| NSF Org: |
TI Translational Impacts |
| Recipient: |
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| Initial Amendment Date: | June 24, 2016 |
| Latest Amendment Date: | June 24, 2016 |
| Award Number: | 1621576 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Peter Atherton
patherto@nsf.gov (703)292-8772 TI Translational Impacts TIP Dir for Tech, Innovation, & Partnerships |
| Start Date: | July 1, 2016 |
| End Date: | June 30, 2017 (Estimated) |
| Total Intended Award Amount: | $225,000.00 |
| Total Awarded Amount to Date: | $225,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
55 COURT ST FL 2 BOSTON MA US 02108-2111 (203)915-3136 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
404 Broadway B Cambridge MA US 02139-1631 |
| Primary Place of Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | SBIR Phase I |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.041 |
ABSTRACT
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project extends to academics and industry stakeholders holding intellectual or financial interests that are impacted by climate change. Given growing evidence for climate change-driven increases in extreme weather events over recent years, it has become increasingly important for stakeholders to factor climate change into their resilience plans. Engineering firms must embed changes in risks into engineering design processes due to increased urbanization, coastal inhabitancy, and climate change impacts. Insurance companies need to base risk assessments, underwriting strategies, and reinsurance purchasing decisions on quantitative methods that appropriately consider credible, probabilistic projections of changes in extremes with appropriate uncertainty bounds. Public agencies, municipalities, and private organizations must implement resilience strategies for critical infrastructure that will withstand climate extremes at decadal to multidecadal scales. This project focuses on developing and translating patent-protected research to analytics and products that address the emerging needs of these industry stakeholders. The publications and software developed via this proposal will significantly advance best practices in hazard risk assessment and climate change adaptation, and a sample of the New England design storm curves will be made freely available to support educational and outreach efforts.
This Small Business Innovation Research (SBIR) Phase I project aims to address the deep uncertainties in climate projections rooting from intrinsic variability and longstanding gaps in physics understanding. The project will consist of developing a Physics-Guided Statistical Modeling (PGSM) framework for probabilistically quantifying projected changes in regional precipitation extremes, and translating those projections to actionable, climate change-informed local design storm curves. The initial focus is on precipitation extremes given that theory and evidence suggest climate change-driven increases in storm severity in many regions, that these projections are needed to enhance design curves, and given they are crucial inputs to flood models that will be pursued aggressively in subsequent efforts. The project will culminate in multiple deliverables, including (1) peer reviewed scientific publications, (2) a proprietary spatio-temporal precipitation extremes database, and (3) design storm curves for a New England testbed, the last of which will be disseminated via a software prototype.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Intellectual Merit and Broader Impacts
Climate change is considered a global threat that will continue to exacerbate extreme weather and natural hazards that drive billions of dollars in losses. The private sector is unequipped, the public sector is ill-positioned, and academia is not structured to drive climate change adaptation at scale. risQ was founded to enable climate-innovation at the nexus of these three stakeholder efforts.
There is a growing need for all industries to bolster climate resilience. However, there are minimal financial incentives for implementing climate adaptation measures and inadequate resources for incorporating data on climate change into long-term investment and day-to-day decision-making. The insurance industry must lead the effort to effectuate incentives that make adaptation financially advantageous. It is imperative that (re)insurance companies gain a clear understanding of the adverse impacts of climate change on extreme weather and annual (re)insured losses, as well as the positive impacts policyholder adaptation.
risQ’s focus is to drive this acute and specific understanding around climate impacts within the (re)insurance industry, as well as provide tools to incorporate this quantitative understanding into risk management frameworks. We expect that successful adoption of climate-informed risk management within the (re)insurance industry will result in more coherent adaptation incentives for entities operating in critical infrastructure sectors (e.g., agriculture, real estate, energy). These sectors plays an integral role in the well-being, productivity, and stability of the United States, and each sector’s successful adaptation will result in a more resilient and sustainable nation. This SBIR Phase I project catalyzed risQ’s effort to effectuate this climate change adaptation at scale.
SBIR Phase I Project Outcomes
risQ’s NSF SBIR Phase I project resulted in multiple technical advancements, strengthened commercial validation, bolstered credibility, and deep industry know-how. Over the past year, we have positioned risQ as a potential climate analytics leader in the (re)insurance and catastrophe modeling industries. Technical results/outcomes of our NSF SBIR Phase I project included:
- Physics-Guided Statistical Modeling (PGSM) framework for modeling short- to long-term changes in extreme precipitation risk. This model is a novel advancement beyond the classic utilization of GCMs via ensemble averaging, and has served as the basis for a peer-reviewed academic journal publication that will generate long-standing credibility for risQ.
- Machine learning based model for downscaling our extreme precipitation projections to spatial scales that are relevant for financial investment and (re)insurance risk management decisions.
- Software prototype that demonstrates the financial benefits of leveraging climate analytics for (re)insurance risk management, portfolio diversification, underwriting, and capital solvency modeling.
The National Science Foundation expects all SBIR Phase I grantees to conduct in-depth primary research via ‘discovery interviews’ with target customers. The goal of these interviews was to obtain technical and commercial validation for risQ’s envisioned product and business strategy. Over 40 interviews were conducted. Feedback gathered during these interviews provided strong insight into the practices of (re)insurance companies and catastrophe modeling firms. We have validated our hypothesis that organizations operating in each of these industries are not accounting for climate change explicitly in their long-term investment strategies and day-to-day decision-making. Commercial results/outcomes of our NSF SBIR Phase I project included:
- White papers for both the (re)insurance and catastrophe modeling industries. These white papers delineated climate-related risks, commercial barriers to entry, and the need for climate analytics solutions.
- In-depth report summarizing our findings and ultimately providing direction for risQ and future companies entering the climate analytics space, as well as academics looking to contribute research or develop tools for solving similar climate-related problems. This report provides precise estimates of the addressable market opportunity for each target industry segment and natural peril of interest.
- Detailed 5-year business plan with financial projections and a precise go-to-market strategy for future products. This business plan has served as a strategic guide for risQ going forward, as well as material for fundraising purposes.
- Strategic investment offer from a top 10 reinsurance company, serving as a strong signal of validation for our science and commercial viability.
- Pilot project with a catastrophe modeling firm. The goal of this pilot project is to collaborate with a customer to deliver a climate change-informed view of flood risk.
- Reinsurer-sponsored keynote presentation at the 2017 Reinsurance Association of America (RAA) Cat Risk Management Conference this past February in Orlando, Florida. Our presentation garnered positive feedback and has bolstered our credibility within the (re)insurance industry.
Next steps for risQ during the NSF SBIR Phase II project include: (1) Rapid and iterative product development based on frequent engagements with (re)insurance firms; (2) Generalization of the technology developed in Phase I to include additional climate change related phenomena and hazards, including predicted changes in tornado activity, drought, temperature averages/extremes, wind perils, and sea level rise; (3) Tailoring modular software for clients interested in understanding climate-induced risks to agricultural, real estate, and energy infrastructure investments.
Last Modified: 07/26/2017
Modified by: Evan A Kodra
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