1,759 research outputs found

    The importance of interactive chemistry for stratosphere–troposphere coupling

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    Recent observational and modeling studies suggest that stratospheric ozone depletion not only influences the surface climate in the Southern Hemisphere (SH), but also impacts Northern Hemisphere (NH) spring, which implies a strong interaction between dynamics and chemistry. Here, we systematically analyze the importance of interactive chemistry with respect to the representation of stratosphere–troposphere coupling and in particular the effects on NH surface climate during the recent past. We use the interactive and specified chemistry version of NCAR's Whole Atmosphere Community Climate Model coupled to an ocean model to investigate differences in the mean state of the NH stratosphere as well as in stratospheric extreme events, namely sudden stratospheric warmings (SSWs), and their surface impacts. To be able to focus on differences that arise from two-way interactions between chemistry and dynamics in the model, the specified chemistry model version uses a time-evolving, model-consistent ozone field generated by the interactive chemistry model version. We also test the effects of zonally symmetric versus asymmetric prescribed ozone, evaluating the importance of ozone waves in the representation of stratospheric mean state and variability. The interactive chemistry simulation is characterized by a significantly stronger and colder polar night jet (PNJ) during spring when ozone depletion becomes important. We identify a negative feedback between lower stratospheric ozone and atmospheric dynamics during the breakdown of the stratospheric polar vortex in the NH, which contributes to the different characteristics of the PNJ between the simulations. Not only the mean state, but also stratospheric variability is better represented in the interactive chemistry simulation, which shows a more realistic distribution of SSWs as well as a more persistent surface impact afterwards compared with the simulation where the feedback between chemistry and dynamics is switched off. We hypothesize that this is also related to the feedback between ozone and dynamics via the intrusion of ozone-rich air into polar latitudes during SSWs. The results from the zonally asymmetric ozone simulation are closer to the interactive chemistry simulations, implying that under a model-consistent ozone forcing, a three-dimensional (3-D) representation of the prescribed ozone field is desirable. This suggests that a 3-D ozone forcing, as recommended for the upcoming CMIP6 simulations, has the potential to improve the representation of stratospheric dynamics and chemistry. Our findings underline the importance of the representation of interactive chemistry and its feedback on the stratospheric mean state and variability not only in the SH but also in the NH during the recent past.</p

    Predicting Landscape-Scale CO 2 Flux at a Pasture and Rice Paddy with Long-Term Hyperspectral Canopy Reflectance Measurements

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    Measurements of hyperspectral canopy reflectance provide a detailed snapshot of information regarding canopy biochemistry, structure and physiology. In this study, we collected 5 years of repeated canopy hyperspectral reflectance measurements for a total of over 100 site visits within the flux footprints of two eddy covariance towers at a pasture and rice paddy in northern California. The vegetation at both sites exhibited dynamic phenology, with significant interannual variability in the timing of seasonal patterns that propagated into interannual variability in measured hyperspectral reflectance. We used partial least-squares regression (PLSR) modeling to leverage the information contained within the entire canopy reflectance spectra (400–900 nm) in order to investigate questions regarding the connection between measured hyperspectral reflectance and landscape-scale fluxes of net ecosystem exchange (NEE) and gross primary productivity (GPP) across multiple timescales, from instantaneous flux to monthly integrated flux

    DEEP: A dual EEG pipeline for developmental hyperscanning studies

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    Cutting-edge hyperscanning methods led to a paradigm shift in social neuroscience. It allowed researchers to measure dynamic mutual alignment of neural processes between two or more individuals in naturalistic contexts. The ever-growing interest in hyperscanning research calls for the development of transparent and validated data analysis methods to further advance the field. We have developed and tested a dual electroencephalography (EEG) analysis pipeline, namely DEEP. Following the preprocessing of the data, DEEP allows users to calculate Phase Locking Values (PLVs) and cross-frequency PLVs as indices of inter-brain phase alignment of dyads as well as time-frequency responses and EEG power for each participant. The pipeline also includes scripts to control for spurious correlations. Our goal is to contribute to open and reproducible science practices by making DEEP publicly available together with an example mother-infant EEG hyperscanning dataset

    Ultrafast dynamics in unaligned MWCNTs decorated with metal nanoparticles

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    The relaxation dynamics of unaligned multi-walled carbon nanotubes decorated with metallic nanoparticles have been studied by using transient optical measurements. The fast dynamics due to the short-lived free-charge carriers excited by the pump are not affected by the presence of nanoparticles. Conversely, a second long dynamics, absent in bare carbon nanotubes, appears only in the decorated samples. A combination of experiment and theory allows us to ascribe this long dynamics to relaxation channels involving electronic states localized at the tube-nanoparticle interface

    DEEP: A dual EEG pipeline for developmental hyperscanning studies

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    Cutting-edge hyperscanning methods led to a paradigm shift in social neuroscience. It allowed researchers to measure dynamic mutual alignment of neural processes between two or more individuals in naturalistic contexts. The ever-growing interest in hyperscanning research calls for the development of transparent and validated data analysis methods to further advance the field. We have developed and tested a dual electroencephalography (EEG) analysis pipeline, namely DEEP. Following the preprocessing of the data, DEEP allows users to calculate Phase Locking Values (PLVs) and cross-frequency PLVs as indices of inter-brain phase alignment of dyads as well as time-frequency responses and EEG power for each participant. The pipeline also includes scripts to control for spurious correlations. Our goal is to contribute to open and reproducible science practices by making DEEP publicly available together with an example mother-infant EEG hyperscanning dataset

    Exaggerated aggression and decreased anxiety in mice deficient in brain serotonin

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    Serotonin is a major neurotransmitter in the central nervous system (CNS). Dysregulation of serotonin transmission in the CNS is reported to be related to different psychiatric disorders in humans including depression, impulsive aggression and anxiety disorders. The most frequently prescribed antidepressants and anxiolytics target the serotonergic system. However, these drugs are not effective in 20–30% of cases. The causes of this failure as well as the molecular mechanisms involved in the origin of psychological disorders are poorly understood. Biosynthesis of serotonin in the CNS is initiated by tryptophan hydroxylase 2 (TPH2). In this study, we used Tph2-deficient (Tph2−/−) mice to evaluate the impact of serotonin depletion in the brain on mouse behavior. Tph2−/− mice exhibited increased depression-like behavior in the forced swim test but not in the tail suspension test. In addition, they showed decreased anxiety-like behavior in three different paradigms: elevated plus maze, marble burying and novelty-suppressed feeding tests. These phenotypes were accompanied by strong aggressiveness observed in the resident–intruder paradigm. Despite carrying only one copy of the gene, heterozygous Tph2+/− mice showed only 10% reduction in brain serotonin, which was not sufficient to modulate behavior in the tested paradigms. Our findings provide unequivocal evidence on the pivotal role of central serotonin in anxiety and aggression

    Kinetic models with randomly perturbed binary collisions

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    We introduce a class of Kac-like kinetic equations on the real line, with general random collisional rules, which include as particular cases models for wealth redistribution in an agent-based market or models for granular gases with a background heat bath. Conditions on these collisional rules which guarantee both the existence and uniqueness of equilibrium profiles and their main properties are found. We show that the characterization of these stationary solutions is of independent interest, since the same profiles are shown to be solutions of different evolution problems, both in the econophysics context and in the kinetic theory of rarefied gases

    The physical theory of noise in reactors and reactor-like systems

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/32152/1/0000206.pd
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