Tropical cyclone dataset for a high-resolution global nonhydrostatic atmospheric simulation.

This dataset is a time series of tropical cyclones simulated using the high-resolution Nonhydrostatic Icosahedral Atmospheric Model (NICAM). By tracking tropical cyclones from 30 years of simulation data, 2,463 tracks that include the life stages of precursors (pre-TCs), tropical cyclones (TCs), and post-tropical cyclones (post-TCs), if any, were extracted. Each track data includes the time, latitude, longitude, maximum wind speed, minimum pressure, elapsed time since onset, and life-stage label of the tropical cyclone.

Molecular characteristics of an adhesion molecule containing cholesterol-dependent cytolysin-motif produced by mitis group streptococci.

Streptococcus pseudopneumoniae (SPpn) is a relatively new species closely related to S. pneumoniae (SPn) and S. mitis (SM) belonging to the Mitis group of the genus Streptococcus (MGS).

Projected Future Changes in Tropical Cyclones Using the CMIP6 HighResMIP Multimodel Ensemble.

Future changes in tropical cyclone properties are an important component of climate change impacts and risk for many tropical and midlatitude countries. In this study we assess the performance of a multimodel ensemble of climate models, at resolutions ranging from 250 to 25 km. We use a common experimental design including both atmosphere-only and coupled simulations run over the period 1950-2050, with two tracking algorithms applied uniformly across the models.

Cytotoxic property of Streptococcus mitis strain producing two different types of cholesterol-dependent cytolysins.

Streptococcus mitis strain Nm-65 secretes an atypical 5-domain-type cholesterol-dependent cytolysin (CDC) called S. mitis-derived human platelet aggregation factor (Sm-hPAF) originally described as a platelet aggregation factor. Sm-hPAF belongs to Group III CDC that recognize both membrane cholesterol and human CD59 as the receptors, and shows preferential activity towards human cells.

Madden-Julian Oscillation prediction skill of a new-generation global model demonstrated using a supercomputer.

Global cloud/cloud system-resolving models are perceived to perform well in the prediction of the Madden-Julian Oscillation (MJO), a huge eastward -propagating atmospheric pulse that dominates intraseasonal variation of the tropics and affects the entire globe. However, owing to model complexity, detailed analysis is limited by computational power. Here we carry out a simulation series using a recently developed supercomputer, which enables the statistical evaluation of the MJO prediction skill of a costly new-generation model in a manner similar to operational forecast models.