PCAR Pilot Grants

PCAR Pilot Grants enable UMass scientists to create new collaborations in atmospheric research.

Current Pilot Grants

PCAR funded the first round of pilot grants in the spring of 2024. A solicitation for a new round of Pilot Grants will be issued in the Fall of 2024.

Apply for a Pilot Grant!

Spring 2024 Pilot Grants:

The following projects were selected in the initial  round: 

Piloting a Global Water Use Estimation routine using Remote Sensing and Deep Learning 

Casey Brown1, Colin Gleason1, Kostas Andreadis1, Jay Taneja2  
1College of Engineering 
2College of Information and Computer Science  

Growing water scarcity amid a changing and variability climate imperils food supply systems, domestic water supply and aquatic ecosystems around the world. The problem is a fundamental mismatch between water demand, a function of societal choices, and water supply, a function of the earth’s climate system. The PIs propose to directly address this problem by leveraging advances in machine learning and the recently launched Surface Water and Ocean Topography (SWOT) satellite to close this gap of knowledge in the global water cycle. The work represents interdisciplinary research linking remote sensing hydrology, computer science, and economics. The outcome will be a proof of concept remotely observed water demand estimation model for the Rio Grande that compares favorably with the locally developed model. The results are intended to position our team for the anticipated Schmidt Futures Foundation Virtual Institute for Earth’s Water (VIEW) RFP late in 2024. 

Using UAV sensor technologies for informing flood forecasting 

Konstantinos Andreadis1, Brian Yellen2 
1College of Engineering 
2College of Natural Sciences  

Mapping the characteristics of flood inundation (duration, extent etc.) is very important for understanding its impacts on communities, infrastructure, and the environment. Ground-based surveys are difficult to obtain during a flood event, and therefore many efforts for mapping inundation over large areas have focused on remote sensing. Global navigation satellite system (GNSS) can provide signals of opportunity, enabling the detection and monitoring of different land surface properties such as the presence of water. Given the progress in small unmanned aerial vehicles (UAVs) and their increasing use in environmental monitoring, we aim to explore the potential of GNSS-R observations in providing inundation maps that can potentially inform flood forecasts. The PIs propose to assess the feasibility of using a UAV with a low-cost GNSS-R sensor mounted to map water inundation, and build a processing pipeline that feeds those inundation maps into a flood model. Potential application of this technology would be the development of flood inundation forecasts that are initialized/constrained by the drone-based observations as well as the near real-time monitoring of flood-affected areas during an event. As the primary application of the proposed technology is flood monitoring and forecasting, the PIs plan to use this initial demonstration to target funding opportunities from DHS, NASA, and DOE.  

 

Deployable Offshore Radar for Hurricane Genesis Monitoring 

Stephen Frasier, College of Engineering (in collaboration with the Lamont-Doherty Earth Observatory of Columbia University) 

In collaboration with researchers from the Lamont-Doherty Earth Observatory (LDEO), it is proposed to develop a deployable meteorological radar system suitable for an offshore platform to be used to monitor developing weather in its environment. The proposed application is ultimately a network of such autonomous systems that could monitor developing weather systems in the tropical Atlantic, thereby providing valuable input for hurricane genesis detection and modeling. As the frequency and intensity of such events increases due to climate change, timely detection methods are critical.  
The deployable radar will be of similar scale as existing fixed and mobile X-band radars developed by UMass. However, as it will be on a floating platform, it will be necessary for it to compensate for platform motion due to the underlying sea state. To this end, LDEO has obtained a gimbaled satellite dish and associate control system. The PI will work with LDEO to integrate and test this approach with a suitable radar transmitter/receiver and data acquisition and control system. This may include components from the UMass X-Pol radar.  
The prototype radar system will be evaluated on a barge or similar platform likely on Long Island Sound. The results of this effort will provide justification and motivation for a larger development proposal to the National Science Foundation.