Q A_1.pdf

SBIR 2016-1

Questions and Answers #1 October 23, 2015

Q: Can we receive the White Paper mentioned in Subtopic 8.4.1W?

A: A copy is attached.

In order to ensure fair competition, all communication must be routed through the CO to ensure all potential offerors receive the same information.

Executive Summary

As an agency within the National Oceanic and Atmospheric Administration (NOAA), the National Weather Service (NWS) is evolving to better support a WeatherReady Nation. This evolution requires a shift from text products and one-size-fits-all information to customizable, up-to-date information that meets the variety of decision needs of a variety of decision-makers. It requires more accurate and timely forecasts and warnings that provide location-specific information needed for the decisions being made. An exciting new technology may improve the services the NWS provides to decision-makers.

Small unmanned aerial vehicles (UAVs) can fly video camera equipment and weather sensors, at low altitudes, providing meteorologists with information not previously available to them that can be critical for providing better decision-support services. From more accurate high-resolution model output leading to customizable warnings, to better information for fire weather, aviation, or marine support, to research that supports improved forecasts and warnings, the data provided by a small UAV could further NWS efforts to achieve its two-pronged mission of protecting life and property and enhancing the national economy.

This document illustrates the many potential applications of small UAVs to the NWS mission, and a methodology in which this effort can be accomplished.

Introduction

The National Weather Service (NWS), an agency within the National Oceanic and Atmospheric Administration (NOAA), is on an evolutionary path in support of a WeatherReady Nation (NWS 2013).

This effort aims to develop a more weather resilient nation better prepared to respond to, and recover from, natural disasters such as tornadoes, hurricanes, floods, and winter storms.

The focus of the WeatherReady Nation evolution, within the individual Weather Forecast Office (WFO), is Decision-Support Services (DSS), the means of providing critical information in support of a variety of decisions made by a variety of decision-makers. DSS requires an operational shift at the WFO, from simply generating forecast and warning text products that present one-size-fits-all information that is updated as needed, to customizable, always up-to-date threat information, in a form that customers can understand and base decisions on. This includes a shift from:

- an average forecast for the day, to hourly forecast trend information;

- warning information that everyone gets, to customizable, location-specific information that includes time of threat for a location, and potential impact; and

- a focus on large-scale global computer forecast models, to high-resolution, impact-focused models.

One of the most significant advances in support of accurate DSS is high-resolution short-term numerical weather prediction models, such as the HRRR and the NARRE (Fig 1). These models can predict a variety of hazards hours in advance. However, their accuracy can be dependent on the data ingested into the models.

The NWS acquires weather data at surface stations every hour, 24 hours per day. Aloft, however, data are only collected twice per day through radiosondes connected to weather balloons (Fig 2).

The problem is that hazard environments can change rapidly, both in time and space. Without environment measurements prior to hazard formation, meteorologists are left to depend on computer model forecasts, which incorporate satellite and radar data as well as surface observations.

When the model accurately predicts hazard environment, it can produce an accurate hazard-related forecast utilized for DSS efforts. Otherwise, the model may not accurately predict the hazard, impeding DSS efforts.

For other efforts, from damage surveying, to flood/surge inundation mapping, to fire weather support, there is clear value in acquiring data from above to improve DSS efforts.

Small Unmanned Aerial Vehicles

A new technology has been developed over the past decade that aims to meet the data requirements of the NWS in providing effective decision-support services (DSS) to decision-makers. Small unmanned aerial vehicles (UAVs), loaded with either a video camera or weather sensor payload, which can fly at low altitudes, could accomplish many of these requirements.

NOAA has previously demonstrated value of large UAVs (e.g. Predator) in research associated with hurricanes. These craft, however, are prohibitively expensive when it comes to smaller-scale applications of value to agencies within and associated with NOAA, and with respect to UAV commercialization. Numerous manufacturers of small UAVs have formed, yielding a broad scope of potential small craft. One example is Prioria Robotics, Inc, a company in Gainesville, Florida that manufactures two key UAVs, the Maveric fixed-wing UAV (Fig 3), and the Hex vertical-takeoff-or-landing (VTOL) UAV (Fig 4). These types of craft could carry payloads to achieve NWS- or NOAA-related missions.

Achievable NWS Requirements Using Small UAVs

There are numerous data requirements for the NWS that could be achieved using small UAVs. The following is a lengthy, but not necessarily a complete, list of potential utilizations.

1) More complete/accurate storm damage surveys.

This would be particularly useful in rural areas with few roads which make ground surveys difficult.

Aerial surveys yield much more accurate results more quickly than ground surveys where roads may not intersect a damage path.

2) Better river flood and storm surge inundation mapping using more recent topographic data utilizing LIDAR.

We presently utilize data that are several years to perhaps a decade old. Having the latest information can support high-resolution inundation mapping which we are presently exploring.

LIDARs are becoming light enough and inexpensive enough to include as a payload on a small UAV for topographic mapping.

3) Acquiring low-level temperature/moisture information for improved short-term winter storm (precipitation-type) forecasts.

Accurate high-resolution model forecasts require more frequent low-level thermal/moisture environment analyses than the twice/day radiosondes provide. More accurate short-term forecasts of precipitation-type changeover are critical in decision support, and could be achievable through frequent UAV low-level environment measurements of temperature and humidity.

4) Acquiring low-level environment information more frequently, in support of higher-resolution model forecasts of severe thunderstorm and tornado potential.

Storm environments can change rapidly in time and space, as demonstrated with NOAA’s prior Wind Profiler Demonstration Network. Having shear information is critical for determining tornado potential. While WSR-88D radars provide vertical wind profile information, it has accuracy issues, and is lacking prior to storm development.

5) Acquiring low-level environment information more frequently, in support of higher-resolution model forecasts of excessive rainfall and flooding.

Environments supporting excessive rainfall and floods depend on certain environmental conditions.

More frequent low-level environment analyses support better high-resolution model output that thus support more timely and accurate forecasts/warnings.

6) Potential utility for monitoring boundaries that may lead to thunderstorm initiation, especially in situations when satellite view is blocked by high cloudiness.

It may be possible to discriminate between boundaries likely to initiate new thunderstorms and those that do not. In addition, lightning potential can be more accurate discerned with better low-level temperature and moisture data (relating to atmospheric instability and potential thunderstorm depth above the freezing level).

7) More frequent low-level environment analyses for more accurate high-resolution model forecasts in support of NWS Decision Support Services prior to and during high-impact events (e.g.

hazardous materials spill).

The future of the NWS focuses on decision-support, including on-site support. UAVs could provide critical local area (and upstream area) information to provide better decision-support guidance to the key partners of the NWS (e.g. emergency managers, other government agencies, etc.).

These data may help improve short-term high-resolution computer model output, that can support better short-term forecasts and warnings. A key example is “Warn-On-Forecast”, a methodology of utilizing high-resolution convective models to help extend threat lead times for severe thunderstorms and tornadoes. Frequent low-level environment analyses are critical to the accuracy of the model output used for short-term forecasts and warnings.

8) Improved aviation forecasts of low conditions at times when satellite view is blocked by high clouds.

UAVs could provide critical above-surface information at times when satellite data are not helpful, leading to more accurate aviation forecasts for aviation decision-makers.

9) Wildfire support…both environment information to provide better support with respect to the spread of wildfires and smoke, as well as wildfire imagery for Incident Command.

Currently, IMETs bring surface observation equipment when providing wildfire support. Having a means to collect data above the ground may be critical for HYSPLIT/CAMEO/ALOHA modeling of fire/smoke/fume spread. In addition, video cameras can help fire crews better assess fire spread, to better place resources out of harm’s way.

10) Research-to-Operations…serve as a tool for improving our understanding of, and modeling of, meteorological phenomena.

This is a wide-ranging item for better understanding what we try to model/predict. For example, a research study on why some boundaries (e.g. outflow boundaries, sea breezes) generate convection, while others do not, in seemingly similar environments.

11) A beneficial tool for the ecological realm that the NWS is evolving toward (e.g. red bloom monitoring).

Collaborative partnerships between multiple NOAA agencies are achievable with UAVs. The NWS is starting to explore these avenues.

12) A potential tool for rip current monitoring, swell assessment, even last-minute tsunami threat assessment.

Our office has lost most of its buoys…making it difficult to assess swell and rip current hazard, which is the greatest weather-/water-related source of loss of life in the JAX area of responsibility. UAVs could allow the NWS to monitor swell conditions just offshore, and provide more accurate beach hazard forecasts.

13) Possible tool for monitoring river conditions for improved river flood forecasts.

This can be particularly valuable in situations with multiple crests…initial crests can lead people to assume a threat has ended, when a greater crest is still upstream. We presently do not have enough river observation equipment deployed to know where/when these additional crests (from delayed runoff) will occur.

14) Better assessment of river (lake) ice to improve forecasting of ice jam freeze-up and break-up potential.

This could lead to improved warning information of floods caused by ice jams.

15) Assessment of road conditions during and shortly after a weather event.

After winter weather or excessive rainfall events, road conditions are important to people. While reports of road closures or weather-related road impacts are relayed by law enforcement and DOT to the NWS, the extent of the issues would be better revealed through UAV imaging.

16) Potential tool for visually assessing landslide/avalanche potential in areas of terrain.

While some measurements are available for the NWS, a larger-scale view from UAVs may be more valuable.

17) Wildfire burn scar evaluation for evaluating flood and mudslide potential.

Burn scars left by large wildfires contribute to an increase risk of flash floods and mudslides. While large burn scars can be evaluated using satellite data…small UAVs can assist in evaluating small-scale scars.

18) Evaluating structural integrity of levee’s and earthen dams.

In partnership with other agencies (e.g. Emergency Management, USGS), small UAVs could be utilized to evaluate the structural integrity of a levee or dam to make better flash flood warning decisions for communities with sufficient lead time to take protective action.

19) Improved forecasts where observation data are missing (e.g. impacts of rivers/lakes on temperature and wind forecasts over adjacent land areas, and monitoring wind/wave conditions on inland lakes).

The NWS designs a gridded forecast database that supports customizable forecast information for decision support. This includes location-specific information. In areas where no surface observation data are available, the accuracy of these forecasts for those locations is unknown. UAVs could be utilized to evaluate thermal and moisture differences in these areas compared to areas where surface observation equipment are available, leading to better location-specific forecasts in data-void areas.

20) Possible low-level air quality utilization for UAVs.

The air quality program is a new one for the NWS. UAVs could provide beneficial low-level environment information in support of air quality forecasts…in a partnership with local governments.

21) Potential monitoring of conditions that promote dense fog, and smoke/fog combos, that generate dangerous conditions on highways/interstates.

Predicting dense fog vs. heavy dew is a present-day weather challenge, and usually relates to moisture depth through a shallow layer above the ground. Computer models are not very good at predicting this, as they may mishandle shallow moisture depth. UAV data just above the ground may help forecasters discriminate between heavy dew environments and dense fog environments.

This utility could allow response by law enforcement/DOT to prevent accidents/fatalities when these conditions occur. The conditions can be difficult to see at night on satellite imagery, especially when blocked by a layer of high-level cloudiness. UAVs could be used to assess road conditions.

22) Determining the accuracy of questionable weather observation data (e.g. from non-NWS sources).

Some surface observation data are not owned by the NWS, and can be of questionable accuracy. Bad data can lead to erroneous analyses and short-term model forecasts. UAVs might provide a means to evaluate the accuracy of these observations, compared to NWS observation sites, and allow forecasters to remove bad data from being used in numerical model forecasts.

23) Satellite and Radar Data “Truthing” for small-scale features.

Satellite data are more reliable for detecting large-scale vs. small-scale features. Small UAVs could be utilized to confirm what satellite data suggest. Radar data only show conditions above the ground.

Small UAVs could be used to confirm conditions at the ground resulting from the weather hazards indicated by radar imagery.

24) A tool for collecting before and after damage imagery.

This could be beneficial for areas in the path of a tropical cyclone, and even a “derecho” (large convective wind-producing system).

25) Better area-of-responsibility assessment for new employees of a given office.

It is critical for a new forecaster to understand their area of responsibility, including creeks that are flashy in nature, areas particularly susceptible to flood or storm surge inundation, etc. Imagery of terrain, key topographic features, key problem areas (e.g. levees) and more could be valuable information to new forecasters.

Benefits of Small UAVs to the NWS

Most of the above requirements are achievable with a small UAV that can ascend up to a level of 1,000 to 1,500 ft (although reaching a level of 3,000 to 5,000 ft would be even more advantageous), and return to its launch point, making the vehicle and its payloads re-usable. For NWS applications, the UAV would carry the following payloads, either together or interchangeably:

- Video camera that records ground-level imagery from a height of up to 400 ft AGL;

- Weather sensor package that records data up to at least 1,000 to 1,500 ft AGL; and

- Other useful payloads (e.g., LIDAR).

The NWS could achieve many mission-related benefits from utilizing small UAVs, such as:

- much more accurate storm damage surveys;

- improved river flood forecasting by recognizing inundation from multiple crests, and providing more data input for river forecast models;

- greater data input into more frequently run, high-resolution models;

- ability to evaluate the accuracy of questionable observation data (particularly from non-NWS sources); and

- research that could support improved operations, such as improved understanding of why some boundaries generate thunderstorms and others do not, despite being in similar environments.

In addition, there are some utilizations that can support multi-agency collaborations, be it within NOAA, or with others such as the Department of Transportation, regional or local Emergency Management agencies, etc.

Cost-Effective UAV Solutions for the NWS

Small UAVs can range substantially in price, from under $10,000 to over $70,000. While the upfront cost may be substantial, the operating costs in subsequent years would be small due to:

- the re-usable nature of the payloads; and

- UAV lifespan of at least 5 years.

In addition, the ease of transporting these resources to where they are needed can reduce the NWS UAV requirement from 240 UAVs (considering 2 per unmanned aviation system for each of 120 field offices), at a cost of $12-18 million, to a shareable resource of 40 UAVs (for 20 unmanned aviation systems) at just one-sixth of the cost ($2-3 million). The ability to share resources with other agencies and organizations could also reduce the cost burden to any one agency or organization.

The real value is seen in the national economic savings resulting from improved DSS (e.g. not closing a business, when located within a warning area, but not directly in the path of the hazard). For the improvement in the short-fuse warning program with the change from “county-based” to “storm-based”, which reduced warning area where no threat existed by over 70%, one study demonstrated potential economic savings of at least $100 million per year to U.S. citizens (NWS 2007). Savings of at least that amount could be expected by acquiring the observation data necessary to support the high-resolution models to be used in the future “Warn-on-Forecast” initiative that aims to increase warning lead times up to an hour. Efforts that reduce closures of businesses, airports, schools, etc., where no imminent threat exists, would dramatically support the additional mission of the NWS in “enhancing the national economy”.

The Need for a Full Demonstration of Small UAV Capabilities

The potential benefits to the NWS, and to the customers the agency serves, are numerous and substantial enough to support a large-scale demonstration of the capabilities of small UAVs. They have been demonstrated on numerous occasions with respect to low-altitude imaging. Further investigation, and UAV design refinement, will be needed to demonstrate capability of flying at altitudes of 1,000 ft AGL and higher, within conditions such as heavy precipitation, icing, and stronger turbulent flow that may reach or exceed 40kts, to record observations above the ground. The demonstration would evaluate:

- Air worthiness of the UAV in carrying a given payload to a given height;

- Ability to collect the needed data and return it to the launch site;

- Ability to efficiently relocate the UAV to alternate locations; and

- Demonstration of cost-effectiveness for the NWS.

References

NWS 2007: Storm-based Warnings Team Report. U.S. Dept. of Commerce. 45pp.

[Available online at http://www.nws.noaa.gov/sbwarnings/docs/Polygon_Report_Final.pdf .]

NWS 2013: National Weather Service Weather-Ready Nation Roadmap.

http://www.nws.noaa.gov/com/weatherreadynation/files/nws_wrn_roadmap_final_april17.pdf

Figures

Figure 1. Comparison of HRRR model radar reflectivity forecast vs. radar observation for a severe thunderstorm line event in the Mid-Atlantic region. (source: USAToday.com)

Figure 2. Example of a balloon launch with a radiosonde. (source: NOAA)

Figure 3. Maveric UAS, from Prioria Robotics, Inc. (source: http://www.prioria.com/maveric/ )

Figure 4. HEX UAS, from Prioria Robotics, Inc. (source: http://www.prioria.com/hex/)