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Journal Articles

Image-based view selection for shape comparison of mode water regions in virtual reality spaces

Yano, Midori; Ito, Takayuki*; Tanaka, Yusuke*; Matsuoka, Daisuke*; Araki, Fumiaki*; Czauderna, T.*; Stephens, K.*

Proceedings of Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo 2020 (SNA + MC 2020), p.201 - 208, 2020/10

Visual analysis plays an important role in understanding and evaluating the climate models, their variables, and their outputs because complex processes are required for the tuning of the climate models. Virtual Reality (VR) technologies are effective for 3D visualization and have been recently employed for visual analysis of more various scientific data. However, researchers may have some problematic situations while using VR space depending on user operations and target geometries. Here, we propose an image-based view selection method to solve these situations and understand differences in ocean states between simulations and observations based on shapes of mode water regions. This view selection takes evaluation criteria for shape comparison of mode water regions generated from simulations and observations into account. This paper introduces two example cases applying this view selection and discusses on a degree of shape matching of mode water regions of each case.

Oral presentation

FACE-N project; Free-Air CO$$_{2}$$ Enrichment study for paddy rice with a focus on its effect on nitrogen cycle

Hayashi, Kentaro*; Hasegawa, Toshihiro*; Tokida, Takeshi*; Ono, Keisuke*; Matsuda, Kazuhide*; Toyoda, Sakae*; Yano, Midori*; Sudo, Shigeto*; Wagai, Rota*; Matsushima, Miwa*; et al.

no journal, , 

National Institute for Agro-Environmental Sciences, Japan, established new Free-Air CO$$_{2}$$ Enrichment (FACE) facilities for paddy rice in central Japan (Tsukuba FACE) in April, 2010. Early FACE studies were originally designed to investigate changes in plant growth, crop yield, and carbon cycle under elevated CO$$_{2}$$ and temperature. In addition to these research agenda, a three-year project at Tsukuba FACE that assesses the changes in nitrogen cycle due to climate manipulation (FACE-N) started in April, 2010. The FACE-N project has the following themes: (1) atmosphere-paddy exchange of nitrogen; (2) nitrogen-related processes in a soil-rice system; and (3) development of the sophisticated nitrogen cycling model at a plot scale and of the regional nitrogen assessment system using remote-sensing technique and geographic information system (GIS).

Oral presentation

Tanpopo Working Group report; Space exposure of microbes and organic materials

Yokobori, Shinichi*; Kobayashi, Kensei*; Mita, Hajime*; Yabuta, Hikaru*; Nakagawa, Kazumichi*; Narumi, Issei; Hayashi, Nobuhiro*; Tomita, Kaori*; Kawaguchi, Yuko*; Shimizu, Yasuyuki*; et al.

no journal, , 

no abstracts in English

Oral presentation

VR system for observing the ferocity of typhoon on environment

Yang, A.*; Yano, Midori; Koyama, Tsubasa*; Ito, Takayuki*

no journal, , 

Visualization techniques are often used to understand observed and simulated weather data. Traditionally, two-dimensional visualization methods of scalar fields (temperature, pressure, etc.) and vector fields (wind direction) have been frequently used to visualize weather data. Meanwhile, three-dimensional visualization techniques are indispensable to understand three-dimensional mechanisms of meteorological phenomena. In this report, we propose a VR system to observe their three-dimensional structures of typhoons. This study aims to reproduce shapes and tracks of typhoons around Japan. This paper describes an overview of the system, and discusses knowledge about typhoons that can be potentially obtained by this system and merits of the system.

Oral presentation

In-situ ensemble visualization for analyzing pollutant dispersion

Yano, Midori; Kawamura, Takuma; Hasegawa, Yuta; Idomura, Yasuhiro

no journal, , 

Uncertainty quantification in numerical simulations is important for improving the reliability of simulation results. In-Situ visualization techniques that visualize simulations at runtime are available to evaluate large-scale, high-speed, and cutting-edge ensemble simulations using supercomputers. This study proposes an in-situ visualization method for ensemble simulations and applies it to analyze statistical properties in ensemble calculations of real-time plume dispersion analysis.

Oral presentation

In-Situ statistical analysis of plume dispersion simulations

Yano, Midori; Kawamura, Takuma; Hasegawa, Yuta; Idomura, Yasuhiro

no journal, , 

Visualizing a large amount of ensemble data and time series data generated from extreme scale simulations is difficult because of limitations on the performance of data I/O, data transfer, and visualization. In-Situ visualization techniques that visualize simulations at runtime are promising solutions for this problem. This study proposes an in-situ statistical analysis method, applies it to time-series data of a real-time plume dispersion simulation, and analyzes winds and concentration statistically using a scatter plot and glyph in a target 3D space. Users can map statistical data to glyph design and visualize statistical properties of the simulation interactively.

Oral presentation

In-Situ visualization for analyzing ensemble data of plume dispersion simulations

Yano, Midori; Kawamura, Takuma; Shimomura, Kazuya; Sugihara, Kenta; Idomura, Yasuhiro

no journal, , 

In the field of computational fluid dynamics (CFD), ensemble simulations, which are initialized including random initial errors, are important for evaluating uncertainties of the simulation results. Recently, many in-situ visualization techniques that visualize simulations at runtime have been developed because of limitations on the performance of data I/O, data transfer, and visualization for a large amount of ensemble data generated from extreme-scale CFD simulations. This study proposes an in-situ ensemble visualization, applies it to ensemble data of a real-time plume dispersion simulation, and analyzes pollutant concentrations statistically.

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