Multi-Doppler Processing in Phased Array Weather Radar Network Environment for Three-Axis Velocity Retrieval

Three-axis velocity retrieval is especially important for aviation because aviation is more sensitive to wind than other modes of civil transportation such as railways and shipping. Although civil aviation is roughly separated to the en-route and landing or taking-off phases, the latter does more seriously need weather supports. It is well known that the three-axis velocity retrievals from airport radars or lidars contribute to alarm hazardous windshears or turbulences [1], [2]. Furthermore, since updraft is the main cause of thunderstorm electrification [3], the three-axis velocity retrievals can be used to indicate lightning hazardous areas in order to reduce lightning strikes to airplanes, which are one of important issues in the current airport operation [4].

Since most of lightning strikes happen in the landing or taking-off phase, a tactical support for lightning avoidance around airports is of valid means. It is generally preferred that tactical weather supports is provided by high-resolution radar data to detect airport-hazardous weather phenomena whose scale is less than one hour. For accuracy of three-axis velocity retrieval, moreover, multiple radar environment is desired. In Japan, Toshiba corporation and Osaka university developed a high temporal resolution radar that utilizes phased array technologies (phased array weather radar; PAWR) by funding from National Institute of Information and Communications Technology (NICT) [5]. The PAWR has a fast scanning capability of 60-km coverage in 30 sec, which is sufficiently able to contribute tactical weather supports around airports. Today three PAWRs have been deployed and operated, and two of the three redundantly cover the Osaka international airport.

In this presentation, a three-axis velocity retrieval method is proposed. For the tactical lightning avoidance, the proposed method focuses especially on accurate retrieval of vertical velocities. The proposed method formulates a linear equation which relates three-axis and radial velocity fields, and solve the equation with a constraint of spatial correlation of wind velocities [6]. The constraint works for accurate retrieval especially of vertical velocities at low heights. In the presentation, its methodology and performance evaluations based on simulation and actual observation will be explained. A result of the simulation evaluations is exemplified in Figure 1 which compares a typical method (left) and the proposed method (center) with the simulation truth (right). Each panel displays a horizontal field of vertical velocity retrievals at 1500-m height. Note that the simulation assumes a four-radar environment. A typical method calculates least square estimation with respect to an arbitrary spatial grid, and it outputs a fluctuated retrieval field because measured radial velocities are not sensitive to vertical velocities at low heights. In the proposed method, meanwhile, the constraint works for suppressing the fluctuations, and retrieves vertical velocities which agree well with the simulation truth.

Figure 1: Horizontal field of retrieved vertical velocities at 1500-m height; left) typical least square estimator, center) proposed method, and right) simulation truth.

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[2] T. Iijima, N. Matayoshi, and E. Yoshikawa, “Development and Evaluation of Low-Level Turblences Advisory Display for Aircraft Operation,” in Proceedings of 29th Congress of the International Council of the Aeronautical Sciences, St. Petersburg, 2014.

[3] D. R. MacGorman and W. D. Rust, The Electrical Nature of Storms, Oxford University Press, 1998.

[4] E. Yoshikawa, T. Okada, A. Kanda, S. Yoshida, T. Adachi, K. Kusunoki, and T. Ushio, “Development of Tactical Lightning Avoidance Product for Terminal Weather Support,” AGU Fall Meeting, SF, 2015.

[5] E. Yoshikawa, T. Ushio, Z. Kawasaki, S. Yoshida, T. Morimoto, F. Mizutani, and M. Wada, “MMSE Beam Forming on Fast-Scanning Phased Array Weather Radar,” IEEE Trans. Geosci. Remote Sens., 51(5), 3077–3088 (2013).

[6] R. J. Doviak and D. S. Zrnic, Doppler Radar and Weather Observations, second edition, Dover Publication Inc., 1993, pp. 386–422.