Substorms are a phenomenon in the magnetosphere–ionosphere system, which are characterised by brightening of an auroral arc and enhancement of electric currents in the polar ionosphere. Since substorms are difficult to predict, this study treats a substorm occurrence as a stochastic phenomenon and represents the substorm occurrence rate with a machine learning model. We then analyse the response of substorm activity to solar wind conditions by feeding synthetic solar wind data into the model.

The East Asian winter monsoon causes orographic snowfall over the windward side of the Japanese islands (facing the Sea of Japan and the northwesterly winter monsoon flow) and negative temperature anomalies around Japan. In this study, we reconstruct the outbreak of the winter monsoon around Japan for the winter from the 1840s to the early 1850s by using daily weather information recorded in old Japanese diaries and early daily instrumental temperature data.

The relationships between auroral activity and the solar-wind conditions are modeled with a machine-learning technique. The impact of various solar-wind parameters on the auroral activity is then evaluated by putting artificial inputs into the trained machine-learning model. One of the notable findings is that the solar-wind density effect on the auroral activity is emphasized under high solar-wind speed and weak solar-wind magnetic field.

This study assesses the applicability of the RPAS-based photogrammetric approach for a high-definition geomorphometry of hummocks, i.e., characteristic morphological features in the surface of debris avalanche deposits caused by a gigantic sector collapse of a volcanic mountain body. Satellite-based topographic data were also utilized to estimate the source volume of the sector collapse. We provide new, detailed insights into the characteristics of the debris avalanche and potential hazards.

Solar activity and climate show correlations over a wide range of timescales. It is important to understand the behavior of the 27-day solar rotational period in lightning activities because it provides an opportunity to understand how the sun influences weather and climate. We analyzed lightning data extracted from diaries written in Kyoto, Japan from the mid-17th to the mid-18th century. Lightning shows the signal of the 27-day period; however, it disappeared during the Maunder Minimum.