242 Comparison of the Precipitation Estimation from GPM Dual-frequency Radar and Ground-based Doppler Weather Radar in Southern China

Thursday, 31 August 2017
Zurich DEFG (Swissotel Chicago)
Asi Zhang, Sun Yat-Sen Univ., Guangzhou, China; and S. Chen, S. Fan, L. Wang, and T. Zhan

Precipitation is one of the basic elements of regional and global climate change. Not only does the precipitation have a great impact on the earth’s hydrosphere, but also plays a crucial role in the global energy balance. S-band ground-based dual-polarization radar has the excellent performance of identifying the different phase states of precipitation, which can dramatically improve the accuracy of hail identification and quantitative precipitation estimation (QPE). However, the ground-based radar cannot measure the precipitation in mountains, sparsely populated plateau, desert and ocean because of the ground-based radar void. The Unites States National Aeronautics and Space Administration (NASA) and Japan Aerospace Exploration Agency (JAXA) have launched the Global Precipitation Measurement (GPM) for almost three years. GPM is equipped with a GPM Microwave Imager (GMI) and a Dual-frequency (Ku- and Ka-band) Precipitation Radar (DPR) that covers the globe between 65°S and 65°N. The main parameters and the detection method of DPR are different from those of ground-based radars, thus, the DPR’s reliability and capability need to be investigated and evaluated by the ground-based radar.

This paper compares precipitation derived from the ground-based radar measurement to that derived from the DPR’s observations. The ground-based radar is a S-band dual-polarization radar deployed near an airport in the west of Zhuhai city. The ground-based quantitative precipitation estimates are with a high resolution of 1km×1km×6min. Figure below gives the S-band radar’s location with a certain range of 239km. It shows that this radar covers the whole Pearl River Delta of China, including Hong Kong and Macao. In order to quantify the DPR precipitation quantification capabilities relative to the S-band radar, statistical metrics are computed and defined as follows: the difference (Dif) between DPR and the S-band radar observation, root-mean-squared error (RMSE) and correlation coefficient (CC). Meanwhile, POD and FAR are used to further evaluate the rainfall capacity of the DPR. The comparisons performed between the DPR and the S-band radar are expected to provide a useful reference not only for algorithm developers but also the end users in hydrology, ecology, weather forecast service and so on.

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