Visualizing uncertainties in a storm surge ensemble data assimilation and forecasting system

Handle URI:
http://hdl.handle.net/10754/575634
Title:
Visualizing uncertainties in a storm surge ensemble data assimilation and forecasting system
Authors:
Hollt, Thomas; Altaf, Muhammad; Mandli, Kyle T.; Hadwiger, Markus ( 0000-0003-1239-4871 ) ; Dawson, Clint N.; Hoteit, Ibrahim ( 0000-0002-3751-4393 )
Abstract:
We present a novel integrated visualization system that enables the interactive visual analysis of ensemble simulations and estimates of the sea surface height and other model variables that are used for storm surge prediction. Coastal inundation, caused by hurricanes and tropical storms, poses large risks for today's societies. High-fidelity numerical models of water levels driven by hurricane-force winds are required to predict these events, posing a challenging computational problem, and even though computational models continue to improve, uncertainties in storm surge forecasts are inevitable. Today, this uncertainty is often exposed to the user by running the simulation many times with different parameters or inputs following a Monte-Carlo framework in which uncertainties are represented as stochastic quantities. This results in multidimensional, multivariate and multivalued data, so-called ensemble data. While the resulting datasets are very comprehensive, they are also huge in size and thus hard to visualize and interpret. In this paper, we tackle this problem by means of an interactive and integrated visual analysis system. By harnessing the power of modern graphics processing units for visualization as well as computation, our system allows the user to browse through the simulation ensembles in real time, view specific parameter settings or simulation models and move between different spatial and temporal regions without delay. In addition, our system provides advanced visualizations to highlight the uncertainty or show the complete distribution of the simulations at user-defined positions over the complete time series of the prediction. We highlight the benefits of our system by presenting its application in a real-world scenario using a simulation of Hurricane Ike.
KAUST Department:
Computer Science Program; Water Desalination and Reuse Research Center (WDRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Visual Computing Center (VCC); Physical Sciences and Engineering (PSE) Division; Environmental Science and Engineering Program; Earth Fluid Modeling and Prediction Group
Publisher:
Springer Science + Business Media
Journal:
Natural Hazards
Issue Date:
15-Jan-2015
DOI:
10.1007/s11069-015-1596-y
Type:
Article
ISSN:
0921030X
Sponsors:
We would like to thank the anonymous reviewers for the constructive comments. Research reported in this publication was supported by the King Abdullah University of Science and Technology (KAUST).
Appears in Collections:
Articles; Environmental Science and Engineering Program; Physical Sciences and Engineering (PSE) Division; Computer Science Program; Visual Computing Center (VCC); Water Desalination and Reuse Research Center (WDRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorHollt, Thomasen
dc.contributor.authorAltaf, Muhammaden
dc.contributor.authorMandli, Kyle T.en
dc.contributor.authorHadwiger, Markusen
dc.contributor.authorDawson, Clint N.en
dc.contributor.authorHoteit, Ibrahimen
dc.date.accessioned2015-08-24T08:34:41Zen
dc.date.available2015-08-24T08:34:41Zen
dc.date.issued2015-01-15en
dc.identifier.issn0921030Xen
dc.identifier.doi10.1007/s11069-015-1596-yen
dc.identifier.urihttp://hdl.handle.net/10754/575634en
dc.description.abstractWe present a novel integrated visualization system that enables the interactive visual analysis of ensemble simulations and estimates of the sea surface height and other model variables that are used for storm surge prediction. Coastal inundation, caused by hurricanes and tropical storms, poses large risks for today's societies. High-fidelity numerical models of water levels driven by hurricane-force winds are required to predict these events, posing a challenging computational problem, and even though computational models continue to improve, uncertainties in storm surge forecasts are inevitable. Today, this uncertainty is often exposed to the user by running the simulation many times with different parameters or inputs following a Monte-Carlo framework in which uncertainties are represented as stochastic quantities. This results in multidimensional, multivariate and multivalued data, so-called ensemble data. While the resulting datasets are very comprehensive, they are also huge in size and thus hard to visualize and interpret. In this paper, we tackle this problem by means of an interactive and integrated visual analysis system. By harnessing the power of modern graphics processing units for visualization as well as computation, our system allows the user to browse through the simulation ensembles in real time, view specific parameter settings or simulation models and move between different spatial and temporal regions without delay. In addition, our system provides advanced visualizations to highlight the uncertainty or show the complete distribution of the simulations at user-defined positions over the complete time series of the prediction. We highlight the benefits of our system by presenting its application in a real-world scenario using a simulation of Hurricane Ike.en
dc.description.sponsorshipWe would like to thank the anonymous reviewers for the constructive comments. Research reported in this publication was supported by the King Abdullah University of Science and Technology (KAUST).en
dc.publisherSpringer Science + Business Mediaen
dc.subjectEnsemble dataen
dc.subjectInteractive Visualizationen
dc.subjectStorm surgeen
dc.subjectVisual analysisen
dc.titleVisualizing uncertainties in a storm surge ensemble data assimilation and forecasting systemen
dc.typeArticleen
dc.contributor.departmentComputer Science Programen
dc.contributor.departmentWater Desalination and Reuse Research Center (WDRC)en
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentVisual Computing Center (VCC)en
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Divisionen
dc.contributor.departmentEnvironmental Science and Engineering Programen
dc.contributor.departmentEarth Fluid Modeling and Prediction Groupen
dc.identifier.journalNatural Hazardsen
dc.contributor.institutionInstitute for Computational Engineering and Sciences, University of Texas at AustinAustin, TX, United Statesen
dc.contributor.institutionColumbia University in the City of New YorkNew York, NY, United Statesen
kaust.authorHollt, Thomasen
kaust.authorAltaf, Muhammaden
kaust.authorHadwiger, Markusen
kaust.authorHoteit, Ibrahimen
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.