Rain rate estimates using phased array weather radar network in Kansai area, Japan
Abstract
A rain rate estimation methodology with a sequentially varying radar reflectivity (Z) and rain rate relationship (R) is proposed to improve rain rate estimation accuracy of the networked single polarization phased array weather radars (SP-PAWRs) installed in Kansai area, Japan. The SP-PAWR is designed to conduct three dimensional precipitation measurement of a radar reflectivity factor and Doppler characteristics, in less than 10 or 30 seconds in a range of 20 or 60 km, respectively. The value of the rain rate with the existing X-band radar network comprising dual-polarization radars, which are installed in Kansai area, and the radar reflectivity factor of the SP-PAWRs are used to obtain the time variation in the Z-R relationship. In the networked area of the SP-PAWRs, a rain attenuation correction method is applied to avoid the effect of a rain attenuation. The proposed method is compared with estimation methods using the Marshall-Palmer (MP) relationship and the attenuation coefficient (k), which does not change during an observation period. From the comparison results between the three different rain rate estimations and the rain rate of the three rain gauges installed on the ground in the networked area, we discuss the estimation accuracy of the proposed method. When the 60 min accumulated rain rate is less than 10 mm, there are no differences between three estimation methods. The mean error (ME) and root mean square error (RMSE) of the proposed method are less than 1 mm, and the estimation accuracies of the other two methods are nearly equivalent. On the other hand, for a rain rate of more than 30 mm, the RMSEs of the MP and k-R methods are more than 13 mm. In the proposed method, the RMSE is 4 mm. The proposed method is significantly more accurate than the other two methods, when weather conditions include heavy rain. In this presentation, we will show the temporal variation of the Z-R relationship, which is obtained by the radar reflectivity of SP-PAWR network and the rain rate of the X-band polarimetric radar network.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.A31H2933K
- Keywords:
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- 3310 Clouds and cloud feedbacks;
- ATMOSPHERIC PROCESSESDE: 3360 Remote sensing;
- ATMOSPHERIC PROCESSESDE: 1821 Floods;
- HYDROLOGYDE: 1853 Precipitation-radar;
- HYDROLOGY