencer. The data are discussed in terms of the hypothesis that the CTCF-dependent silencer stabilizes the level of ggPRX gene transcription in erythroid cells where the promoter of this gene may be influenced by positive cis-regulatory signals activating alpha-globin gene transcription.

Comparison of US inactivated split-virus and Russian live attenuated, cold-adapted trivalent influenza vaccines in Russian schoolchildren

In a blinded, placebo-controlled study, the reactogenicity, immunogenicity, and clinical efficacy of single doses of US inactivated split-virus and Russian live attenuated, cold-adapted influenza vaccines were compared in 555 schoolchildren in Vologda, Russia. Serial serum samples were collected and school absenteeism was assessed. Systemic reactions were rare, but local reactions (primarily erythema at the injection site) were observed in 27% of the inactivated vaccine group, and coryza (12%) and sore throat (8%) were observed in the attenuated vaccine group. At 4 weeks after vaccination a > or = 4-fold rise in titer of hemagglutination inhibition antibody to A (H1N1), A (H3N2), and B was noted, respectively, among 78%, 88%, and 53% of children who received inactivated vaccine and among 55%, 79%, and 30% of children who received attenuated vaccine. The vaccine efficacy for preventing school absenteeism due to respiratory illness during the period of peak influenza activity was 56% for inactivated vaccine and 47% for attenuated vaccine.