Data that effectively demonstrate the benefits of a 3D CAPPI algorithm
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Updated: Jan 22, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Published on: December 10, 2012
Yura Kim1,2, Masayuki Maki1, Dong-In Lee2
1Research and Education Center for Natural Hazards, Kagoshima University, Japan.
Abstract:
The data presented in this article are related to the research article entitled "Three-dimensional analysis of the initial stage of convective precipitation using an operational X-band polarimetric radar network" [1]. The data presented were obtained using a three-dimensional constant-altitude plan-position-indicator (3D CAPPI), which was generated by a new method proposed by [1]. The data used to create the 3D CAPPI were derived from two X-band polarimetric radar installations in the Kanto region of Japan, Ebina (139.39°E, 35.40°N), and Shin-yokohama (139.60°E, 35.51°N). These data are superior to operational radar data in terms of their temporal and spatial resolution. These high resolution data can indicate a rapidly developing storm, such as localized precipitation. It is particularly important to understand the early stages of storms in terms of numerical and short-term models. These data show the time of appearance, life cycle, and evolution of each cell that constitutes a storm in three-dimensional detail.
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