Increasing U.S. Communities’ and Businesses’ Resilience to Extreme Events

The NOAA Climate Program Office’s Communication, Education, and Engagement (CEE) Division is announcing four new one-year projects in Fiscal Year (FY) 2019 that will help U.S. local governments, communities, businesses, and other stakeholders adapt and increase resilience to climate-related impacts and extreme events. The competitively selected projects total $150,000 in awards.

Billion-dollar disasters in the United States from extreme weather and climate events have more than quadrupled in number and cost since 1980. According to the 2018 State of the Climate report, tropical cyclones were well above average with over 10 percent of the named cyclones reaching Category 5 intensity level. To better prepare themselves and manage risks to valued assets from rising impacts, Americans are increasingly turning to NOAA for actionable climate information.

Some of the aftermath of storm surge from Hurricane Florence: a boat pushed inland onto high ground. Photo courtesy the Morehead City National Weather Service Forecast Office.

A key part of CEE’s mission is to help U.S. communities and businesses better understand and manage their climate-related risks and opportunities, for instance improving resilience to extreme events. To achieve this mission, CEE manages and maintains the U.S. Climate Resilience Toolkit (CRT), offering easy public access to federal science-based information, tools, data products, and expertise. These resources are designed to help U.S. decision makers, resource managers, municipal planners, business and policy leaders protect and manage their valued assets. Average annual CRT visit rates to use these resources have risen by roughly 53% per year over the last three years.

Complementing the CRT, the CEE Division initiated a public-private partnership to establish the Resilience Ecosystem—an open and inclusive community of organizations and individuals who are interested in collaboration in order to improve the efficiency and effectiveness of climate adaptation and resilience-building practices so that, together, they may achieve much more than would be possible if each worked independently.

“CEE aims to help incentivize collaboration through these cooperative agreement awards,” said David Herring, CEE Division Chief. “Emphasis in this competition is on integration of existing tools, resources, and methodologies that result in improved efficiency, greater scalability, more interoperability, and new wholes that are greater than the sum of their parts.”

The four new projects funded by the CEE Division in FY19 are:

  • Integrating Climate and Socioeconomic Data to Map Risk Exposure
    • PI: Patty Gude, Headwaters Economics
    • Co-PI: Art DeGaetano, Northeast Regional Climate Center (NRCC) at Cornell University
    • This project will integrate two open-access tools: Neighborhoods at Risk, hosted by Headwaters Economics, and the Applied Climate Information System (ACIS), hosted by the NRCC. This will address users’ requests for more customizable outputs, such as visualization of selected thresholds (e.g., heat and precipitation), for any location in the U.S. and for user-selected predictive time periods.

  • Connecting Decision-Makers with Vetted Adaptation Service Providers through an Open-Access Registry
    • PI: Jessica Hitt, EcoAdapt
    • Co-PIs: Beth Gibbons and Rachel Jacobson, American Society of Adaptation Professionals (ASAP); and Lara Hansen, EcoAdapt
    • This project will develop and publish a free, online Registry of Adaptation Service Professionals who are available to provide guidance and decision support to managers and planners from communities and organizations of all sizes as they seek to make climate-informed decisions. Specifically, this project will move the Registry beyond its current beta development phase.

  • Enhancing the Climate Explorer with Suggested Top Hazards
    • PI: Jessica Cahail, Azavea
    • Co-PI: Jeff Hicks, Fernleaf Interactive
    • This project will enhance NOAA’s open-source Climate Explorer tool by adding a core feature from Azavea’s Temperate — a separate adaptation planning and decision-support solution that provides the ability to display potential future climate hazards for cities nationwide.

  • Resilient Rural America Project, Phase 2
    • PI: Gwen Griffith, Model Forest Policy Program
    • Co-PI(s): Lara Hansen, EcoAdapt, and Barbara Cozzens, Key-Log Economics
    • The Resilient Rural America Project (RRAP) proposes to accelerate rural climate adaptation by strengthening the ability of adaptation professionals to meet the needs of underserved rural jurisdictions, organizations, and businesses; and enable rural leaders to take action on their specific priority resilience strategies. In phase 2, the project will produce and publish a training module focused on practical steps to implement the resilience strategies called for in climate-ready comprehensive plans.

GRANTS/FFO NEWS


2 Mar 2021

Powerful New Software Helps Expedite Weather and Climate Forecasting Improvements

Monsoon shower in New Mexico. Credit: John Folwer. Used under a Creative Commons Licesnse 

Much like a doctor tries to diagnose the cause of a patient’s symptoms, a team of NOAA-funded researchers has been helping to diagnose the causes behind poor weather and climate model forecasts. Now, thanks to the team’s new model evaluation software, scientists can more quickly and easily identify the source of model errors to accelerate improvements and help Americans better plan and respond.

Developed by the NOAA Climate Program Office’s Model Diagnostics Task Force (MDTF), the software package was recently transferred to NOAA’s Geophysical Fluid Dynamics Laboratory (GFDL) where it has already led to significant advancements in model performance, including forecasts of regional precipitation and extreme events like monsoons. 

“Many long-standing model biases have been cut roughly by half,” said David Neelin, UCLA Professor of Atmospheric and Oceanic Sciences and MDTF Lead, about the new software. “These improvements are critical for advancing a number of NOAA priorities.”

Diving deeper into weather and climate model errors

Americans are increasingly seeking accurate weather and climate forecasts from NOAA. But to improve model errors and provide more reliable forecasts, scientists can’t just fix temperature or precipitation—there’s no single knob or equation in the model controlling each variable. Model developers need to go deeper and address issues with underlying physical and chemical processes in the models that drive these errors.

With this in mind, the NOAA Climate Program Office’s Modeling, Analysis, Predictions, and Projections (MAPP) program, in partnership with GFDL, created the Model Diagnostic Task Force (MDTF). The Task Force brings together researchers and scientists from universities, national modeling centers, and research laboratories to focus on “diagnostics” that evaluate or diagnose the error source in different atmospheric, land, and ocean processes in models.

Creating the MDTF was motivated by the 2012 Working Group on Numerical Experimentation (WGNE) Task Force, which advocated for a diagnostic framework focused on the Madden Julian Oscillation—an eastward moving disturbance of clouds and rain that circles the tropics every 30-60 days. Since 2015, the MDTF has expanded on that concept and has been developing software that collects diagnostics for many key weather and climate model processes—called Process Oriented Diagnostics (PODs)—produced by researchers at universities and modeling centers, into a central framework that can be readily used as a model evaluation tool. 

The image illustrates multiple weather climate and model process areas included in the new Model Diagnostic Task Force software package.

“The idea is to work closely with modeling centers to come up with a way to enable the modeling community outside of the centers [...] to easily contribute their diagnostics,” said Eric Maloney, Colorado State University Professor and MDTF Co-lead, during a 2017 interview with NOAA. “Then, modeling centers will be able to apply the diagnostics to their simulations to hopefully lead to fantastic modeling improvements in an accelerated fashion.”

Now at GFDL, the package is also moving to an open development framework on GitHub to encourage diagnostic contributions from the public, facilitate the exchange of ideas between modeling centers and the scientific community, and make it easier for researchers to integrate their work. By engaging the modeling community through a collaborative approach, the package could help quicken the transition of research innovations into advances in life-saving forecasts and projections. 

“Ultimately, 10 years down the line, I think that model diagnosis work [...] may be some of my most important contributions,” Maloney said.

An evolving evaluation software for more accurate forecasts and projections

The MDTF’s evolving software package has eight different diagnostics implemented, 11 under development to be included by 2022, and 28 proposed which may be implemented by 2024. Current diagnostics help tackle things like atmospheric convection, clouds, and radiative processes, while near-term diagnostics will cover tropical and extratropical cyclones and phenomena like the El Niño-Southern Oscillation. In the longer-term, future diagnostics will address key processes that drive our climate’s sensitivity to greenhouse gas emissions and other processes critical to modeling marine ecosystem variability and change.

“A lot of the diagnostics are aligned with key NOAA priorities—high impact water events, extreme weather events, weather and climate events that have high societal and economic impacts,” said John Krasting, who now oversees the development of the package at GFDL. “This package allows users of our models and model developers to explore NOAA mission-relevant processes and identify how we’re doing and ways we can improve.”

Development of the software framework for process-oriented diagnostics was most recently supported by the National Oceanic and Atmospheric Administration (NOAA) Climate Program Office Modeling, Analysis, Predictions and Projections (MAPP) Program (grant # NA18OAR4310280). Additional support was provided by University of California Los Angeles, the Geophysical Fluid Dynamics Laboratory, the National Center for Atmospheric Research, Colorado State University, Lawrence Livermore National Laboratory and the US Department of Energy.

All of the process-oriented diagnostics modules (PODs) were contributed by members of the NOAA Model Diagnostics Task Force with MAPP support.

 

 

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