Total of Funding Awarded $2.5M per year – Eleven Selected Projects
Observations from the surface through the troposphere serve as critical inputs for the analysis and forecasts of the operational weather enterprise for the protection of life and property and enhancement of the national economy. Given that the relative scarcity of high resolution surface and planetary boundary layer/tropospheric observations impedes progress in skillful predictions of high-impact and disruptive weather, the Observations program aims to fund research that focuses on technologies with the potential to improve the accuracy, reliability, spatial coverage, cost effectiveness, deployability, safety, and sustainability of observations for eventual use by the operational weather enterprise including NOAA, the National Mesonet Program, the private sector, and other government sectors.
For the FY23 WPO Observations Program competition, eleven observations-focused projects were selected for funding. These projects aim to develop, demonstrate, and/or analyze innovative sensor and observing technologies and strategies that have high potential for advancing an observation systems portfolio that is mission-effective, integrated, adaptable, and affordable.
The WPO Observations Program, in collaboration with the NWS and other NOAA stakeholders, developed the following six priorities:
- Analyses of existing weather observations
- Analyses of gaps in current observations
- Fire Weather
- Mesonet Boundary Layer Observations
- Tropical Cyclone Observations
- Innovative observing technologies including observations of opportunity
The total of funding awarded* for the eleven selected projects is approximately $2.5M per year for this competition. Projects may be for up to two years, with up to $300,000/year. Two-year projects will begin August 1st, 2023.
*Award totals are distributed over the life of the projects and conditional on appropriations
Projects Selected
| Project Title | PI’s /Co-PI’s | Project Description |
|---|---|---|
| Supporting NWS Post-Fire Flash-Flood Warnings with Multi-Sensor Burn Scar Mapping | Sam Batzli (SSEC/CIMS/University of Wisconsin-Madison) PI Javier Villegas Bravo (CISESS) Co-PI Roger Michaelides (Washington University in St. Louis) Co-PI | This award will leverage existing satellite sensors, including Visible Infrared Imaging Radiometer Suite, Geostationary Operational Environmental Satellite-R, Series Advanced Baseline Imager, and Sentinel-1A C-Band Synthetic Aperture Radar to develop prototype burn scar mapping products. These products will be near real-time, data-fused, gridded products that can be tested in Geographic Information Systems and web map services. They will address the immediate need for better burn scar maps to help forecasters issue timely warnings for post-fire flash flooding. |
| Adjusting Aircraft Wind Observations to 1-minute Sustained Winds for Improved Analysis of TC Intensity and Structure | Heather Holbach (Florida State University/COAPS) PI Mark Bourassa (Florida State University/COAPS) Co-PI | This award will focus on improving the interpretation of the various wind speed data obtained by instruments mounted on the NOAA WP-3D hurricane hunter aircraft (flight-level, Stepped-Frequency Microwave Radiometer, Tail-Doppler Radar, and dropsondes). It will determine how the wind speeds measurements from each of these instruments can be adjusted to a 1-minute sustained wind that matches a standard. Forecasters can compare the aircraft data when analyzing hurricane intensity and structure more accurately and forecast models can utilize the new method by applying the adjustments to aircraft wind speed data being assimilated. |
| Venturing into the Vertical: Optimizing Boundary Layer Profiling in Mesonets | Joshua Gebauer (CIWRO/OU) Lead PI Tyler Bell (CIWRO/OU) PI Antonio Segales (CIWRO/OU) PI Elizabeth Smith (NSSL) PI | This project will perform observing system simulation experiments to study the optimal design of a 3D mesonet. It will use the results of the observing system simulation experiments to design and test field deployments of existing boundary layer profiling instrumentation, i.e. CopterSonde uncrewed aerial system and Collaborative Lower Atmospheric Mobile Profiling System 2, to prototype a 3D mesonet during high-impact weather. |
| Application of Machine Learning Techniques to the Automated Quality Control of Airborne Doppler Radar Data Used in Operational Analysis of Hurricane Winds and Reflectivity | Michael Fischer (University of Miami/CIMAS) PI Michael Bell (Colorado State University/CIRA) Co-PI | The project will train the radar machine learning quality control methods to find the best approach to improve present NOAA Tail Doppler Radar data, and to find a method that can most rapidly be applied to new radar systems, in particular the Airborne Phased Array Radar that is the proposed radar to be mounted on the aircraft replacement of the NOAA WP-3D aircraft. It is crucial that NOAA adapt quickly to avoid temporary loss of this important operational data set when new radar systems, such as the possible Airborne Phased Array Radar system, come online when the NOAA WP-3D are retired and replaced. |
| Pilot Upgrade of NOAA NDBC Coastal Weather Buoys for Improved Monitoring of Weather and Climate Principal Investigator | Yolande Serra (CICOES/University of Washington) PI Karen Grissom (NOAA NDBC) Co-PI Meghan Cronin (NOAA PMEL) Co-PI | This award is to design a prototype operational NOAA National Data Buoy Center Coastal Weather Buoy that measures collocated subsurface and surface variables in real-time and provides quality controlled data capable of characterizing air-sea interaction and subsurface ocean heat content and mixed layer variability in the Gulf Stream extension region. |
| Building a Comprehensive Capability in Operational HAFS to Assimilate All Available Tropical Cyclone Inner-Core Observations | Altug Aksoy (University of Miami/CIMAS) PI | The proposed effort for this award to develop a comprehensive capability to acquire, preprocess, quality control, and assimilate all tropical cyclone inner-core aircraft observations in the NOAA Hurricane Analysis and Forecasting System (HAFS). It will improve existing preprocessing, quality control, and thinning/superobbing capabilities to ultimately improve the NOAA HAFS tropical cyclone inner-core data assimilation capabilities and work to add a new capacity to the system. The current NOAA operational model Hurricane Weather and Research Forecast (HWRF) system will be replaced with the HAFS in 2023. |
| Real-time Visualization and Interpretation of the Hurricane Wind Structure and Intensity: From Flight Level to the Surface | Zorana Jelenak (UCAR) PI Heather Holbach (Florida State University/COAPS) Co-PI Altug Aksoy (University of Miami/CIMAS) Co-PI | The project team will utilize the Imaging Wind and Rain Airborne Profiler 3D wind and reflectivity measurements together with the Flight level, Stepped-Frequency Microwave Radiometer, Tail Doppler Radar, and Global Positioning System dropsonde wind observations to improve estimates of storm structure and intensity by 1) providing near real time tools to assess the differences, uncertainties and quality of data between sensors 2) providing new rain estimates and 3) quantify the impact of the unique fine resolution Imaging Wind and Rain Airborne Profiler wind and reflectivity 3-dimensional profiles. |
| Evaluating and Integrating Black Globe Temperature Observations into Operational WBGT Forecasts | Sheila Saia (NC State Climate Office/NC State University) PI | The proposed effort for this award aims to improve the regional National Weather Service forecasts and National Digital Forecast Database wet bulb globe temperature forecasts to ultimately enhance extreme heat risk forecasts across the United States. |
| Development of Real-Time Multistatic Passive Radar Networks for Severe Weather Prediction | Patrick Skinner (CIWRO/OU) PI David Schvartzman (ARRC/OU) Co-PI David Bodine (ARRC/OU) Co-PI Samuel Emmerson (ARRC/OU) Co-PI Pierre Emmanuel Kirstetter (ARRC/OU) Co-PI Caleb Fulton (ARRC/OU) Co-PI Robert Palmer (ARRC/OU) Co-PI Todd Lindley (NOAA NWS WFO Norman, Oklahoma) Co-PI | The award aims to leverage recent technological advances for producing low-cost passive bistatic radar receivers to deploy two 5-receiver, multistatic radar networks with the Norman and Tulsa Weather Surveillance Radar-1988 Doppler sites in Oklahoma. This will enable observation and retrieval of the 3D wind field in convective storms over a broad region, greatly expanding the observing capabilities of the Weather Surveillance Radar-1988 Doppler sites. |
| Assessment of the impact of New York State Mesonet profiler network and new profiling instruments on the skill of high impact weather predictions in New York State | Tammy Weckwerth, NCAR/EOL PI Junkyung Kay (NCAR/EOL) Co-PI James O. Pinto (NCAR/RAL) Co-PI Junhong Wang (NYS Mesonet/University at Albany) Co-PI | The objectives of this work are to conduct a series of Observing System Experiments and Observing System Simulation Experiments to evaluate how the current New York State Mesonet impacts the skill of high impact weather prediction and to explore the potential benefits of adding new profiling capabilities (e.g., MicroPulse Differential absorption lidar and Uncrewed Aircraft Systems) and/or new stations to the existing New York State Mesonet profiler network. |
| Maturation of a Standalone Aircraft Derived Atmospheric Observation System for Improved Operational Forecasting | Michael McPartland (MIT Lincoln Laboratory) PI Jason English (Colorado State University/CIRES) Co-PI | The proposed effort will build upon the accomplishments of a previously NOAA-funded effort to develop and demonstrate a low-cost, standalone Mode S Enhanced Surveillance aircraft derived atmospheric observation system for enhanced weather forecasting and improved and expanded boundary layer observations. |
