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Chaotic dynamical systems are sensitive to the initial conditions, which are crucial for climate forecast. These properties are often used to inform the design of data assimilation (DA), a method used to estimate the exact initial condition. However, obtaining the instability properties are burdensome for complex problems both numerically and analytically. Here, we suggest a different viewpoint. We show that the skill of DA can be used to infer the instability properties of a dynamical system.

The weather is chaotic and hard to predict, but the chaos implies an effective control where a small control signal grows rapidly to make a big difference. This study proposes the Control Simulation Experiment where we apply a small signal to control “the nature” in a computational simulation. Idealized experiments with a low-order chaotic system show successful results by small control signals of only 3 % of the observation error. This is the first step toward the realistic weather simulations.

In this research, the South Atlantic Anomaly (SAA), the middle latitude and the high latitude region is analyzed. The method apply is using power spectrum analysis method and 4 active period (Period during occurrence of geomagnetic storm) and 4 normal period (Period during no occurrence of geomagnetic storm) is examine. The result indicate SAA region tend to be persistent during both period in comparison to other region in this research. The SAA region may be influence by the ring current.

Glacial isostatic adjustment is the delayed reaction of the Earth's lithosphere and mantle to changing mass load of ice sheets or water. The deformation behavior of the Earth's surface depends on the ability of the Earth's mantle to flow, i.e. its viscosity. It can be estimated from sea level observations. In our study we simulate using sea level observations from the past to estimate mantle viscosity. That knowledge is essential for understanding current sea level changes due to melting ice.

When the internal solitary wave propagates to the continental shelf and slope, the polarity reverses due to the shallower water depth. In this process, the internal solitary wave dissipates energy and enhances diapycnal mixing, thus affecting the local oceanic environment. In this study, we used reflection seismic data to evaluate the spatial distribution of the diapycnal mixing around the polarity-reversing internal solitary waves.