Analysis of the effect of initial conditions on the initial development of a turbulent jet

The effect of the initial condition at the jet exit on the downstream evolution, particularly within the potential core length, were numerically investigated as well as with available experimental data. In order to select the most dependable computational model for the present numerical experiment, a comparative study has been performed with different turbulence models at k-epsilon level, and it was found that the k-epsilon-gammma model yields superior prediction accuracy over other conventional models. The calculated results show that the potential core length and the spreading rate the initial mixing layer are dependent on the initial length scale as well as the turbulent kinetic energy at the jet exit. Such effect of the initial length scale increases with higher initial turbulence level. An empirical parameter has been devised to collapse the calculated data of the potential core length and the spreading rate with various initial conditions onto a single curve

Slow and soft passage through tipping point of the Atlantic Meridional Overturning Circulation in a changing climate

Paleo-proxy records suggest that the Atlantic Meridional Overturning Circulation (AMOC) exhibits a threshold for an abrupt change, a so-called tipping point. A classical bifurcation theory, a basis of the tipping dynamics of AMOC implicitly assumes that the tipping point is fixed. However, when a system is subjected to time-varying forcing (e.g., AMOC exposed to ice meltwater) an actual tipping point can be overshot due to delayed tipping, referred to as the slow passage effect. Here, using an Earth system model of intermediate complexity and a low-order model with freshwater forcing, we show that the tipping point of AMOC is largely delayed by the slow passage effect. It causes a large tipping lag of up to 1300 years, and strongly relaxes the abruptness of tipping as well. We further demonstrate that the tipping modulation can actively occur in past, present, and future climates by quantifying the effect during Dansgaard-Oeschger events, meltwater pulse 1A (MWP-1A), and current Greenland ice sheet melting. The suggested slow passage effect may explain the observed lagged AMOC collapse to MWP-1A of about 1000 years and provides implications tipping risk in the future

Frequent Occurrence of Mitochondrial DNA Mutations in Barrett’s Metaplasia without the Presence of Dysplasia

BACKGROUND: Barrett's esophagus (BE) is one of the most common premalignant lesions and can progress to esophageal adenocarcinoma (EA). The numerous molecular events may play a role in the neoplastic transformation of Barrett's mucosa such as the change of DNA ploidy, p53 mutation and alteration of adhesion molecules. However, the molecular mechanism of the progression of BE to EA remains unclear and most studies of mitochondrial DNA (mtDNA) mutations in BE have performed on BE with the presence of dysplasia. METHODS/FINDINGS: Thus, the current study is to investigate new molecular events (Barrett's esophageal tissue-specific-mtDNA alterations/instabilities) in mitochondrial genome and causative factors for their alterations using the corresponding adjacent normal mucosal tissue (NT) and tissue (BT) from 34 patients having Barrett's metaplasia without the presence of dysplasia. Eighteen patients (53%) exhibited mtDNA mutations which were not found in adjacent NT. mtDNA copy number was about 3 times higher in BT than in adjacent NT. The activity of the mitochondrial respiratory chain enzyme complexes in tissues from Barrett's metaplasia without the presence of dysplasia was impaired. Reactive oxygen species (ROS) level in BT was significantly higher than those in corresponding samples. CONCLUSION/SIGNIFICANCE: High ROS level in BT may contribute to the development of mtDNA mutations, which may play a crucial role in disease progression and tumorigenesis in BE

Argonne National Laboratory Reports

Cross sections for inelastic collisions of slow electrons and the dipole oscillator-strength distribution for the neon atom are given in tabular form. The results are based on experimental data that were checked and adjusted for internal consistency

Fokker–Planck dynamics of the El Niño-Southern Oscillation

© 2020, The Author(s). The asymmetric nature of the El Niño-Southern Oscillation (ENSO) is explored by using a probabilistic model (PROM) for ENSO. Based on a Fokker–Planck Equation (FPE), PROM describes the dynamics of a nonlinear stochastic ENSO recharge oscillator model for eastern equatorial Pacific temperature anomalies and equatorial Pacific basin-averaged thermocline depth changes. Eigen analyses of PROM provide new insights into the stationary and oscillatory solutions of the stochastic dynamical system. The first probabilistic eigenmode represents a stationary mode, which exhibits the asymmetric features of ENSO, in case deterministic nonlinearities or multiplicative noises are included. The second mode is linked to the oscillatory nature of ENSO and represents a cyclic asymmetric probability distribution, which emerges from the key dynamical processes. Other eigenmodes are associated with the temporal evolution of higher order statistical moments of the ENSO system. The model solutions demonstrate that the deterministic nonlinearity plays a stronger role in establishing the observed asymmetry of ENSO as compared to the multiplicative stochastic part.11Nsciescopu

Understanding climate changes in East Asia and Europe based on spatial climate analogs

Spatial climate analogs effectively illustrate how a location’s climate may become more similar to that of other locations from the historical period to future projections. Also, novel climates (emerging climate conditions significantly different from the past) have been analyzed as they may result in significant and unprecedented ecological and socioeconomic impacts. This study analyzes historical to future spatial climate analogs across East Asia and Europe, in the context of climatic impacts on ecology and human health, respectively. Firstly, the results of climate analogs analysis for ecological impacts indicate that major cities in East Asia and Europe have generally experienced novel climates and climate shifts originating from southern/warmer regions from the early 20th century to the current period, primarily attributed to extensive warming. In future projections, individual cities are not expected to experience additional significant climate change under a 1.5 °C global warming (warming relative to pre-industrial period), compared to the contemporary climate. In contrast, robust local climate change and climate shifts from southern/warmer regions are expected at 2.0 °C and 3.0 °C global warming levels. Specially, under the 3.0 °C global warming, unprecedented (newly emerging) climate analogs are expected to appear in a few major cities. The climate analog of future projections partially align with growing season length projections, demonstrating important implications on ecosystems. Human health-relevant climate analogs exhibit qualitatively similar results from the historical period to future projections, suggesting an increasing risk of climate-driven impacts on human health. However, distinctions emerge in the specifics of the climate analogs analysis results concerning ecology and human health, emphasizing the importance of considering appropriate climate variables corresponding to the impacts of climate change. Our results of climate analogs present extensive information of climate change signals and spatiotemporal trajectories, which provide important indicators for developing appropriate adaptaion plans as the planet warms

A low-order dynamical model for fire-vegetation-climate interactions

Climate conditions play a key role in determining the occurrence and severity of wildfires. Despite the impacts of wildfires on ecosystems, human livelihoods, and air quality, little is known conceptually about how natural or anthropogenic shifts in climate may influence the fire activity on a regional or global scale. Here, we introduce a new low order dynamical model that describes the nonlinear interactions between climate, vegetation (fire fuel) and fire probabilities. This 1-dimensional model describes the influence of precipitation and temperature on burned area and fuel availability. Estimating key parameters from observations, the model successfully reproduces the spatio-temporal variability of wildfire occurrences, particularly, in semi-arid regions in Africa, South America, and northern Australia. The fidelity of the model translates into a high degree of longer-term predictability of fire conditions in these vulnerable regions. Our new low-order modeling framework may provide guidance to forestry managers to assess fire risks under present and future climate conditions.11Nsciescopu