Award Abstract # 2103754
Large-scale CoPe: Megalopolitan Coastal Transformation Hub (MACH): Researching complex interactions between climate hazards and communities to inform governance of coastal risk.

NSF Org: RISE
Integrative and Collaborative Education and Research (ICER)
Recipient: RUTGERS, THE STATE UNIVERSITY
Initial Amendment Date: July 30, 2021
Latest Amendment Date: March 21, 2025
Award Number: 2103754
Award Instrument: Cooperative Agreement
Program Manager: Manda S. Adams
amadams@nsf.gov
 (703)292-4708
RISE
 Integrative and Collaborative Education and Research (ICER)
GEO
 Directorate for Geosciences
Start Date: August 1, 2021
End Date: July 31, 2026 (Estimated)
Total Intended Award Amount: $19,935,916.00
Total Awarded Amount to Date: $19,255,398.00
Funds Obligated to Date: FY 2021 = $11,320,090.00
FY 2023 = $7,935,308.00
History of Investigator:
  • Robert Kopp (Principal Investigator)
    Robert.Kopp@rutgers.edu
  • Klaus Keller (Co-Principal Investigator)
  • Carolyn Kousky (Co-Principal Investigator)
  • Victoria Ramenzoni (Co-Principal Investigator)
  • Ning Lin (Co-Principal Investigator)
Recipient Sponsored Research Office: Rutgers University New Brunswick
3 RUTGERS PLZ
NEW BRUNSWICK
NJ  US  08901-8559
(848)932-0150
Sponsor Congressional District: 12
Primary Place of Performance: Rutgers University New Brunswick
Piscataway
NJ  US  08854-3925
Primary Place of Performance
Congressional District:
06
Unique Entity Identifier (UEI): M1LVPE5GLSD9
Parent UEI:
NSF Program(s): SPECIAL EMPHASIS PROGRAM,
CoPe-Coastlines and People
Primary Program Source: 01002324DB NSF RESEARCH & RELATED ACTIVIT
01002122DB NSF RESEARCH & RELATED ACTIVIT

01002526DB NSF RESEARCH & RELATED ACTIVIT

01002425DB NSF RESEARCH & RELATED ACTIVIT

4082CYXXDB NSF TRUST FUND

01002324DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 4444
Program Element Code(s): 061900, 097Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.050

ABSTRACT

Risks from rising seas, shifting storms, and eroding coastlines, as well as changing ecosystems and development patterns, are escalating in coastal megalopolises around the world. Local, state, and federal climate risk management decisions are interacting with one another and coastal dynamics in complex ways that will shape risk patterns for decades. However, the frameworks informing these decisions are often ill-suited for sustained, complex environmental changes unfolding under deep uncertainty and often reinforce existing inequities. The CoPe Megapolitan Coastal Transformation Hub (MACH) aims to develop climate-resilient decision-making frameworks to equitably support coastal communities. Fundamental research questions will be addressed through co-production of climate research, with the intended legacy of producing a replicable model for climate risk management. The project is driven by demographically representative stakeholder engagement, which will be sustained through the continuous engagement of researchers with a Collaborative Stakeholder Advisory Panel. MACH partners with organizations that are trusted by and routinely represent, serve, and engage socially vulnerable and historically underrepresented populations in target communities. MACH will broaden participation in the STEM workforce by engaging community college faculty in the development of research priorities and by working with community college faculty and students to incorporate critical service-learning. In addition to facilitating interdisciplinary science through a broad range of academic partners, the Hub advances CoPe goals by linking researchers with coastal community stakeholders and decision-makers to ultimately co-develop dynamic adaptation policy pathways for navigating a deeply uncertain future in an equitable manner.

To overcome challenges in the dynamics of natural-human systems drive coastal climate risk, MACH will bring natural scientists, social scientists, civil engineers, and humanists together with coastal stakeholders and decision-makers in the New York City-New Jersey-Philadelphia region to co-produce knowledge that informs climate-resilient development pathways of coastal communities. MACH?s convergence research agenda will provide fundamental insights into the complex interactions between coastal climate hazards, landforms, and decisions that shape the distribution, dynamics, and uncertainties of increasing climate risks. It will facilitate flexible, equitable, and robust planning to manage coastal climate risks, building upon the iterative process of framing, analyzing, implementing, and monitoring adaptation systems that constitutes the Dynamic Adaptive Policy Pathway (DAPP) co-production framework. It will address three fundamental questions: 1) How can an improved scientific understanding of the integrated natural-human-decision system inform coastal climate risk management and the design of mission-oriented basic research? 2) How do the dynamics of coastal natural-human systems drive hazards and risks? 3) How do dynamic interactions among decisions affecting the coastal system at different scales and time horizons influence exposures, vulnerabilities, and risks?

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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 44)
Tebaldi, Claudia and Aðalgeirsdóttir, Guðfinna and Drijfhout, Sybren and Dunne, John and Edwards, Tamsin L. and Fischer, Erich and Fyfe, John C. and Jones, Richard G. and Kopp, Robert E. and Koven, Charles and Krinner, Gerhard and Otto, Friederike and Rua "The hazard components of representative key risks. The physical climate perspective" Climate Risk Management , v.40 , 2023 https://doi.org/10.1016/j.crm.2023.100516 Citation Details
Bamber, J. L. and Oppenheimer, M. and Kopp, R. E. and Aspinall, W. P. and Cooke, Roger M. "Ice Sheet and Climate Processes Driving the Uncertainty in Projections of Future Sea Level Rise: Findings From a Structured Expert Judgement Approach" Earth's Future , v.10 , 2022 https://doi.org/10.1029/2022EF002772 Citation Details
Begmohammadi, Amirhosein and Blackshaw, Christine Y. and Lin, Ning and Gori, Avantika and Wallace, Elizabeth and Emanuel, Kerry and Donnelly, Jeffrey P. "Integrating ClimatologicalHydrodynamic Modeling and Paleohurricane Records to Assess Storm Surge Risk" Journal of Geophysical Research: Oceans , v.129 , 2024 https://doi.org/10.1029/2023JC020354 Citation Details
Begmohammadi, Amirhosein and Wirasaet, Damrongsak and Lin, Ning and Dietrich, J Casey and Bolster, Diogo and Kennedy, Andrew B "Subgrid modeling for compound flooding in coastal systems" Coastal Engineering Journal , 2024 https://doi.org/10.1080/21664250.2024.2373482 Citation Details
Camus, Paula and Haigh, Ivan D. and Quinn, Niall and Wahl, Thomas and Benson, Thomas and Gouldby, Ben and Nasr, Ahmed A. and Rashid, Md Mamunur and Enríquez, Alejandra R. and Darby, Stephen E. and Nicholls, Robert J. and Nadal-Caraballo, Norberto C. "Tracking the spatial footprints of extreme storm surges around the coastline of the UK and Ireland" Weather and Climate Extremes , v.44 , 2024 https://doi.org/10.1016/j.wace.2024.100662 Citation Details
Dangendorf, Sönke and Hendricks, Noah and Sun, Qiang and Klinck, John and Ezer, Tal and Frederikse, Thomas and Calafat, Francisco M. and Wahl, Thomas and Törnqvist, Torbjörn E. "Acceleration of U.S. Southeast and Gulf coast sea-level rise amplified by internal climate variability" Nature Communications , v.14 , 2023 https://doi.org/10.1038/s41467-023-37649-9 Citation Details
Depsky, Nicholas and Bolliger, Ian and Allen, Daniel and Choi, Jun Ho and Delgado, Michael and Greenstone, Michael and Hamidi, Ali and Houser, Trevor and Kopp, Robert E. and Hsiang, Solomon "DSCIM-Coastal v1.1: an open-source modeling platform for global impacts of sea level rise" Geoscientific Model Development , v.16 , 2023 https://doi.org/10.5194/gmd-16-4331-2023 Citation Details
Enriquez, Alejandra R and Wahl, Thomas and Talke, Stefan A and Orton, Philip M and Booth, James F and Agulles, Miguel and Santamaria-Aguilar, Sara "MatFlood: An efficient algorithm for mapping flood extent and depth" Environmental Modelling & Software , v.169 , 2023 https://doi.org/10.1016/j.envsoft.2023.105829 Citation Details
Feng, Kairui and Ouyang, Min and Lin, Ning "Tropical cyclone-blackout-heatwave compound hazard resilience in a changing climate" Nature Communications , v.13 , 2022 https://doi.org/10.1038/s41467-022-32018-4 Citation Details
Gilmore, Elisabeth A. and Kousky, Carolyn and St.Clair, Travis "Climate change will increase local government fiscal stress in the United States" Nature Climate Change , v.12 , 2022 https://doi.org/10.1038/s41558-022-01311-x Citation Details
Gori, Avantika and Lin, Ning "Projecting Compound Flood Hazard Under Climate Change With Physical Models and Joint Probability Methods" Earth's Future , v.10 , 2022 https://doi.org/10.1029/2022EF003097 Citation Details
(Showing: 1 - 10 of 44)

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