ALBERT

Description: Arctic low level clouds are considered to play a significant role in the Arctic climate system. In this study, we examined a temperature dependence of precipitating ice particle number concentrations of Arctic mixed-phase clouds observed by continuous ground-based in situ measurements. Precipitating particles were measured using an optical disdrometer (MPS, DMT Inc.) at Mt. Zeppelin Observatory in Ny-Alesund (78.9N, 11.9E), Svalbard between years of 2016 and 2020. Based on ground-based cloud radar and lidar observations, we selected a single layer mixed-phase cloud whose cloud-top height was less than 2.5 km. For the ice nucleating particles number concentration (N〈sub〉INP〈/sub〉), we adopted typical number concentrations observed at Mt. Zeppelin. Because N〈sub〉INP〈/sub〉 depends on temperature, we used the value corresponding to the cloud-top temperature. As a result, number concentration fluxes of precipitation particles (F〈sub〉ice〈/sub〉) tended to increase with decreasing temperature below approximately -15°C and they agreed with F〈sub〉INP〈/sub〉 within one order of magnitude. On the other hand, at temperatures above -10°C, F〈sub〉ice〈/sub〉 was several orders of magnitude higher than F〈sub〉INP. 〈/sub〉In this paper, we discuss possible reasons for these temperature dependences of F〈sub〉ice.〈/sub〉

Description: Recently, continuous or periodic multivariate geophysical/geochemical monitoring at active volcanoes has become increasingly common worldwide. While it facilitates a comprehensive understanding of volcanic processes, day-to-day fluctuations in multiple data during a non-eruptive stage sometimes complicate distinguishing between unrest and background activity. Furthermore, different datasets often appear to contradict each other. Here, we face a challenge in quantitatively assessing unrest events based on multiple data of various kinds. This study has piloted the application of the volcanic unrest index (VUI) proposed by Potter et al. (2015) to one of the selected Japanese volcanoes on a research basis. First, we modified their template of the VUI worksheet in New Zealand to fit Mt Tokachidake in northern Japan. Then, we applied it to the monitoring records since 1964 to calculate the monthly index. Here, we introduced four categories: seismology, geodesy, geothermics, and geochemistry, with some specific entries for each. Parameter ranges were set to evaluate each time series based on a five-point scale from 0 to 4. The VUI is an integrated evaluation method for diverse data, developed as a communication tool with non-scientists and not for prediction purposes (Potter et al. 2015). One of the advantages of the VUI is its capability to assess the severity of a particular unrest event in an intuitive and transferrable way, i.e., how rare it is among all records at that volcano. Although we may need further tuning, our first trial looks reasonable, as the only magmatic eruptive event in 1989-90 follows the prolonged period of elevated VUIs.