Increasing model vertical resolution may not necessarily lead to improved atmospheric predictability.

The widely accepted existence of an inherent limit of atmospheric predictability is usually attributed to weather's sensitive dependence on initial conditions. This signature feature of chaos was first discovered in the Lorenz system, initially derived as a simplified model of thermal convection. In a recent study of a high-dimensional generalization of the Lorenz system, it was reported that the predictability of its chaotic solutions exhibits a non-monotonic dimensional dependence. Since raising the dimension of the Lorenz system is analogous to refining the model vertical resolution when viewed as a thermal convection model, it is questioned whether this non-monotonicity is also found in numerical weather prediction models. Predictability in the sense of sensitive dependence on initial conditions can be measured based on deviation time, that is, the time of threshold-exceeding deviations between the solutions with minute differences in initial conditions. Through ensemble experiments involving both the high-dimensional generalizations of the Lorenz system and real-case simulations by a numerical weather prediction model, this study demonstrates that predictability can depend non-monotonically on model vertical resolution. Further analysis shows that the spatial distribution of deviation time strongly contributes to this non-monotonicity. It is suggested that chaos, or sensitive dependence on initial conditions, leads to non-monotonic dependence on model vertical resolution of deviation time and, by extension, atmospheric predictability.

Exploring Risk and Protective Factors for Cyberbullying and Their Interplay: Evidence from a Sample of South Korean College Students.

This study explored risk and protective factors for cyberbullying perpetration and examined whether they independently and interactively predicted cyberbullying perpetration. Based on key propositions of micro-level theories of crime and delinquency, we adopted two risk factors, cyberbullying victimization and association with cyberbullying peers, and two protective factors, morality and self-control. Using a sample of South Korean college students (N = 244; 112 women (45.9%), 132 men (54.1%); Mean (age) = 22), we found that the two risk factors were positively associated with cyberbullying perpetration, while only one of the two protective factors, which is morality, had a negative relationship with cyberbullying perpetration. In addition, the two protective factors partially buffered the effects of both risk factors on cyberbullying perpetration. The implications and limitations of these findings were also discussed.

Existence of multiple scales in uncertainty of numerical weather prediction.

Numerical weather prediction provides essential information of societal influence. Advances in the initial condition estimation have led to the improvement of the prediction skill. The process to produce the better initial condition (analysis) with the combination of short-range forecast and observation over the globe requires information about uncertainty of the forecast results to decide how much observation is reflected to the analysis and how far the observation information should be propagated. Forecast ensemble represents the error of the short-range forecast at the instance. The influence of observation propagating along with forecast ensemble correlation needs to be restricted by localized correlation function because of less reliability of sample correlation. So far, solitary radius of influence is usually used since there has not been an understanding about the realism of multiple scales in the forecast uncertainty. In this study, it is explicitly shown that multiple scales exist in short-range forecast error and any single-scale localization approach could not resolve this situation. A combination of Gaussian correlation functions of various scales is designed, which more weighs observation itself near the data point and makes ensemble perturbation, far from the observation position, more participate in decision of the analysis. Its outstanding performance supports the existence of multi-scale correlation in forecast uncertainty.

The Dynamics of Intra-Family Relationships During Incarceration and the Implications for Children of Incarcerated Parents.

The current study examines effects of changes in intra-family relationships after parental incarceration on internalizing behaviors of the children of incarcerated parents. Using data from a sample of 249 incarcerated parents with minor children in South Korea, the present study found that perceived degradation of family relationships among inmate parents, their non-incarcerated spouses, and children was a significant risk factor of internalizing behaviors of children of incarcerated parents. The current study also found that inmate parents who had more frequent family contact were more likely to perceive improvements of all forms of intra-family relationships during incarceration. The implications of these findings are discussed.