Gonzalo and sandy

Greg Foss; Fuqing Zhang; Yonghui Weng; Erin Munsell; Anne Bowen; Dave Semeraro; Arnav Kaul; Nick Sehy

doi:10.1145/3093338.3104162

Gonzalo and sandy

Greg Foss
, Fuqing Zhang
, Yonghui Weng
, Erin Munsell
, Anne Bowen
, Dave Semeraro
, Arnav Kaul
, Nick Sehy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This PEARC17 Visualization Showcase entry "Gonzalo and Sandy" is a video compilation of several short animations selected from the project, "Predictability and Data Assimilation of Severe Weather and Tropical Cyclones" supported by the Extreme Science and Engineering Discovery Environment via its Extended Collaborative Support Service (XSEDE ECSS). The animations visualize data based on Atlantic hurricanes Gonzalo, and Sandy the storm that devastated the United States East Coast, most notably the New Jersey shore.

Original language	English (US)
Title of host publication	PEARC 2017 - Practice and Experience in Advanced Research Computing 2017
Subtitle of host publication	Sustainability, Success and Impact
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450352727
DOIs	https://doi.org/10.1145/3093338.3104162
State	Published - Jul 9 2017
Event	2017 Practice and Experience in Advanced Research Computing, PEARC 2017 - New Orleans, United States Duration: Jul 9 2017 → Jul 13 2017

Publication series

Name	ACM International Conference Proceeding Series
Volume	Part F128771

Other

Other	2017 Practice and Experience in Advanced Research Computing, PEARC 2017
Country/Territory	United States
City	New Orleans
Period	7/9/17 → 7/13/17

All Science Journal Classification (ASJC) codes

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

Access to Document

10.1145/3093338.3104162

Cite this

Foss, G., Zhang, F., Weng, Y., Munsell, E., Bowen, A., Semeraro, D., Kaul, A., & Sehy, N. (2017). Gonzalo and sandy. In PEARC 2017 - Practice and Experience in Advanced Research Computing 2017: Sustainability, Success and Impact Article a74 (ACM International Conference Proceeding Series; Vol. Part F128771). Association for Computing Machinery. https://doi.org/10.1145/3093338.3104162

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title = "Gonzalo and sandy",

abstract = "This PEARC17 Visualization Showcase entry {"}Gonzalo and Sandy{"} is a video compilation of several short animations selected from the project, {"}Predictability and Data Assimilation of Severe Weather and Tropical Cyclones{"} supported by the Extreme Science and Engineering Discovery Environment via its Extended Collaborative Support Service (XSEDE ECSS). The animations visualize data based on Atlantic hurricanes Gonzalo, and Sandy the storm that devastated the United States East Coast, most notably the New Jersey shore.",

author = "Greg Foss and Fuqing Zhang and Yonghui Weng and Erin Munsell and Anne Bowen and Dave Semeraro and Arnav Kaul and Nick Sehy",

note = "Publisher Copyright: {\textcopyright} 2017 Copyright held by the owner/author(s).; 2017 Practice and Experience in Advanced Research Computing, PEARC 2017 ; Conference date: 09-07-2017 Through 13-07-2017",

year = "2017",

month = jul,

day = "9",

doi = "10.1145/3093338.3104162",

language = "English (US)",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

booktitle = "PEARC 2017 - Practice and Experience in Advanced Research Computing 2017",

}

Foss, G, Zhang, F, Weng, Y, Munsell, E, Bowen, A, Semeraro, D, Kaul, A & Sehy, N 2017, Gonzalo and sandy. in PEARC 2017 - Practice and Experience in Advanced Research Computing 2017: Sustainability, Success and Impact., a74, ACM International Conference Proceeding Series, vol. Part F128771, Association for Computing Machinery, 2017 Practice and Experience in Advanced Research Computing, PEARC 2017, New Orleans, United States, 7/9/17. https://doi.org/10.1145/3093338.3104162

Gonzalo and sandy. / Foss, Greg; Zhang, Fuqing; Weng, Yonghui et al.
PEARC 2017 - Practice and Experience in Advanced Research Computing 2017: Sustainability, Success and Impact. Association for Computing Machinery, 2017. a74 (ACM International Conference Proceeding Series; Vol. Part F128771).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Gonzalo and sandy

AU - Foss, Greg

AU - Zhang, Fuqing

AU - Weng, Yonghui

AU - Munsell, Erin

AU - Bowen, Anne

AU - Semeraro, Dave

AU - Kaul, Arnav

AU - Sehy, Nick

PY - 2017/7/9

Y1 - 2017/7/9

N2 - This PEARC17 Visualization Showcase entry "Gonzalo and Sandy" is a video compilation of several short animations selected from the project, "Predictability and Data Assimilation of Severe Weather and Tropical Cyclones" supported by the Extreme Science and Engineering Discovery Environment via its Extended Collaborative Support Service (XSEDE ECSS). The animations visualize data based on Atlantic hurricanes Gonzalo, and Sandy the storm that devastated the United States East Coast, most notably the New Jersey shore.

AB - This PEARC17 Visualization Showcase entry "Gonzalo and Sandy" is a video compilation of several short animations selected from the project, "Predictability and Data Assimilation of Severe Weather and Tropical Cyclones" supported by the Extreme Science and Engineering Discovery Environment via its Extended Collaborative Support Service (XSEDE ECSS). The animations visualize data based on Atlantic hurricanes Gonzalo, and Sandy the storm that devastated the United States East Coast, most notably the New Jersey shore.

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UR - https://www.scopus.com/pages/publications/85025803520#tab=citedBy

U2 - 10.1145/3093338.3104162

DO - 10.1145/3093338.3104162

M3 - Conference contribution

AN - SCOPUS:85025803520

T3 - ACM International Conference Proceeding Series

BT - PEARC 2017 - Practice and Experience in Advanced Research Computing 2017

PB - Association for Computing Machinery

T2 - 2017 Practice and Experience in Advanced Research Computing, PEARC 2017

Y2 - 9 July 2017 through 13 July 2017

ER -

Gonzalo and sandy

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

Access to Document

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