NOAA-OAR-OWAQ-2019-2005820 Full Announcement.pdf

FY2019 Office of Weather and Air Quality Research Programs

TABLE OF CONTENTS

I. Funding Opportunity Description 4

A. Program Objective 4 B. Program Priorities 12 C. Program Authority 23

II. Award Information 23 A. Funding Availability 23 B. Project/Award Period 24 C. Type of Funding Instrument 26

III. Eligibility Information 26 A. Eligible Applicants 26 B. Cost Sharing or Matching Requirement 27 C. Other Criteria that Affect Eligibility 27

IV. Application and Submission Information 27 A. Address to Request Application Package 27 B. Content and Form of Application 27 C. Unique Entity Identifier and System for Award Management (SAM) 32 D. Submission Dates and Times 32 E. Intergovernmental Review 33 F. Funding Restrictions 33 G. Other Submission Requirements 35

V. Application Review Information 37 A. Evaluation Criteria 37 B. Review and Selection Process 39 C. Selection Factors 40 D. Anticipated Announcement and Award Dates 40

VI. Award Administration Information 41 A. Award Notices 41 B. Administrative and National Policy Requirements 41 C. Reporting 44

VII. Agency Contacts 45 VIII. Other Information 45

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ANNOUNCEMENT OF FEDERAL FUNDING OPPORTUNITY

EXECUTIVE SUMMARY

Federal Agency Name(s): Oceanic and Atmospheric Research (OAR), National Oceanic and Atmospheric Administration (NOAA), Department of Commerce

Funding Opportunity Title: FY2019 Office of Weather and Air Quality Research Programs

Announcement Type: Initial

Funding Opportunity Number: NOAA-OAR-OWAQ-2019-2005820

Catalog of Federal Domestic Assistance (CFDA) Number: 11.459, Weather and Air Quality Research

Dates: Each of the eight grant competitions within this Fiscal Year (FY) 2019 funding opportunity announcement will have its own staggered due dates for Letters of Intent and full applications. Please see Section IV.D “Submission Dates and Times” for these varying due dates. Grant period length and recommended start dates for the funded projects will also vary with each competition as listed in Section II.B “Project/Award Period”.

Funding Opportunity Description: There will be eight grant competitions from this notification valued at approximately $16,200,000 as follows: 1) High Impact Weather Testbeds, 2) Joint Technology Transfer Initiative (JTTI), 3) Air Quality Research and Forecasting, 4) Verification of the Origins of Rotation in Tornadoes Experiment - Southeast U.S. (VORTEX-SE), 5) Infrasound Detection of Tornadoes and High Impact Weather, 6) Next Generation of Mesoscale Weather Observing Platforms, 7) Snowpack and Soil Moisture Observations and Data Assimilation to Improve the National Water Model (NWM), and 8) Subseasonal to Seasonal (S2S).

These eight competitions in this notification of funding opportunity reflect multiple science objectives spanning time scales from the very short-term (hours) to seasonal and from weather and water observations and modeling to social and behavioral science. It is focused on improving NOAA’s understanding and ultimately its weather and water forecasting services through engagement with the external scientific community on key science gaps of mutual interest through funded grant opportunities.

One of the key themes is supporting applied research and development that leads to the demonstration in NOAA’s testbeds during the project period of new high impact weather, water, and air quality observing and forecasting applications, including new data or products, improved analysis techniques, better statistical or dynamic forecast models and techniques, and

Federal Funding Opportunity Page 2 of 45 communication of that information to better inform the public. It is expected that NOAA’s support of these new capabilities will speed the transition of this new research into operations in order to improve NOAA weather and water services for the public.

The subseasonal to seasonal objectives focus on baseline understanding of predictability, advancement of community-driven, NOAA modeling initiatives, and increasing the utility of multi-model ensembles for end users. By facilitating new capabilities on the subseasonal to seasonal range, NOAA seeks to increase resiliency of national infrastructure, support land- and marine-based economic vitality and mitigation efforts, advance month-to-month operational applications, and better position local, regional, and national decision-makers for successful responses to adverse weather events.

VORTEX-SE is a NOAA-led effort to understand the aspects of tornadoes in the Southeast U.S.

that lead to an increased risk of death and injury in that region. The project emphasizes research, often interdisciplinary in nature, across the spectrum from meteorology to social, behavioral, economic, and engineering sciences. This year’s funding opportunity continues the emphases of previous years.

Finally, this announcement includes three competitions focused on improving the critical observing system technologies needed to underpin improved forecasts. They are focused on improved snowpack and soil moisture observations, improved mesoscale observations, and innovation in infrasound technology for detection of severe weather.

NOAA’s National Weather Service (NWS) is also announcing a companion Fiscal Year (FY) 2019 federal grant funding opportunity to this OAR opportunity through their Collaborative Science, Technology, and Applied Research (CSTAR) Program in early October 2018. Please search for funding opportunity number NOAA-NWS-NWSPO-2019-2005754 in https://www.grants.gov to learn more about this additional NOAA funding opportunity. CSTAR funds research that is often directed toward local forecasting applications at NWS Weather Forecast Offices, while OAR/OWAQ funds research that is often directed at national forecasting applications at NWS national forecast centers, though there can be overlap.

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FULL ANNOUNCEMENT TEXT

I. Funding Opportunity Description

A. Program Objective

1. High Impact Weather Testbeds

Project proposals submitted to this competition will focus on applied research, development, and, in particular, the demonstration and testing of that research in NOAA’s quasi-operational forecasting environment through engagement with one of NOAA’s testbeds (http://www.testbeds.noaa.gov/) . The high impact weather focus areas included in this competition include tornadoes, severe wind and hail storms, tropical cyclones, heavy rainfall, winter weather such as heavy snow and ice, and flooding, including coastal, inland, and flash flooding. The three NOAA testbeds relevant to these focus areas and this competition are a) the Joint Hurricane Testbed (JHT), b) the Hazardous Weather Testbed (HWT), and c) the Hydrometeorology Testbed (HMT). Projects associated with other NOAA testbeds are not supported in this competition.

The High Impact Weather Testbed program, a component of the U.S. Weather Research Program (USWRP), supports projects that will transition applied research to NOAA’s operations and services through close collaboration with NOAA testbeds. Close collaboration with the testbeds is critical and therefore required of all projects. The focus is on mature projects that are ready or nearly ready to be tested in a quasi-operational forecasting environment through one of the above testbeds. It is in these testbeds where project outcomes, such as new observing systems and data products, improved data analysis techniques, or better statistical or dynamic models and forecast techniques, will be presented to operational forecasters through the testbed and evaluated for potential future implementation in the National Weather Service (NWS) forecast offices at the local, regional, and/or national center levels to improve services to the public.

It is expected that NOAA’s funding support of these new forecasting capabilities will speed the transition of this new research and technology into forecasting operations in the next three to five years in order to improve NOAA weather and water services for the public.

Testbed projects that address improvements to NOAA’s existing or near-term future technologies, e.g., numerical models or forecast techniques that NOAA already employs, are most appropriate for this funding opportunity as opposed to those that propose totally new revolutionary models or approaches that would not reasonably be expected to be operationally implementable within NOAA’s existing operational framework in the next three to five years.

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For additional testbed program information, please review the supplemental Information Sheet for the High Impact Weather Testbed competition in the grant package associated with this announcement at https://www.grants.gov.

2. Joint Technology Transfer Initiative

The U.S. faces a spectrum of high impact environmental hazards that cause havoc on people’s lives and the nation’s economy. Through improved forecasting of the events, better communication and preparedness, loss of lives and property damage can be reduced. While NOAA is the sole U.S. government authority for issuing official weather forecasts and warnings for life threatening events, the broader weather enterprise plays an important role in communication and dissemination of information tailored to specific customers.

Through this Joint Technology Transfer Initiative (JTTI) announcement, OWAQ/OAR/NOAA is seeking proposals to support further development, testing and evaluation of mature weather research that has potential for improving NOAA’s NWS operational capabilities, particularly in the areas of advancing numerical weather prediction capabilities that seamlessly integrate in the NOAA Unified Forecast System (UFS), water prediction capabilities, and forecasting extreme precipitation and flooding events.

3. Air Quality Research and Forecasting

Air quality has improved significantly in recent decades following passage of the Clean Air Act in 1970. There are still many areas of the country, however, where the public is exposed to unhealthy levels of air pollutants and sensitive ecosystems are damaged by air pollution.

This was especially evident this year when wildfires were numerous over large parts of Western North America and because of high surface ozone episodes during heat wave scenarios in the East. To help the nation mitigate these impacts, NOAA works with the Environmental Protection Agency (EPA), state and local air quality agencies, academia, and the private sector to provide sophisticated air quality forecast capability for the Nation called the National Air Quality Forecasting Capability (NAQFC).

The current NOAA operational forecast challenges for fine particulate matter (PM2.5) and ozone predictions include improving emissions from sources such as wildfire smoke and dust, chemical mechanisms (e.g., representation of secondary organic aerosols) that accounts for reactions from wildfire-associated species, accuracy of meteorological predictions for fields such as planetary boundary layer height and flows in complex terrain and near coasts, chemical boundary conditions, and tempo-spatially resolved trans-boundary influences.

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These are among the challenges producing seasonal biases in air quality forecast guidance.

Bias correction post-processing algorithms have been implemented operationally to reduce these biases.

For additional program information on the NAQFC and this competition, please review the supplemental Information Sheet for the Air Quality Research and Forecasting competition in the grant package associated with this announcement at https://www.grants.gov.

4. Verification of the Origins of Rotation in Tornadoes Experiment in the Southeast U.S.

(VORTEX-SE)

VORTEX-SE is a research program intended to improve tornado forecasts and warnings in the southeastern U.S by obtaining new knowledge of atmospheric processes that are conducive to tornadoes, and of special importance, in the Southeast. This will be achieved through examination of historical data, special datasets collected in the field as supported by VORTEX-SE, and the application of state-of-the-art numerical weather prediction and data assimilation systems. Further, VORTEX-SE will explore avenues for more effectively communicating tornado forecasts to the public, and evaluate aspects of public vulnerability, risk perception and response to these forecasts in order to more effectively mitigate damage, injuries, and loss of life from tornadoes.

When examining measures of the threat posed by tornadoes to life and property, the southeastern U.S. has six of the eight most vulnerable states. Some of the vulnerability is due to issues such as a relatively large proportion of the population residing in mobile homes, which are known to be unsafe even in moderate strength tornadoes. Another above- normal risk in the Southeast is that many tornadoes occur during nighttime hours, associated with over half the deaths and injuries. Further, tornado casualties are disproportionately in the late fall and winter months, which are not typically associated with tornadoes according to conventional understanding or public perception, and they often occur under conditions of marginal thermodynamic instability but very strong vertical wind shear. Hence, there are many issues in the continuum spanning meteorological understanding to public awareness and perception that must be addressed in order to reduce the high tornado vulnerability in the Southeast.

For additional program information on VORTEX-SE and this competition, please review the supplemental Information Sheet for the VORTEX-SE competition in the grant package associated with this announcement at https://www.grants.gov.

5. Infrasound Detection of Tornadoes and High Impact Weather

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This competition focuses on the specific technology of infrasound data collection and applications to the understanding, detection, and warning for tornadoes and high impact weather.

Innovative research over the past 40+ years has demonstrated the potential of infrasonic technology for the detection of a variety of geophysical phenomena, including tornadoes.

Infrasound (specifically near-infrasound) is the range of acoustic frequencies just below the audible and approximately in the 0. 5 to 10 Hz frequency range. Infrasound can travel great distances with little atmospheric absorption (sometimes over 1000 km) but can take many minutes to an hour to travel these distances. It can take about five minutes for infrasound waves to travel only about 100 km.

Limited studies using Doppler radars and visual observations for verification have shown correspondence between the occurrence of tornadoes and the generation of infrasound from the same region as detected by specially-designed ground-based infrasonic observation networks deployed in the United States, mostly on the Colorado plains. Also there have been very limited studies addressing the potential of improved understanding of hurricanes, tornadoes associated with landfalling hurricanes, and related phenomena (e. g., land spouts) through infrasound data collection. There are many uncertainties due to the limited amount of data that has been collected to study the phenomena.

NOAA plans to support up to several studies under this program to improve our understanding of infrasound as it relates to the detection of tornadoes in the U. S., particularly the Southeast U.S., the potential operational forecasting and warning benefits, and the limits of temporal and spatial detectability with various infrasound observing network configurations (e. g., how precise can source locations be determined, measures of detectability and warning such as false alarm rate and probability of detection, etc.).

Because of limited available funding, NOAA will not support studies under this funding opportunity related to the engineering design and development of infrasonic observing sensor hardware. Infrasonic sensors in the desired frequency range have been developed and are available commercially. NOAA would support the deployment of sensor networks and collection of such data in the approximate 0. 5-10 Hz near-infrasound range from existing sensors. We are most interested in the follow up analysis of that data, through comparison with historic archived infrasonic data and other available coincident meteorological observation data leveraged from the concurrent VORTEX-SE field campaign or other available environmental data, that could produce meaningful practical results for NOAA’s mission and improved understanding with limited funding over a two year time span.

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Projects appropriate for this competition would be at a Readiness Level (RL) ranging from RL 3 to RL 7 and have potential to transition to operations at NOAA or the weather and water enterprise within the next 3 to 7 years. NOAA Readiness Levels are defined later in this Section I.A.

6. Next Generation of Mesoscale Weather Observing Platforms

The National Academy of Science reports: Observing Weather and Climate From the Ground Up (2009), and The Future of Atmospheric Boundary Layer Observing, Understanding, and Modeling, Proceedings of a Workshop (2018) underscore the importance of improved observations of the lower atmosphere (a region that is not particularly well-sampled by satellites) to better understand and predict specific high impact weather events.

Currently, the relative absence of high-resolution planetary boundary layer profiles impedes progress to meet this societal need. Therefore, this funding opportunity will focus on research and development to advance the next generation of operational mesoscale weather observing platforms needed by NOAA and its partners in the weather and water enterprise.

Projects appropriate for this competition should be at a Readiness Level (RL) ranging from RL 5 to RL 7 and have potential to transition to operations with proper life cycle considerations at NOAA or other components of the weather and water enterprise within the next 3 to 5 years.

7. Snowpack and Soil Moisture Observations and Data Assimilation to Improve the National Water Model (NWM)

In the United States and around the world, water security is increasingly in jeopardy. Too much water, too little water, or water of poor quality can endanger life, property, economies and ecosystems. The societal impacts are underscored by the 126 fatalities and $10.9 billion damage from flash floods and river floods in 2016 (http://www.nws.noaa.gov/om/hazstats/sum16.pdf). Data from 1980–2018 (as of July 9, 2018), shows there have been 29 flooding events with losses exceeding $1 billion (CPI- Adjusted) each across the United States. During this same period there have been 25 drought events with losses exceeding $1 billion.

In this context, NOAA is embarking on a comprehensive effort to give people, businesses, and governments better access to the water information they need for their unique circumstances, so that they may take appropriate actions to address water-related risks and manage their water resources more efficiently and effectively.

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A cornerstone of this effort is the National Water Model (NWM) that was made operational in August 2016. The NWM is a collaborative effort among a number of academic and federal research partners. The basis for the NWM is the community-based Weather Research and Forecasting Model Hydrological modeling system (WRF-Hydro) framework developed by the National Center for Atmospheric Research (NCAR). The development and implementation of the NWM is the result of strong collaboration with NCAR and a partnership with the Consortium of Universities for the Advancement of Hydrologic Sciences, Inc., the National Science Foundation, and Federal Integrated Water Resources Science and Services partners. The NWM simulates the water cycle with mathematical representations of the different processes and how they fit together. This complex representation of physical processes such as snowmelt and infiltration and water movement through the soil layers varies significantly with changing elevations, soils, vegetation types and a host of other variables. Additional details on the NWM and WRF-Hydro can be found at http://water.noaa.gov/about/nwm and https://ral.ucar.edu/projects/wrf_hydro/overview.

Both snow depth (snow water equivalent) and soil moisture are important in the hydrologic cycle and as inputs to the NWM, but current measurements of both are spatially and temporally sparse and not well assimilated and parameterized into the physics of the NWM.

Improving the efficiency, effectiveness, and accuracy of obtaining, and applying these measurements will improve the outputs of the NWM and the benefits to society. For example, the importance of snowpack to the nation’s water budget cannot be overstated. In the Western U.S., 85% of freshwater runoff originates as snowmelt. In the Eastern U.S., nine of the most significant floods of the 20th century were directly related to snowmelt (https://www.weather.gov/news/162602-airborne).

Through this announcement, OAR’s Office of Weather and Air Quality (OWAQ) is soliciting proposals to support research and development that has a strong potential to improve the observations of snow depth (snow water equivalent) and soil moisture data that can be used and assimilated to expand and improve the NWM and contribute directly to the mission of NOAA's National Water Center.

Projects appropriate for this competition would be at a Readiness Level (RL) ranging from RL 5 to RL 7 and have potential to transition to operations with proper life cycle considerations at NOAA or the weather and water enterprise within the next 3 to 5 years.

8. Subseasonal to Seasonal

OAR seeks to fulfill the subseasonal to seasonal (two weeks out to two years) requirements

Federal Funding Opportunity Page 9 of 45 of the Weather Research and Forecasting Innovation Act of 2017. The program will address a spectrum of issues on the subseasonal to seasonal time frame at various stages of research readiness, and will advance predictive capability and understanding of precipitation on the subseasonal to seasonal scale, via:

-improved data assimilation especially coupled data assimilation including new observation types, -Earth system model processes for precipitation and high-impact events, -ensemble techniques, composition, and post-processing, including multi-model ensembles.

The portfolio will emphasize models and components in NOAA’s Unified Forecast System (UFS) and the North American Multi-Model Ensemble and ongoing multi-model ensemble efforts on the subseasonal to seasonal timescale. For proposals having equivalent scientific merit, preference will be given to projects working with NOAA’s UFS.

For additional program information on Subseasonal to Seasonal prediction and this competition, please review the supplemental Information Sheet for the Subseasonal to Seasonal competition in the grant package associated with this announcement at https://www.grants.gov.

NOAA Readiness Levels

The above NOAA program objectives for each of the eight competitions describe overarching science gaps that we are targeting to address with our external partners in the next five years. More specific targeted program priorities are defined in the following section. To achieve success with these objectives in the end, we must advance this funded science and technology from the research stage all the way to practical applications, operations, and commercialization as appropriate. Readiness levels (RLs), as adopted by NOAA and other federal agencies, are a means to broadly classify the technical maturity of a project using a numerical scale from 1 to 9 and a corresponding progressive spectrum from research to development to demonstration to deployment. These RLs are defined in NOAA’s Policy on Research and Development Transitions described in NOAA Administrative Order 216-105B at http://www.corporateservices.noaa.gov/ames/administrative_orders/chapter_216/216- 105B.html in the context of NOAA’s overall process for transitioning funded research into applications or operations or commercialization.

Regardless of whether your project outcomes are anticipated to be transitioned to NOAA applications, operations, or commercialization in the future, each proposal application submitted to one of the competitions listed above in this announcement must assess and

Federal Funding Opportunity Page 10 of 45 identify what is the current estimated RL for your proposed project and what will be the projected future RL upon project completion (see Sections IV.B.1(c) and IV.B.2(c)(4)).

OAR routinely tracks the advancement of RLs of all funded projects as a measure of how successful we are in advancing research to practical benefits to the public. Readiness levels are defined below.

RL 1 (Basic Research): Basic research, experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundations of phenomena and observable facts, without any particular application or use in view. Basic research can be oriented or directed towards some broad fields of general interest, with the explicit goal of a range of future applications.

RL 2 (Applied Research): Applied research, original investigation undertaken in order to acquire new knowledge. It is, however, directed primarily towards a specific, practical aim or objective. Applied research is undertaken either to determine possible uses for the findings of basic research, or to determine new methods or ways of achieving specific and predetermined objectives.

RL 3 (Development): Proof-of-concept for system, process, product, service, or tool; this can be considered an early phase of experimental development; feasibility studies may be included.

RL 4 (Development): Successful evaluation of system, subsystem, process, product, service, or tool in a laboratory or other experimental environment; this can be considered an intermediate phase of development.

RL 5 (Development): Successful evaluation of system, subsystem process, product, service, or tool in relevant environment through testing and prototyping; this can be considered the final stage of development before demonstration begins.

RL 6 (Demonstration): Demonstration of a prototype system, subsystem, process, product, service, or tool in relevant or test environment (potential demonstrated).

RL 7 (Demonstration): Prototype system, process, product, service or tool demonstrated in an operational or other relevant environment (functionality demonstrated in near-real world environment; subsystem components fully integrated into system).

RL 8 (Demonstration): Finalized system, process, product, service or tool tested, and shown to operate or function as expected within user's environment; user training and documentation completed; operator or user approval given.

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RL 9 (Deployment): System, process, product, service or tool deployed and used routinely.

B. Program Priorities

NOAA’s highest priorities for each of the eight separate competitions funded through this announcement are identified below. Applicants for a given competition below should clearly indicate and address in their proposal one or more of the associated priorities for that specific competition. Proposals not directly associated with one or more of these priorities are discouraged.

1. High Impact Weather Testbeds

The program priorities are listed below for each of the three testbeds funded through this testbed competition. Applicants should clearly indicate in their proposal the specific testbed(s) relevant to their proposal. Priorities that span multiple testbeds are listed below under the “Interdisciplinary Testbed Priorities” section.

Hydrometeorology Testbed (HMT) Priorities

HMT-1: Identify and validate new or improved methods, models, or decision support tools to improve probabilistic winter precipitation forecasts for snowfall amounts and/or ice accumulation, e.g., convection allowing models (CAMs) out to Day 3 and machine learning forecast tools. Improve the statistical reliability and spatial resolution of these probabilistic forecasts.

HMT-2: Identify and validate new or improved methods, models, or decision support tools to improve flash flood monitoring and forecasting, e.g. CAMs out to Day 3, machine learning forecast tools, or Weather Parameter in Context Tools. Improve the statistical reliability and spatial resolution of these probabilistic forecasts.

HMT-3: Identify and validate new or improved ways of enhancing forecaster use of probabilistic precipitation or ice accumulation short-range and medium-range forecasts, including 1) best practices for conveying the uncertainty inherent in these forecasts, including the possibility of different types of messaging for different time scales of meteorological phenomena and 2) assessing and communicating the likely impacts associated with these forecasts.

HMT-4: Identify and validate new or improved methods, observations, decision support tools, and models to improve understanding or evaluate forecast performance of extreme

Federal Funding Opportunity Page 12 of 45 precipitation events, from short-range forecasts extending into Week 2 forecasts.

HMT-5: Identify and validate new or improved methods, data assimilation, models, or decision support tools to improve utilization of precipitation forecasts and production of streamflow forecasts from NOAA’s operational National Water Model (both deterministic and probabilistic). This could include evaluation of the existing NWM.

Hazardous Weather Testbed (HWT) Priorities

HWT-1: Identify and validate concepts and techniques to improve NOAA’s convection-allowing/resolving ensemble forecast system performance from the rapidly updating, very short-term (next-few hours) through the next few days for tornado, large hail, damaging wind, lightning, and fire weather applications, including sensitivity to factors such as number of ensemble members, data assimilation methodology, experimental observation systems, scale-appropriate initial conditions and lateral boundary conditions perturbations, and physics diversity.

HWT-2: Identify and validate innovative post-processing and verification techniques for NOAA’s deterministic models and ensembles across spatial and temporal scales to create skillful and reliable probabilistic thunderstorm and severe hazard threat guidance from the very short term (i.e., next hour) through the Day 8 forecast period in support of the FACETs (Forecasting a Continuum of Environmental Threats) concept. In addition to developing reliable techniques, projects may include assessment of the limits to predictability for these hazards.

Joint Hurricane Testbed (JHT) Priorities

JHT-1: Improved operational analysis of the surface wind field in tropical cyclones, including the analysis of center location, the maximum sustained winds, and winds affecting elevated terrain and high-rise buildings; as well as guidance for changes in tropical cyclone size/wind structure and related parameters, including combined sea heights. Maximum wind estimation enhancements could include improved utility of microwave satellite and radar data, modernization the satellite-based classification system for monitoring subtropical cyclones (e.g., the Herbert-Poteat Technique), and improved techniques for estimating the intensity of tropical cyclones passing over and north of sea-surface temperature gradients.

JHT-2: New applications of ensemble modeling systems for track, intensity and structure forecasting, including development of guidance on targeting supplemental observations (e.g., synoptic surveillance) that take into account hurricane forecaster use as well as data

Federal Funding Opportunity Page 13 of 45 assimilation needs and dynamically-based wind-speed probabilities. These could include techniques for day 6 and 7 forecasts.

JHT-3: Improved tropical cyclone intensity guidance including the onset, duration, and magnitude of rapid intensification events; over-water rapid weakening events; as well as statistically based real-time guidance on guidance for track and intensity, which could include multi-model consensus approaches provided in probabilistic and other formats, and estimation of intensity error bounds. These could include techniques for day 6 and 7 forecasts.

JHT-4: Guidance for tropical cyclone genesis including the following: techniques or products to support pre-genesis disturbance track, intensity, size, and wind speed probability forecasts; guidance for tropical cyclone genesis at both the short-range (0-48 hours) and the medium-range (48-120 hours) that exhibits a high probability of detection and a low false alarm rate for, and/or provides probability of, genesis; and techniques to diagnose and predict the formation of tropical cyclones via transition of non-classical disturbances, e.g.

monsoon depressions, subtropicals, hybrids, etc., and to forecast track, intensity, and structure prior to tropical cyclone transition.

JHT-5: Advanced coastal inundation modeling and/or applications, visualization, or dissemination technology that enhances operational storm surge forecast accuracy or delivery.

JHT-6: Development of probabilistic wave height forecasts in tropical cyclones for a possible new public product geared toward the marine community.

Interdisciplinary Testbed (IT) Priorities

There are some priorities listed below that may span multiple testbeds among HMT, HWT, and/or JHT. If addressed in a proposal, it may benefit the proposed project if multiple testbeds were engaged where appropriate, though that is not required.

IT-1: (HMT and HWT) Identify and validate via quasi-operational testbed demonstrations new high temporal and spatial resolution in-situ and remotely-sensed observation datasets and dynamically consistent 3-D objective data analysis techniques to provide the best state of the current environment. This would lead to improve the detection, tracking, and analysis of severe convective and winter weather phenomena (tornado, hail, strong winds, precipitation type such as freezing rain, sleet, snow, etc.) and to support warning, nowcasts, and short-term forecasts for convective and winter weather hazards.

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IT-2: (HMT, HWT, and JHT) Apply and integrate relevant social and behavioral science methodologies into the above testbed priority areas to improve forecasters’ use of convection-allowing/resolving data, techniques, and guidance, as well as end-users’ ability to receive, assess, understand, and respond to forecasts and warnings for convective, tropical, and winter weather hazards, including understanding and messaging of probabilistic hazard information.

2. Joint Technology Transfer Initiative (JTTI)

JTTI-1: Improving numerical weather prediction modeling through data assimilation (DA), post-processing, and verification capabilities to include:

JTTI-1(a): Efforts leading to improvement of forecasting through advancement of improved assimilation of new and current observations. The assimilation techniques preferably include development and testing of hybrid Gridpoint-Statistical-Interpolation-based ensemble data assimilation techniques for convective scale models and ensembles. The data assimilation efforts should be able to integrate in the Joint Center for Satellite Data Assimilation’s Joint Effort for Data assimilation Integration (JEDI) system (http://www.jcsda.noaa.gov/). The new data sets may include in-situ data or remotely sensed data from ground-based, aircraft, unmanned aerial systems, space-based platforms, or high resolution cloud impacted radiances from current and future NOAA operational satellite such as GOES-16, GOES-17 and JPSS. Also solicited are DA efforts for ocean, sea ice and wind waves ("marine JEDI") both for initializing the corresponding model components, and for working toward coupled DA.

JTTI-1(b): Efforts leading to merging seamlessly the shorter and longer time scale modeling efforts in the Earth System Modeling Framework (ESMF) and Unified Forecast System (UFS) framework. The major presently-unaddressed gap identified in NOAA's capabilities is the assessment and development of high-resolution (10-13 km) global ensemble and DA capabilities. The central goal for NOAA to be addressed is to merge present 10-13 km operational models (GFS, RAP, NAM parent, SREF) into a coherent set of products and capabilities to enable convective scale modeling within the ESMF and UFS.

JTTI-1(c): Development, testing and evaluation of coupled model applications starting from presently-available coupled model prototypes for the UFS. Prototype coupled models presently available include various combinations of Atmosphere - Ocean - Ice - Wave coupling (FV3, MOM6, CICE5 and WW3), as well as wave-surge coupling (ADCIRC, WW3).

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JTTI-1(d): Development, testing and evaluation of high resolution ensemble post processing and verification tools for the prediction of hazardous weather associated with convective storms, such as significant rainfall, flash flooding, hail, and strong winds. Also post-processing efforts leading to development of forecast verification techniques and tools for convective scale storms based on comparison of forecasts with analyses and observational data sets. These verification efforts associated with such techniques and tools must be compatible with or integrated in Developmental Testbed Center's (DTC) Model Evaluation tools (MET) (http://www.dtcenter.org/met/users/).

JTTI-2: Improving water prediction capabilities to include efforts to enhance hydrologic prediction through improved data assimilation and model extension for hydrological data sets into the NWS National Water Model (NWM) or other operational hydrologic model (e.g. HEFS) used at NOAA. These data sets include rainfall, snow, soil moisture, stream flow, and groundwater. Additionally, high RL capabilities to post-process model output in order to estimate flood extent and depth are encouraged.

JTTI-3: Improving extreme precipitation forecasting to include:

JTTI-3(a): Develop, test and evaluate improved methods, models, or decision support tools to advance prediction of extreme rainfall events, including the application of convection-allowing and ensemble modeling approaches, artificial intelligence, and statistical forecast tools.

JTTI-3(b): Develop, test, evaluate improved methods, models, or decision support tools to advance prediction of winter precipitation events (snow/ice accumulations, precipitation type transitions, cyclogenesis), including the application of convection-allowing and ensemble modeling approaches, artificial intelligence, and statistical forecast tools.

JTTI-3(c): Improved techniques to assess and quantify forecast uncertainty during the forecast process, and assess end user understanding of this uncertainty output.

3. Air Quality Research and Forecasting

A NOAA-sponsored workshop on the future direction of air quality forecasting research in November 2014 and other related workshops, publications, and operational forecasting experience over the past five years have identified the highest priority air quality forecasting science gaps that need to be addressed to improve NOAA air quality forecasting services over the next 5-10 years.

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AQRF-1: Development and evaluation of high-resolution (1-4 km) air quality forecast capabilities that are consistent with NOAA weather forecast models at these resolutions, including two-way coupled models, for representation of local phenomena such as fine-scale processes in coastal region, over complex terrain, or in urban areas, especially those that take advantage of recent air quality field experiments.

AQRF-2: FV3 model-driven meteorological predictions will be used by NAQFC with on-line coupling in the near future. This future NAQFC system comprised of FV3 with an on-line EPA chemistry model should be developed and evaluated for both the warm and cool seasons for likely occurrence of poor air quality episodes. Investigations into the impact of use of the FV3 model with basic and advanced physics options are encouraged along with better understanding and improvement of model performance over urban, rural, mountainous and coastal areas.

AQRF-3: Improved spatial and temporal estimates of anthropogenic and natural pollutant emissions, including wildfire smoke and dust and other potential sources of model biases, using NOAA satellite remote sensing and other data sources

AQRF-4: Explore and quantify the potential value of ensemble model approaches and post processing to operational air quality forecasting

AQRF-5: Improved model representation in the FV3 model of physical/chemical processes for long range transport including lateral boundary conditions for regional models and regional/local phenomena for improvement in skill of ozone and fine PM forecast guidance

4. VORTEX-SE

Priorities for VORTEX-SE are established by considering input from a Scientific Steering Committee and through participation of the broader research and operational community in annual workshops and an online community forum. The forum can be joined at https://vlab.ncep.noaa.gov/web/vortexse, and the latest version of the Science Plan is available at http://www.nssl.noaa.gov/projects/vortexse/science2018.pdf. The VORTEX-SE program priorities, briefly described here, can be found in more detail in the competition Information Sheet in the grant package associated with this announcement at https://www.grants.gov.

VORTEX-SE-1: Storm processes affecting tornado potential. Processes that are associated with the occurrence of non-classical tornadoes (e.g., QLCS, convective clusters, embedded

Federal Funding Opportunity Page 17 of 45 supercells, etc.) continue to be of special interest in the VORTEX-SE. This topic includes radar-based climatology studies of these events and their signatures and precursors in conventional and polarimetric radar data. Observational studies utilizing already-collected VORTEX-SE data are encouraged, as are numerical simulation studies. No funds are available for new field observations via this competition; see the VORTEX-SE Information Sheet for details regarding possible future observing campaigns.

VORTEX-SE-2: Clarification of the scales and character of mesoscale processes that are associated with forecast uncertainty on all operational time scales. For example, 1) numerical studies using approaches such as Observing System Simulation Experiments (OSSE), Ensemble Sensitivity Analysis (ESA), data denial experiments, etc. to help inform future observation needs for both fundamental research and efforts to improve numerical prediction; 2) verification of the importance of variations in CAPE, thermodynamic stability, and vertical wind shear on scales of considerably smaller than 200 km in ways that locally enhance tornado potential in otherwise more benign-appearing environments. Use of data collected previously in VORTEX-SE, and during the November 2018 - April 2019 “Meso18-19” field campaign, is strongly encouraged.

VORTEX-SE-3: Studies of the interactions of the co-evolution of draft structure, radar and satellite signatures, and lightning flash character and frequency (e.g., using LDM and/or LNA data) in potentially tornadic storms.

VORTEX-SE-4: Tornadoes in landfalling tropical cyclones (LTC). To lay the groundwork for possible future field observations, we seek improved understanding of the antecedent environments that support tornadoes in the convective bands of LTCs and LTCs transitioning into extratropical cyclones.

VORTEX-SE-5: Understanding and reducing societal vulnerability to tornadoes. This topic has three main emphases that are of a strongly interdisciplinary nature: 1) investigating how physical, social, and economic factors interact to contribute to harm from tornadoes in the Southeast, and which intersections of factors are the most important contributors in different local and household circumstances; 2) understanding different populations’ capacities and current practices that can be utilized and leveraged to alleviate vulnerabilities and reduce harm from tornadoes in the Southeast; and 3) understanding the factors and decisions that enhance individual survival of tornadoes under different circumstances.

VORTEX-SE-6: Research on operational NWS and partners’ forecast and warning decision-making process, and public response. The two main emphases in this topic are 1) investigating forecasters’ interpretations and use of different types of information in

Federal Funding Opportunity Page 18 of 45 decisions about whether, when, and how to issue warnings and other products; and 2) understanding how probabilistic hazard and warning information affects the forecast and warning process and information gaps that contribute to uncertainty and challenges in decision making.

VORTEX-SE-7: Risk communication, risk perception, and information use in protective decision making (with a focus on members of the public and other end-users). This topic has three primary emphases: 1) understanding the interpretations and uses of probabilistic hazard information, warnings and other information by different members of the public in different circumstances; 2) understanding the perception, use, and interpretation of tornado information prior to and during the concurrent hazard scenarios of landfalling tropical cyclones; and 3) investigating intersections among information, vulnerabilities and capacities, and protective decision making.

5. Infrasound Detection of Tornadoes and High Impact Weather

The following program priorities are among the most important activities that NOAA would support to help demonstrate the potential value of infrasound technology for tornado understanding, detection, and warning, especially when applied to the Southeast U. S.

Collection and analysis of new infrasonic data for strong and weak tornadoes in the Southeast U. S. during the project period are highly encouraged.

Infrasound-1: Demonstrate how infrasound information can enhance tornado threat predictive capability of the NWS (e. g., size, strength, lead time, location, etc.). The operational benefits to the NWS of infrasound for the detection and warning of tornadoes (including tornadoes from landfalling hurricanes) to improve warning lead time have been evaluated in the early 2000’s in coordination with NWS forecast offices in Colorado and Kansas but have not been fully studied. Working or partnering with NOAA or other meteorologists, in particular NWS Weather Forecast Office science personnel, is highly encouraged during the course of the project so that operational weather forecasters can evaluate the potential future benefits of this technology.

Infrasound-2: Measure infrasound from tornadic storms also scanned with Doppler and polarimetric radars and observed by lightning sensors and storm chasers and compare the data to relate the infrasound characteristic to the physical attributes of tornadoes deduced by these observations and to identify the radiating mechanisms responsible for infrasound generation. The physical mechanisms in tornadic thunderstorms that might generate these acoustic waves is uncertain but has been postulated to be caused by various sources, including radial vibration processes of the vortex core, flow instabilities, and corotating

Federal Funding Opportunity Page 19 of 45 multiple vortices. Past studies suggest some ability to determine vortex size and strength based on the frequency of the infrasound. Comparison with Doppler radar data is encouraged to confirm that infrasound signals attributed to tornadoes are indeed associated with radar-observed mesocyclone and/or tornado circulations and/or actual observed tornado tracks.

How can the physical generating mechanism (e.g., tornadoes) be definitively identified, and how can false alarms from non-tornadic sources be identified and reduced to make sure that a tornado source is being isolated from other irrelevant sources?

Infrasound-3: Study infrasound propagation in complex atmospheric environments associated with severe weather (e.g., with outflow boundaries, mesocyclones, high shear) and in regions of complex terrain to determine detectability efficiency by ground networks.

Past studies have focused on the high plains of Colorado and not in other diverse regions of the U. S. such as in the Southeast U. S where complex terrain and potentially complex ducting environments may have important effects on infrasound propagation and detection by ground-based observing networks.

Infrasound-4: Collect infrasonic data during VORTEX-SE observational field campaigns and other times and to leverage other existing ancillary environmental observations collected and funded through other sources.

Infrasound-5: Develop improved algorithms for real time processing of infrasonic data and subsequent display that present infrasonic data in quickly-accessible forms that can be easily interpreted by operational meteorologists.

6. Next Generation of Mesoscale Weather Observing Platforms

Mesoscale weather observing-1: Advancements in land-based remote sensing technologies and UAS based technologies are desired for mesoscale weather observing platforms.

Specifically technologies that characterize boundary layer vertical profiles of water vapor, temperature, pressure, and winds, and the use of these observations with in-situ observations to obtain an optimal mix of observations to improve the detection and prediction of high-impact / disruptive weather events.