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JDR Vol.16 No.3 pp. 410-414
(2021)
doi: 10.20965/jdr.2021.p0410

Note:

Study on Water Level Prediction Using Observational Data from a Multi-Parameter Phased Array Weather Radar

Kazuhiro Yoshimi*,†, Masakazu Wada*, and Yukio Hiraoka**

*Defense & Electronic Systems Division, Toshiba Infrastructure Systems & Solutions Corporation
72-34 Horikawa-cho, Saiwai-ku, Kawasaki, Kanagawa 212-8585, Japan

Corresponding author

**Social Systems Division, Toshiba Infrastructure Systems & Solutions Corporation, Kanagawa, Japan

Received:
October 1, 2020
Accepted:
December 4, 2020
Published:
April 1, 2021
Keywords:
MP-PAWR, VIL Nowcast, water level prediction, sewerage management system
Abstract

A dual-polarization, phased array weather radar, also known as the multi-parameter phased array weather radar (MP-PAWR), was developed by the Japanese Cross-ministerial Strategic Innovation Promotion (SIP) Program. Since this weather radar has been made into an active phased array, three-dimensional observation of weather phenomena can be realized at high speed by means of electrical scanning in the elevation direction and mechanical scanning in the azimuth direction. This is expected to shed light on hydrological processes in river basins, such as those of urban rivers, and improve prediction accuracy. In this study, river water levels in urban areas were estimated from vertically integrated liquid (VIL) Nowcast water content results, a meteorological forecasting method based on the three-dimensional observation MP-PAWR data, using a synthesized rational formula. A runoff analysis for urban basins was carried out using the rainfall forecast results based on MP-PAWR observational data. Since it is known that this formula can be used to deliver a rapid response time for runoff phenomena in the basin, it is possible to fully exploit the features of the MP-PAWR. This study shows how MP-PAWR is used in a series of hydrological processes. In this paper, we report the results of a basic study on water level predictions based on MP-PAWR observational data and also present future prospects for the use of this technology.

Cite this article as:
Kazuhiro Yoshimi, Masakazu Wada, and Yukio Hiraoka, “Study on Water Level Prediction Using Observational Data from a Multi-Parameter Phased Array Weather Radar,” J. Disaster Res., Vol.16, No.3, pp. 410-414, 2021.
Data files:
References
  1. [1] A. Kato and M. Maki, “Localized heavy rainfall near Zoshigaya, Tokyo, Japan on 5 August 2008 observed by X-band polarimetric radar – preliminary analysis –,” The Scientific Online Letters on the Atmosphere (SOLA), Vol.5, pp. 89-92, 2009.
  2. [2] E. Nakakita, H. Sato, and K. Yamaguchi, “Studies on Formation Mechanism of Vertical Vortex Tube inside Cumulonimbus Cloud for Accuracy Improvement of Guerilla-Heavy Rainfall Prediction,” Disaster Prevention Research Institute Annuals, Vol.60, No.B, pp. 539-558, 2017 (in Japanese).
  3. [3] H. Kikuchi, T. Suezawa, T. Ushio, N. Takahashi, H. Hanado, K. Nakagawa, M. Osada, T. Maesaka, K. Iwanami, K. Yoshimi, F. Mizutani, M. Wada, and Y. Hobara, “Initial Observations for Precipitation Cores with X-Band Dual Polarized Phased Array Weather Radar,” IEEE Trans. on Geoscience and Remote Sensing, Vol.58, Issue 5, pp. 3657-3666, 2020.
  4. [4] T. Adachi, K. Kusunoki, S. Yoshida, K. Arai, and T. Ushio, “High-Speed Volumetric Observation of a Wet Microburst Using X-Band Phased Array Weather Radar in Japan,” AMS Monthly Weather Review, Vol.144, Issue 10, pp. 3749-3765, 2016.
  5. [5] T. Suezawa, A. Onuki, H. Kikuchi, and T. Ushio, “Evaluation of Precipitation Measurements with Multi Parameter Phased Array Weather Radar,” American Geophysical Union Fall Meeting 2018, A31H-2945, 2018.
  6. [6] D.-S. Kim, M. Maki, S. Shimizu, and D.-I. Lee, “X-band dual-polarization radar observations of precipitation core development and structure in a multi-cellular storm over Zoshigaya, Japan, on August 5, 2008,” J. Meteor. Soc. Japan, Vol.90, No.5, pp. 701-719, 2012.
  7. [7] S. Tsuchiya, M. Kawasaki, and H. Godo, “Improvement of the Radar Rainfall Accuracy of Xrain by Modifying of Rainfall Attenuation Correction and Compositing Radar Rainfall,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.71, No.4, pp. I_457-I_462, 2015 (in Japanese).
  8. [8] K. Hirano and M. Maki, “Imminent Nowcasting for Severe Rainfall Using Vertically Integrated Liquid Water Content Derived from X-Band Polarimetric Radar,” J. of the Meteorological Society of Japan, Ser. II, Vol.96A, pp. 201-220, 2018.
  9. [9] A. Watanabe, T. Sasada, N. Watanabe, and T. Yamada, “Theoretical Derivation of Synthesized Rational Formula,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.68, No.4, pp. I_499-I_504, 2012 (in Japanese).

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Last updated on May. 04, 2021