Aperture Size Considerations for Future Operational Phased Array Weather Radar

Phased array radar (PAR) is under consideration as a replacement architecture for the next generation U.S. operational weather radar network (Stailey and Hondl, 2016). More efficient and rapid scanning enabled by PAR can improve severe weather warning performance, as demonstrated by Yussouf and Stensrud (2010) and Heinselman et al (2015). PAR may also facilitate improved coverage at low altitudes through deployment of “gap-fillers” and/or more capable weather processing channels on aircraft surveillance radars. Recent analyses (Cho and Kurdzo, 2018; Kurdzo et al, 2018) indicate that enhanced low altitude coverage would improve the accuracy of both tornado and flash flood warnings.

The current operational weather service radar (WSR-88D) utilizes a 1^o pencil beam in order to provide cross-range resolution sufficient for detection of severe weather signatures (e.g. tornadic Doppler velocity couplets) at significant range from the radar. Achieving equivalent angular resolution using a PAR that may be steered well off broadside requires a very large array. Notional PAR configurations supporting weather observations have assumed 20,000 to 30,000 transmit-receive elements for each antenna face (Weber et al (2007), Doviak et al. (2017)).

Recent evolution of gallium-nitride (GaN) power-amplifier (PA) technology indicates that, in the near future, relatively low-cost active array transmit-receive (TR) elements will be capable of transmitting ~50 W peak power with duty cycles of 10%. This has significant implications for meteorological PAR. An array sized as above to provide 1^o angular resolution could transmit two orders of magnitude more average power than the current WSR-88D.

This paper considers three implications of this possibly very large power-aperture excess relative to the WSR-88D:

• Meteorological PAR would inherently be capable of providing surveillance services well beyond repetitive weather volume scanning, including aircraft search and track and/or high-sensitivity “stares” to provide atmospheric parameters in “clear air” (Zrnic et al., 2019). Using an adapted version of the radar search equation (Skolnik, 2008) we show that a PAR with 1^o beamwidth is significantly “over-sized” from a power-aperture perspective, even assuming a future goal of 1 weather volume scan per minute. If architected using highly- (or all-) digital arrays, it is straightforward to show that with appropriate scanning techniques (e.g. Zrnic et al, 2015, Weber et al, 2017), meteorological PAR can support a variety of operational surveillance missions with no compromise to its core weather volume scanning requirement;
• Strong consideration should be given to a more dense radar network based on smaller-aperture, “right-sized” PARs. For a given total aperture deployment (# radars times antenna area per radar) this could substantially improve low-altitude coverage while maintaining, on average, equivalent cross-range resolution. Using antenna size and radar network density as independent variables, we model implications for performance parameters (coverage, spatial resolution, sensitivity, scan rate) and network life-cycle costs;
• The aperture size of meteorological PAR will be dominated by requirements for angular resolution rather than sensitivity. Research should be conducted to develop PAR techniques that increase effective angular resolution relative to the physical beamwidth θ_3dB (deg) ≈ 100/√N (Skolnik, 2008). Here N is the number of TR elements comprising the antenna. If effective, such techniques could reduce the required density of a radar network based on smaller aperture PARs or reduce the size (and cost) of radars in a network with laydown similar to that of the WSR-88D. As examples of candidate approaches, we discuss techniques employing multiple-input-multiple-output (MIMO) or, alternatively, constrained, iterative image deconvolution (Schafer et al., 1981). Both approaches assume a highly digital, sparse array to reduce the number of TR-elements required.

The overarching purpose of this paper is to encourage consideration of new architectures for the future operational meteorological radar network that efficiently incorporate rapid evolution in PAR technology. Radar configurations and network designs largely based on today’s surveillance system will likely be far from optimal.

References:

Stailey, J.E. and K.D. Hondl, 2016: Multifunction phased array radar for aircraft and weather surveillance, Proc. IEEE, 104, pp 649-659.

537. Yussouf and D.J. Stensrud, 2010: Impact of phased-array radar observations over a short assimilation period: observing system simulation experiments using an ensemble Kalman filter, Mon. Wea. Rev., 138, pp. 517-537.

Heinselman, P.L., D.S. LaDue, M. Kingfield and R. Hoffman, 2015: Tornado warning decisions using phased-array radar data. Weather Forecasting, 30, pp 57-78.

Cho, J.Y.N. and J.M. Kurdzo, 2018: Weather radar network benefit model for tornadoes, submitted to J. Appl. Met. and Climate.

Kurdzo. J.M, E.F. Clemons, J.Y.N. Cho, P.L. Heinselman and N. Yussouf, 2018: Quantification of radar QPE performance based on SENSR network design possibilities, Conference Proc., IEEE Radar Conference, Oklahoma City, OK

Weber, M.E., J.Y.N. Cho, J.S. Herd, J.M. Flavin, W.E. Benner and G.S. Torok, 2007: The next-generation multimission US surveillance radar network, Bull. Amer. Meteor. Soc., 88, pp. 1739-1751.

Doviak, R., M.E. Weber and D.S. Zrnic, 2017: Weather and aircraft surveillance requirements for a 10-cm wavelength multi-function phased array radar, AMS. Conf. Rad. Met., Chicago, Ill.

Skolnik, M.I., 2008: Radar Handbook, 3^rd ed., New York: McGraw-Hill

Zrnic, D.S., V. Melnikov, R. Doviak and R. Palmer, 2015: Scanning strategy for the multifunction phased array radar to satisfy aviation and meteorological needs, IEEE Geosci. Remote Sens. Lett., 12, pp. 1204-1208.

Weber, M.E., J.Y.N. Cho, H.G. Thomas, 2017:Command and control for multifunction phased array radar, IEEE Trans. Geosci. Remote Sens., 55, pp.5899-5912.

Zrnic, D., S. Koch, R. Palmer, M. Weber, K. Hondl, G. McFarquhar and M. Jain, 2019: How an agile-beam polarimetric phased array radar can add to the observing capabilities of the NWS, this conf.

Schafer, R.W., R. M. Mersereau and M.A. Richards, 1981: Constrained iterative restoration algorithms, Proc. IEEE, 69, pp. 432-451.

Affiliations:

¹ NOAA OAR National Severe Storms Laboratory and University of Oklahoma Cooperative Institute for Mesoscale Meteorological Studies, Norman, OK

² Massachusetts Institute of Technology Lincoln Laboratory, Lexington, MA

This abstract was prepared with funding provided by NOAA/Office of Oceanic and Atmospheric Research under NOAA-University of Oklahoma Cooperative Agreement #NA11OAR4320072, U.S. Department of Commerce. The statements, findings, conclusions, and recommendations are those of the author(s) and do not necessarily reflect the views of NOAA or the U.S. Department of Commerce.