PREEVENTS Track 2: Collaborative Research: A Dynamic Unified Framework for Hurricane Storm Surge Analysis and Prediction Spanning across the Coastal Floodplain and Ocean
PREEVENTS Track 2: Collaborative Research: A Dynamic Unified Framework for Hurricane Storm Surge Analysis and Prediction Spanning across the Coastal Floodplain and Ocean
批准号:
1855096
负责人:
Laxmikant Kale
金额:
$40.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-08-15 至 2024-07-31
中文摘要
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英文摘要
Storm-driven coastal flooding is influenced by many physical processes including riverine discharges, regional rainfall, wind, atmospheric pressure, wave-induced set up, wave runup, tides, and fluctuating baseline ocean water levels. Operational storm surge models such as those used by NOAA's Ocean Prediction Center (Extratropical Surge and Tide Operational Forecast System) incorporate a variety of these processes including riverine discharges, atmospheric winds and pressure, waves, and tides. However, coastal surge models do not typically incorporate the impact of rainfall across the coastal floodplain nor fluctuations in background water levels due to the oceanic density structure. Nonetheless, the floodplain hydrology and ocean baseline water levels provide vital controls in riverine and estuarine environments (e.g., the dramatic effect seen in the Houston metropolitan region during Hurricane Harvey in 2017 and in North Carolina during Hurricane Florence in 2018). Recent events have shown that a unified approach that incorporates all the relevant physical processes is critical for accurate predictive simulations of coastal flooding due to extreme events. This project will tackle this challenge by melding hydrology, hydraulics, and waves into a dynamic unified computational framework that uses unstructured meshes spanning from the deep ocean to upland areas and across the coastal floodplain. Improved capacity for flood risk managers, the insurance industry, and city planners to evaluate flood risk across the entire coastal floodplain. Improved models will lead to better guidance on development and construction practices, will help make cities more resilient and will reduce risk for coastal populations and infrastructure. In addition, this work will improve coastal flood forecasting enabling federal, state, and local disaster managers, to optimize issuing warnings for evacuation and emergency planning. The collaboration between the ocean circulation, coastal hydrodynamics, and hydrology modeling communities fostered by this project will help support ambitious projects such as NOAA's National Water Center's National Integrated Water Model, which is at the preliminary stages of integration of hydrology and coastal hydrodynamics. Training of students at the intersection of hydrology, coastal hydrodynamics, physical oceanography, and computational mathematics, to help develop and apply ever-more complex and advanced models in academia, government and industry.The proposed unified framework will improve the predicted water level gradient and flows throughout the coastal floodplain by integrally considering the rainfall-driven hydrology within the coastal floodplain as well as improving the background open ocean water level. Well-developed but coarse global ocean models will be heterogeneously coupled to high-resolution 2D shallow water equation models in order to account for large-scale baroclinic ocean processes that impact coastal water levels. Interface strategies and conditions between heterogeneous physics will be developed that allow the interfaces to move in time and space for the range of physics from dry to surface runoff to pressurized flow. Applying the right physics and associated mathematical models as the storms evolve will result in more robust and accurate models, as well as much more efficient models. This will dynamically account for the hydrologic - hydrodynamic interaction of water across the floodplain. Dynamic load balancing will account for widely varying computational (CPU) costs for each set of physics and the dynamic migration of the physics will be implemented within the heterogeneous parallel computing environment.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
Runtime Techniques for Automatic Process Virtualization
自动流程虚拟化的运行时技术
DOI:
--
发表时间:
2022
期刊:
51st International Conference on Parallel Processing Workshops (ICPP 2022 Workshops
影响因子:
--
作者:
[Ramos, Evan, White, Sam, Bhosale, Aditya, Kale, Laxmikant]
通讯作者:
Kale, Laxmikant
OAC Core: Small: Collaborative Research: Scalable distributed algorithms for tree structured astronomical data
-
批准号:1910428
-
项目类别:Standard Grant
-
资助金额:$35.0万
-
财政年份:2019
-
负责人:Laxmikant Kale
-
依托单位:
SI2-SSI: Collaborative Research: ParaTreet: Parallel Software for Spatial Trees in Simulation and Analysis
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批准号:1550554
-
项目类别:Standard Grant
-
资助金额:$17.0万
-
财政年份:2016
-
负责人:Laxmikant Kale
-
依托单位:
Collaborative Research: CDS&E: Evolution of the High Redshift Galaxy and AGN Populations
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批准号:1312913
-
项目类别:Standard Grant
-
资助金额:$9.0万
-
财政年份:2013
-
负责人:Laxmikant Kale
-
依托单位:
SI2-SSI: Collaborative Research: Scalable, Extensible, and Open Framework for Ground and Excited State Properties of Complex Systems
-
批准号:1339715
-
项目类别:Continuing Grant
-
资助金额:$238.32万
-
财政年份:2013
-
负责人:Laxmikant Kale
-
依托单位:
Simplifying Parallel Programming for CSE Applications using a Multi-Paradigm Approach
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批准号:0833188
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项目类别:Standard Grant
-
资助金额:$80.0万
-
财政年份:2008
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负责人:Laxmikant Kale
-
依托单位:
CSR---SMA: BigSim: Performance Prediction for Petascale Machines and Applications
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批准号:0720827
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项目类别:Continuing Grant
-
资助金额:$0.0万
-
财政年份:2007
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负责人:Laxmikant Kale
-
依托单位:
Collaborative Research: Advanced Parallel Computing Techniques with Applications to Computational Cosmology
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批准号:0205611
-
项目类别:Standard Grant
-
资助金额:$100.0万
-
财政年份:2002
-
负责人:Laxmikant Kale
-
依托单位:
NGS: Performance Modeling and Programming Environments for PetaFlop Computers and the Blue Gene Machine
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批准号:0103645
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项目类别:Continuing Grant
-
资助金额:$75.0万
-
财政年份:2001
-
负责人:Laxmikant Kale
-
依托单位:
The Chare Kernal Parallel Programming System
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批准号:9106608
-
项目类别:Standard Grant
-
资助金额:$19.97万
-
财政年份:1991
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负责人:Laxmikant Kale
-
依托单位:
Optimized and Compiled Parallel Execution of Logic Programs
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批准号:8902496
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项目类别:Standard Grant
-
资助金额:$16.63万
-
财政年份:1989
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负责人:Laxmikant Kale
-
依托单位:
Parallel Evaluation of Logic Programs: The Reduce-or Process Model
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批准号:8700988
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项目类别:Standard Grant
-
资助金额:$16.31万
-
财政年份:1987
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负责人:Laxmikant Kale
-
依托单位:
海外基金