Earthquakes have triggered numerous landslides, and much progress has been made in their study. But, so far, the dynamic behavior of slope disasters still lacks understanding, such as whether there is a definite energy and spacial distribution of earthquake-induced landslides or whether giant landslides and small landslides follow different formation mechanisms. In this study, we attempt to answer these questions from the point of view of the self-organized critical (SOC) theory.

Long-lived eddies are an important part of the ocean circulation. Here a dataset for studying eddies in the Gulf of Mexico is created through the analysis of trajectories of drifting instruments. The method involves the identification of quasi-periodic signals, characteristic of particles trapped in eddies, from the displacement records, followed by the creation of a measure of statistical significance. It is expected that this dataset will be of use to other authors studying this region.

We used regional climate networks (RCNs) to identify past heatwaves and droughts in Germany. RCNs provide information for whole areas and can provide many details of extreme events. The RCNs were constructed on the grid of the E-OBS data set. Time series correlation was used to construct the networks. Network metrics were compared to standard extreme indices and differed considerably between normal and extreme years. The results show that RCNs can identify severe and moderate extremes.

We propose an enhanced correlation identification (ECI) algorithm to attenuate background noise. The cross-correlation matching method is helpful for the extraction of useful components of the raw SSIP data and suppression of background noise. Experiments on both synthetic and real SSIP data show that the ECI algorithm is proposed to preserve the valid information of the raw SSIP data to display the actual location and shape of adjacent high-resistivity anomalies.

The MLE and ApEn values of the D_st indicate that chaotic and dynamical complexity responses are high during minor geomagnetic storms, reduce at moderate geomagnetic storms and decline further during major geomagnetic storms. However, the MLE and ApEn values obtained from solar wind electric field (VB_s) indicate that chaotic and dynamical complexity responses are high with no significant difference between the periods that are associated with minor, moderate and major geomagnetic storms.

Turbulent mixing in the ocean is mainly attributed to internal wave breaking, but the modulation of the mesoscale environment is unclear. The spatially inhomogeneous and seasonally variable diapycnal diffusivities in the upper Philippine Sea were estimated from Argo float data using a strain-based, fine-scale parameterization. Internal tides contributed significant diapycnal mixing here, with the mesoscale environment greatly regulating the intensity and spatial inhomogeneity of tidal mixing.

A homogenization of Navier–Stokes to wave scales allows us to determine that air bubbles suspended near the ocean surface modify the momentum equation, specifically enhancing the vorticity in the flow. A model was derived that relates the rain rate to the production of air bubbles near the ocean surface. At wave scales, the air bubbles enhance the wave dissipation for small gravity or capillary waves.