860 Modeling Radar QPE Performance based on SENSR Network Design Possibilities

Wednesday, 10 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
James M. Kurdzo, MIT Lincoln Laboratory, Lexington, MA; and J. Y. N. Cho and E. F. Clemons

In 2016, the FAA, NOAA, DoD, and DHS initiated a feasibility study for a Spectrum Efficient National Surveillance Radar (SENSR). The goal is to assess approaches for vacating the 1.3- to 1.35-GHz radio frequency band currently allocated to FAA/DoD long-range radars so that this band can be auctioned for commercial use. As part of this goal, the participating agencies have developed preliminary performance requirements that not only assume minimum capabilities based on legacy radars, but also recognize the need for enhancements in future radar networks. The relatively low density of the legacy radar networks, especially the WSR-88D network, had led to the goal of enhancing low-altitude weather coverage. With multiple design metrics and network possibilities still available to the SENSR agencies, the benefits of low-altitude coverage must be assessed quantitatively. This study takes a regression approach to modeling Quantitative Precipitation Estimation (QPE) differences based on network density, array size, and polarimetric bias. These factors create a pareto front of cost-benefit for QPE in a new radar network, and these results can be used to determine appropriate tradeoffs for SENSR requirements. Preliminary results of this study are presented, including early datasets used for model training and comparisons of cases with artificially altered radar characteristics. A description of eventual application to a national network is provided, including the climatological datasets to be used and any normalization that will need to be taken into account.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner