The impact of COVID-19 lockdown measures on the Indian summer monsoon

Aerosol concentrations over Asia play a key role in modulating the Indian summer monsoon (ISM) rainfall. Lockdown measures imposed to prevent the spread of the COVID-19 pandemic led to substantial reductions in observed Asian aerosol loadings. Here, we use bottom-up estimates of anthropogenic emissions based on national mobility data from Google and Apple, along with simulations from the ECHAM6-HAMMOZ state-of-the-art aerosol-chemistry-climate model to investigate the impact of the reduced aerosol and gases pollution loadings on the ISM. We show that the decrease in anthropogenic emissions led to a 4 W m−2 increase in surface solar radiation over parts of South Asia, which resulted in a strengthening of the ISM. Simultaneously, while natural emission parameterizations are kept the same in all our simulations, the anthropogenic emission reduction led to changes in the atmospheric circulation, causing accumulation of dust over the Tibetan plateau (TP) during the pre-monsoon and monsoon seasons. This accumulated dust has intensified the warm core over the TP that reinforced the intensification of the Hadley circulation. The associated cross-equatorial moisture influx over the Indian landmass led to an enhanced amount of rainfall by 4% (0.2 mm d−1) over the Indian landmass and 5%–15% (0.8–3 mm d−1) over central India. These estimates may vary under the influence of large-scale coupled atmosphere–ocean oscillations (e.g. El Nino Southern Oscillation, Indian Ocean Dipole). Our study indicates that the reduced anthropogenic emissions caused by the unprecedented COVID-19 restrictions had a favourable effect on the hydrological cycle over South Asia, which has been facing water scarcity during the past decades. This emphasizes the need for stringent measures to limit future anthropogenic emissions in South Asia for protecting one of the world's most densely populated regions

Testing the assumptions of linear prediction analysis in normal vowels

This paper develops an improved surrogate data test to show experimental evidence, for all the simple vowels of US English, for both male and female speakers, that Gaussian linear prediction analysis, a ubiquitous technique in current speech technologies, cannot be used to extract all the dynamical structure of real speech time series. The test provides robust evidence undermining the validity of these linear techniques, supporting the assumptions of either dynamical nonlinearity and/or non-Gaussianity common to more recent, complex, efforts at dynamical modelling speech time series. However, an additional finding is that the classical assumptions cannot be ruled out entirely, and plausible evidence is given to explain the success of the linear Gaussian theory as a weak approximation to the true, nonlinear/non-Gaussian dynamics. This supports the use of appropriate hybrid linear/nonlinear/non-Gaussian modelling. With a calibrated calculation of statistic and particular choice of experimental protocol, some of the known systematic problems of the method of surrogate data testing are circumvented to obtain results to support the conclusions to a high level of significance

Relaxation oscillations and negative strain rate sensitivity in the Portevin - Le Chatelier effect

A characteristic feature of the Portevin - Le Chatelier effect or the jerky flow is the stick-slip nature of stress-strain curves which is believed to result from the negative strain rate dependence of the flow stress. The latter is assumed to result from the competition of a few relevant time scales controlling the dynamics of jerky flow. We address the issue of time scales and its connection to the negative strain rate sensitivity of the flow stress within the framework of a model for the jerky flow which is known to reproduce several experimentally observed features including the negative strain rate sensitivity of the flow stress. We attempt to understand the above issues by analyzing the geometry of the slow manifold underlying the relaxational oscillations in the model. We show that the nature of the relaxational oscillations is a result of the atypical bent geometry of the slow manifold. The analysis of the slow manifold structure helps us to understand the time scales operating in different regions of the slow manifold. Using this information we are able to establish connection with the strain rate sensitivity of the flow stress. The analysis also helps us to provide a proper dynamical interpretation for the negative branch of the strain rate sensitivity.Comment: 7 figures, To appear in Phys. Rev.

High order amplitude equation for steps on creep curve

We consider a model proposed by one of the authors for a type of plastic instability found in creep experiments which reproduces a number of experimentally observed features. The model consists of three coupled non-linear differential equations describing the evolution of three types of dislocations. The transition to the instability has been shown to be via Hopf bifurcation leading to limit cycle solutions with respect to physically relevant drive parameters. Here we use reductive perturbative method to extract an amplitude equation of up to seventh order to obtain an approximate analytic expression for the order parameter. The analysis also enables us to obtain the bifurcation (phase) diagram of the instability. We find that while supercritical bifurcation dominates the major part of the instability region, subcritical bifurcation gradually takes over at one end of the region. These results are compared with the known experimental results. Approximate analytic expressions for the limit cycles for different types of bifurcations are shown to agree with their corresponding numerical solutions of the equations describing the model. The analysis also shows that high order nonlinearities are important in the problem. This approach further allows us to map the theoretical parameters to the experimentally observed macroscopic quantities.Comment: LaTex file and eps figures; Communicated to Phys. Rev.

Sex differences in stress-induced sleep deficits

Sleep disruptions are hallmarks in the pathophysiology of several stress-related disorders, including Major Depressive Disorder (MDD) and Post-Traumatic Stress Disorder (PTSD), both known to disproportionately affect female populations. Although previous studies have attempted to investigate disordered sleep in women, few studies have explored and compared how repeated stress affects sleep in both sexes in either human or animal models. We have previously shown that male rats exhibit behavioral and neuroendocrine habituation to 5 days of repeated restraint, whereas females do not; additional days of stress exposure are required to observe habituation in females. This study examined sex differences in sleep measures prior to, during, and after repeated restraint stress in adult male and female rats. Our data reveal that repeated stress increased time spent awake and decreased slow-wave sleep (SWS) and REM sleep (REMS) in females, and these effects persisted over 2 days of recovery. In contrast, the effects of stress on males were transient. These insomnia-like symptoms were accompanied by a greater number of exaggerated motor responses to waking from REMS in females, a phenotype similar to trauma-related nightmares. In sum, these data demonstrate that repeated stress produces disruptions in sleep that persist days after the stress is terminated in female rats. These disruptions in sleep produced by 5 days of repeated restraint may be due to their lack of habituation

A dynamical approach to the spatiotemporal aspects of the Portevin-Le Chatelier effect: Chaos,turbulence and band propagation

Experimental time series obtained from single and poly-crystals subjected to a constant strain rate tests report an intriguing dynamical crossover from a low dimensional chaotic state at medium strain rates to an infinite dimensional power law state of stress drops at high strain rates. We present results of an extensive study of all aspects of the PLC effect within the context a model that reproduces this crossover. A study of the distribution of the Lyapunov exponents as a function of strain rate shows that it changes from a small set of positive exponents in the chaotic regime to a dense set of null exponents in the scaling regime. As the latter feature is similar to the GOY shell model for turbulence, we compare our results with the GOY model. Interestingly, the null exponents in our model themselves obey a power law. The configuration of dislocations is visualized through the slow manifold analysis. This shows that while a large proportion of dislocations are in the pinned state in the chaotic regime, most of them are at the threshold of unpinning in the scaling regime. The model qualitatively reproduces the different types of deformation bands seen in experiments. At high strain rates where propagating bands are seen, the model equations are reduced to the Fisher-Kolmogorov equation for propagative fronts. This shows that the velocity of the bands varies linearly with the strain rate and inversely with the dislocation density, consistent with the known experimental results. Thus, this simple dynamical model captures the complex spatio-temporal features of the PLC effect.Comment: 17 pages, 18 figure

Multifractal burst in the spatio-temporal dynamics of jerky flow

The collective behavior of dislocations in jerky flow is studied in Al-Mg polycrystalline samples subjected to constant strain rate tests. Complementary dynamical, statistical and multifractal analyses are carried out on the stress-time series recorded during jerky flow to characterize the distinct spatio-temporal dynamical regimes. It is shown that the hopping type B and the propagating type A bands correspond to chaotic and self-organized critical states respectively. The crossover between these types of bands is identified by a large spread in the multifractal spectrum. These results are interpreted on the basis of competing scales and mechanisms.Comment: 4 pages, 6 figures To be published in Phys. Rev. Lett. (2001

Chaos or Noise - Difficulties of a Distinction

In experiments, the dynamical behavior of systems is reflected in time series. Due to the finiteness of the observational data set it is not possible to reconstruct the invariant measure up to arbitrary fine resolution and arbitrary high embedding dimension. These restrictions limit our ability to distinguish between signals generated by different systems, such as regular, chaotic or stochastic ones, when analyzed from a time series point of view. We propose to classify the signal behavior, without referring to any specific model, as stochastic or deterministic on a certain scale of the resolution $\epsilon$, according to the dependence of the $(\epsilon,\tau)$-entropy, $h(\epsilon, \tau)$, and of the finite size Lyapunov exponent, $\lambda(\epsilon)$, on $\epsilon$.Comment: 24 pages RevTeX, 9 eps figures included, two references added, minor corrections, one section has been split in two (submitted to PRE

Sub-Banded Reconstructed Phase Spaces for Speech Recognition

A novel method combining filter banks and reconstructed phase spaces is proposed for the modeling and classification of speech. Reconstructed phase spaces, which are based on dynamical systems theory, have advantages over spectral-based analysis methods in that they can capture nonlinear or higher-order statistics. Recent work has shown that the natural measure of a reconstructed phase space can be used for modeling and classification of phonemes. In this work, sub-banding of speech, which has been examined for recognition of noise-corrupted speech, is studied in combination with phase space reconstruction. This sub-banding, which is motivated by empirical psychoacoustical studies, is shown to dramatically improve the phoneme classification accuracy of reconstructed phase space-based approaches. Experiments that examine the performance of fused sub-banded reconstructed phase spaces for phoneme classification are presented. Comparisons against a cepstral-based classifier show that the proposed approach is competitive with state-of-the-art methods for modeling and classification of phonemes. Combination of cepstral-based features and the sub-band RPS features shows improvement over a cepstral-only baseline

Air pollution reductions caused by the COVID-19 lockdown open up a way to preserve the Himalayan glaciers

The rapid melting of glaciers in the Hindu Kush Himalayas (HKH) during recent decades poses an alarming threat to water security for larger parts of Asia. If this melting persists, the entirety of the Himalayan glaciers are estimated to disappear by end of the 21st century. Here, we assess the influence of the spring 2020 COVID-19 lockdown on the HKH, demonstrating the potential benefits of a strict emission reduction roadmap. Chemistry–climate model simulations, supported by satellite and ground measurements, show that lower levels of gas and aerosol pollution during lockdown led to changes in meteorology and to a reduction in black carbon in snow (2 %–14 %) and thus a reduction in snowmelt (10 %–40 %). This caused increases in snow cover (6 %–12 %) and mass (2 %–20 %) and a decrease in runoff (5 %–55 %) over the HKH and Tibetan Plateau, ultimately leading to an enhanced snow-equivalent water (2 %–55 %). We emphasize the necessity for immediate anthropogenic pollution reductions to address the hydro-climatic threat to billions of people in southern Asia.</p