paint-brush
pyParaOcean, A System for Visual Analysis of Ocean Data: Acknowledgments and Referencesby@oceanography

pyParaOcean, A System for Visual Analysis of Ocean Data: Acknowledgments and References

Too Long; Didn't Read

In this paper, researchers introduce pyParaOcean, enhancing ocean data visualization in Paraview for dynamic process tracking and event detection.
featured image - pyParaOcean, A System for Visual Analysis of Ocean Data: Acknowledgments and References
Oceanography: Everything You Need to Study the Ocean HackerNoon profile picture

Authors:

(1) Toshit Jain, Indian Institute of Science Bangalore, India;

(2) Varun Singh, Indian Institute of Science Bangalore, India;

(3) Vijay Kumar Boda, Indian Institute of Science Bangalore, India;

(4) Upkar Singh, Indian Institute of Science Bangalore, India;

(5) Ingrid Hotz, Indian Institute of Science Bangalore, India and Department of Science and Technology (ITN), Linköping University, Norrköping, Sweden;

(6) P. N. Vinayachandran, Indian Institute of Science Bangalore, India;

(7) Vijay Natarajan, Indian Institute of Science Bangalore, India.

Acknowledgments

This research was funded by a grant from SERB, Govt. of India (CRG/2021/005278), partial support from National Supercomputing Mission, DST, the J. C. Bose Fellowship awarded by the SERB, DST, Govt. of India, the Dr. Ram Kumar IISc Distinguished Visiting Chair Professorship in EECS, and a scholarship from MoE, Govt. of India. Part of this work was carried out towards partial fulfilment of a thesis requirement at BITS Pilani.

References

[AGL05] AHRENS J., GEVECI B., LAW C.: Paraview: An end-user tool for large data visualization. The visualization handbook 717 (2005). 2 [AGT∗19] AFZAL S., GHANI S., TISSINGTON G., LANGODAN S.,


[AGT∗19] AFZAL S., GHANI S., TISSINGTON G., LANGODAN S.,DASARI H. P., RAITSOS D. E., GITTINGS J. A., JAMIL T., SRINIVASAN M., HOTEIT I.: RedSeaAtlas: A visual analytics tool for spatiotemporal multivariate data of the red sea. In EnvirVis: Workshop on Visualization in Environmental Sciences (EnvirVis2019) (2019), pp. 25–32. 1


[AHG∗19] AFZAL S., HITTAWE M. M., GHANI S., JAMIL T., KNIO O., HADWIGER M., HOTEIT I.: The state of the art in visual analysis approaches for ocean and atmospheric datasets. Computer Graphics Forum 38, 3 (2019), 881–907. 1, 4


[AMM17] AMORES A., MELNICHENKO O., MAXIMENKO N.: Coherent mesoscale eddies in the North Atlantic subtropical gyre: 3-D structure and transport with application to the salinity maximum. Journal of Geophysical Research: Oceans 122, 1 (2017), 23–41. 5


[BNBD∗07] BENITEZ-NELSON C. R., BIDIGARE R. R., DICKEY T. D., LANDRY M. R., LEONARD C. L., BROWN S. L., NENCIOLI F., RII Y. M., MAITI K., BECKER J. W., ET AL.: Mesoscale eddies drive increased silica export in the subtropical pacific ocean. Science 316, 5827 (2007), 1017–1021. 1


[DAN12] DINESHA V., ADABALA N., NATARAJAN V.: Uncertainty visualization using HDR volume rendering. The Visual Computer 28 (2012), 265–278. 1


[FD06] FRASER S., DICKSON B.: Data mining geoscientific data sets using self organizing maps. Mastering the Data Explosion in the Earth and Environmental Sciences, Extended Abstracts (2006), 5–7. 1


[Fer23] Ferret. https://ferret.pmel.noaa.gov/Ferret/, 2023. [Online; accessed 28-April-2023]. 1


[FFH21] FRIEDERICI A., FALK M., HOTZ I.: A winding angle framework for tracking and exploring eddy transport in oceanic ensemble simulations. In EnvirVis: Workshop


[GEP04] GUO D., EVANGELINOS C., PATRIKALAKIS N.: Flow feature extraction in oceanographic visualization. In Proceedings of Computer Graphics International Conference (07 2004), pp. 162–173. doi:10. 1109/CGI.2004.1309207. 5


[GSK∗08] GROCHOW K., STOERMER M., KELLEY D., DELANEY J., LAZOWSKA E.: COVE: A visual environment for ocean observatory design. Journal of Physics: Conference Series 125, 1 (2008), 012092. 1


[KNR∗07] KUMAR S. P., NUNCIO M., RAMAIAH N., SARDESAI S., NARVEKAR J., FERNANDES V., PAUL J. T.: Eddy-mediated biological productivity in the Bay of Bengal during fall and spring intermonsoons. Deep Sea Research Part I: Oceanographic Research Papers 54, 9 (2007), 1619–1640. 4


[LJP∗19] LI S., JAROSZYNSKI S., PEARSE S., ORF L., CLYNE J.: Vapor: A visualization package tailored to analyze simulation data in earth system science. Atmosphere 10, 9 (2019), 488. 1


[Mad08] MADEC G.: NEMO ocean engine. Note du Pôle de modélisation, Institut Pierre-Simon Laplace (IPSL), France, No 27, ISSN No 1288-1619, 2008. 2


[MAIS16] MATSUOKA D., ARAKI F., INOUE Y., SASAKI H.: A new approach to ocean eddy detection, tracking, and event visualization– application to the northwest pacific ocean. Procedia Computer Science 80 (2016), 1601–1611. 5


[McW90] MCWILLIAMS J. C.: The vortices of two-dimensional turbulence. Journal of Fluid mechanics 219 (1990), 361–385. 4


[McW08] MCWILLIAMS J. C.: The nature and consequences of oceanic eddies. Ocean modeling in an eddying regime 177 (2008), 5–15. 1


[MJD∗99] MCNEIL J., JANNASCH H., DICKEY T., MCGILLICUDDY D., BRZEZINSKI M., SAKAMOTO C.: New chemical, bio-optical and physical observations of upper ocean response to the passage of a mesoscale eddy off bermuda. Journal of Geophysical Research: Oceans 104, C7 (1999), 15537–15548. 1


[myO23] Copernicus myOcean. https://marine.copernicus. eu/access-data/ocean-visualisation-tools, 2023. [Online; accessed 28-April-2023]. 1


[NL15] NOBRE C., LEX A.: OceanPaths: Visualizing multivariate oceanography data. In Proceedings of the Eurographics Conference on Visualization (EuroVis 2015) - Short Papers (2015), The Eurographics Association. doi:10.2312/eurovisshort.20151124. 1


[Oku70] OKUBO A.: Horizontal dispersion of floatable particles in the vicinity of velocity singularities such as convergences. Deep sea research and oceanographic abstracts 17, 3 (1970), 445–454. 4


[PBI04] PARK S., BAJAJ C., IHM I.: Visualization of very large oceanography time-varying volume datasets. In Computational Science-ICCS 2004: 4th International Conference, Kraków, Poland, June 6-9, 2004, Proceedings, Part II 4 (2004), Springer, pp. 419–426. 1


[pyF23] pyferret. https://ferret.pmel.noaa.gov/Ferret/, 2023. [Online; accessed 28-April-2023]. 1


[Ros89] ROSENBLUM L. J.: Visualizing oceanographic data. IEEE computer graphics and applications 9, 3 (1989), 14–19. 1


[RR10] ROBINSON I. S., ROBINSON I. S.: Mesoscale ocean features: Eddies. Discovering the Ocean from Space: The unique applications of satellite oceanography (2010), 69–114. 1


[Sar13] SARMIENTO J. L.: Ocean biogeochemical dynamics. In Ocean Biogeochemical Dynamics. Princeton university press, 2013. 4


[SDVN22] SINGH U., DHIPU T. M., VINAYACHANDRAN P. N., NATARAJAN V.: Front and skeleton features based methods for tracking salinity propagation in the ocean. Computers & Geosciences 159 (2022), 104993. doi:https://doi.org/10.1016/j.cageo. 2021.104993. 5


[TFL∗17] TIERNY J., FAVELIER G., LEVINE J. A., GUEUNET C., MICHAUX M.: The Topology Toolkit. IEEE Transactions on Visualization and Computer Graphics 24, 1 (2017), 832–842. 5


[TZG∗17] TOYE H., ZHAN P., GOPALAKRISHNAN G., KARTADIKARIA A. R., HUANG H., KNIO O., HOTEIT I.: Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing. Ocean Dynamics 67, 7 (Jul 2017), 915–933. doi:10.1007/ s10236-017-1064-1. 2


[VCMN04] VINAYACHANDRAN P. N., CHAUHAN P., MOHAN M., NAYAK S.: Biological response of the sea around Sri Lanka to summer monsoon. Geophysical Research Letters 31, 1 (2004). 6


[VY98] VINAYACHANDRAN P. N., YAMAGATA T.: Monsoon response of the sea around Sri Lanka: generation of thermal domes and anticyclonic vortices. Journal of Physical Oceanography 28, 10 (1998), 1946– 1960. 5, 6


[WHP∗11] WILLIAMS S., HECHT M., PETERSEN M., STRELITZ R., MALTRUD M., AHRENS J., HLAWITSCHKA M., HAMANN B.: Visualization and analysis of eddies in a global ocean simulation. Computer graphics forum 30, 3 (2011), 991–1000. 5


[XLWD19] XIE C., LI M., WANG H., DONG J.: A survey on visual analysis of ocean data. Visual Informatics 3, 3 (2019), 113–128. 1, 2


This paper is available on arxiv under CC 4.0 license.