Abstract. Seasonal and diurnal variations in the direction of propagation of medium-scale travelling ionospheric disturbances (MSTIDs) have been investigated by analyzing sea echo returns detected by the TIGER SuperDARN radar located in Tasmania (43.4 • S, 147.2 • E geographic; −54.6 • ). A strong dependency on local time was found, as well as significant seasonal variations. Generally, the propagation direction has a northward (i.e. equatorward) component. In the early morning hours the direction of propagation is quite variable throughout the year. It then becomes predominantly northwest and changes to northeast around 09:00 LT. In late fall and winter it changes back to north/northwest around 15:00 LT. During the other seasons, northward propagation is very obvious near dawn and dusk, but no significant northward propagation is observed at noon.It is suggested that the variable propagation direction in the morning is related to irregular magnetic disturbances that occur at this local time. The changes in the MSTID propagation directions near dawn and dusk are generally consistent with changes in ionospheric electric fields occurring at these times and is consistent with dayside MSTIDs being generated by the Lorentz force.

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Pruning is one of the most important tree fruit production activities, which is highly dependent on human labor. Skilled labor is in short supply, and the increasing cost of labor is becoming a big issue for the tree fruit industry. Meanwhile, worker safety is another issue in the manual pruning. Growers are motivated to seek mechanical or robotic solutions for reducing the amount of hand labor required for pruning. Identifying tree branches/canopies with sensors as well as automated operating pruning activity are the important components in the automated pruning system. This paper reviews the research and development of sensing and automated systems for branch pruning in apple production. Tree training systems, pruning strategies, 3D structure reconstruction of tree branches, and practice mechanisms or robotics are some of the developments that need to be addressed for an effective tree branch pruning system. Our study summarizes the potential opportunities for automatic pruning with machine-friendly modern tree architectures, previous studies on sensor development, and efforts to develop and deploy mechanical/robotic systems for automated branch pruning. We also describe two examples of qualified pruning strategies that could potentially simplify the automated pruning decision and pruning end-effector design. Finally, the limitations of current pruning technologies and other challenges for automated branch pruning are described, and possible solutions are discussed.